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Obesity

Larry H. Bernstein, MD, FCAP, Curator

Leaders in Pharmaceutical Intervention

2010 Douglas L. ColemanJeffrey M. Friedman

Shaw Laureates 2009 Life Science and Medicine

Douglas L. Coleman (6 October 1931 – 16 April 2014) was a scientist and professor at The Jackson Laboratory, in Bar Harbor, Maine. His work predicted that the ob gene encoded the hormoneleptin,[1] later co-discovered in 1994 by Jeffrey Friedman, Rudolph Leibel and their research teams at Rockefeller University.[2][3][4][5][6][7][8] This work has had a major role in our understanding of the mechanisms regulating body weight and that cause of humanobesity.[9]

Coleman was born in Stratford, Ontario. He obtained his BS degree from McMaster University in 1954 and his PhD in Biochemistry from the University of Wisconsin in 1958. He was elected a member of the US National Academy of Sciences in 1998. He won the Shaw Prize in 2009,[10] the Albert Lasker Award for Basic Medical Research in 2010, the 2012 BBVA Foundation Frontiers of Knowledge Award in the Biomedicine category and the 2013 King Faisal International Prize for Medicine[11] jointly with Jeffrey M. Friedman[9] for the discovery of leptin.

http://www.nytimes.com/2014/04/26/us/douglas-l-coleman-82-dies-found-a-genetic-cause-of-obesity.html

The Genetics of Obesity

Winner of the  2013 KFIP Prize for  Medicine

Professor Douglas Coleman was born on October 5, 1931, in Stratford, Ontario, Canada. He obtained a B.Sc. in Chemistry in 1954 from McMaster University in Hamilton, Ontario, then went to the University of Wisconsin in Madison, WI, U.S.A., where he obtained M.S. and Ph.D. degrees in Biochemistry in 1956 and 1958, respectively. He served as a Research Assistant at the University of Wisconsin from 1954-1957 and as E.I. Dupont de Nemours Fellow from 1957-1958. He joined the Jackson Laboratory in Bar Harbor, ME, where he spent his entire career rising from Associate Staff Scientist In 1958 to Senior Staff Scientist in 1968. He also served as Assistant Director for Research from 1969-1970 and Interim Director  from 1975-1976. Upon his retirement in 1991, he was appointed Senior Staff Scientist Emeritus at Jackson. He was also consultant to the National Health Institutes, serving on the Metabolism Study Section from 1972-1974 and was frequently consulted on various other special study sections involving genetic diabetes, obesity and nutrition. He also served as Visiting Professor at the University of Geneva (1979-1980).

Professor Coleman’s research interests focus on biochemical genetics, regulation of metabolism, obesity, diabetes and hormone action. He is best known for his studies on the obesity-diabetes syndrome. He discovered the db gene, one of the two genes responsible for the genetic events regulating appetite control. He carried out a series of fundamental experiments with parabiotic mice which demonstrated the hormone-hormone receptor axis of leptin and the leptin receptor long before their discovery. The discoveries of Coleman and Friedman represent one of the most important biological breakthroughs in recent decades.

Professor Coleman received several prestigious awards and honors, including the Claude Bernard Medal by the European Diabetes Foundation in 1977, the Distinguished Alumni Award in Science by McMaster University in 1999, the Gairdner International Award in 2005, the Shaw Prize for Life Sciences and Medicine in 2009 (jointly with Jeffrey M. Friedman), the Albert Lasker Basic Medical Research Award (jointly with Jeffrey M. Friedman) and the Outstanding Forest Stewardship Award (Maine Forest Service). He was elected to the National Academy of Sciences in 1991, and was awarded Honorary D.Sc. from Louisiana State University in 2005 and Honorary D.Sc. from McMaster University in 2006. He is a member of the American Association of Biological Chemists.

Professor Douglas Leonard Coleman was awarded the prize because the research findings by him and Professor Friedman led to the identification and characterization of the leptin pathway. This seminal discovery has had a major impact on our understanding of the biology of obesity, describing some of the key afferent pathways in body weight regulation active in man. Their fundamental discoveries have also helped in the recognition of more illuminating views of the endocrine system. Because of their major contribution to the field of the genetics of obesity they have been awarded King Faisal International Prize in Medicine for the year 2013.

Leaping for leptin: the 2010 Albert Lasker Basic Medical Research Award goes to Douglas Coleman and Jeffrey M. Friedman

Ushma S. Neill

J Clin Invest. 2010 Oct 1; 120(10): 3413–3418.
Published online 2010 Sep 21. doi:  10.1172/JCI45094

Douglas Coleman never intended to study diabetes or obesity. Jeffrey M. Friedman had childhood dreams of being a veterinarian. But together, the two scientists have opened the field of obesity research to molecular exploration. On September 21, the Albert and Mary Lasker Foundation announced that they will award Coleman and Friedman (Figure (Figure1)1) with the 2010 Albert Lasker Basic Medical Research Award in recognition of their contributions toward the discovery of leptin, a hormone that regulates appetite and body weight. This hormone provides a key means by which changes in nutritional state are sensed and in turn modulate the function of many other physiologic processes. The story of the discovery of the first molecular target of obesity is one of tenacity and determination.

Figure 1

Douglas Coleman (left) and Jeffrey M. Friedman (right) share the 2010 Albert Lasker Basic Medical Research Award for the discovery of leptin, a breakthrough that opened obesity research to molecular exploration.

From Canada to Maine

Douglas Coleman was raised in Ontario, Canada, the only child of English immigrant parents, who encouraged him to excel in school; he recalled, “Although my parents never had the luxury of completing high school, they always encouraged me to pursue a higher education, and in high school, I developed a keen interest in chemistry and biology.” Coleman pursued his interest in chemistry at McMaster University. It was there he met his future wife, Beverly Benallick, “the only girl to graduate in Chemistry in the Class of 1954.” During his time at McMaster University, Coleman began to focus on organic chemistry and had the fortune of working with, “a very dynamic professor, Sam Kirkwood, who not only taught me the rudiments of biochemistry, but also instilled an appreciation of the scientific method.” Kirkwood encouraged Coleman to continue his biochemistry studies at the University of Wisconsin, at which he received a PhD in 1958.

In those days, postdoctoral fellowships were rare, and graduates had two options: academia or industry. Coleman took a third option, as an associate staff scientist at what was then known as the Roscoe B. Jackson Memorial Laboratory in Bar Harbor, Maine. Coleman has noted, “My intention was to stay one or two years, expanding my skills in multiple fields, especially genetics and immunology. To my great pleasure, The Jackson Laboratory provided a rich environment, including world-class animal models of disease, interactive colleagues, and a backyard that included the stunning beauty of Acadia National Park.” The Coleman family put down roots, raising their three sons there as Coleman rose through the ranks to senior staff scientist and served terms as assistant director of research and interim director (Figure (Figure2).2). He noted, “Without a doubt, I was lucky in my choice of starting my career at The Jackson Laboratory. It was a wonderful place in which to work, and I never pursued another position.”

Figure 2

Coleman at the bench at The Jackson Laboratory in 1960.

Making magic from a mutant

His early work involved muscular dystrophy and the development of a new field, mammalian biochemical genetics, establishing that genes control enzyme turnover as well as structure. However, his focus changed when a colleague asked for his help characterizing a mutant (Figure (Figure3)3) that had spontaneously arisen at the labs. He recalled, “Initially, I had no intention of studying the diabetes/obesity syndrome, but in 1965, a spontaneous mouse mutation was discovered, and I began research that would consume much of my scientific thought for the better part of three decades.” The new mutant was polydipsic and polyuric as well as being massively obese and hyperphagic. His colleague, Katherine Hummel, was studying diabetes insipidus and asked if he could determine whether the new mutant had diabetes insipidus or mellitus. He reported back that it was diabetes mellitus: “Her initial response was that she was not interested, but I convinced her that with a little further work we could produce a solid manuscript announcing this potentially valuable mutant to the world.” This mouse owed its phenotype to two defective copies of a gene that researchers dubbed diabetes (db) (1).

Figure 3

Wild-type and obese mice.

When Coleman and his colleagues began characterizing the db/db mouse, they began to ponder whether some circulating factor might regulate the severity of diabetes: perhaps a factor in the normal mouse could inhibit the development of the obesity and diabetes found in the db/db mutant. Conversely, perhaps a circulating factor present in the db/db mouse might cause the diabetes-like syndrome in the normal mouse. If the hypothetical factor was carried through the blood, Coleman reasoned, they could test for its presence by linking the blood supplies of the various mouse strains — an experimental setup called parabiosis. Fortunately, others at The Jackson Laboratory were using parabiosis to assess whether any circulating factors were involved in anemic mutants, and they were able to show Coleman how to do it successfully.

When Coleman hooked the wild-type mice and the db/db mice together, rather than overeating, as the db/dbmice did, the wild-type mice stopped eating and died from starvation (Figure (Figure44 and ref. 2). His hypothesis was correct: the db/db mice indeed must have released a factor that inhibited the wild-type animals’ drive to eat, but the mutant animals could not respond to it.

Figure 4

Summary of parabiosis experiments performed by Coleman.

Coleman needed more proof of this mystery circulating factor regulating food intake. He turned to another overweight mouse that also had arisen by chance at The Jackson Laboratory, this one called “obese,” whose aberrant physiology arises from two defective copies of a different gene (ob) (3). Unfortunately, the ob/obmouse was on a different genetic background, and due to immune-mediated rejection, parabiosis could only be performed successfully on mice with the same strain background. Coleman described his need for resolve, “Since the obese and diabetic mutants were on different genetic backgrounds, it took years for me to be able to perform all of the desired pairings.”

Coleman persevered and finally got the strains to match so he could successfully hook them together in a parabiosis experiment. When joined to a db/db mouse, the ob/ob mouse stopped eating and starved to death, while the db/db mouse remained obese, just as the normal mice had in the previous experiment. In contrast, attaching wild-type mice to ob/ob animals did nothing to the wild-type mice and caused the ob/ob mice to limit their food consumption and gain less weight (Figure (Figure4).4). Coleman concluded that the ob/ob mice failed to produce a hormone that inhibits eating, while the db/db mice overproduced it but lack the receptor to transmit the hormonal signal (4).

Coleman faced some skepticism for his conclusion that obesity was not just about willpower and eating habits but also involved chemical and genetic factors. In this regard, he said, “When I published these findings, the long-standing dogma was that obesity was a behavioral problem (a lack of willpower) and not a physiological problem (a hormonal imbalance). I had to deal with this behavioral dogma most of my career.”

To validate his hypothesis, Coleman would need to identify the db and ob genes and protein products, a task that proved to be an insurmountable challenge at the time. He noted, “Definitive proof of my conclusions required isolating the satiety factor — a feat that resisted rigorous experimentation.” That is, until Jeffrey Friedman set his sights upon the task.

 After his third year of internal medicine residency at Albany Medical Center Hospital, Friedman  had no concrete plans for the following year, as he was not scheduled to begin a fellowship at the Brigham and Women’s Hospital in Boston until a year later. Friedman recalled, “I had no particular plans for the gap year, and John Balint, one of my professors, thought I might like research — why he thought I might have some particular aptitude, I can’t really tell. He said, ‘I have this friend at Rockefeller [Mary Jeanne Kreek], why don’t you go spend a year with her and see if you like research?’ I didn’t know what else I was going to do. My mother thought I should go spend the year as a ship’s doctor.”
A fat chance

Friedman was enraptured by what Kreek studied: how molecules control behavior. “That was 1981 and it was beginning to be evident that molecular biology was going to have a big impact, so instead of going to the Brigham for a fellowship, I abandoned medicine and decided to get a PhD with Jim Darnell [2002 Lasker award winner for his work in RNA processing and cytokine signaling], who was one of the leaders in molecular biology,” he noted. Friedman’s thesis was on the regulation of liver gene expression — how genes are turned on and off as liver regenerates. However, there was something he did on the side that was more impactful: Kreek had asked him to work with Bruce Schneider, another faculty member at Rockefeller University, to make an RIA for β-endorphin. However, Schneider’s primary interest was not in β-endorphin, but rather in cholecystokinin (CCK). In 1979, Rosalyn Yalow had published a paper in which she reported reduced levels of CCK in the brain of ob/ob mice and boldly claimed that CCK was the circulating factor that caused the ob/ob mice to be fat (5). Friedman recalled, “Well, Bruce had the exact opposite data, this was published in the JCI (6), and this started a battle with Yalow over who was correct. To address this, in 1982 Don Powell, Bruce, and I set out to clone the Cck gene so we could map it. We collaborated with Peter D’Eustachio at NYU, who showed that it was on chromosome 9 (7); ob is on 6, db is on 4. I still have Peter’s notebook entry from that time in which he wrote, ‘CCK does not map to chromosome 6, home ofob.’” So the question for Friedman became, if the circulating hormone is not CCK, then what is? When he started his own laboratory in 1986 at Rockefeller, he set out to find it, and as he recalls, “In a way what theob mouse represented to me was another instance where a molecule was controlling a behavior, the same as in Mary Jeanne’s lab.”

Do these genes make me look fat?

In the mid ’80s, positional cloning was not easy, but Friedman turned to the then-new techniques of physical gene mapping, complimented by conventional genetic mapping in mice. It had long been known that the obgene resided somewhere on mouse chromosome 6, but narrowing down the region was arduous, as the trait is recessive, necessitating the breeding of several generations. Friedman and his laboratory first determined which DNA markers were inherited along with the obese phenotype in over 1,600 mice crossbred from obese and nonobese strains. He remembers, “It was a mind numbing exercise you hoped someday would lead somewhere.” Since the genetic and physical maps are colinear, DNA markers that were linked to ob in genetic crosses could be used to clone the surrounding DNA. Using this approach, they eventually identified the portion of the genome in which all markers were always coinherited with ob among the progeny of the crosses. This region defined the chromosomal region in which the ob gene resided. As they had predicted when the crosses were set up, this region corresponded to an approximately 300,000–base pair region on chromosome 6. They then screened recombinant clones across this region for exon-intron boundaries, which indicate the presence of genes. One of the first three genes they isolated was expressed exclusively in adipose tissue, and the expression of the mutant gene was found to be 20 times greater in one of the ob/ob mutants than in controls. In a second mutant, the gene was not expressed at all, providing clear evidence that this gene encoded the ob gene. When they looked in the human genome, they found an ob homolog that was 84% identical with the mouse ob gene, establishing ob as a highly conserved, biologically important gene (8).

Once a fat-specific gene was found in the vicinity of ob, he remembered being almost numb with excitement as a set of confirmatory experiments unfolded. “I went in late on a Saturday night, and I found a radioactive probe for this gene, and I found a blot with RNA from fat tissue of normal and mutant mice. I hybridized the blot that evening and washed it at 1 in the morning. I couldn’t sleep, and I woke up at 5 or 6 and developed the blot. When I looked at the data, I immediately knew that we had cloned ob. When I saw it, I was in the darkroom, and I pulled up the film and looked at it under the light and got weak-kneed. I sort of fell backwards against the wall. This gene was in the right region of the chromosome, it was fat specific, and its expression was altered in two independent strains of ob mice. Before this, we didn’t know where ob would be expressed — and while fat was one of the tissues I considered, in principle the gene could have been expressed in any specialized cell type anywhere that had no obvious relationship to fat. But on the other hand, seeing a gene in the right region expressed exclusively in the fat . . . that gets your attention.” When he found out at 6 in the morning, he called his wife and said “we did it!,” and then, a few hours later he, called his former PhD advisor Jim Darnell: “I told him but I wasn’t sure he believed me.” That afternoon, he met some friends at Pete’s Tavern, “and we opened a bottle of champagne, and I told them, ‘I think this is going to be pretty big.’”

Next Friedman set his sights on actually identifying the product secreted by the ob gene and validating Coleman’s circulating hormone hypothesis. Together with Stephen Burley, his laboratory engineered E. colito fabricate the secreted protein, generated antibodies that would bind it, and showed that humans and rodents secrete it. In the last sentence of the 1995 Science paper describing these findings, Friedman “propose[d] that this 16-KD protein be called leptin, derived from the Greek root leptos, meaning thin” (9). The paper also showed that db/db mice made excess quantities of leptin, as predicted by Coleman, and its levels in plasma decreased in normal animals and obese humans after weight loss. He remembered, “It was an unbelievable time in the lab. The idea that there was this hormone that regulated body weight, and that we had found it, was just unimaginable. I’d wake up in the middle of the night just smiling.”

As for the name leptin, it has not only a Greek root, but a French one too. At a meeting, Friedman met Frenchman Roger Guillemin, who won a Nobel Prize for his work on peptide hormone production by the brain. A few weeks after the meeting, Friedman got a letter from him that he recalls saying, “I really liked what you had to say, but I have one quibble: you refer to these as obesity genes, but I think they are lean genes because the normal allele keeps you thin. But calling them lean genes sounds awkward. The nicest sounding root for thin is from Greek, so I propose you call ob and db ‘lepto-genes.’” So when it came time to name it, Friedman remembered Guillemin’s suggestion, and therein, the name leptin was coined.

Leptin’s legacy

Later in 1995, another group described the leptin receptor (10), and then subsequently, Friedman and another group showed that this leptin receptor is encoded by the db gene and has multiple forms, one of which is defective in Coleman’s originally described db/db mice (11, 12). Friedman also showed that the leptin receptor is especially abundant in the hypothalamus in which leptin can activate signal transduction and phosphorylation of the Stat3 transcription factor (13).

Over the years, numerous laboratories have studied leptin’s mechanism of action. Leptin acts on receptors expressed in groups of neurons in the hypothalamus, in which it inhibits appetite, in part, by counteracting the effects of neuropeptide Y, a potent feeding stimulant secreted by cells in the gut and in the hypothalamus, by thwarting the effects of anandamide, another potent feeding stimulant, and by promoting the synthesis of α-MSH (melanocyte stimulating hormone), an appetite suppressant (14). Leptin is produced in large amounts by white adipose tissue but can also be produced in lesser amounts by brown adipose tissue, syncytiotrophoblasts, ovaries, skeletal muscle, stomach, mammary epithelial cells, bone marrow, pituitary, and liver. Leptin’s actions are also not limited to regulating food intake, as it is has been shown to have roles in fertility, immunity, angiogenesis, and surfactant production. Friedman adds that the hormone, “has effects on many physiological systems, including the immune system where it modulates T cells, macrophages, and platelets. It now appears that leptin provides a key means by which nutritional state can regulate a host of other physiological systems.” While most of these actions are mediated by effects on the CNS, two of many key questions are, which of leptin’s effects on peripheral systems are direct, and which are indirect via the brain?

A magic bullet?

The first proof that leptin was important in humans came in 1997 when Stephen O’Rahilly and colleagues found two morbidly obese children who carried a mutation in the leptin gene (15). These researchers went on to show that leptin-replacement therapy could be useful in individuals with leptin mutations (16). Injection of leptin into these children led to rapid weight loss and markedly reduced food intake (Figure (Figure5).5). Leptin-replacement therapy also has potent effects in other clinical settings, including lipodystrophy, a disease state in which animals and humans have little white fat and develop severe diabetes, with profound insulin resistance and high plasma lipid levels. Because this syndrome is associated with low circulating levels of leptin, Shimomura and colleagues tested the effects of leptin-replacement therapy in mice and showed that it was highly effective (17); similar efficacy was later shown in humans (18). More recently, leptin treatment has shown a profound anti-diabetic effect in type 1 diabetic animals (19). Leptin replacement has also been shown to be of clinical benefit in other states of leptin deficiency, including hypothalamic amenorrhea (20).

Figure 5

Effects of r-metHuLeptin on the weight a child with congenital leptin deficiency.

Excited by leptin’s potential for the treatment of obesity, the biotech company Amgen paid $20 million to Rockefeller to license the hormone. With so much of the world’s population overweight or obese, a treatment or cure would be a major advance in public health and would likely be very lucrative. Amgen sponsored a large clinical trial, giving leptin to overweight adults, but while a subset of obese patients lost significant amounts of weight on leptin, the average magnitude of the effect was minimal, dampening hopes that leptin was the magic bullet in the obesity fight (21). After the trial, Amgen announced that they had suspended studies of the effects of leptin for the treatment of human obesity.

Friedman says he understands why the trials failed: “Even before leptin was tested in obese patients, we knew from animal studies that this hormone was not likely to be a panacea for every obese patient and that the response seen in ob/ob mice wasn’t going to be the typical case for obese humans. Leptin levels are elevated in obese humans, suggesting that obesity is often associated with leptin resistance and raising the possibility that increasing already high levels was going to be of arguable benefit.” The key to making leptin work may be in coaxing the brain to respond to leptin: some people are simply not sensitive enough or they develop resistance. Friedman predicts that through personalized medicine, doctors may at some point be able to identify which obese people will respond to leptin. In the meantime, there is some clinical evidence that leptin’s ability to reduce weight among obese patients can be restored by combining it with other agents (22).

The thrill of discovery

For all the social implications, potential profits, and medical possibilities, Friedman is circumspect but proud about the discovery of leptin, saying, “whether it finds its way into general usage as an antiobesity drug, the use of modern methods to identify and target the components of the leptin- signaling pathway will, I believe, form the basis for new pharmacological approaches to the treatment of obesity and other nutritional disorders.” Coleman agrees, stating that “with the discovery of leptin and the subsequent cloning of the leptin receptor, the field exploded. With these findings, two long-standing misconceptions were definitively laid to rest: obesity was not merely a behavioral problem but rather had a significant physiological component; and adipose tissue was not merely a fat-storage site but rather an important endocrine organ.”

Both Coleman and Friedman (Figure (Figure6)6) were overwhelmed and humbled by the news that they would receive the 2010 Lasker Award for Basic Medical Research. Coleman notes, “I have always viewed this award as one of the most esteemed of the several truly prestigious biomedical research awards, and it is with great pride and humility that I accept this prestigious prize. I was also especially delighted to learn that I would be sharing this award with Jeffrey Friedman, who always acknowledged my earlier contributions to our field.” Friedman added, “It is an honor to join a group of other winners who really are at the highest level of science. To be placed among them is just hard to fathom.”

Figure 6

Coleman and Friedman, together at The Jackson Laboratory, in 1995.

Coleman retired from his scientific career in 1991. He has said that at his retirement ceremony “someone commented that my career was characterized by the ability to use the simplest technique to answer the most complex biological questions.” Friedman, however, is still at the bench and active as ever in his hunt to determine exactly how leptin regulates food intake. Through their determination and persistence, the two have provided a molecular framework for understanding obesity, but they have different opinions about how much luck played into their findings. Coleman has noted that he favors the Louis Pasteur quote, “Luck favors the prepared mind.” But Friedman has a different perspective, stating “my story suggests that in many cases, the prepared mind is favored by chance.”

Acknowledgments

As Coleman was away and unavailable for comment during the preparation of this article, his quotations were taken from an autobiography he wrote when accepting the Shaw prize in 2009, from his acceptance remarks for the Lasker prize, and from a profile written by Luther Young posted on the Bangor Daily Newsin 2009 ( http://www.bangordailynews.com/story/Hancock/Scientists-work-at-Jackson-Lab-lauded,118612?print=1).

References
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8. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature. 1994;372(6505):425–432. doi: 10.1038/372425a0. [PubMed][Cross Ref]
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17. Shimomura I, Hammer RE, Ikemoto S, Brown MS, Goldstein JL. Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature. 1999;401(6748):73–76. doi: 10.1038/43448.[PubMed] [Cross Ref]
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22. Roth JD, et al. Leptin responsiveness restored by amylin agonism in diet-induced obesity: evidence from nonclinical and clinical studies. Proc Natl Acad Sci U S A. 2008;105(20):7257–7262. doi: 10.1073/pnas.0706473105. [PMC free article] [PubMed] [Cross Ref]
Autobiography of Jeffrey M Friedman

My laboratory identified leptin, a hormone that is produced by fat tissue. Leptin acts on the brain to modulate food intake and functions as an afferent signal in a feedback loop that regulates weight. My route to this hormone is filled with a number of chance events and turns of fate that were in no way predictable at the time that I started my career.I grew up in the suburbs of New York City in a village where children had enormous freedom. I recall from an early age riding my bicycle everywhere without my parents, or anyone else for that matter, knowing my whereabouts. My father was a radiologist and my mother was a teacher. No one in my family or community had pursued an academic career and at the time I was completely unaware of the possibility that one could make a career in science. In my family, the highest level of achievement was to become a doctor and, despite my earliest dreams of a career as a professional athlete (made unlikely by a notable lack of talent) and a later wish to become a veterinarian, I became a doctor.I was originally trained in internal medicine with some subspecialty training in gastroenterology. In medical school and as a medical resident, I participated in some modest research studies. The first piece of work I completed related to the effects of dietary salt on the regulation of blood pressure. After completing this project, I excitedly submitted a paper for publication. I remember one of the reviews verbatim: “This paper should not be published in the Journal of Clinical Investigation or anywhere else.” Fortunately, one of my mentors in medical school still thought I might have some aptitude for research. He suggested that I go to The Rockefeller University to work in a basic science research laboratory. I joined the laboratory of Dr Mary-Jeanne Kreek to study the effects of endorphins in the development of narcotic addiction.I was fascinated by the idea that endogenous molecules could alter behaviour and emotional state. At The Rockefeller University, I met another scientist, Bruce Schneider. Bruce was studying cholecystokinin (CCK), a peptide hormone that is secreted by intestinal cells. CCK aids digestion by stimulating the secretion of enzymes from the pancreas and bile from the gallbladder. CCK had also been found in neurons of the brain, although its function there was less clear. In the late 1970s, it was shown that injections of CCK reduce food intake. This finding appealed to me as another example of how a single molecule can change behavior. One other fact also piqued my interest: There were indications that the levels of CCK were decreased in a genetically obese ob/ob mouse. These mutant mice are massively obese as a consequence of a defect in a single gene. The mice eat excessively and weigh 3 to 5 times as much as normal mice. It was thus hypothesized that CCK functions as an endogenous appetite suppressant and that a deficiency of CCK caused the obesity evident in ob/ob mice. Fascinated by this possibility, I set out to establish the possible role of CCK in the pathogenesis of obesity in these animals. To do this I was going to need additional training in basic research, so I abandoned my plans to continue medical training in gastroenterology and instead entered the PhD program at The Rockefeller University.As a PhD student I worked in the laboratory of Jim Darnell, studying the regulation of gene expression in liver, and learning the basic tools of molecular biology. But I carried my interest in the ob/ob gene with me. At the end of my graduate studies, two colleagues and I successfully isolated the CCK gene from mouse. One of the first studies we performed after isolating the gene was to determine its chromosomal position. We found that the CCK gene was not on chromosome 6, where the ob mutation had been localized, which thus excluded defective CCK as the cause of the obesity. The question thus remained: What is the nature of the defective gene in ob/ob mice?

After receiving my PhD in 1986, I became an assistant professor at The Rockefeller University and set out to answer this question. The culmination of what proved to be an 8-year odyssey was the identification of the ob gene in 1994. We now know that the ob gene encodes the hormone leptin. The discovery of this hormone, a singular event in my life, was absolutely exhilarating. The realization that nature had happened upon such a simple and elegant solution for regulating weight was the closest thing I have ever had to a religious experience. Subsequent studies revealed that injections of leptin dramatically decrease the food intake of mice and other mammals. My current studies now focus on several questions, including the one that originally aroused my interest in this mutation: How is it that a single molecule – leptin – profoundly influences feeding behavior? An esteemed colleague of mine remarked recently that I had searched for the ob gene primarily so that I could approach the question I had started with. It is as yet unclear whether I will succeed in understanding how a single molecule can influence a complex behaviour.

  1. Coleman, DL (1978). “Obese and Diabetes: two mutant genes causing diabetes-obesity syndromes in mice”. Diabetologia 14: 141–148. doi:10.1007/bf00429772.
  2. Jump up^ Green ED, Maffei M, Braden VV, Proenca R, DeSilva U, Zhang Y, Chua SC Jr, Leibel RL, Weissenbach J, Friedman JM. (August 1995). “The human obese (OB) gene: RNA expression pattern and mapping on the physical, cytogenetic, and genetic maps of chromosome 7”.Genome Research 5 (1): 5–12. doi:10.1101/gr.5.1.5.PMID 8717050.
  3. Jump up^ Shell E (January 1, 2002). “Chapter 4: On the Cutting Edge”. The Hungry Gene: The Inside Story of the Obesity Industry. Atlantic Monthly Press. ISBN 978-1-4223-5243-4.
  4. Jump up^ Shell E (January 1, 2002). “Chapter 5: Hunger”. The Hungry Gene: The Inside Story of the Obesity Industry. Atlantic Monthly Press.ISBN 978-1-4223-5243-4.
  5. Jump up^ Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM (December 1994). “Positional cloning of the mouse obese gene and its human homologue”. Nature 372 (6505): 425–432.doi:10.1038/372425a0. PMID 7984236.
  6. Jump up^ Rosenbaum M (1998). “Leptin”. The Scientist Magazine.
  7. Jump up^ Okie S (February 11, 2005). “Chapter 2: Obese Twins and Thrifty Genes”. Fed Up!: Winning the War Against Childhood Obesity. Joseph Henry Press, an imprint of the National Academies Press. ISBN 978-0-309-09310-1.
  8. Jump up^ Zhang, Y; Proenca, P; Maffei, M; Barone, M; Leopold, L; Friedman, JM. (1994). “Positional cloning of the mouse obese gene and its human homologue”. Nature 372 (6505): 425–432.doi:10.1038/372425a0. PMID 7984236.
  9. ^ Jump up to:a b Friedman, Jeffrey (2014). “Douglas Coleman (1931–2014) Biochemist who revealed biology behind obesity”. Nature 509 (7502): 564. doi:10.1038/509564a. PMID 24870535.
  10. Jump up^ Shaw Prize 2009
  11. Jump up^ King Faisal Prize 2013 for Medicine

A Metabolic Master Switch Underlying Human Obesity

Researchers find pathway that controls metabolism by prompting fat cells to store or burn fat

Aug 21, 2015  http://www.technologynetworks.com/Metabolomics/news.aspx?ID=182195

Researchers find pathway that controls metabolism by prompting fat cells to store or burn fat.

Obesity is one of the biggest public health challenges of the 21st century. Affecting more than 500 million people worldwide, obesity costs at least $200 billion each year in the United States alone, and contributes to potentially fatal disorders such as cardiovascular disease, type 2 diabetes, and cancer.

But there may now be a new approach to prevent and even cure obesity, thanks to a study led by researchers at MIT and Harvard Medical School. By analyzing the cellular circuitry underlying the strongest genetic association with obesity, the researchers have unveiled a new pathway that controls human metabolism by prompting our adipocytes, or fat cells, to store fat or burn it away.

“Obesity has traditionally been seen as the result of an imbalance between the amount of food we eat and how much we exercise, but this view ignores the contribution of genetics to each individual’s metabolism,” says senior author Manolis Kellis, a professor of computer science and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and of the Broad Institute.

New mechanism found

The strongest association with obesity resides in a gene region known as “FTO,” which has been the focus of intense scrutiny since its discovery in 2007. However, previous studies have failed to find a mechanism to explain how genetic differences in the region lead to obesity.

“Many studies attempted to link the FTO region with brain circuits that control appetite or propensity to exercise,” says first author Melina Claussnitzer, a visiting professor at CSAIL and instructor in medicine at Beth Israel Deaconess Medical Center and Harvard Medical School. “Our results indicate that the obesity-associated region acts primarily in adipocyte progenitor cells in a brain-independent way.”

To recognize the cell types where the obesity-associated region may act, the researchers used annotations of genomic control switches across more than 100 tissues and cell types. They found evidence of a major control switchboard in human adipocyte progenitor cells, suggesting that genetic differences may affect the functioning of human fat stores.

To study the effects of genetic differences in adipocytes, the researchers gathered adipose samples from healthy Europeans carrying either the risk or the non-risk version of the region. They found that the risk version activated a major control region in adipocyte progenitor cells, which turned on two distant genes, IRX3 and IRX5.

Control of thermogenesis

Follow-up experiments showed that IRX3 and IRX5 act as master controllers of a process known as thermogenesis, whereby adipocytes dissipate energy as heat, instead of storing it as fat. Thermogenesis can be triggered by exercise, diet, or exposure to cold, and occurs both in mitochondria-rich brown adipocytes that are developmentally related to muscle, and in beige adipocytes that are instead related to energy-storing white adipocytes.

“Early studies of thermogenesis focused primarily on brown fat, which plays a major role in mice, but is virtually nonexistent in human adults,” Claussnitzer says. “This new pathway controls thermogenesis in the more abundant white fat stores instead, and its genetic association with obesity indicates it affects global energy balance in humans.”

The researchers predicted that a genetic difference of only one nucleotide is responsible for the obesity association. In risk individuals, a thymine (T) is replaced by a cytosine (C) nucleobase, which disrupts repression of the control region and turns on IRX3 and IRX5. This then turns off thermogenesis, leading to lipid accumulation and ultimately obesity.

By editing a single nucleotide position using the CRISPR/Cas9 system — a technology that allows researchers to make precise changes to a DNA sequence — the researchers could switch between lean and obese signatures in human pre-adipocytes. Switching the C to a T in risk individuals turned off IRX3 and IRX5, restored thermogenesis to non-risk levels, and switched off lipid storage genes.

“Knowing the causal variant underlying the obesity association may allow somatic genome editing as a therapeutic avenue for individuals carrying the risk allele,” Kellis says. “But more importantly, the uncovered cellular circuits may allow us to dial a metabolic master switch for both risk and non-risk individuals, as a means to counter environmental, lifestyle, or genetic contributors to obesity.”

Success in human and mouse cells

The researchers showed that they could indeed manipulate this new pathway to reverse the signatures of obesity in both human cells and mice.

In primary adipose cells from either risk or non-risk individuals, altering the expression of either IRX3 or IRX5 switched between energy-storing white adipocyte functions and energy-burning beige adipocyte functions.

Similarly, repression of IRX3 in mouse adipocytes led to dramatic changes in whole-body energy balance, resulting in a reduction of body weight and all major fat stores, and complete resistance to a high-fat diet.

“By manipulating this new pathway, we could switch between energy storage and energy dissipation programs at both the cellular and the organismal level, providing new hope for a cure against obesity,” Kellis says.

The researchers are currently establishing collaborations in academia and industry to translate their findings into obesity therapeutics. They are also using their approach as a model to understand the circuitry of other disease-associated regions in the human genome.

Flipping a Genetic Switch on Obesity?

Illustration of a DNA switchWhen weight loss is the goal, the equation seems simple enough: consume fewer calories and burn more of them exercising. But for some people, losing and keeping off the weight is much more difficult for reasons that can include a genetic component. While there are rare genetic causes of extreme obesity, the strongest common genetic contributor discovered so far is a variant found in an intron of the FTO gene. Variations in this untranslated region of the gene have been tied to differences in body mass and a risk of obesity [1]. For the one in six people of European descent born with two copies of the risk variant, the consequence is carrying around an average of an extra 7 pounds [2].

Now, NIH-funded researchers reporting in The New England Journal of Medicine [3] have figured out how this gene influences body weight. The answer is not, as many had suspected, in regions of the brain that control appetite, but in the progenitor cells that produce white and beige fat. The researchers found that the risk variant is part of a larger genetic circuit that determines whether our bodies burn or store fat. This discovery may yield new approaches to intervene in obesity with treatments designed to change the way fat cells handle calories.

The team—led by Melina Claussnitzer of Beth Israel Deaconess Medical Center, Boston, and Manolis Kellis of the Massachusetts Institute of Technology (MIT), Cambridge—started with a basic question: where in the body does this variant act to influence weight? For the answer, the team turned to the NIH-funded Roadmap Epigenomics Project. There, they found comprehensive data on 127 human cell types and the occurrence of common chemical modifications that act like volume knobs to turn gene activity “up” or “down” based on changes in the way DNA is packaged. While the FTO gene is active in the human brain, the team couldn’t connect any differences there with obesity.

They began to wonder whether this obesity-risk variant affected FTO at all (and prior studies had suggested this [4]). Maybe it operated at a distance to change the expression of other protein-coding genes? Sure enough, further study in fat collected from patients showed that the obesity risk variant works in those progenitor cells to control the activity of two other genes, IRX3 andIRX5, both found quite a distance away.

The fat in people with the obesity risk variant and greater expression of IRX3 and IRX5 genes contains fewer beige cells than normal. Beige cells, which were discovered just three years ago [5], are produced sometimes by fat cell progenitors to burn rather than stockpile energy. This new evidence suggests that beige fat may play an unexpectedly important role in protecting against obesity.

Using a method they developed last year [6], the researchers traced the effects of the obesity risk variant to a single nucleotide change—a small typo in the DNA sequence that changes a “T” to a “C.” They then used the nifty CRISPR-Cas genome editing system (see Copy-Editing the Genome) to switch between this obesity risk variant and the protective variant in human cells. As the researchers did this, they saw fat cells turn energy-burning heat production off and back on again. In other words, the obesity signature in the cells could be turned on and off at the flip of this genetic switch!

They also showed in mice that the shift toward energy-burning beige cells led to weight loss. Animals engineered in a way that blocked Irx3 expression in adipose tissue became significantly thinner with no change in their eating or exercise habits. This new collection of evidence suggests that treatments designed to program fat cells to burn more energy (such as antagonists against the IRX3 or IRX5 proteins) might have similar benefits in people, and the researchers are working with collaborators in academia and industry to pursue this line of investigation.

This is a great example of how discoveries about genetic factors in common disease, uncovered by applying the genome-wide association study (GWAS) approach to large numbers of affected and unaffected individuals, are revealing critical and previously unknown pathways in human biology and medicine. This case also points out how our terminology may need attention, however; for the last several years, this genetic variant for obesity has been called “the FTO variant,” perhaps it should now be called “the IRX3/5 variant.”

Genes, of course, are only part of the story. It’s still important to eat healthy, limit your portions, and maintain a regular exercise program. Leading an active lifestyle both keeps weight down and improves the overall sense of well being.

References:

[1] FTO genotype is associated with phenotypic variability of body mass index.Yang J, Loos RJ, Powell JE, TM, Frayling TM, Hirschhorn JN, Goddard ME, Visscher PM, et al. Nature. 2012 Oct 11;490(7419):267-72.

[2] A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Frayling TM, Timpson NJ, Weedon MN, Morris AD, Smith GD, Hattersley AT, McCarthy MI, et al. Science. 2007 May 11;316(5826):889-94.

[3] FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. Claussnitzer M, Dankel SN, Kim KH, Quon G, Meuleman W, Haugen C, Glunk V, Sousa IS, Beaudry JL, Puviindran V, Abdennur NA, Liu J, Svensson PA, Hsu YH, Drucker DJ, Mellgren G, Hui CC, Hauner H, Kellis M. N Engl J Med. 2015 Aug 19. [Epub ahead of print]

[4] Obesity-associated variants within FTO form long-range functional connections with IRX3. Smemo S, Tena JJ, Kim KH, Hui CC, Gomez-Skarmeta JL, Nobrega MA, et al. Nature 2014 Mar 20; 507(7492):371-375.

[5] Beige adipocytes are a distinct type of themogenic fat cell in mouse and human. Wu J, Boström P, Sparks LM, Schrauwen P, Spiegelman BM. Cell 2012 Jul 20:150(2):366-376.

[6] Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms. Claussnitzer M, Dankel SN, Klocke Mellgren G, Hauner H, Laumen H, et al. Cell. 2014 Jan 16;156(1-2):343-58.

Links:

Manolis Kellis (Massachusetts Institute of Technology, Cambridge)

What are overweight and obesity? (National Heart, Lung, and Blood Institute/NIH)

NIH Roadmap Epigenomics Project

NIH Support: National Human Genome Research Institute; National Institute of General Medical Sciences

MiR-93 Controls Adiposity via Inhibition of Sirt7 and Tbx3

CELL REPORTS · AUGUST 2015
Impact Factor: 8.36 · DOI: 10.1016/j.celrep.2015.08.006 

https://www.researchgate.net/publication/281394525_MiR-93_Controls_Adiposity_via_Inhibition_of_Sirt7_and_Tbx3

Conquering obesity has become a major socioeconomic challenge. Here, we show that reduced expression of the miR-25-93-106b cluster, or miR-93 alone, increases fat mass and, subsequently, insulin resistance. Mechanistically, we discovered an intricate interplay between enhanced adipocyte precursor turnover and increased adipogenesis. First, miR-93 controls Tbx3, thereby limiting self-renewal in early adipocyte precursors. Second, miR-93 inhibits the metabolic target Sirt7, which we identified as a major driver of in vivo adipogenesis via induction of differentiation and maturation of early adipocyte precursors. Using mouse parabiosis, obesity in mir-25-93-106b(-/-) mice could be rescued by restoring levels of circulating miRNA and subsequent inhibition of Tbx3 and Sirt7. Downregulation of miR-93 also occurred in obese ob/ob mice, and this phenocopy of mir-25-93-106b(-/-) was partially reversible with injection of miR-93 mimics. Our data establish miR-93 as a negative regulator of adipogenesis and a potential therapeutic option for obesity and the metabolic syndrome.

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Diet and Exercise

Writer and Curator: Larry H. Bernstein, MD, FCAP 

 

Introduction

In the last several decades there has been a transformation in the diet of Americans, and much debate about obesity, type 2 diabetes mellitus, hyperlipidemia, and the transformation of medical practice to a greater emphasis on preventive medicine. This occurs at a time that the Western countries are experiencing a large portion of the obesity epidemic, which actually diverts attention from a larger share of malnutrition in parts of Africa, Asia, and to a greater extent in India. This does not mean that obesity or malnutrition is exclusively in any parts of the world. But there is a factor at play that involves social factors, poverty, education, cognition, anxiety, and eating behaviors, food preferences and food balance, and activities of daily living. The epidemic of obesity also involves the development of serious long term health problems, such as, type 2 diabetes mellitus, sarcopenia, fracture risk, pulmonary disease, sleep apnea in particular, and cardiovascular and stroke risk. Nevertheless, this generation of Western society is also experiencing a longer life span than its predecessors. In this article I shall explore the published work on diet and exercise.

 

‘‘Go4Life’’ exercise counseling, accelerometer feedback, and activity levels in older people

Warren G. Thompson, CL Kuhle, GA Koepp, SK McCrady-Spitzer, JA Levine
Archives of Gerontology and Geriatrics 58 (2014) 314–319
http://dx.doi.org/10.1016/j.archger.2014.01.004

Older people are more sedentary than other age groups. We sought to determine if providing an accelerometer with feedback about activity and counseling older subjects using Go4Life educational material would increase activity levels. Participants were recruited from independent living areas within assisted living facilities and the general public in the Rochester, MN area. 49 persons aged 65–95(79.5 + 7.0 years) who were ambulatory but sedentary and overweight participated in this randomized controlled crossover trial for one year. After a baseline period of 2 weeks, group 1 received an accelerometer and counseling using Go4Life educational material (www.Go4Life.nia.nih.gov) for 24 weeks and accelerometer alone for the next 24 weeks. Group 2 had no intervention for the first 24 weeks and then received an accelerometer and Go4Life based counseling for 24 weeks. There were no significant baseline differences between the two groups. The intervention was not associated with a significant change inactivity, body weight, % body fat, or blood parameters (p > 0.05). Older (80–93) subjects were less active than younger (65–79) subjects (p = 0.003). Over the course of the 48 week study, an increase in activity level was associated with a decline in % body fat (p = 0.008). Increasing activity levels benefits older patients. However, providing an accelerometer and a Go4Life based exercise counseling program did not result in a 15% improvement in activity levels in this elderly population. Alternate approaches to exercise counseling may be needed in elderly people of this age range.

It is generally recommended that older adults be moderately or vigorously active for 150 min each week. A systematic review demonstrated that only 20–60% of older people are achieving this goal. These studies determined adherence to physical activity recommendations by questionnaire. Using NHANES data, it has been demonstrated that older people meet activity recommendations 62% of the time using a self-report questionnaire compared to 9.6% of the time when measured by accelerometry. Thus, objective measures suggest that older people are falling even more short of the goal than previously thought. Most studies have measured moderate and vigorous activity. However, light activity or NEAT (non-exercise activity thermogenesis) also has an important effect on health. For example, increased energy expenditure was associated with lower mortality in community-dwelling older adults. More than half of the extra energy expenditure in the high energy expenditure group came from non-exercise (light) activity. In addition to reduced total mortality, increased light and moderate activity has been associated with better cognitive function, reduced fracture rate (Gregg et al., 1998), less cardiovascular disease, and weight loss in older people. A meta-analysis of middle-aged and older adults has demonstrated greater all-cause mortality with increased sitting time. Thus, any strategy which can increase activity (whether light or more vigorous) has the potential to save lives and improve quality of life for older adults. A variety of devices have been used to measure physical activity.

A tri-axial accelerometer measures movement in three dimensions. Studies comparing tri-axial accelerometers with uniaxial accelerometers and pedometers demonstrate that only certain tri-axial accelerometers provide a reliable assessment of energy expenditure. This is usually due to failure to detect light activity. Since light activity accounts for a substantial portion of older people’s energy expenditure, measuring activity with a questionnaire or measuring steps with a pedometer do not provide an accurate reflection of activity in older people.

A recent review concluded that there is only weak evidence that physical activity can be improved. Since increasing both light and moderate activity benefit older people, studies demonstrating that physical activity can be improved are urgently needed. Since accelerometry is the best way to accurately assess light activity, we performed a study to determine if an activity counseling program and using an accelerometer which gives feedback on physical activity, can result in an increase in light and moderate activity in older people. We also sought to determine whether counseling and accelerometer feedback would result in weight loss, change in % body fat, glucose, hemoglobin A1c, insulin, and fasting lipid profile.

The main results of the study are both the experimental and control group lost weight (about 1 kg) at 6months (p = 0.04 and 0.02, respectively). The experimental group was less active at 6 months but not significantly while the control group was significantly less active at 6 months (p = 0.006) than at baseline. The experimental group had a modest decline in cholesterol (p = 0.03) and an improvement in Get Up & go time (p = 0.03) while the control group had a slight improvement in HgbA1c (p = 0.01). However, the main finding of the study was that there were no differences between the two groups on any of these variables. Thus, providing this group of older participants with an accelerometer and Go4Life based counseling resulted in no increase in physical activity, weight loss or change in glucose, lipids, blood pressure, or body fat. There were no differences within either group or between groups from 6 to 12 months on any of the variables (data not shown). While age was correlated with baseline activity, it did not affect activity change indicating that younger participants did not respond to the program better than older participants. Performance on the Get Up and Go test and season of the year did not influence the change in activity. There were no differences in physical activity levels at 3 or 9 months.

There was a significant correlation (r = -0.38, p = 0.006) between change in activity and change in body fat over the course of the study. Those subjects (whether in the experimental or control group) who increased their activity over the course of the year were likely to have a decline in % body fat over the year while those whose activity declined were likely to have increased %body fat. There was no correlation between change in activity and any of the other parameters including weight and waist circumference (data not shown).

Older adults are the fastest growing segment of the population in the US, but few meet the minimum recommended 30 min of moderate activity on 5 days or more per week (Centers for Disease Control and Prevention, 2002). Our study found that within the geriatric population, activity declines as people age. We saw a 2.4% decline per year cross-sectionally. This finding agrees with a recent cohort study (Bachman et al., 2014). In that study, the annual decline accelerated with increasing age. Thus, there is a need to increase activity particularly in the oldest age groups. The United States Preventive Services Task Force concluded that the evidence that counseling improves physical activity is weak (Moyer and US Preventive Services Task Force, 2012). The American Heart Association reached similar conclusions (Artinian et al., 2010). Thus, new ways of counseling older patients to counter the natural decline in activity with age are urgently needed.

Applying health behavior theory to multiple behavior change: Considerations and approaches

Seth M. Noar, Melissa Chabot, Rick S. Zimmerman
Preventive Medicine 46 (2008) 275–280
http://dx.doi.org:/10.1016/j.ypmed.2007.08.001

Background.There has been a dearth of theorizing in the area of multiple behavior change. The purpose of the current article was to examine how health behavior theory might be applied to the growing research terrain of multiple behavior change. Methods. Three approaches to applying health behavior theory to multiple behavior change are advanced, including searching the literature for potential examples of such applications. Results. These three approaches to multiple behavior change include

(1) a behavior change principles approach;

(2) a global health/behavioral category approach, and

(3) a multiple behavioral approach.

Each approach is discussed and explicated and examples from this emerging literature are provided. Conclusions. Further study in this area has the potential to broaden our understanding of multiple behaviors and multiple behavior change. Implications for additional theory-testing and application of theory to interventions are discussed.

Many of the leading causes of death in the United States are behavior-related and thus preventable. While a number of health behaviors are a concern individually, increasingly the impact of multiple behavioral risks is being appreciated. As newer initiatives funded by the National Institutes of Health and Robert Wood Johnson Foundation begin to stimulate research in this important area, a critical question emerges: How can we understand multiple health behavior change from a theoretical standpoint? While multiple behavior change interventions are beginning to be developed and evaluated, to date there have been few efforts to garner a theory-based understanding of the process of multiple health behavior change. Given that so little theoretical work currently exists in this area, our main purpose is to advance the conversation on how health behavior theory can help us to achieve a greater understanding of multiple behavior change. The approaches discussed have implications for both theory-testing as well as intervention design.

A critical question that must be asked, is whether there is a common set of principles of health behavior change that transcend individual health behaviors. This is an area where much data already exists, as health behavior theories have been tested across numerous health behaviors.The integration of findings from studies across diverse behavioral areas, is not what it could be. Godin and Kok (1996) reviewed studies of the TPB applied to numerous health-related behaviors. Across seven categories of health behaviors, they found TPB components to offer similar prediction of intention but inconsistent prediction of behavior.They concluded that the nature of differing health behaviors may require additional constructs to be added to the TPB, such as actual (versus perceived) behavioral control. Prochaska et al. (1994) examined decisional balance across stages of change for 12 health-related behaviors. Similar patterns were found across nearly all of these health behaviors, with the “pros” of changing generally increasing across the stages, the “cons” decreasing, and a pro/con crossover occurring in the contemplation or preparation stages of change. Prochaska et al. (1994) concluded that clear commonalties exist across these differing health behaviors which were examined in differing samples. Finally, Rosen (2000) examined change processes from the TTM across six behavioral categories, examining whether the trajectory of change processes is similar or different across stages of change in those health areas. He found that for smoking cessation, cognitive change processes were used more in earlier stages of change than behavioral processes, while for physical activity and dietary change, both categories of change processes increased together.

A second approach is the following: Rather than applying theoretical concepts to specific behaviors, such concepts might be applied at the general or global level. A general orientation toward health may not lead directly to specific health behaviors, but it may increase the chances of particular health-related attitudes, which may in turn lead to specific health behaviors. In fact, although Ajzen and Timko (1986) found general health attitudes to be poor predictors of behavior, such attitudes were significantly related to specific health attitudes and perceived behavioral control over specific behaviors. It is likely that when we consider multiple behaviors that we may discover an entire network of health attitudes and beliefs that are interrelated. In fact, studies of single behaviors essentially take those behaviors out of the multi-attitude and multi-behavioral context in which they are embedded. For instance, although attitudes toward walking may be a better predictor of walking behavior than attitudes toward physical activity, walking behavior is part of a larger “physical activity” behavioral category. While predicting that particular behavior may be best served by the specific measure, the larger category is both relevant and of interest. Thus, it may be that there are higher order constructs to be understood here.

A third approach is a multiple behavioral approach, or one which focuses on the linkages among health behaviors. It shares some similarities to the approach just described. Here the focus is more strictly on how particular  interventions were superior to comparison groups for 21 of 41 (51%) studies (3 physical activity, 7 diet, 11 weight loss/physical activity and diet). Twenty-four studies had indeterminate results, and in four studies the comparison conditions outperformed eHealth interventions. Conclusions: Published studies of eHealth interventions for physical activity and dietary behavior change are in their infancy. Results indicated mixed findings related to the effectiveness of eHealth interventions. Interventions that feature interactive technologies need to be refined and more rigorously evaluated to fully determine their potential as tools to facilitate health behavior change.

 

A prospective evaluation of the Transtheoretical Model of Change applied to exercise in young people 

Patrick Callaghan, Elizabeth Khalil, Ioannis Morres
Intl J Nursing Studies 47 (2010) 3–12
http://dx.doi.org:/10.1016/j.ijnurstu.2009.06.013

Objectives:To investigate the utility of the Transtheoretical Model of Change in predicting exercise in young people. Design: A prospective study: assessments were done at baseline and follow-up 6 months later. Method: Using stratified random sampling 1055 Chinese high school pupils living in Hong Kong, 533 of who were followed up at 6 months, completed measures of stage of change (SCQ), self-efficacy (SEQ), perceptions of the pros and cons of exercising (DBQ) and processes of change (PCQ). Data were analyzed using one-way ANOVA, repeated measures ANOVA and independent sample t tests.
Results:The utility of the TTM to predict exercise in this population is not strong; increases in self-efficacy and decisional balance discriminated between those remaining active at baseline and follow-up, but not in changing from an inactive (e.g.,Precontemplation or Contemplation) to an active state (e.g.,Maintenance) as one would anticipate given the staging algorithm of the TTM.
Conclusion:The TTM is a modest predictor of future stage of change for exercise in young Chinese people. Where there is evidence that TTM variables may shape movement over time, self-efficacy, pros and behavioral processes of change appear to be the strongest predictors

 

A retrospective study on changes in residents’ physical activities, social interactions, and neighborhood cohesion after moving to a walkable community

Xuemei Zhu,Chia-Yuan Yu, Chanam Lee, Zhipeng Lu, George Mann
Preventive Medicine 69 (2014) S93–S97
http://dx.doi.org/10.1016/j.ypmed.2014.08.013

Objective. This study is to examine changes in residents’ physical activities, social interactions, andneighbor-hood cohesion after they moved to a walkable community in Austin, Texas.
Methods. Retrospective surveys (N=449) were administered in 2013–2014 to collect pre-and post-move data about the outcome variables and relevant personal, social, and physical environmental factors. Walkability of each resident’s pre-move community was measured using the Walk Score. T tests were used to examine the pre–post move differences in the outcomes in the whole sample and across subgroups with different physical activity levels, neighborhood conditions, and neighborhood preferences before the move. Results. After the move, total physical activity increased significantly in the whole sample and all subgroups except those who were previously sufficiently active; lived in communities with high walkability, social interactions, or neighborhood cohesion; or had moderate preference for walkable neighborhoods. Walking in the community increased in the whole sample and all subgroups except those who were previously sufficiently active, moved from high-walkability communities, or had little to no preference for walkable neighborhoods. Social interactions and neighborhood cohesion increased significantly after the move in the whole sample and all subgroups.
Conclusion.This study explored potential health benefits of a walkable community in promoting physically and socially active lifestyles, especially for populations at higher risk of obesity. The initial result is promising, suggesting the need for more work to further examine the relationships between health and community design using pre–post assessments.

 

Application of the transtheoretical model to identify psychological constructs influencing exercise behavior: A questionnaire survey

Young-Ho Kim
Intl J Nursing Studies 44 (2007) 936–944
http://dx.doi.org:/10.1016/j.ijnurstu.2006.03.008

Background: Current research on exercise behavior has largely been attempted to identify the relationship between psychological attributes and the initiation or adherence of exercise behavior based on psychological theories. A limited data are available on the psychological predictors of exercise behavior in public health. Objectives: The present study examined the theorized association of TTM of behavior change constructs by stage of change for exercise behavior. Methods: A total of 228 college students selected from 2 universities in Seoul were surveyed. Four Korean-version questionnaires were used to identify the stage of exercise behavior and psychological attributes of adolescents. Data were analyzed by frequency analysis, MANOVA, correlation analysis, and discriminant function analysis.
Results: Multivariate F-test indicated that behavioral and cognitive processes of change, exercise efficacy, and pros differentiated participants across the stages of exercise behavior. Furthermore, exercise behavior was significantly correlated with the TTM constructs, and that overall classification accuracy across the stages of change was 61.0%. Conclusions:The present study supports the internal and external validity of the Transtheoretical Model for explaining exercise behavior. As this study highlights, dissemination must increase awareness but also influences perceptions regarding theoretically based and practically important exercise strategies for public health professionals.

 

 

Does more education lead to better health habits? Evidence from the school reforms in Australia?

Jinhu Li, Nattavudh Powdthavee
Social Science & Medicine 127 (2015) 83-91
http://dx.doi.org/10.1016/j.socscimed.2014.07.021

The current study provides new empirical evidence on the causal effect of education on health-related behaviors by exploiting historical changes in the compulsory schooling laws in Australia. Since World War II, Australian states increased the minimum school leaving age from 14 to 15 in different years. Using differences in the laws regarding minimum school leaving age across different cohorts and across different states as a source of exogenous variation in education, we show that more education improves people’s diets and their tendency to engage in more regular exercise and drinking moderately, but not necessarily their tendency to avoid smoking and to engage in more preventive health checks. The improvements in health behaviors are also reflected in the estimated positive effect of education on some health outcomes. Our results are robust to alternative measures of education and different estimation methods.

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Anorexia Nervosa and Related Eating Disorders

Writer and Curator: Larry H. Bernstein, MD, FCAP 

 

Introduction

Anorexia nervosa is a stress related disorder that occurs mainly in women, closely related to bulimia, and is related to self-esteem, or to a preoccupation with how the individual would like to see themselves. It is not necessarily driven by conscious motive, but lies in midbrain activities that govern hormonal activity and social behavior

 

Eating disorders

Christopher G Fairburn, Paul J Harrison
Lancet 2003; 361: 407–16

Eating disorders are an important cause of physical and psychosocial morbidity in adolescent girls and young adult women. They are much less frequent in men. Eating disorders are divided into three diagnostic categories: anorexia nervosa, bulimia nervosa, and the atypical eating disorders. However, the disorders have many features in common and patients frequently move between them, so for the purposes of this Seminar we have adopted a transdiagnostic perspective. The cause of eating disorders is complex and badly understood. There is a genetic predisposition, and certain specific environmental risk factors have been implicated. Research into treatment has focused on bulimia nervosa, and evidence-based management of this disorder is possible. A specific form of cognitive behavior therapy is the most effective treatment, although few patients seem to receive it in practice. Treatment of anorexia nervosa and atypical eating disorders has received remarkably little research attention.

Eating disorders are of great interest to the public, of perplexity to researchers, and a challenge to clinicians. They feature prominently in the media, often attracting sensational coverage. Their cause is elusive, with social, psychological, and biological processes all seeming to play a major part, and they are difficult to treat, with some patients actively resisting attempts to help them.

Anorexia nervosa and bulimia nervosa are united by a distinctive core psychopathology, which is essentially the same in female and male individuals; patients overevaluate their shape and weight. Whereas most of us assess ourselves on the basis of our perceived performance in various domains—eg, relationships, work, parenting, sporting prowess—patients with anorexia nervosa or bulimia nervosa judge
their self-worth largely, or even exclusively, in terms of their shape  and weight and their ability to control them. Most of the other features
of these disorders seem to be secondary to this psychopathology and to its consequences—for example, self-starvation. Thus, in anorexia nervosa there is a sustained and determined pursuit of weight loss and, to the extent that this pursuit is successful, this behavior is not seen as a problem. Indeed, these patients tend to view their low weight as an accomplishment rather than an affliction. In bulimia nervosa, equivalent attempts to control shape and weight are undermined by frequent episodes of uncontrolled overeating (binge eating) with the result that patients  often describe themselves as failed anorexics.  The core psychopathology has other manifestations; for example,  many patients mislabel certain adverse physical and emotional states as feeling fat, and some repeatedly scrutinize aspects of their shape,
which could contribute to them overestimating their size.

Panel 1: Classification and diagnosis of eating disorders

Definition of an eating disorder

  • There is a definite disturbance of eating habits or weight- control behavior
  • Either this disturbance, or associated core eating disorder features, results in a clinically significant impairment of physical health or psychosocial functioning (core eating disorder features comprise the disturbance of eating and any associated over-evaluation of shape or weight)
  • The behavioral disturbance should not be secondary to any general medical disorder or to any other psychiatric condition

Classification of eating disorders

  • Anorexia nervosa
  • Bulimia nervosa
  • Atypical eating disorders (or eating disorder not otherwise specified)

Principal diagnostic criteria

  • Anorexia nervosa
  1. Over-evaluation of shape and weight—ie, judging self-worth largely, or exclusively, in terms of shape and weight
  2. Active maintenance of an unduly low bodyweight—eg, body-mass index 17·5 kg/m2
  3. Amenorrhea in post-menarche females who are not taking an oral contraceptive. The value of the amenorrhea criterion can be questioned since most female patients who meet the other two diagnostic criteria are amenorrheic, and those who menstruate
    seem to resemble closely those who do not
  • Bulimia nervosa
  1. Over-evaluation of shape and weight—ie, judging self-worth largely,
    or exclusively, in terms of shape and weight
  2. Recurrent binge eating—i.e., recurrent episodes of uncontrolled overeating
  3. Extreme weight-control behavior—e.g., strict dietary restriction, frequent self-induced vomiting or laxative misuse

Diagnostic criteria for anorexia nervosa are not met

  • Atypical eating disorders

Eating disorders of clinical severity that do not conform to the diagnostic criteria for anorexia nervosa or bulimia nervosa

Research into the pathogenesis of the eating disorders has focused almost exclusively on anorexia nervosa and bulimia nervosa. There is undoubtedly a genetic predisposition and a range of environmental risk factors, and there is some information with respect to the identity and relative importance of these contributions. However, virtually nothing is known about the individual causal processes involved, or about how they interact and vary across the development and maintenance of the disorders.

 

Panel 3: Main risk factors for anorexia nervosa and bulimia nervosa

  • General factors
  1. Female
  2. Adolescence and early adulthood
  3. Living in a Western society
  • Individual-specific factors

Family history

  • Eating disorder of any type
  • Depression
  • Substance misuse, especially alcoholism (bulimia nervosa)
  • Obesity (bulimia nervosa)

Premorbid experiences

  • Adverse parenting (especially low contact, high expectations, parental discord)
  • Sexual abuse
  • Family dieting
  • Critical comments about eating, shape, or weight from family and others
  • Occupational and recreational pressure to be slim Premorbid characteristics

Low self-esteem

  • Perfectionism (anorexia nervosa and to a lesser extent bulimia nervosa)
  • Anxiety and anxiety disorders
  • Obesity (bulimia nervosa)
  • Early menarche (bulimia nervosa)

There has been extensive research into the neurobiology of eating disorders. This work has focused on neuropeptide and monoamine (especially 5-HT) systems thought to be central to the physiology of eating and weight regulation. Of the various central and peripheral abnormalities reported, many are likely to be secondary to the aberrant eating and associated weight loss. However, some aspects of 5-HT function remain abnormal after recovery, leading to speculation that there is a trait monoamine abnormality that might predispose to the development of eating disorders or to associated characteristics such as perfectionism. Furthermore, normal dieting in healthy women alters central 5-HT function, providing a potential mechanism by which eating disorders might be precipitated in women vulnerable for other reasons.

Specific psychological theories have been proposed to account for the development and maintenance of eating disorders. Most influential in terms of treatment have been cognitive behavioral theories. In brief, these theories propose that the restriction of food intake that characterizes the onset of many eating disorders has two main origins, both of which may operate. The first is a need to feel in control of life, which gets displaced onto controlling eating. The second is over-evaluation of shape and weight in those who have been sensitized to their appearance. In both instances, the resulting dietary restriction is highly reinforcing. Subsequently, other processes begin to
operate and serve to maintain the eating disorder.

 

Depression, coping, hassles, and body dissatisfaction: Factors associated with disordered eating

Rose Marie Ward, M. Cameron Hay
Eating Behaviors 17 (2015) 14–18
http://dx.doi.org/10.1016/j.eatbeh.2014.12.002

The objective was to explore what predicts first-year college women’s disordered eating tendencies when they arrive on campus. The 215 first-year college women completed the surveys within the first 2 weeks of classes. A structural model examined how much the Helplessness, Hopelessness, Haplessness Scale, the Brief COPE, the Brief College Student Hassle Scale, and the Body Shape Questionnaire predicted eating disordered tendencies (as measured by the Eating Attitudes Test). The Body Shape Questionnaire, the Helplessness, Hopelessness, Haplessness Scale (inversely), and the Denial subscale of the Brief COPE significantly predicted eating disorder tendencies in first-year college women. In addition, the Planning and Self-Blame subscales of the Brief COPE and the Helplessness, Hopelessness, Haplessness Scale predicted the Body Shape Questionnaire. In general, higher levels on the Helplessness, Hopelessness, Haplessness Scale and higher levels on the Brief College Student Hassle Scale related to higher levels on the Brief COPE. Coping seems to remove the direct path from stress and depression to disordered eating and body dissatisfaction.

Eating disorders and disordered eating on college campuses are a pervasive problem. Research estimates that approximately 8–13.5% of college women meet the criteria for clinically diagnosed eating disorders such as anorexia nervosa, bulima nervosa, or eating disorders not otherwise specified. In addition, negative moods and stress seem to relate eating disorders. Diagnosable eating disorders emerge in the broader context of disordered eating, that is — engaging in practices such as restricting calories, eating less fat, skipping meals, using nonprescription diet pills, using laxatives, or inducing vomiting. Whereas disordered eating is broadly associated with the dynamics of human development in adolescence in the United States and the socio-cultural pressure to be thin, college environments may particularly predispose young women to disordered eating. In a national survey, 57% of female college students reported trying to lose weight, while only 38% of female college students categorized themselves as overweight.

The mean for the overall EAT scale was 8.89 (SD=9.26, mode=2, median = 6, range 0 to 60). Over 13% (n = 22) of the sample met the criteria for potential eating disorders with overall scores of 20 or greater. One primary model was tested using the quantitative measurement data. The model fit the data, χ2 (n = 191, 72) = 89.33, p = .08, CFI N .99, TLI = .99, and RMSEA = .035.

Note: Only significant paths shown; *p < .05; **p < .01; ***p < .001; HHH = Helplessness, Hopelessness, Haplessness Scale; Hassles = Brief College Student Hassle Scale; EAT = Eating Attitudes Test-26; BSQ = Body Satisfaction Questionnaire; CFI = Comparative Fit Index; TLI = Tucker-Lewis Index; RMSEA = Root Mean Squared Error of Approximation.

Structural modeling predicting eating disorder tendencies

Structural modeling predicting eating disorder tendencies

Structural modeling predicting eating disorder tendencies. Note: Only significant paths shown; *p < .05; **p < .01; **p < .001; HHH = Helplessness, Hopelessness, Haplessness Scale; Hassles = Brief College Student Hassle Scale; EAT = Eating Attitudes Test-26; BSQ = Body Satisfaction Questionnaire; CFI = Comparative Fit Index; TLI= Tucker–Lewis Index; RMSEA = Root Mean Squared Error of Approximation.

By identifying the risk factors through research, interventions can be developed that empower people to take control of their own eating behavior. This kind of intervention is supported by the finding that those students with more agentive, active coping styles, or who did not report frequent experiences of helplessness, haplessness, and hopelessness were less likely to have disordered eating behaviors. Whereas active coping has been associated with lower disordered eating in some studies (e.g., Ball & Lee, 2000), others suggest a more complicated relationship between denial or avoidant coping and disordered eating.

 

The cognitive behavioral model for eating disorders: A direct evaluation in children and adolescents with obesity

Veerle Decaluwe, Caroline Braet
Eating Behaviors 6 (2005) 211–220
http://dx.doi.org:/10.1016/j.eatbeh.2005.01.006

Objective: The cognitive behavioural model of bulimia nervosa. The clinical features and maintenance of bulimia nervosa. In K.D. Brownell, and J.P. Foreyt (Eds.), Handbook of eating disorders: physiology, psychology and treatment of obesity, anorexia and bulimia (pp. 389–404). New York: Basic Books.] provides the theoretical framework for cognitive behavior therapy of Bulimia Nervosa. For a long time it was assumed that the model can also be used to understand the mechanism of binge eating among obese individuals. The present study aimed to test whether the specific hypotheses derived from the cognitive behavioral theory of bulimia nervosa are also valid for children and adolescents with obesity. Method: The prediction of the model was tested using structural equation modeling. Data were collected from 196 children and adolescents.  Results: In line with the model, the results suggest that a lower self-esteem predicts concerns about eating, weight and shape, which in turn predict dietary restraint, which then further is predictive of binge eating.
Discussion: The findings suggest that the mechanisms specified in the model of bulimia nervosa is also operational among obese youngsters. The cognitive behavioral model of Bulimia Nervosa (BN), outlined by Fairburn, Cooper, and Cooper (1986), provides the theoretical framework for cognitive behavior therapy of BN (Fairburn, Marcus, & Wilson, 1993; Wilson, Fairburn, & Agras, 1997). According to this model, over-evaluation of eating, weight and shape plays a central role in the maintenance of BN. It is assumed that over-concern in combination with a low self-esteem can lead to dietary restraint (e.g. strict dieting and other weight control behavior). However, the rigid and unrealistic dietary rules are difficult to follow and the eating behavior is seen as a failure. Moreover, minor dietary slips are considered as evidence of lack of control and can lead to an all-or-nothing reaction in which all efforts to control eating are abandoned. This condition makes people vulnerable to binge eating. In order to minimize weight gain as a result of overeating, some patients practice compensatory purging (compensatory vomiting or laxative misuse).

The present study aimed to directly evaluate the model among a population of children and adolescents suffering from obesity. It is justified to study this model in a group at-risk. Binge eating is [V. Decaluwe´, C. Braet / Eating Behaviors 6 (2005) 211–220] not restricted to adulthood and is recognized among children with obesity as well (Decaluwe´ & Braet, 2003). Even in childhood, associated eating and shape concerns and comorbid psychopathology are manifest. Until now, little is known about how the risk factors for BED operate. A case-control study by Fairburn et al. (1998) reported a number of adverse factors in childhood, carrying a higher risk of developing BED, including negative self-evaluation, parental depression, adverse experiences (sexual or physical abuse and parental problems), overweight and repeated exposure to negative comments about shape, weight and eating. Moreover, it seems that childhood obesity is not only a risk factor for developing BED, but also one of the risk factors for the development of BN (Fairburn, Welch, Doll, Davies, & O’Connor, 1997). If Fairburn’s model is able to predict binge eating in an obese population, we can discover how the risk factors are related to one another and how they are operating to predict disordered eating among obese youngsters.

To conclude, in the present study, we were interested whether the cognitive behavioral theory would predict disordered eating in a young obese population. Because the study focuses on subjects at risk for developing binge-eating problems, BED or BN, we considered the cognitive behavioral theory as a risk factor model for eating disorders rather than a model for the maintenance of eating disorders.

  1. Method

2.1. Design

The prediction of the models was evaluated using structural equation modeling (LISREL 8.50; Jo¨reskog & So¨rbom, 2001). The dependent variables were binge eating, over-evaluation of eating, shape and weight, and dietary restraint. The independent variable was self-esteem. Purging behavior was not included in the structural equation modeling since binge eating among children occurs in the absence of compensatory behavior. Next, it is worth noting that the concept of self-esteem is implicit in the original cognitive model of BN. In order to compare the present research with the study of Byrne and McLean (2002), self-esteem was included in the evaluation of the model.

A sample of 196 children and adolescents with obesity (78 boys and 118 girls) between the ages of 10 and 16 participated in the study (M=12.73 years, SD=1.75). All subjects were seeking help for obesity. The sample consisted of children seeking inpatient or outpatient treatment. All children seeking inpatient or outpatient treatment between July 1999 and December 2001 were invited to participate. The response rate was 72%. Children younger than 10 or older than 16 and mentally retarded children were excluded from the study. All participating children obtained a diagnosis of primary obesity. The group had a mean overweight of 172.69% (SD=27.09) with a range of 120–253%. The study was approved by the local research ethics committee. The subjects were visited at their homes before they entered into treatment. Informed consent was obtained from both the children and their parents. Two subjects (1%), both female, met the full diagnostic criteria for BED and 18 subjects (9.2%) experienced at least one binge-eating episode over the previous three months (overeating with loss of control), but did not endorse all of the other DSM-IV criteria that are required for a diagnosis of BED.

To conclude, in the present study, we were interested whether the cognitive behavioral theory would predict disordered eating in a young obese population. Because the study focuses on subjects at risk for developing binge-eating problems, BED or BN, we considered the cognitive behavioral theory as a risk factor model for eating disorders rather than a model for the maintenance of eating disorders.

A two-step procedure was followed to construct the measurement model. We first conducted a confirmatory factor analysis on the variance–covariance matrix of the items of the exogenous construct (independent latent variable) b self-esteem Q. The construct b self-esteem Q is composed of 5 items of the Global self-worth subscale of the SPPA. Goodness-of-fit statistics were generated by the analysis. Items with poor loading (absolute t-value = 1.96) were removed. This resulted in a satisfactory model, χ2 (2)=6.23, p=0.04, GFI=0.97, AGFI=0.87 after omitting 1 item. The parameter estimates between the observed items and the latent variable ranged from 0.49 to 0.88.

Self-esteem was highly negatively correlated with over-evaluation of eating, weight and shape (standardized ϒ=-0.59, t=-5.05), indicating that higher levels of concerns about eating, weight and shape were associated with a lower self-esteem. Over-evaluation of eating, weight and shape, in turn, was shown to be significantly related with dietary restraint (standardized β=0.70, t=2.71), indicating that more concerns about eating, weight or shape were associated with higher levels of dietary restraint. Finally, dietary restraint was significantly associated with binge eating (standardized β=0.45, t=2.14), indicating that higher levels of dietary restraint were associated with a higher level of binge eating. The feedback from binge eating to over-evaluation of eating, weight and shape was not significant. Overall, the results appeared to suggest that a lower self-esteem predicts concerns over eating, weight and shape, which in turn predict dietary restraint. This would then be predictive of binge eating.

To our knowledge, this was the first study that directly evaluated the CBT model of BN among children. Overall, the model was found to be a good fit of the data. The main predictions of the model were confirmed. We can conclude that the CBT model provides a relatively valid explanation of the prediction of binge-eating problems in a young obese sample. Three findings supported the model and one finding did not confirm the model.

First, in line with the model, the construct self-esteem was a predictor of the over-evaluation of eating, weight and shape. This finding is also consistent with findings of Byrne and McLean (2002) and previous research in children and adolescents, which also found an association between over-concern with weight and shape and a lower self-esteem.

Second, the over-evaluation of eating, weight and shape, in turn, was a direct predictor of dietary restraint. Our findings were in line with prospective studies that found that thin-ideal internalization and body dissatisfaction (components of the over-evaluation of shape and weight) had a significant effect on dieting. Our findings also support the cross sectional study of Womble et al. (2001), who found a direct association between body dissatisfaction and dietary restraint among obese women. As in adults, children seem to respond in the same manner by dieting to lose weight. To our knowledge, the relationship between over-evaluation and dietary restraint has never been explored before among children with obesity.

Third, in accordance with the CBT model of BN, the key pathway between dietary restraint and binge eating was confirmed: higher levels of dietary restraint were associated with higher rates of binge eating. It seems that the subjects of this study were not able to maintain their dietary restraint.

 

Transdiagnostic Theory and Application of Family-Based Treatment for Youth With Eating Disorders

Katharine L. Loeb, James Lock, Rebecca Greif, Daniel le Grange
Cognitive and Behavioral Practice 19 (2012) 17-30

This paper describes the transdiagnostic theory and application of family-based treatment (FBT) for children and adolescents with eating disorders. We review the fundamentals of FBT, a transdiagnostic theoretical model of FBT and the literature supporting its clinical application, adaptations across developmental stages and the diagnostic spectrum of eating disorders, and the strengths and challenges of this approach, including its suitability for youth. Finally, we report a case study of an adolescent female with eating disorder not otherwise specified (EDNOS) for whom FBT was effective. We conclude that FBT is a promising outpatient treatment for anorexia nervosa, bulimia nervosa, and their EDNOS variants. The transdiagnostic model of FBT posits that while the etiology of an eating disorder is unknown, the pathology affects the family and home environment in ways that inadvertently allow for symptom maintenance and progression. FBT directly targets and resolves family level variables,  including secrecy, blame, internalization of illness, and extreme active or passive parental responses to the eating disorder. Future research will test these mechanisms, which are currently theoretical.

 

The Evolution of “Enhanced” Cognitive Behavior Therapy for Eating Disorders: Learning From Treatment Nonresponse

Zafra Cooper and Christopher G. Fairburn
Cognitive and Behavioral Practice 18 (2011) 394–402

In recent years there has been widespread acceptance that cognitive behavior therapy (CBT) is the treatment of choice for bulimia nervosa. The cognitive behavioral treatment of bulimia nervosa (CBT-BN) was first described in 1981. Over the past decades the theory and treatment have evolved in response to a variety of challenges. The treatment has been adapted to make it suitable for all forms of eating disorder—thereby making it “transdiagnostic” in its scope— and treatment procedures have been refined to improve outcome. The new version of the treatment, termed enhanced CBT (CBT-E) also addresses psychopathological processes “external” to the eating disorder, which, in certain subgroups of patients, interact with the disorder itself. In this paper we discuss how the development of this broader theory and treatment arose from focusing on those patients who did not respond well to earlier versions of the treatment.

In recent years there has been widespread acceptance that cognitive behavior therapy (CBT) is the treatment of choice for bulimia nervosa (National Institute for Health and Clinical Excellence, 2004; Wilson, Grilo, & Vitousek, 2007; Shapiro et al., 2007). The cognitive behavioral treatment of bulimia nervosa (CBT-BN) was first described in 1981 (Fairburn). Several years later, Fairburn (1985) described further procedural details along with a more complete exposition of the theory upon which the treatment was based (1986). This theory has since been extensively studied and the treatment derived from it, CBT-BN (Fairburn et al., 1993), has been tested in a series of treatment trials (e.g., Agras, Crow, et al., 2000; Agras, Walsh, et al., 2000; Fairburn, Jones, et al., 1993). A detailed treatment manual was published in 1993 (Fairburn, Jones, et al.). In 1997 a supplement to the manual was published (Wilson, Fairburn, & Agras) and the theory was elaborated in the same year (Fairburn).

According to the cognitive behavioral theory of bulimia nervosa, central to the maintenance of the disorder is the patient’s over-evaluation of shape and weight, the so-called “core psychopathology” [Fig. 1 – not shown – schematic form the core eating disorder maintaining mechanisms (modified from Fairburn, Cooper, & Shafran, 2003 )]. Most other features can be understood as stemming directly from this psychopathology, including the dietary restraint and restriction, the other forms of weight-control behavior, the various forms of body checking and avoidance, and the preoccupation with thoughts about shape, weight, and eating (Fairburn, 2008).

The only feature of bulimia nervosa that is not obviously a direct expression of the core psychopathology is binge eating. The cognitive behavioral theory proposes that binge eating is largely a product of a form of dietary restraint (attempts to restrict eating), which may or may not be accompanied by dietary restriction (actual undereating). Rather than adopting general guidelines about how they should eat, patients try to adhere to multiple demanding, and highly specific, dietary rules and tend to react in an extreme and negative fashion to the (almost inevitable) breaking of these rules.

A substantial body of evidence supports CBT-BN, and the findings indicate that CBTBN is the leading treatment. However, at best, half the patients who start treatment make a full and lasting response. Between 30% and 50% of patients cease binge eating and purging, and a further proportion show some improvement while others drop out of treatment or fail to respond. These findings led us to ask the question, “Why aren’t more people getting better?”

In the light of our experience with patients, we proposed that in certain patients one or more of four additional maintaining processes interact with the core eating disorder maintaining mechanisms and that when this occurs they constitute further obstacles to change. The first of these maintaining mechanisms concerns the influence of extreme perfectionism (“clinical perfectionism”). The second concerns difficulty coping with intense mood states (“mood intolerance”). Two other mechanisms concern the impact of unconditional and pervasive low self-esteem (“core low self-esteem”), and marked interpersonal problems (“interpersonal difficulties”).  This new theory represents an extension of the original theory illustrated in Fig. 1. Fig. 2 shows in schematic form both the core maintaining mechanisms and the four hypothesized additional mechanisms.

This program of work illustrates the value of focusing attention on those patients who benefit least from treatment. Doing so resulted in the enhanced form of CBT, which appears to be markedly more effective and more useful (in terms of the full range of patients treated) than its forerunner, CBT-BN.

 

A novel measure of compulsive food restriction in anorexia nervosa: Validation of the Self-Starvation Scale (SS)

Lauren R. Godier, Rebecca J. Park
Eating Behaviors 17 (2015) 10–13
http://dx.doi.org/10.1016/j.eatbeh.2014.12.004

The characteristic relentless self-starvation behavior seen in Anorexia Nervosa (AN) has been described as evidence of compulsivity,with increasing suggestion of transdiagnostic parallels with addictive behavior. There is a paucity of standardized self-report measures of compulsive behavior in eating disorders (EDs). Measures that index the concept of compulsive self-starvation in AN are needed to explore the suggested parallels with addictions. With this aima novel measure of self-starvation was developed (the Self-Starvation Scale, SS). 126 healthy participants, and 78 individuals with experience of AN, completed the new measure along with existing measures of eating disorder symptoms, anxiety and depression. Initial validation in the healthy sample indicated good reliability and construct validity, and incremental validity in predicting eating disorder symptoms. The psychometric properties of the SS scale were replicated in the AN sample. The ability of this scale to predict ED symptoms was particularly strong in individuals currently suffering from AN. These results suggest the SS may be a useful index of compulsive food restriction in AN. The concept of ‘starvation dependence’ in those with eating disorders, as a parallel with addiction, may be of clinical and theoretical importance.

The compulsive nature of Anorexia Nervosa (AN) has increasingly been compared to the maladaptive cycle of compulsive drug-seeking behavior (Barbarich-Marsteller, Foltin, & Walsh, 2011). Individuals with AN engage in persistent weight loss behavior, such as extreme self-starvation and excessive exercise, to modulate anxiety associated with ingestion of food, in a similar way to the use of mood altering drugs in substance dependence. Substance dependence is described as a persistent state in which there is a lack of control over compulsive drug-seeking, and lack of regard for the risk of serious negative consequences, which may parallel the relentlessness with which individuals with AN pursue weight loss despite profoundly negative physiological and psychological consequences.

Considering the parallels suggested between AN and substance dependence, it may be useful to use the concept of ‘dependence’ on starvation when measuring compulsive behaviors in eating disorders (EDs) such as AN. For that reason, a novel measure of self-starvation, the Self-Starvation Scale (SS) was derived, in part by adapting the Yale Food Addiction Scale (YFAS) (Gearhardt, Corbin, & Brownell, 2009) for this construct.

The set of online questionnaires was created using Bristol Online Surveys (BOS; Institute of Learning and Research Technology, University of Bristol, UK). In addition to the new measure described below, ED symptoms were measured using the Eating Disorder Examination-Questionnaire (EDE-Q) (Fairburn & Beglin, 2008), and the Clinical Impairment Assessment (CIA) (Bohn & Fairburn, 2008). Depression symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) (Kroenke, Spitzer, & Williams, 2001). Anxiety symptoms were measured using the Generalized Anxiety Disorder Assessment-7 (GAD-7) (Spitzer, Kroenke, Williams, & Lowe, 2006). The mirror image concept of ‘food addiction’ was measured using the YFAS (Gearhardt et al., 2009). Excessive exercise was measured using the Compulsive Exercise Test (CET) (Taranis, Touyz, & Meyer, 2011). Impulsivity was measured using the Barratt Impulsivity Scale-11 (BIS-11) (Patton, Stanford, & Barratt, 1995). Substance abuse symptoms were measured using the Leeds Dependence Questionnaire (LDQ) (Raistrick et al., 1994).

The results of this study suggest that using the criteria of dependence in capturing compulsive self-starvation behavior in AN may have some validity. The utility of this criteria in capturing compulsive behavior across disorders, including AN, suggests that compulsivity as a construct of behavior may have transdiagnostic application (Godier & Park, 2014; Robbins, Gillan, Smith, de Wit, & Ersche, 2012), on which disorder-specific themes are superimposed.

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Endothelial Dysfunction (release into the circulation of damaged endothelial cells) as A Risk Marker for Ischemia and MI

Reporter and Curator: Larry H Bernstein, MD, FCAP

Endothelial Dysfunction: An Early Cardiovascular Risk Marker in Asymptomatic Obese Individuals with Prediabete

AK Gupta, E Ravussin, DL Johannsen, AJ Stull,WT.Cefalu and WD Johnson at Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA Brit J Med & Med Res 2012; 2(3):413-423 [www.ScienceDomain.org]

provides an exceedingly interesting insight into the relationship between type 2 diabetes mellitus, obesity and risk for cardiovascular disease in patients who are asymptomatic prediabetics, defined as a fasting blood glucose between 1000 and 1240 mg/L, or a Hb A1c (may not accurate for African Americans) between 5.6 and 6.5.  They would be expected to show an abnormal 5-hr GTT.

Obesity is associated with the release from adipocytes of adiponectin, which it has been reported is countered by resistin.  We might also have the effect of the insulin secreting beta cell, that releases insulin without a relationship to an anabolic function, through IGF-1 related to feedback to the pituitary GH, which takes a dominant catabolic role. Thus, insulin resistance. This is an oversimplification, and far greater depth is found elsewhere.

This study is consistent with another study on  Metabolism Influences Cancer

Reuben Shaw, Ph.D., a geneticist and researcher at the Salk Institute: Metabolism Influences Cancer

Recent development on Human Stem Cell Therapies for comorbidity and Cardiovascular disease

Human Stem Cell Therapies: UCSD New Discovery addressing the Limiting Factor and Providing the Solution

https://pharmaceuticalintelligence.com/2014/01/06/human-stem-cell-therapies-ucsd-new-discovery-addressing-the-limiting-factor-and-providing-the-solution/

This study reported a potential early marker of myocardial infarction by the release into the circulation of damaged endothelial cells that are to be measured in patients suspected of severe ischemia in a clinical trial.  The question that I raised in my comment was whether this would have to be a special immunochemical assay of tagged cells, and if that were the case, would it be measured on an automated flow-based hemocytometer, which can differentiate several populations of cells – granulocytes, lymphocytes, red cells, platelets, immature granuloytes, BLASTS.  That would be a very practical extension of the technology for labs worldwide.

Abstract

Aims: To elucidate if endothelial dysfunction is an early CV risk marker in obese men and women with prediabetes.
Study Design: Cross-sectional study.

Place and Duration of Study: Clinical Research Unit, Pennington Biomedical Research Center, Baton Rouge, LA. United States.

Background: Overweight and obese status denotes an increasing adipose tissue burden which spills over into ectopic locations, including the visceral compartment, muscle and liver. Associated co-morbidities enhance cardiovascular (CV) risk. Endothelium which is the largest receptor-effector end-organ in our bodies, while responding to numerous physical and chemical stimuli maintains vascular homeostasis. Endothelial dysfunction (ED) is the initial perturbation, which precedes fatty streak known to initiate atherosclerosis: insidious process which often culminates as sudden catastrophic CV adverse event.

Methodology:  Asymptomatic men and women; [n=42] coming in after an overnight fast had demographic, anthropometric, clinical chemistry and

  • resting endothelial function (EF)
  • increased test finger peripheral arterial tone (PAT) relative to control;
    • expressed as relative hyperemia index (RHI)] assessments.

Results: Adults with desirable weight [n=12] and overweight [n=8] state, had normal fasting plasma glucose [Mean(SD)]: FPG [91.1(4.5), 94.8(5.8) mg/dL], insulin [INS, 2.3(4.4), 3.1(4.8) µU/ml], insulin sensitivity by homeostasis model assessment [HOMA-IR, 0.62(1.2), 0.80(1.2)] and desirable resting clinic blood pressure [SBP/DBP, 118(12)/74(5), 118(13)/76(8) mmHg].

Obese adults [n=22] had

  • prediabetes [FPG, 106.5(3.5) g/dL],
  • hyperinsulinemia [INS 18.0(5.2) µU/ml],
  • insulin resistance [HOMA-IR .59(2.3)],
  • prehypertension [PreHTN; SBP/DBP 127(13)/81(7) mmHg] and
  • endothelial dysfunction [ED;
  • reduced RHI 1.7(0.3) vs. 2.4(0.3); all p<0.05].

Age-adjusted RHI correlated with BMI [r=-0.53; p<0.001]; however,

    • BMI-adjusted RHI was not correlated with age [r=-0.01; p=0.89].

Conclusion: Endothelial dysfunction reflective of cardiometabolic changes in obese adults can be an early risk marker for catastrophic CV events.

Keywords: Fasting plasma glucose; healthy adults; reverse cholesterol transport pathway; insulin resistance; body weight; relative hyperemia index.

ABBREVIATIONS

ADA: American Diabetes association; BMI: body mass index; CVD: cardiovascular disease; CV: cardiovascular; DBP: diastolic blood pressure; ED: endothelial dysfunction; EF: resting endothelial function; FPG: fasting plasma glucose; HOMA-IR: homeostasis model assessment; INS: insulin; JNC 7: Joint National Commission 7; LDL-C/HDL-C: low density lipoprotein cholesterol to high density lipoprotein; NCEP ATP III: National Cholesterol Education Program Adult Treatment Panel III; PAT: peripheral arterial tone; PreDM: prediabetes; PreHTN: prehypertension; PBRC: Pennington Biomedical Research Center; RHI: relative hyperemia index; SBP: systolic blood pressure; Total-C/HDL-C: total cholesterol to high density lipoprotein cholestrol; TG/HDL-C: triglycerides to high density lipoprotein cholesterol; WC: waist circumference.

Introduction

Healthy adults with no chronic medical conditions, on no prescription medications (n=24) and with low cardiovascular risk, in a randomized-order, cross-over clinical trial, with a 2 week washout period, exhibitd improved endothelial function (measured with flow mediated dilatation) with a diet rich in antioxidants (Franzini et al., 2012). Healthy over weight and obese volunteers with normal glucose appear to attenuate flow mediated dilation after high
glycemic index carbohydrate meals (Suessenbacher et al., 2011). In matched (age, work place, physical activity, tobacco use, blood pressure, serum lipids and family history of premature coronary artery disease) male shift and no shift workers, peripheral endothelial function (peripheral arterial tone (PAT) index obtained with the EndoPAT technique) was impaired in shift workers, suggesting elevated cardiovascular risk (Lavi et al., 2009).

Endothelial function thus appears to be an exquisitely sensitive marker for a variety of populations, under various conditions. Although endothelial function has been evaluated in numerous disease conditions and perturbed with a variety of agents, there has, to our knowledge, not been a comparison of resting endothelial function in free living healthy lean, overweight and obese subjects. Using a noninvasive assessment for resting endothelial function (by measuring the peripheral arterial tone, Bonetti et al., 2004), we tested the hypothesis that fasting glucose escalation in otherwise asymptomatic obese men and women is functionally reflected as endothelial dysfunction.

Endothelial Function

Assessment of resting endothelial function was done with the participant in fasting state, after having avoided stimulants (caffeine, tobacco, alcohol, exercise) for 12 hours, at the same fixed clock hour (range 8-10 AM), using the EndoPAT 2000 device manufactured by ITAMAR Medical®. This assessment technique has been previously validated (Bonetti et al., 2004), has been used in numerous (>250) peer reviewed publications (Carty et al., 2012; Kuvin et al., 2003) and has been in routine use in our clinical core. Briefly: subjects coming
in from home, after an overnight fast and having avoided stimulants for 12-hours, were placed in a supine position for 20 minutes in a quiet room before the test. A patented single use finger sleeve was then placed on the index finger of each hand to continuously measure peripheral arterial tone. A blood pressure cuff applied to the upper arm of the non-dominant arm (test arm) was then used to occlude the brachial artery for 5 minutes. This was followed by a rapid release. The dominant arm without any manipulation served as the control. The
built in, validated software integrated the data gathered from the finger sleeves of the control (undisturbed) and the test arms (during the baseline, occlusion and release phases), thus providing the relative hyperemia index (RHI) for the test arm. This flow mediated dilatation induced change in the test arm, relative to the control arm, served as the measure for endothelial function (RHI).

The subjects with desirable and overweight body weight were significantly younger [36.7(19.1) and 27.4(3.9) years, respectively], than those who were obese [53.2(11.6) years]. We performed correlations between the measure for endothelial function (RHI) and confounding factors like BMI, age and gender. Age-adjusted RHI correlated with BMI [r=- 0.53, p<0.001]; however, BMI-adjusted RHI was not associated with age [r=-0.01, p=0.89]. Fig. 1 depicts panels for the regression line for RHI as a function of age, (and BMI, glucose
and HOMA-IR, respectively) superimposed on a scatter plot. No correlation was observed between endothelial function and age (r²=0.07), while endothelial function was highly correlated with body mass index, glucose and insulin sensitivity (r²=0.3).

DISCUSSION

Asymptomatic obese adults with prediabetes (when compared to asymptomatic desirable weight and overweight adults with normal glucose), exhibit above the upper limits for desirable fasting plasma total cholesterol (>200mg/dL) and triglycerides (>150 mg/dL), but due to a relatively lower HDL-C display higher cardiac risk ratios (Total-C/HDL-C; p=0.05 and TG/HDL-C; p=0.02). A lower HDL-C and the elevated cardiac risk ratios are early clinical indicators for an impaired reverse cholesterol transport (RCT) pathway, a process by which cholesterol from the periphery is transported to the liver (Tall, 1998). The RCT pathway has been shown to be a sensitive indicator of the net flux (deposition vs. removal) of cholesterol homeostasis at the endothelium (Gupta et al., 1993; Tall et al., 2000). It is at the endothelium that the first fatty streaks, which over time deteriorate into atherosclerosis, have been shown to develop (Rosenfeld et al., 2000).

Impaired endothelial dysfunction is the first step in the process of atherosclerosis, even before the development of the fatty streak (Davignon, 2004; Ross 1999). These healthy obese men and women with prediabetes, prehypertension and impaired reverse cholesterol transport pathway were assessed to have impaired resting endothelial function, which is consistent with latent early onset cardiovascular disease.

We have demonstrated a high prevalence of isolated prediabetes or prehypertension and co-existing prediabetes and prehypertension, among the otherwise healthy US adults (Gupta et al., 2011). We have also elucidated that asymptomatic obese adults with overly heightened systemic inflammation, tend to have prediabetes and prehypertension (Gupta et al., 2010a). These individuals by various conventional measures (larger waist circumference, exacerbated systemic inflammation, higher insulin resistance, elevated triglycerides, lower high-density lipoprotein cholesterol, above average cardiac risk ratios and a significant co-existence of two or three concomitant metabolic risk factors) appear to be on an accelerated pathway towards early adverse cardiovascular events (Gupta et al., 2010a, 2010b). With this study we provide a dynamic, non-invasive, functional correlate: significant resting endothelial dysfunction, as an early biomarker for pre-atherosclerosis in obese adults with prediabetes.

Increased organ ectopic adipose burden especially in the muscle and liver appears to drive clinically recognizable adverse cardio metabolic changes (Hamdy et al., 2006). Increased inflammation (local and systemic) along with enhanced insulin resistance (liver, muscle) manifests as dysglycemia, dyslipidemia, excess reactive oxygen species, hyper-coagulablility and loss of blood pressure control (Gastaldelli et al., 2010).

We demonstrate an early impairment in the reverse cholesterol transport pathway, indicating a net deposition versus removal of cholesterol at the endothelium. In asymptomatic obese men and women with predisease  conditions (prediabetes and prehypertension) when contrasted with ideal bodyweight or overweight adults with normoglycemia and normal blood pressure, resting endothelial dysfunction can be an early warning sign for future catastrophic cardiovascular adverse events.

© 2012 Gupta et al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Asahara T, Murohara T, Sullivan A, et al. Isolation of putative progenitor endothelial cells for angiogenesis. Science 1997;275:964-967.

Takahashi T, Kalka C, Masuda H, et al. Ischemia- and cytokine-induced mobilization of bone marrow-derived endothelial progenitor cells for neovascularization. Nat Med 1999;5:434-438.

Kocher AA, Schuster MD, Szabolcs MJ, et al. Neovascularization of ischemic myocardium by human bone-marrow-derived angioblasts prevents cardiomyocyte apoptosis, reduces remodeling and improves cardiac function. Nat Med 2001;7:430-436.

Rauscher FM, Goldschmidt-Clermont PJ, Davis BH, et al. Aging, progenitor cell exhaustion, and atherosclerosis. Circulation 2003;108:457-463.

Hill JM, Zalos G, Halcox JPJ, et al. Circulating endothelial progenitor cells, vascular function, and cardiovascular risk. N Engl J Med 2003;348:593-600.

Vasa M, Fichtlscherer S, Adler K, et al. Increase in circulating endothelial progenitor cells by statin therapy in patients with stable coronary artery disease. Circulation 2001;103:2885-2890

Laufs U, Werner N, Link A, et al. Physical training increases endothelial progenitor cells, inhibits neointima formation, and enhances angiogenesis. Circulation 2004;109:220-226.

Werner N, Kosiol S, Schiegl T, et al. Circulating endothelial progenitor cells and cardiovascular outcomes. N Engl J Med 2005;353:999-1007.

Aicher A, Heeschen C, Mildner-Rihm C, et al. Essential role of endothelial nitric oxide synthase for mobilization of stem and progenitor cells. Nat Med 2003;9:1370-1376.

Wollert KC, Meyer GP, Lotz J, et al. Intracoronary autologous bone-marrow cell transfer after myocardial infarction: the BOOST randomised controlled clinical trial. Lancet 2004;364:141-148.

Zhang H, Vakil V, Braunstein M, et al. Circulating endothelial progenitor cells in multiple myeloma: implications and significance. Blood 2005;105:3286-3294

Lyden D, Hattori K, Dias S, et al. Impaired recruitment of bone-marrow-derived endothelial and hematopoietic precursor cells blocks tumor angiogenesis and growth. Nat Med 2001;7:1194-1201.

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Larry H Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2013-12-08/larryhbern/Developments-in-the-Genomics-and-Proteomics-of-Type-2-Diabetes-Mellitus-and-Treatment-Targets

Researchers Solve a Mystery about Type 2 Diabetes Drug

AB SCIEX TripleTOF® and QTRAP® technologies support breakthrough medical study.
Published: Friday, November 22, 2013
Researchers from St. Vincent’s Institute of Medical Research in Melbourne, Australia, in collaboration with researchers at McMaster University in Canada, are reportedly the first to discover how the type 2 diabetes drug metformin actually works, providing a molecular understanding that could lead to the development of more effective therapies. Mass spectrometry technologies from AB SCIEX played a critical role in the analysis that led to this breakthrough finding.  The research is published in this month’s issue of the journal Nature Medicine.
Doctors have known for decades that metformin helps treat type 2 diabetes.  However, questions had lingered for more than 50 years whether this drug, which is available as a generic drug,
  • worked to lower blood glucose in patients by directly working on the glucose.
People with type 2 diabetes have high blood sugar levels and have trouble converting sugar in their blood into energy because of low levels of insulin. For treating this condition, metformin is considered the most widely prescribed anti-diabetic drug in the world.
Until now, no one had been able to explain adequately how this drug lowers blood sugar. According to this new study, the drug works by reducing harmful fat in the liver. People who take metformin reportedly often have a fatty liver, which is frequently caused by obesity.
“Fat is likely a key trigger for pre-diabetes in humans,” said Professor Bruce Kemp, PhD, the Head of Protein Chemistry and Metabolism at St. Vincent’s Institute of Medical Research.  “Our study indicates that
  • metformin doesn’t directly reduce sugar metabolism, as previously suspected, but instead
  •  reduces fat in the liver, which in turn allows insulin to work effectively.”
The breakthrough in pinning down how the drug functions began with the researchers making
  • genetic mutations to the genes of two enzymes, ACC1 and ACC2,
in mice, so they could no longer be controlled.  What happened next surprised the researchers:
  • the mice didn’t get fat as expected,
but Associate Professor Gregory Steinberg, PhD at McMaster University noticed that
  • the mice had fatty livers and a pre-diabetic condition.
Then the researchers put the mice on
  • a high fat diet and they became fat, while metformin
  • did not lower the blood sugar levels of the mutant mice.
The findings are expected to help researchers better directly target the condition, which affects over 100 million people around the world, according to published reports. It is also believed that with the mystery of metformin solved, the application of the drug could go beyond just diabetes and potentially be used to treat other medical conditions.
“AB SCIEX mass spectrometry solutions help researchers explore big questions and conduct breakthrough studies, such as this remarkable type 2 diabetes study,” said Rainer Blair, President of AB SCIEX.   “In order to understand disease at the molecular level, researchers need the sensitive detection and reproducible quantitation provided by AB SCIEX tools. We enable the research community to solve biological mysteries and rethink the possibilities to transform health.
For the research conducted by the Australian and Canadian researchers, the analysis at the molecular level was optimized on AB SCIEX instrumentation, including the AB SCIEX TripleTOF® 5600 and the AB SCIEX QTRAP® 5500 system.
The TripleTOF system, with its high-speed, high-quality MS/MS capabilities,
  • was used for the discovery of key proteins and phosphopeptides.
The QTRAP system, with its high sensitivity MRM (multiple reaction monitoring) capabilities,
  • was used for quantitation of metabolites, including nucleotides and malonyl-CoA. 

Bardoxolone Methyl in Type 2 Diabetes and Stage 4 Chronic Kidney Disease

D de Zeeuw, T Akizawa, P Audhya, GL Bakris, M Chin, ….,and GM Chertow, for the BEACON Trial Investigators
Type 2 diabetes mellitus is the most important cause of progressive chronic kidney disease in the developed and developing worlds. Various therapeutic approaches to slow progression, including
  • restriction of dietary protein,
  • glycemic control, and
  • control of hypertension,
have yielded mixed results.1-3 Several randomized clinical trials have shown that
  • inhibitors of the renin–angiotensin–aldosterone system significantly reduce the risk of progression,4-6 although
  • the residual risk remains high.7
None of the new agents tested during the past decade have proved effective in late-stage clinical trials.8-12
Oxidative stress and impaired antioxidant capacity intensify 
  • with the progression of chronic kidney disease.13
In animals with chronic kidney disease,
  • oxidative stress and inflammation
  • are associated with impaired activity of the nuclear 1 factor (erythroid-derived 2)–related factor 2 (Nrf2) transcription factor.
The synthetic triterpenoid bardoxolone methyl and its analogues are the most potent known activators of the Nrf2 pathway. Studies involving humans,14 including persons with type 2 diabetes mellitus and stage 3b or 4 chronic kidney disease, have shown that
  • bardoxolone methyl can reduce the serum creatinine concentration for up to 52 weeks.15
We designed the Bardoxolone Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus: the Occurrence of Renal Events (BEACON) trial to test the hypothesis that
  • treatment with bardoxolone methyl reduces the risk of end-stage renal disease (ESRD) or death from cardiovascular causes
among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease.

Methods

Study Design and Oversight

The BEACON trial was a phase 3, randomized, double-blind, parallel-group, international, multicenter trial of
  • once-daily administration of bardoxolone methyl (at a dose of 20 mg in an amorphous spray-dried dispersion formulation), as compared with placebo.
Participants were receiving background conventional therapy that included 
  • inhibitors of the renin–angiotensin–aldosterone system,
  • insulin or other hypoglycemic agents, and, when appropriate,
  • other cardiovascular medications.
The trial design and the characteristics of the trial participants at baseline have been described previously.16,17
Reata Pharmaceuticals sponsored the trial. The trial was jointly designed by employees of the sponsor and the academic investigators who were members of the steering committee. The steering committee, which was led by the academic investigators and included members who were employees of the sponsor, supervised the trial design and operation. An independent data and safety monitoring committee reviewed interim safety data every 90 days or on an ad hoc basis on request. The sponsor collected the trial data and transferred them to independent statisticians at Statistics Collaborative. The sponsor also contracted a second independent statistical group (Axio Research) to support the independent data and safety monitoring committee. The trial protocol was approved by the institutional review board at each participating study site. The protocol and amendments are available with the full text of this article at NEJM.org. The steering committee takes full responsibility for the integrity of the data and the interpretation of the trial results and for the fidelity of the study to the protocol. The first and last authors wrote the first draft of the manuscript. All the members of the steering committee made the decision to submit the manuscript for publication.

Study Population

Briefly, we included adults with 
  • type 2 diabetes mellitus and
  • an estimated glomerular filtration rate (GFR) of 15 to <30 ml per minute per 1.73 m2 BSA.
  1. Persons with poor glycemic control,
  2. uncontrolled hypertension, or
  3. a recent cardiovascular event (≤12 weeks before randomization) or
  4. New York Heart Association class III or IV heart failure were excluded.
Additional inclusion and exclusion criteria are listed in Table S1 in the Supplementary Appendix, available at NEJM.org. All the patients provided written informed consent.

Randomization and Intervention

 Randomization was stratified according to study site with the use of variable-sized blocks. The steering committee, sponsor, investigators, and trial participants were unaware of the group assignments. After randomization,
  • patients received either bardoxolone methyl or placebo.
The prescription of all other medications was at the discretion of treating physicians, who were encouraged to adhere to published clinical-practice guidelines. Patients underwent event ascertainment and laboratory testing according to the study schema shown in Figure S1 in the Supplementary Appendix. Ambulatory blood-pressure monitoring was performed in a substudy that included 174 patients (8%).
The statistical analysis plan defined the study period as the number of days from randomization to a common study-termination date. In the case of patients who were still receiving the study drug on the termination date, data on vital events were collected for an additional 30 days.
Outcomes
 The primary composite outcome was ESRD or death from cardiovascular causes. We defined ESRD as
  • the need for maintenance dialysis for 12 weeks or more or kidney transplantation.
If a patient died before undergoing dialysis for 12 weeks, the independent events-adjudication committee adjudicated whether the need for dialysis represented ESRD or acute renal failure. Patients who declined dialysis and who subsequently died were categorized as having had ESRD. All ESRD events were adjudicated. Death from cardiovascular causes was defined as death due to either cardiovascular or unknown causes.
The trial had three prespecified secondary outcomes —
  1. first, the change in estimated GFR as calculated with the use of the four-variable Modification of Diet in Renal Disease study equation, with serum creatinine levels calibrated to an isotope-dilution standard for mass spectrometry;
  2. second, hospitalization for heart failure or death due to heart failure; and
  3. third, a composite outcome of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes.

The events-adjudication committee, whose members were unaware of the study assignments, evaluated whether

  • ESRD events,
  • cardiovascular events,
  • neurologic events, and
  • deaths
met the prespecified criteria for primary and secondary outcomes (described in detail in the Supplementary Appendix).
Statistical Analysis
We calculated that we needed to enroll 2000 patients on the basis of the following assumptions:

  • a two-sided type I error rate of 5%, an event rate of 24% for the primary composite outcome in the placebo group during the first 2 years of the study,
  • a hazard ratio of 0.68 (bardoxolone methyl vs. placebo) for the primary composite outcome,
  • discontinuation of the study drug by 13.5% of the patients in the bardoxolone methyl group each year, and
  • a 2.5% annual loss to follow-up in each group.

Under these assumptions, if 300 patients had a primary composite outcome, the statistical power would be 85%.

We collected and analyzed all outcome data in accordance with the intention-to-treat principle. We calculated Kaplan–Meier product-limit estimates of
  • the cumulative incidence of the primary composite outcome.
We computed hazard ratios and 95% confidence intervals with the use of Cox proportional-hazards regression models with adjustment for

  • the baseline estimated GFR and urinary albumin-to-creatinine ratio.

We performed analogous analyses for secondary time-to-event outcomes. Given the abundance of early adverse events, we also report discrete cumulative incidences at 4 weeks and 52 weeks.

For longitudinal analyses of estimated GFR, we performed mixed-effects regression analyses using

  1. study group,
  2. time,
  3. the interaction of study group with time,
  4. estimated GFR at baseline,
  5. the interaction of baseline estimated GFR with time, and
  6. urinary albumin-to-creatinine ratio as covariates, and
  7. we compared the means between the bardoxolone methyl group and the placebo group.
We adopted similar approaches when examining the effects of treatment on other continuous measures assessed at multiple visits. Since the between-group difference in the primary composite outcome was not significant,
secondary and other outcomes with P values of less than 0.05 were considered to be nominally significant.
Statistical analyses were performed with the use of SAS software, version 9.3 (SAS Institute). Additional details of the statistical analysis are provided in the Supplementary Appendix.

Results

Patients

From June 2011 through September 2012, a total of 2185 patients underwent randomization, including 1545 (71%) in the United States, 334 (15%) in the European Union, 133 (6%) in Australia, 87 (4%) in Canada, 46 (2%) in Israel, and 40 (2%) in Mexico. Figure S2 in the Supplementary Appendix shows the disposition of the study participants.
As shown in Table 1Table 1Baseline Characteristics of the Patients in the Intention-to-Treat Population., the patients were diverse with respect to age, sex, race or ethnic group, and region of origin;
  • diabetic retinopathy and neuropathy were common conditions among the patients,
  • as was overt cardiovascular disease.
See Table S2 in the Supplementary Appendix for a more detailed description of the characteristics of the patients at baseline; Figure S3 in the Supplementary Appendix shows the distribution of baseline estimated GFR and urinary albumin-to-creatinine ratio.
Drug Exposure
The median duration of exposure to the study drug was 7 months (interquartile range, 3 to 11) among patients randomly assigned to bardoxolone methyl and
  • 8 months (interquartile range, 5 to 11) among those randomly assigned to placebo.
Figure S4 in the Supplementary Appendix shows the time to discontinuation of the study drug. Table S3 in the Supplementary Appendix shows the reasons that patients discontinued the study drug and the reasons that patients discontinued the study.
  • The median duration of follow-up was 9 months in both groups.

Outcomes

Primary Composite Outcome
A total of 69 of 1088 patients (6%) randomly assigned to bardoxolone methyl and 69 of 1097 (6%) randomly assigned to placebo had a primary composite outcome (hazard ratio in the bardoxolone methyl group vs. the placebo group, 0.98; 95% confidence interval [CI], 0.70 to 1.37; P=0.92) (Figure 1AFigure 1Kaplan–Meier Plots of the Time to the First Event of the Primary Outcome and Its Components.).
  • Death from cardiovascular causes occurred in 27 patients randomly assigned to bardoxolone methyl and in 19 randomly assigned to placebo (hazard ratio, 1.44; 95% CI, 0.80 to 2.59; P=0.23) (Figure 1B).
  • ESRD developed in 43 patients randomly assigned to bardoxolone methyl and in 51 randomly assigned to placebo (hazard ratio, 0.82; 95% CI, 0.55 to 1.24; P=0.35) (Figure 1C).

One patient in each group died from cardiovascular causes after the development of ESRD. The mean (±SD) estimated GFR

  • before the development of ESRD was 18.1±8.3 ml per minute per 1.73 m^2 in the bardoxolone methyl group and
  • 14.9±4.0 ml per minute per 1.73 m2 in the placebo group.
Secondary Outcomes
During the study period, 96 patients in the bardoxolone methyl group had heart-failure events (93 patients with at least one hospitalization due to heart failure and 3 patients who died from heart failure without hospitalization),
  • as compared with 55 in the placebo group (55 patients with at least one hospitalization due to heart failure and
  • no patients who died from heart failure without hospitalization) (hazard ratio, 1.83; 95% CI, 1.32 to 2.55; P<0.001) (Figure 2AFigure 2Kaplan–Meier Plots of the Time to the First Event of the Discrete Secondary Outcomes.).
A total of 139 patients in the bardoxolone methyl group, as compared with 86 in the placebo group, had
  • a composite outcome event of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes (hazard ratio, 1.71; 95% CI, 1.31 to 2.24; P<0.001) (Figure 2B).
Incidences of Composite Outcomes and Rates of Death from Any Cause
The cumulative incidences of the primary composite outcome and of the two secondary composite outcomes at 4 weeks and at 52 weeks are shown in Table S4 in the Supplementary Appendix. The rates of death from any cause are shown in Figure S5 in the Supplementary Appendix. From the time of randomization to the end of follow-up, 75 patients died: 44 patients in the bardoxolone methyl group and 31 in the placebo group (hazard ratio, 1.47; 95% CI, 0.93 to 2.32; P=0.10). The causes of death are listed in Table S5 in the Supplementary Appendix.

Estimated GFR

Patients randomly assigned to placebo had a significant mean decline in the estimated GFR from the baseline value (−0.9 ml per minute per 1.73 m2; 95% CI, −1.2 to −0.5), whereas those randomly assigned to bardoxolone methyl had a significant mean increase from the baseline value (5.5 ml per minute per 1.73 m2; 95% CI, 5.2 to 5.9). The difference between the two groups was 6.4 ml per minute per 1.73 m2 (95% CI, 5.9 to 6.9; P<0.001) (Figure 3AFigure 3Estimated Glomerular Filtration Rate (GFR), Body Weight, and Urinary Albumin-to-Creatinine Ratio.).
Physiological Variables
Physiological variables are shown in Table S6 in the Supplementary Appendix. The mean body weight remained stable in the placebo group
  • but declined steadily and substantially in the bardoxolone methyl group (Figure 3B).
There was a significantly smaller decrease from baseline in mean systolic blood pressure in the bardoxolone methyl group than in the placebo group (between-group difference, 1.5 mm Hg [95% CI, 0.5 to 2.5]), and
  • the mean diastolic blood pressure increased from baseline in the bardoxolone methyl group whereas it decreased in the placebo group (between-group difference, 2.1 mm Hg [95% CI, 1.6 to 2.6]).
Blood-pressure results from the substudy in which ambulatory blood-pressure monitoring was performed were similar in direction but were more pronounced (between-group difference of 7.9 mm Hg [95% CI, 3.8 to 12.0] in systolic blood pressure and 3.2 mm Hg [95% CI, 1.3 to 5.2] in diastolic blood pressure).
  • Heart rate also increased significantly in the bardoxolone methyl group, as compared with the placebo group (between-group difference, 3.8 beats per minute; 95% CI, 3.2 to 4.4).
Other Laboratory Variables
Data on laboratory variables are shown in Table S7 in the Supplementary Appendix.
  • The urinary albumin-to-creatinine ratio increased significantly in the bardoxolone methyl group, as compared with the placebo group (Figure 3C).
  • Serum magnesium, albumin, hemoglobin, and glycated hemoglobin levels decreased significantly in the bardoxolone methyl group, as compared with the placebo group.
  • The level of B-type natriuretic peptide increased significantly by week 24 in the bardoxolone methyl group, as compared with the placebo group.
Adverse Events
The rates of serious adverse events are summarized in Table 2Table 2Most Commonly Reported Serious Adverse Events in the Intention-to-Treat Population. Serious adverse events occurred more frequently in the bardoxolone methyl group than in the placebo group (717 events in 363 patients vs. 557 events in 295 patients). There were 11 neoplastic events in the bardoxolone methyl group and 10 in placebo group. The most commonly reported adverse events are summarized in Table S8 in the Supplementary Appendix.

Discussion

The current trial was designed to determine whether bardoxolone methyl, an activator of the cytoprotective Nrf2 pathway, would reduce the risk of ESRD
  • among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease
  • who were receiving guideline-based conventional therapy.
The trial was terminated early because of safety concerns, driven primarily by an increase in cardiovascular events in the bardoxolone methyl group. Bardoxolone methyl did not lower the risk of ESRD or of death from cardiovascular causes, although too few events occurred during the trial to reliably determine the true effect of the drug on the primary composite outcome.
Given the truncated duration of the trial and the number of adjudicated events (46% of the events planned), and assuming no change in any of the original assumptions, we estimated the conditional power of the trial to be less than 40%. Although patients treated with bardoxolone methyl had a significant increase in the estimated GFR, as compared with those who received placebo,
  • there was a significantly higher incidence of heart failure and of the composite outcome of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes in the bardoxolone methyl group.
  • There were numerically more deaths from any cause among patients treated with bardoxolone methyl than among those in the placebo group.
Bardoxolone methyl is among the first orally available antioxidant Nrf2 activators. A small previous study showed that bardoxolone methyl
  • reduced inflammation and oxidative stress13 and
  • induced a decline in the serum creatinine level.
In the 52-Week Bardoxolone Methyl Treatment: Renal Function in CKD/Type 2 Diabetes (BEAM) trial,15 227 patients with type 2 diabetes mellitus and an estimated GFR of 20 to 45 ml per minute per 1.73 m2
  • had a significant increase in the estimated GFR (mean change, 8.2 to 11.4 ml per minute per 1.73 m2, depending on the dose group)
  • that was sustained over the entire trial period.
Muscle spasms and hypomagnesemia were the most common adverse events;
  • there was no increase in the rate of heart failure or other cardiovascular events.
The current trial was designed to determine whether the change in estimated GFR that we anticipated on the basis of the results of the BEAM trial would translate into a slower progression toward ESRD. Although in the current trial ESRD developed in fewer patients in the bardoxolone methyl group than in the placebo group, the early termination of the trial precludes conclusion of the effect on ESRD events.
The mechanism linking bardoxolone methyl to heart failure is unknown. Since an excess in heart-failure events was unanticipated, echocardiography was not performed routinely before randomization. Although weight declined significantly in the bardoxolone methyl group, we were unable to determine whether there was loss of body fat, intracellular (skeletal muscle) water, or extracellular (interstitial) water.
The fall in serum albumin and hemoglobin levels may reflect hemodilution caused by fluid retention.
Bardoxolone methyl also increased blood pressure.
An increase in preload due to volume expansion and an increase in afterload (as reflected by increased blood pressure),
  • coupled with an increase in heart rate,
  • constitute a potentially potent combination of factors that are likely to precipitate heart failure in an at-risk population.
The rise in the level of B-type natriuretic peptide with bardoxolone methyl
  • is consistent with an increase in left ventricular wall stress owing to one or more of these mediators or to unrecognized factors such as
  • impaired diastolic filling of the left ventricle.
After recognizing the initial increase in heart-failure events, the independent data and safety monitoring committee tried to identify
  • clinical characteristics that were associated with patients who were at elevated risk for heart failure
  • after the initiation of bardoxolone methyl therapy (with the possibility of modifying eligibility criteria or otherwise altering the trial),
but the committee was unable to do so. Other, noncardiovascular adverse events were also observed more frequently among patients exposed to bardoxolone methyl than among those who received placebo. Whether the effects of Nrf2 activation, or one or more counterregulatory responses, rendered this particular population vulnerable, is unknown. Zoja et al.18 found an increase in albuminuria and blood pressure along with weight loss in Zucker diabetic fatty rats treated with an analogue of bardoxolone methyl; these effects were not observed in other studies in Zucker diabetic fatty rats or other rodent models or in 1-year toxicologic studies in monkeys.19-21
Why were these adverse effects identified in the current trial and not in the BEAM trial?
  1. First, the number of patient-months of drug exposure in the current trial was roughly 10 times that in the BEAM trial.
  2. Second, the population in the present trial had more severe chronic kidney disease than did the population in the BEAM trial.
Observational studies have shown significantly higher rates of death and cardiovascular events, including heart failure,
  • among patients with stage 4 chronic kidney disease than among patients with stage 3 chronic kidney disease.22
Finally, our trial used an amorphous spray-dried dispersion formulation of bardoxolone methyl at a fixed dose rather than at an adjusted dose. We chose the 20-mg dose and the specific formulation used in the BEACON trial
  1. on the basis of four phase 2 studies of chronic kidney disease (three studies used the crystalline formulation, and one used the amorphous formulation),
  2. a crossover pharmacokinetics study involving humans that used both formulations, and
  3. several studies in animals that used both formulations (Meyer C: personal communication),
to provide an activity and safety profile that was similar to that observed with 75 mg of the crystalline formulation, which was one of the dose levels tested in the BEAM trial.
In conclusion, among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease, bardoxolone methyl did not reduce the risk of the primary composite outcome of ESRD or death from cardiovascular causes. Significantly increased risks of heart failure and of the composite cardiovascular outcome (nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes) prompted termination of the trial.
Alto, CA 93034, or at gchertow@stanford.edu.
Investigators in the Bardoxolone Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus: the Occurrence of Renal Events (BEACON) trial are listed in the Supplementary Appendix, available at NEJM.org.
Table 1. Baseline Characteristics of the Patients in the Intention-to-Treat Population.

Fig 1. Kaplan–Meier Plots of the Time to the First Event of the Primary Outcome and Its Components.

nejmoa1303154_f1   Kaplan–Meier Plot of Cumulative Probabilities of the Primary and Secondary End Points and Death.

Fig 2. Kaplan–Meier Plots of the Time to the First Event of the Discrete Secondary Outcomes

nejmoa1303154_f2  Kaplan–Meier Plot of Cumulative Probabilities of Acute Kidney Injury and Hyperkalemia
Fig 3.  Estimated Glomerular Filtration Rate (GFR), Body Weight, and Urinary Albumin-to-Creatinine Ratio
Table 2  Most Commonly Reported Serious Adverse Events in the Intention-to-Treat Population

References

    1  Klahr S, Levey AS, Beck GJ, et al. The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. N Engl J Med 1994;330:877-884
    2  The ADVANCE Collaborative Group. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med 2008;358:2560-2572
    3  Parving HH, Andersen AR, Smidt UM, Svendsen PA. Early aggressive antihypertensive treatment reduces rate of decline in kidney function in diabetic nephropathy. Lancet 1983;1:1175-1179
    4  Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 2001;345:861-869
    5 Lewis EJ, Hunsicker LG, Clarke WR, et al. Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 2001;345:851-860
   6  Parving HH, Lehnert H, Brochner-Mortensen J, Gomis R, Andersen S, Arner P. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med 2001;345:870-878
    7  Heerspink HJ, de Zeeuw D. The kidney in type 2 diabetes therapy. Rev Diabet Stud 2011;8:392-402
    8  Pfeffer MA, Burdmann EA, Chen CY, et al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N Engl J Med 2009;361:2019-2032
    9   Parving HH, Brenner BM, McMurray JJ, et al. Cardiorenal end points in a trial of aliskiren for type 2 diabetes. N Engl J Med 2012;367:2204-2213
    10   Packham DK, Wolfe R, Reutens AT, et al. Sulodexide fails to demonstrate renoprotection in overt type 2 diabetic nephropathy. J Am Soc Nephrol 2012;23:123-130
Combined Angiotensin Inhibition for the Treatment of Diabetic Nephropathy
Linda F. Fried, M.D., M.P.H., Nicholas Emanuele, M.D., Jane H. Zhang, Ph.D., Mary Brophy, M.D., Todd A. Conner, Pharm.D., William Duckworth, M.D., David J. Leehey, M.D., Peter A. McCullough, M.D., M.P.H., Theresa O’Connor, Ph.D., Paul M. Palevsky, M.D., Robert F. Reilly, M.D., Stephen L. Seliger, M.D., Stuart R. Warren, J.D., Pharm.D., Suzanne Watnick, M.D., Peter Peduzzi, Ph.D., and Peter Guarino, M.P.H., Ph.D. for the VA NEPHRON-D Investigators
N Engl J Med 2013; 369:1892-1903November 14, 2013DOI: 10.1056/NEJMoa1303154
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Background
Combination therapy with angiotensin-converting–enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs) decreases proteinuria; however, its safety and effect on the progression of kidney disease are uncertain.
Methods
We provided losartan (at a dose of 100 mg per day) to patients with type 2 diabetes, a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of at least 300, and an estimated glomerular filtration rate (GFR) of 30.0 to 89.9 ml per minute per 1.73 m2 of body-surface area and then randomly assigned them to receive lisinopril (at a dose of 10 to 40 mg per day) or placebo. The primary end point was the first occurrence of a change in the estimated GFR (a decline of ≥30 ml per minute per 1.73 m2 if the initial estimated GFR was ≥60 ml per minute per 1.73 m2 or a decline of ≥50% if the initial estimated GFR was <60 ml per minute per 1.73 m2), end-stage renal disease (ESRD), or death. The secondary renal end point was the first occurrence of a decline in the estimated GFR or ESRD. Safety outcomes included mortality, hyperkalemia, and acute kidney injury.
Results
The study was stopped early owing to safety concerns. Among 1448 randomly assigned patients with a median follow-up of 2.2 years, there were 152 primary end-point events in the monotherapy group and 132 in the combination-therapy group (hazard ratio with combination therapy, 0.88; 95% confidence interval [CI], 0.70 to 1.12; P=0.30). A trend toward a benefit from combination therapy with respect to the secondary end point (hazard ratio, 0.78; 95% CI, 0.58 to 1.05; P=0.10) decreased with time (P=0.02 for nonproportionality). There was no benefit with respect to mortality (hazard ratio for death, 1.04; 95% CI, 0.73 to 1.49; P=0.75) or cardiovascular events. Combination therapy increased the risk of hyperkalemia (6.3 events per 100 person-years, vs. 2.6 events per 100 person-years with monotherapy; P<0.001) and acute kidney injury (12.2 vs. 6.7 events per 100 person-years, P<0.001).
Conclusions
Combination therapy with an ACE inhibitor and an ARB was associated with an increased risk of adverse events among patients with diabetic nephropathy. (Funded by the Cooperative Studies Program of the Department of Veterans Affairs Office of Research and Development; VA NEPHRON-D ClinicalTrials.gov number, NCT00555217.)
A complete list of investigators in the Veterans Affairs Nephropathy in Diabetes (VA NEPHRON-D) study is provided in the Supplementary Appendix, available at NEJM.org.
Figure 1  Kaplan–Meier Plot of Cumulative Probabilities of the Primary and Secondary End Points and Death.
Figure 2 Kaplan–Meier Plot of Cumulative Probabilities of Acute Kidney Injury and Hyperkalemia

The End of Dual Therapy with Renin–Angiotensin–Aldosterone System Blockade?

Nov 14, 2013       de Zeeuw D.  (Editorial)
 N Engl J Med 2013; 369:1960-1962
Treatment aimed at multiple risk factors and specific markers such as glucose level, blood pressure, body weight, cholesterol levels, and albuminuria has been the main focus to slow cardiovascular and renal risk among patients with diabetes. Among the agents used, those that interrupt the renin–angiotensin–aldosterone system (RAAS) have shown protection that extends beyond decreasing blood pressure. In part, these additional effects may be explained by a decrease in albuminuria.1 Therefore, angiotensin-converting–enzyme (ACE) inhibitors and angiotensin II–receptor blockers (ARBs) have become first-choice drugs in patients with diabetes. Despite some success, the residual cardiovascular and renal risk among patients with diabetes remains

Diabetes: Mouse Studies Point to Kinase as Treatment Target

Published: Nov 24, 2013
By Kristina Fiore, Staff Writer, MedPage Today

Targeting a pathway that plays a major role in both hepatic glucose production and insulin sensitivity may eventually help treat type 2 diabetes, researchers reported.
In a series of experiments in mice, researchers found that inhibition of the kinase CaMKII — or even some of its downstream components — lowered blood glucose and insulin levels, Ira Tabas, MD, PhD, of Columbia University Medical Center in New York City, and colleagues reported online in Cell Metabolism.
The pathway is activated by glucagon signaling in the liver, and appears to have roles in both insulin resistance as well as hepatic glucose production in the liver.
In an earlier study, Tabas and colleagues showed that inhibiting the CaMKII pathway lowered hepatic glucose production by suppressing p38-mediated FoxO1 nuclear localization.
In the current study, they found CaMKII inhibition suppresses levels of the pseudo-kinase TRB3 to improve Akt-phosphorylation, thereby improving insulin sensitivity.
Thus this single pathway targets “two cardinal features of type 2 diabetes — hyperglycemia and defective insulin signaling,” the researchers wrote.
“When we realized we had one common pathway that was responsible for these two disparate processes that, in essence, comprises all of type 2 diabetes, we though it would be an ideal target for new drug therapy,” Tabas told MedPage Today.
Tabas and colleagues conducted several experiments to evaluate the CaMKII pathway.
In one experiment in obese mice, they found that

  • no matter how CaMKII was knocked out, it led to lower blood glucose levels and lower fasting plasma insulin levels in response to a glucose challenge.

The improvements also occurred

  • when they knocked out downstream processes, including p38 and MAPK-activating protein kinase 2 (MK2).

“Thus liver p38 and MK2, like CaMKII, play an important role in the development of hyperglycemia and hyperinsulinemia in obese mice,” they wrote.
In further analyses, the researchers discovered

  • deleting or inhibiting any of these three elements ultimately improved insulin-induced Akt-phosphorylation in obese mice —
  • an important part of improving insulin sensitivity.

And unlike the effects on hepatic glucose production, these changes didn’t occur through effects on FoxO1.
Instead, inhibiting the CaMKII pathway suppressed levels of the pseudo-kinase TRB3, which likely occurred because of suppression of ATF4

  • all of which led to an increase in Akt-phosphorylation and insulin sensitivity.

Indeed, when mice were made to overexpress TRB3, the improvement in phosphorylation disappeared, “indicating that

  • the suppression of TRB3 by CaMKII deficiency is causally important in the improvement in insulin signaling,” they wrote.

As a result, there “appear to be two separate CaMKII pathways,

  • one involved in CaMKII-p38-FoxO1 dependent hepatic glucose production, and
  • the other involved in defective insulin-induced p-Akt,” they wrote.

The findings suggest the possibility of a drug that can target both hyperglycemia and insulin resistance in type 2 diabetes, they said.

Association Between a Genetic Variant Related to Glutamic Acid Metabolism and Coronary Heart Disease in Individuals With Type 2 Diabetes

Lu Qi; Qibin Qi; S Prudente; C Mendonca; F Andreozzi; et al.
JAMA. 2013;310(8):821-828.     http://dx.doi.org/10.1001/jama.2013.276305.

Importance

Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals.

Objective

To identify genetic determinants of CHD that are specific to patients with diabetes.

Design, Setting, and Participants

We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses’ Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses’ Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2 543 016 common genetic variants occurring throughout the genome.

Main Outcomes and Measures

Coronary heart disease—defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries.

Results

A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants,

  • with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10−8).

No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89),

  • consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10−4).

Compared with protective allele homozygotes, rs10911021 risk allele

  • homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048).
  • A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029).

Conclusion and Relevance

A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.

Adipocyte Heme Oxygenase-1 Induction Attenuates Metabolic Syndrome In Both Male And Female Obese Mice

Angela Burgess1,2, Ming Li2, Luca Vanella1, Dong Hyun Kim1, Rita Rezzani4, et al.

1Department of Physiology and Pharmacology, University of Toledo, Toledo, OH 43614
2Department of Pharmacology, New York Medical College, Valhalla, NY 10595
3Department of Medicine, New York Medical College, Valhalla, NY 10595
4Department of Biomedical Sciences and Biotechnology, University of Brescia, Brescia, Italy
5Department of Pediatrics and Center for Applied Genomics, Charles University, Prague, Czech Republic
6The Rockefeller University, New York, New York 10065

Hypertension. 2010 December ; 56(6): 1124–1130.    http://dx.doi.org/10.1161/HYPERTENSIONAHA.110.151423

Abstract

Increases in visceral fat are associated with
  • increased inflammation,
  • dyslipidemia,
  • insulin resistance,
  • glucose intolerance and
  • vascular dysfunction.
We examined the effect of the potent heme oxygenase (HO)-1 inducer, cobalt protoporphyrin (CoPP), on regulation of adiposity and glucose levels in both female and male obese mice. Both lean and obese mice were administered CoPP intraperitoneally, (3mg/kg/once a week) for 6 weeks. Serum levels of
  1. adiponectin,
  2. TNFα,
  3. IL-1β and
  4. IL-6, and
  5. HO-1,
  6. PPARγ,
  7. pAKT, and
  8. pMPK protein expression
were measured in adipocytes and vascular tissue . While female obese mice continued to gain weight at a rate similar to controls, induction of HO-1 slowed the rate of weight gain in male obese mice. HO-1 induction led to lowered blood pressure
levels in obese males and females mice similar to that of lean male and female mice.
HO-1 induction also produced a significant decrease in the plasma levels of IL-6, TNF-α, IL-1β and fasting glucose of obese females compared to untreated female obese mice. HO-1 induction
  • increased the number and
  • decreased the size of adipocytes of obese animals.
HO-1 induction increased adiponectin, pAKT, pAMPK, and PPARγ levels in adipocyte of obese animals. Induction of HO-1, in adipocytes was associated with
  • an increase in adiponectin and
  • a reduction in inflammatory cytokines.
These findings offer the possibility of treating not only hypertension, but also other detrimental metabolic consequences of obesity
  • including insulin resistance and dyslipidemia in obese populations
  • by induction of HO-1 in adipocytes.
Introduction
Moderate to severe obesity is associated with increased risk for cardiovascular complications and insulin resistance in humans1, 2 and animals3, 4. Cardiovascular risk is specifically associated with increased intra-abdominal fat. Women in their reproductive years have a higher BMI than males, which largely reflects increased overall subcutaneous adipose tissue or “gynoid” obesity, this is not associated with increased cardiovascular risk5. However, due to increases in visceral fat with aging, after the age of 60 the fat distribution in females more closely resembles that in males6. Increased androgen levels also often occur after the menopausal transition. These changes in visceral fat content and androgen levels correlate with both central obesity and insulin resistance and are an important determinant of cardiovascular risk7.
Heme oxygenase (HO) catalyzes the breakdown of heme, a potentially harmful pro-oxidant, into its products biliverdin and carbon monoxide, with a concomitant release of iron (reviewed in8). While HO-2 is expressed constitutively, HO-1 is inducible in response to oxidative stress and its induction has been reported to normalize vascular and renal function9–11. Further, induction of HO-1 slows weight gain, decreases levels of TNF-α and IL-6 and increases serum levels of adiponectin in obese rats and obese diabetic mice4, 9, 12.
The association observed between HO-1 and adiponectin has led to the proposal of the existence of a cytoprotective HO-1/adiponectin axis4, 13. Previously, L’Abbate et al,14 have shown that induction of HO-1 is associated with a parallel increase in the serum levels of adiponectin, which has well-documented
  1. insulin-sensitizing,
  2. antiapoptotic,
  3. antioxidative and
  4. anti-inflammatory properties.
Adiponectin is an abundant protein secreted from adipocytes. Once secreted, it mediates its actions by binding to a set of receptors, such as
  • adipoR1 and adipoR2, and also
  • through induction of AMPK signaling pathways15, 16.
In addition, increases in adiponectin play a protective role against TNF mediated endothelial activation17.
In this study, we evaluated the effect of CoPP, a potent inducer of HO-1,
  • on visceral and subcutaneous fat distribution in both female and male obese mice.
We show for the first time a resistance to weight reduction upon administration of CoPP in female obese mice but
  • a significant decrease in inflammatory cytokines.
Despite continued obesity,
  1. CoPP normalized blood pressure levels,
  2. decreased circulating cytokines, and
  3. increased insulin sensitivity in obese females.
CoPP treatment of obese mice
  • increased the number and
  • reduced the size of adipocytes.
CoPP treatment of both male and female obese mice reversed the reduction in adiponectin levels seen in obesity. This study suggests that in spite of continued obesity,
  • HO-1 induction in female obese mice serves a protective role against obesity associated metabolic consequences via expansion of healthy smaller insulin-sensitive adipocytes.

Results

Effect of induction of HO-1 on body weight, appearance, and fat content of female and male obese mice. Previously, we have shown CoPP treatment results in the prevention of weight gain in several male models of obesity including obese and db/db mice and Zucker fat rats4, 12. We extended our studies to examine the effect of CoPP on weight gain in female obese mice. CoPP-treatment prevented weight gain in male obese mice when compared to age-matched male controls (Figure S1). The revention of body weight gain was accompanied by a
reduction in visceral fat in male obese mice. However, female obese mice administered CoPP did not lose weight but continued to gain weight at the same rate as untreated female obese mice (Figure S1). This was in spite of food intake being comparable between the two
groups. CoPP administration decreased subcutaneous fat content in both obese males and females (p<0.05; p<0.05, respectively). CoPP produced a decrease (p<0.05) in visceral fat in male but not in female obese mice when compared to untreated obese mice (Figure S1D).
We examined adipocyte size by haematoxilin-eosin staining in both lean, obese and CoPP treated obese female mice (Figure 1A, upper panel). CoPP treatment resulted in a decrease in adipocyte size (p<0.05) compared to untreated obese animals (Figure 1A, lower left panel). We then examined the number of adipocytes in lean, obese and CoPP-treated obese female mice. The number of adipocytes (mean±SE) in lean, obese and CoPP-treated obese animals was 40.83±3.50, 18.33±1.80 and 32.00±1.67 respectively indicating that CoPP treatment of obese mice increased the number of adipocytes to levels similar to those in lean animals (Figure 1A, lower right panel). Similar results were seen in male animals.
The induction of HO-1 was associated with a reduction in blood pressure (BP). Systolic blood pressure in obese female mice was 142 ± 6.5 mm Hg compared to obese-CoPP treated, 109 ± 8.1 mm Hg, p<0.05. The value in obese female mice treated with CoPP is similar to the blood pressure seen in lean female mice (110 ± 9.6 mm Hg). The systolic blood pressure in obese male mice was 144± 4.5 mm Hg compared to obese-CoPP treated, 104 ± 3.6 mm Hg, p<0.05.
We further examined whether CoPP affects HO-1 expression in adipocyte using immunohistochemistry and western blot analysis. Immunostaining showed increased levels of HO-1 (green staining), located on the surface of adipocytes, after CoPP treatment (p<0.05), compared with female obese mice, Figure 1B. As seen in Figure 1C, HO-1 and

HO-2 levels in adipocyte isolated from lean, untreated female obese mice or female obese mice treated with CoPP. Densitometry analysis showed that HO-1 was increased
significantly in female obese mice treated with CoPP, compared to non-treated female obese mice, p<0.05, which is in agreement with immunohistochemistry results. This pattern of HO expression in obesity occurs in other tissues, including aortas, kidneys and hearts of male obese mice4, 13.
Effect of CoPP on HO-1 expression and HO activity in female and male obese mice
HO-1 protein levels were increased by CoPP treatments in liver and renal tissues similar to that seen in adipocytes. Western blot analysis showed significant differences  (p<0.05) in the ratio of HO-1 to actin in renal of male and female obese and lean mice (Figure S 2A). Obesity decreasd HO-1 levels in both sexes when compared to age matched lean animals.
In addition, HO-1 levels were significantly (p<0.05) lower in obese females compared to obese males (Figure S 2A). This reflects a less active HO system in both male and female
obese animals compared to age matched lean controls. Next, we compared the effect of CoPP on male and female HO-1 gene expression in adipocytes. CoPP increased HO-1
expression in both male and female obese animals compared to untreated obese animals (Figure S 2B, p<0.001 and p<0.001, respectively). Similar results of HO-1 expression were seen in liver tissues (Result not shown).
Effect of CoPP on cytokine levels in female and male obese mice
CoPP administration resulted in a significnt increase in the levels of plasma adiponectin in both female (p<0.001) and male obese (p<0.001) mice (Figure 2A). Untreated female obese animals exhibited a significant (p<0.05) increase in plasma IL-6 levels when compared to age-matched male obese mice (Figure 2B). CoPP decreased plasma IL-6 levels in both female and male obese mice (p<0.05A )p<0.01, respectively) when compared to untreated obese miec. Similar results were observed with plasma TNF-α and IL-1β levels (Figure 2C and 2D). These results indicate that though female obese mice exhibited elevated serum levels of inflammatory cytokines compared to male obese mice, CoPP acts with equal efficacy in both female and male obese animals in reducing inflammation while simultaneously increasing serum adiponectin levels (Figure 2). 

Effect of CoPP on blood glucose and LDL levels in female and male obese mice 

Fasting glucose levels were determined after the development of insulin resistance. CoPP produced a decrease in glucose levels in both fasting female (p<0.05) and male (p<0.001) obese mice when compared to untreated obese control animals (Figure 3A). CoPP reduced LDL levels in both male (p<0.01) and female (p<0.05) obese mice when compared to untreated obese controls (Figure 3B). Treatment with SnMP, increased LDL levels. In separate experiments two weeks apart, glucose levels and insulin sensitivity were determined after development of insulin resistance (Fig. 4A and B). Blood glucose levels in female obese mice were elevated (p<0.01) 30 min after glucose administration and remained elevated. In CoPP-treated female obese mice produced a decrease in glucose but not in the vehicle-treated female obese mice (p<0.01).

Effect of Obesity on Protein Expression Levels of pAKT, pAMPK, and PPARγ levels in female and male obese mice

Western blot analysis of adipocytes harvested from fat tissues,showed significant  differences in basal protein expression levels of pAKT and pAMPK in untreated female obese mice compared to untreated obese male mice. pAMPK levels were higher in obese females compared to obese males (Figure 5A, p< 0.05). This was also the case for pAKT protein levels, where increased levels of pAKT were seen in obese females compared to obese males (Figure 5B, p<0.05). CoPP treatment increased pAMPK and pAKT levels in bothe obese females and obese males. In addition, CoPP administration increased PPARγ levels, in both male (p<0.001) and female (p<0.05) obese mice (Figures 5C).

Discussion

In the current study, we show for the first time that induction of HO-1 regulates adiposity in both male and female animals via an increase in adipocyte HO-1 protein levels. A second novel finding is that induction of HO-1 was associated not only with a decrease in adipocyte cell size but with an increase in adipocyte cell number. Further, induction of HO-1 affects visceral and subcutaneous fat distribution and metabolic function in male obese mice differently than in female obese mice. Despite continued obesity, upregulation of HO-1 induced major improvements in the metabolic profile of female obese mice exhibiting symptoms of Type 2 diabetes including: high plasma levels of proinflammatory cytokines, hyperglycemia, dyslipidemia, and low adiponectin levels. CoPP treatment resulted in increased serum adiponectin levels and decreased blood pressure. Adiponectin is exclusively secreted from adipose tissue, and its expression is higher in subcutaneous rather than invisceral adipose tissue. Increased adiponectin levels reduce adipocyte size and increase adipocyte number12, resulting in smaller, more insulin sensitive adipocytes. Adiponectin has recently attracted much attention because it has insulin-sensitizing properties that enhance fatty acid oxidation, liver insulin action, and glucose uptake and positively affect serum trglyceride levels18–21. Levels of circulating adiponectin are inversely correlated with plasma levels of oxidized LDL in patients with Type 2 diabetes and coronary artery disease, which suggests that low adiponectin levels are associated with an increased oxidative state in the arterial wall22. Thus, increases in adiponectin mediated by upregulation of HO-1 may account for improved insulin sensitivity and reduced levels of LDL and inflammatory cytokines (TNF-α, IL-1β, and IL-6 levels) in both male and female mice.

 Females continued to gain weight in spite of the metabolic improvements. One plausible explanation for this anomaly is the direct effects of HO-1 on adiponectin mediating clonal expansion of pre-adipocytes. This supports the concept that expansion of adipogenesis leads to an increased number of adipocytes of smaller cell size; smaller adipocytes are considered to be healthy, insulin sensitive adipocyte cells that are capable of producing adiponectin23. This hypothesis is supported by the increase in the number of smaller adipocytes seen in
CoPP-treated female obese animals without affecting weight gain when compared to female obese animals. Similar results for the presence were seen in males indicating that this effect is not sex specific.
Upregulation of HO-1 was also associated with increased levels of adipocyte pAKT, and pAMPK and PPARγ levels. Previous studies have indicated that insulin resistance and  impaired PI3K/pAKT signaling can lead to the of endothelial dysfunction24. In the current study, increased HO-1 expression was associated with increases in both AKT and AMPK phosphorylation; these actions may protect renal arterioles from insulin mediated endothelial damage. By this mechanism, increased levels of HO-1 limit oxidative stress and facilitate activation of an adiponectin-pAMPK-pAKT pathway and increased insulin sensitivity. Induction of adiponectin and activation of the pAMPK-AKT pathway has been shown to provide vascular protection25, 26. A reduction in AMPK and AKT levels may also explain why inhibition of HO activity in CoPP-treated obese mice  increased inflammatory cytokine levels while decreasing adiponectin. The action of CoPP in increasing pAKT, pAMPK and PPARγ is associated with improved glucose tolerance and decreased insulin resistant.

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Leptin signaling in mediating the cardiac hypertrophy associated with obesity

Larry H Bernstein, MD, FCAP, Reviewer, and Aviva Lev-Ari, PhD, RN

 

There has been a lot of interest in leptins and both insulin resistance and obesity for the last decade.  The association between obesity and cardiac hypertrophy is also known, but what drives this association.  We have covered heart disease from many aspects in a long series of articles.  The next is a pleasure to take in.

Importance of leptin signaling and signal transducer and activator of transcription-3 activation in mediating the cardiac hypertrophy associated with obesity

Maren Leifheit-Nestler12, Nana-Maria Wagner13, Rajinikanth Gogiraju1,Michael Didié14, Stavros Konstantinides15, Gerd Hasenfuss1 and Katrin Schäfer1*

1Department of Cardiology and Pulmonary Medicine, Heart Research Center, Georg August University Medicine Goettingen, Robert Koch Strasse 40, D-37075, Göttingen, Germany

2Current address: Department of Pediatric Kidney, Liver and Metabolic Diseases, Hannover Medical School, Hannover, Germany

3Current address: Clinic for Anesthesiology and Intensive Care Medicine, University Medicine Rostock, Rostock, Germany

4Department of Pharmacology, Georg August University Medicine Goettingen, Goettingen, Germany

5Current address: Center for Thrombosis and Hemostasis, University Medicine Mainz, Mainz, Germany

J Translational Medicine: Cardiovascular, Metabolic and Lipoprotein Translation. 2013; 11:170.  http://www.translational-medicine.com/content/11/1/170

http://dx.doi.org/10.1186/1479-5876-11-170

This is an Open Access article distributed under the terms of the Creative Commons Attribution License 
http://creativecommons.org/licenses/by/2.0

Abstract

Background

The adipokine leptin and its receptor are expressed in the heart, and

  • leptin has been shown to promote cardiomyocyte hypertrophy in vitro.

Obesity is associated with

  • hyperleptinemia 
  • hypothalamic leptin resistance and
  • an increased risk to develop cardiac hypertrophy and heart failure.

However, the role of cardiac leptin signaling in mediating the cardiomyopathy associated with increased body weight is unclear, in particular, whether it develops subsequently to cardiac leptin resistance or overactivation of hypertrophic signaling pathways via elevated leptin levels.

Methods

The cardiac phenotype of high-fat diet (HFD)-induced obese wildtype (WT) mice was examined and compared to age-matched genetically obese leptin receptor (LepR)-deficient (LepRdb/db) or lean WT mice. To study the role of leptin-mediated STAT3 activation during obesity-induced cardiac remodeling,

  • mice in which tyrosine residue 1138 within LepR had been replaced with a serine (LepRS1138) were also analyzed.

Results

Obesity was associated with hyperleptinemia and elevated cardiac leptin expression in both diet-induced and genetically obese mice.

  • Enhanced LepR and STAT3 phosphorylation levels were detected in hearts of obese WT mice, but not in those with LepR mutations, and
  • exogenous leptin continued to induce cardiac STAT3 activation in diet-induced obese mice.

Although echocardiography revealed signs of cardiac hypertrophy in all obese mice,

  • the increase in left ventricular (LV) mass and diameter was significantly more pronounced in LepRS1138 animals.

LepRS1138 mice also exhibited an increased activation of signaling proteins downstream of LepR, including Jak2 (1.8-fold), Src kinase (1.7-fold), protein kinase B (1.3-fold) or C (1.6-fold). Histological analysis of hearts revealed that the inability of leptin to activate STAT3 in LepRdb/db and LepRS1138 mice

  • was associated with reduced cardiac angiogenesis as well as increased apoptosis and fibrosis.

Conclusions

Our findings suggest that hearts from obese mice continue to respond to elevated circulating or cardiac leptin, which

  • may mediate cardioprotection via LepR-induced STAT3 activation, whereas
  • signals distinct from LepR-Tyr1138 promote cardiac hypertrophy.

On the other hand, the presence of cardiac hypertrophy in obese mice with complete LepR signal disruption indicates that additional pathways also play a role.

Keywords:

Heart; Hypertrophy; Leptin; Obesity; Signal transduction; STAT3

Background

Obesity is frequently associated with elevated circulating leptin levels [1] and an increased risk to develop cardiac hypertrophy [2,3] or heart failure [4]. Clinical studies demonstrated a positive correlation between serum leptin levels and left ventricular (LV) mass or wall thickness [5,6], independent of blood pressure levels, suggesting a direct role for leptin in the pathogenesis of obesity-associated cardiomyopathy. Furthermore, leptin was shown to promote hypertrophy of isolated rat or human ventricular cardiomyocytes [7,8], and

  • this effect could be prevented using neutralizing antibodies [9].

Cardiac hypertrophy also develops in obese rodents fed high-fat diet (HFD)[10,11], and

  • studies in mice with (functional) leptin deficiency suggested that the cardiac hypertrophy developing in states of chronic hyperleptinemia
  • may result from the inability to transduce anti-hypertrophic and/or cardioprotective effects of the adipokine [12,13].

The effects of leptin on cell shortening and intracellular Ca2+ transients were abrogated in cardiomyocytes isolated from HFD-fed obese rats [14], but then others found

  • a preserved signal transduction in response to leptin in hyperleptinemic obese mice [15,16] or rats[17].

The leptin receptor (LepR) belongs to the family of cytokine type I receptors that signal via activation of

  • Janus kinase (Jak)-2 and
  • signal transducer and
  • activator of transcription (STAT)-3 [18].

Analysis of cardiomyocytes ex vivo revealed leptin promotes hypertrophy via activation of p38 and p42/44 MAP kinases as well as protein kinase B (Akt) [19,20]. But it is unknown whether STAT-3 activation downstream of LepR is required to transmit the cardiac effects of leptin and whether it may be involved in mediating protective (i.e. anti-apoptotic, anti-fibrotic or pro-angiogenic) signals, as previously reported in mice with cardiomyocyte-specific STAT-3 deletion [21,22].

In this study, we examined the cardiac phenotype of diet-induced (i.e. with hypothalamic leptin resistance) and genetically obese (i.e. with systemic leptin receptor deficiency) hyperleptinemic mice, developing with age or after continuous β-adrenergic stimulation. Moreover, we determined

  • the importance of leptin-mediated STAT-3 activation
  • for the development of cardiac hypertrophy in obesity
  • by analyzing mice with targeted mutation of the STAT3 binding site within LepR.

Methods

Animals

C57Bl6/J leptin receptor-deficient db/db (LepRdb/db; BKS.Cg Leprdb/Leprdb) mice and C57Bl6/J wildtype (WT) controls were obtained from Harlan Winkelmann, Germany. Mice heterozygous mutant for the LepRS1138 allele (on the congenic B6.129/J background; 98- > 99% homozygous for C57Bl/6; [23]) were obtained from Professor Martin Myers (University of Michigan Medical School, Ann Arbor, USA) and bred at the animal facility of the University of Goettingen, Germany, to generate homozygous mutant obese LepRS1138 mice. Age- and gender-matched WT (LepR+/+) and heterozygous (LepRS/+) littermates were used as controls. To induce obesity, 3 months-old mice were switched to high-fat diet (HFD; D12451) for 4 months, while controls were maintained on normal rodent chow (D12450B; both Research Diets Inc.). The composition of both diets is shown in Additional file 1: Table S1. To examine the cardiac response to hypertrophic stimuli other than leptin, osmotic minipumps (Alzet®; model 2002; Charles River Laboratories) were filled with isoprenaline hydrochloride (Sigma; 20 mg/kg body weight [BW] per day) and implanted for 14 days under the dorsal skinfold of 2 months-old, 2% isoflurane anesthetized mice. At the time of tissue harvest, mice were weighed followed by intraperitoneal anesthesia with a mixture of 2% xylazine (6 mg/kg BW) and 10% ketamine hydrochloride (100 mg/kg BW), and blood was drawn by cardiac puncture. Hearts were rapidly excised, the atria removed and ventricles immediately processed for protein isolation or cryoembedding, respectively. All animal care and experimental procedures had been approved by the institutional Animal Research Committee and complied with national guidelines for the care and use of laboratory animals.

Additional file 1: Table S1. Diet composition.
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Serum analysis

Freshly drawn blood was allowed to clot at room temperature (RT) for 30 min, followed by centrifugation for 10 min at 3,000 rpm. The supernatant was stored at -80°C pending analysis of serum leptin levels using specific enzyme-linked immunoassays (ELISA; R&D Systems).

Echocardiography

Echocardiography was performed by a blinded examiner at the day before tissue harvest in mice under 1.5% isoflurane anesthesia using the VisualSonics Vevo 2100 system (Visualsonics) equipped with a 30 MHz center frequency ultrasound transducer, as previously described [24]. M-mode echocardiographical recordings were used to determine the end-diastolic and end-systolic LV diameter (EDD and ESD, respectively) and the ventricular wall thickness (WTh), corresponding to the mean of the anterior and posterior WTh. LV mass was calculated using the formula: 1.055 × ([AWTh + EDD + PWTh]3 – EDD3). Fractional shortening (FS) was calculated as (EDD – ESD)/EDD × 100. B-mode echocardiography images were used to calculate the heart weight, using the equation: 1.05 × (5/6) × ((Episyst × (Lsyst + ((AWThsyst + PWThsyst)/2))) – (Areasyst × Lsyst)).

Histology and immunohistochemistry

Histochemical analyses were performed on 5 μm-thick frozen cross sections through the LV. For each mouse, 4 sections (approx. 500 μm apart) and 4 randomly selected viewing fields (at 200-fold magnification) per section were analyzed and findings averaged. Cardiac fibrosis was determined after overnight incubation in Bouin’s fixative followed by Masson’s trichrome (MTC) stain. Monoclonal rat antibodies against mouse CD31 (Santa Cruz Biotechnology) were used to detect endothelial cells [24,25]. Their number was manually counted by a person blinded to the mouse genotype and expressed per mm2 or cardiomyocyte, respectively.

Single cardiomyocytes were visualized by incubation with fluorescein-labeled wheat germ agglutinin (WGA; Molecular Probes), followed by determination of the cardiomyocyte cross-sectional area (CSA) using image analysis software (Image ProPlus). Per cross section, at least 10 randomly selected cardiomyocytes were evaluated and results averaged. Apoptosis was analyzed using the ‘In Situ Cell Death Detection kit’ (Roche). Cell nuclei were visualized using 4′,6-diamidino-2-phenylindole (DAPI; Sigma).

Immunoprecipitation and western blot analysis

Membranes were blocked in 1% bovine serum albumine (in TBS, containing 0.1% Tween-20) prior to incubation with antibodies against phosphorylated (p)-Akt (S473) and total Akt, p-Jak2 (Y1007/1008) and total Jak2, p-p38 (T180/Y182) and total p38, p-p42/44 (T202/Y204) and total p42/44, p-Src (Y416) and total Src, p-STAT3 (Y705) and total STAT3, or p-PKC (pan), respectively (all Cell Signaling Technologies), or against leptin (R&D Systems) and GAPDH (Biotrend), respectively. Protein bands were visualized using HRP-conjugated secondary antibodies (Amersham Biosciences), followed by detection with SuperSignal® West Pico Substrate (Pierce). For the analysis of LepR phosphorylation, 100 μg total heart tissue lysates were immunoprecipitated under rotation at 4°C with 2 μg anti-LepR antibody (against an internal domain present in the short and long isoforms of murine LepR; Santa Cruz Biotechnology) plus 50 μL nProtein A Sepharose™ 4 Fast Flow beads (GE Healthcare) followed by detection of phosphorylated tyrosines (p-Tyr [PY20]; Santa Cruz Biotechnology) or LepR. For the analysis of STAT3 phosphorylation in response to acute elevations of circulating leptin, mice were fasted overnight, injected with recombinant murine leptin (1 mg/kg BW i.p.) and hearts harvested 30 min later.

Statistical analysis

Quantitative data are presented as mean ± standard error of the mean (SEM). Normal data distribution was tested using the D’Agostino & Pearson omnibus normality test. When three or more groups were compared, ANOVA was employed, if samples were normally distributed, or Kruskal-Wallis test, if not. For post-hoc comparisons, ANOVA was followed by Bonferroni’s and Kruskal-Wallis by Dunn’s multiple comparison test. Differences before and after isoprenaline infusion were tested using Student’s t-test for paired means. Statistical significance was assumed when P reached a value less than 0.05. All statistical analyses were performed using GraphPad PRISM software, version 4.01 (GraphPad Software Inc).

Results

Clinical and experimental studies revealed that obesity is associated with LV hypertrophy [10,11], an important risk factor for the development of heart failure. As shown in Tables 1 and 2, WT mice fed HFD for 4 months (WT + HFD; mean body weight [BW], 44±1.9 g) to induce obesity exhibited a non-significant trend towards an increased mean heart weight, LV mass and WTh compared to age-matched lean controls fed normal chow (BW, 29±1.0 g). Marked LV hypertrophy was observed in 7 months-old obese LepRdb/db mice (Table 1 and 2), consistent with a previous report [12]. Longitudinal sections through hearts of WT, WT + HFD and LepRdb/db mice are shown in Figure 1A, representative M-mode echocardiography recordings in Figure 1B and cardiac cross-sections after WGA staining to delineate cardiomyocyte borders in Figure 1C. Of note, adiposity in mice with LepR deficiency was more pronounced compared to age-matched WT + HFD mice (Table 1; P < 0.001), in which obesity develops as result of hypothalamic resistance to chronically elevated leptin levels[26].

1479-5876-11-170-1  F1 Cardiac phenotype of lean and obese WT

Figure 1.Cardiac phenotype of lean and obese WT, WT + HFD, LepRS1138 and LepRdb/db mice.
(A)
Representative H&E-stained longitudinal sections through hearts of 7 months-old mice are shown. Magnification, ×10.(B) Representative M-mode echocardiographic recordings.(C) Representative images of wheat germ agglutinin (WGA)-stained myocardial cross sections. The mean cardiomyocyte cross-sectional areas are given in Table 1.

Table 1.Body, visceral fat and heart weights in 7 months-old mice

Table 2.Echocardiographic parameter in 7 months-old mice

The presence of cardiac hypertrophy in LepR-deficient and, to a lesser extent also in diet-induced obese mice, suggests that it develops as a result of the heart’s inability to respond to elevated systemic (Table 1) and/or cardiac (Figure 2A) leptin levels. In this regard, Western blot analysis revealed increased levels of phosphorylated (p-) LepR (Figure 2B) and STAT-3 (Figure 2C) protein in hearts of HFD-induced obese mice (P < 0.05 vs. WT for both), whereas findings in LepRdb/db mice did not differ from those in lean controls or were reduced compared to those in WT + HFD mice (P < 0.05 for differences in LepR phosphorylation). Moreover, both lean and HFD-induced obese WT mice responded to a single i.p. injection of recombinant murine leptin with a significant increase in the cardiac STAT-3 phosphorylation (Figure 2D), suggesting a preserved cardiac leptin signal transduction in hyperleptinemic, diet-induced obese mice.

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Figure 2.Cardiac leptin expression and signal transduction in lean and obese mice.
Protein was extracted from hearts of 7 months-old mice (n = 8 per group) and analyzed for the expression of
(A) leptin, (B)phosphorylated LepR (using immunoprecipitation of LepR, followed by the detection of total phosphotyrosines and LepR) and (C) phosphorylated STAT3. (D) Cardiac STAT3 phosphorylation in response (30 min later) to a single injection of recombinant murine leptin (1 mg/kg BW i.p.) was examined in WT (n = 4) and WT + HFD (n = 6) mice. Results are expressed as -fold increase of controls (black bars) after normalization for total protein and GAPDH expression. The mean ± SEM as well as representative Western blot results are shown. *P < 0.05 and **P < 0.01 vs. WT mice; #P < 0.05 vs. WT + HFD mice.

To further study the role of leptin signaling in the development of cardiac hypertrophy and also to determine, whether the inability of leptin to activate STAT3 contributes to the cardiac maladaptation in obesity, we examined mice in which tyrosine (Tyr)1138 within LepR had been replaced by a serine (LepRS1138). In these mice, leptin cannot signal via STAT3, but continues to be able to activate Jak2 and SH2 domain-containing adapter proteins. Western blot analysis revealed that p-LepR (Figure 2B) and p-STAT3 (Figure 2C) levels in hearts of LepRS1138 mice did not significantly differ from those in WT and LepRdb/db mice. Similar to mice with complete LepR deficiency, lack of LepR-mediated STAT3 activation resulted in severe adiposity, although serum leptin levels were lower than those in LepRdb/db mice (P < 0.001; Table 1). Interestingly, obese LepRS1138 exhibited a more pronounced increase in mean heart weights not only compared to lean or diet-induced obese WT mice, but also compared to LepRdb/db mice (P < 0.001 for all comparisons; Table 1), and differences persisted after normalization for body weight (P < 0.001) or tibia length (P < 0.001). Echocardiography confirmed increased LV mass (P < 0.01) or heart weights (P < 0.001) in LepRS1138 mice compared to their LepRdb/dbcounterparts (Table 2; please also see Figure 1A-C). Moreover, hearts of LepRS1138 mice exhibited elevated levels of phosphorylated Jak2 (P < 0.001 vs. WT; Figure 3A), Src kinase (P < 0.05 vs. WT, WT + HFD and LepRdb/db; Figure 3B), Akt (P < 0.001 vs. LepRdb/db; Figure 3C), PKC (P < 0.05 vs. WT and LepRdb/db, P < 0.01 vs. WT + HFD; Figure 3D) and p38 MAPK (P < 0.01 vs. LepRdb/db; Figure 3E), suggesting that an intact, Tyr1138-independent LepR activation in the presence of elevated leptin levels may have contributed to the pronounced cardiac hypertrophy present in these mice. On the other hand, cardiac levels of p-p42/44 MAPK did not significantly differ between the mouse groups (Figure 3F).

Figure 3. Hypertrophic signal transduction

Figure 3.Hypertrophic signal transduction in hearts of lean and obese mice. Protein was isolated from hearts of 7 months-old WT (n = 15), WT + HFD (n = 12), LepRS1138(n = 15) and LepRdb/db (n = 15) mice and analyzed for the expression of phosphorylated Jak2 (A), Src kinase (B), Akt (C), PKC (D), p38 (E) and p42/44 MAPK (F). Results are expressed as -fold increase of lean control mice (after normalization for total protein [with the exception of PKC] and GAPDH expression). The mean ± SEM as well as representative findings are shown. *P < 0.05, **P < 0.01 and ***P < 0.001 vs. WT mice; #P < 0.05 and ##P < 0.01 vs. WT + HFD mice; §P < 0.05, §§P < 0.01 and §§§P < 0.001 for the difference between LepRdb/db and LepRS1138 mice.

M-mode echocardiography also revealed significantly increased enddiastolic LV diameters in LepRS1138 mice (P < 0.01 vs. WT and LepRdb/db mice; Table 2; representative findings are shown in Figure 1B), suggesting that the observed (over-)activation of LepR signaling together with the inability to induce STAT3 may result in augmented hypertrophy and maladaptive cardiac remodeling. Of note, fractional shortening (FS) was not significantly altered in HFD-induced obese WT mice (P = n.s. vs. WT mice), but found to be increased in both LepRdb/db (P < 0.01 vs. WT and P < 0.001 vs. WT + HFD mice) and LepRS1138mice (P < 0.05 vs. WT and P < 0.001 vs. WT + HFD mice). Histological analyses revealed significantly reduced numbers of CD31-positive capillary endothelial cells in LepRdb/db, and to a lesser extent also in LepRS1138 mice (Figure 4A), whereas the number of TUNEL-positive apoptotic cells (Figure 4B) and the fibrotic tissue area (Figure 4C) were found to be significantly increased in hearts of both LepRS1138 and LepRdb/db mice compared to lean and diet-induced obese WT mice.

Figure 4.Histological analysis of angiogenesis, apoptosis and fibrosis in hearts of lean and obese mice.
Serial cross sections through the LV of WT, WT + HFD, LepR
S1138 and LepRdb/db mice (n = 10 per group) were immunostained and the number of (A) CD31-positive endothelial cells and (B) TUNEL-positive apoptotic cell nuclei determined. Results are expressed per cardiomyocyte and/or mm2.(C) The degree of cardiac fibrosis was quantified after Masson’s trichrome (MTC) staining. Results are expressed as % of total tissue area (at 200-fold magnification). The mean ± SEM as well as representative findings are shown. **P < 0.01 and ***P < 0.001 vs. WT; #P < 0.05, ##P < 0.01 and ###P < 0.001 vs. WT + HFD mice.

Figure 4.Histological analysis  (unable to post)

To examine the specificity of leptin’s hypertrophic action in obesity, the cardiac response of young, i.e. 2 months-old WT (n = 12; body weight, 22 ± 0.9 g), LepRS1138 (n = 9; 34 ± 1.1 g, P < 0.001 vs. WT) and LepRdb/db mice (n = 7; 40 ± 1.3 g; P < 0.001 vs. WT and P < 0.01 vs. LepRS1138) to chronic isoprenaline infusion (20 mg/kg BW per day) was examined. Under basal conditions, similar findings as those in 7 months-old mice were observed, i.e. LepRS1138 mice exhibited an increased heart weight (P < 0.05 vs. LepRdb/db; Figure 5A), LV mass (P < 0.01 vs. WT; Figure 5B) and mean WTh (P < 0.05 vs. WT; Figure 5C), whereas other changes, such as differences in fractional shortening (Figure 5D), ESD (Figure 5E) and EDD (Figure 5F) were not (yet) detected. On the other hand, all mouse groups responded to chronic β-adrenergic stimulation with significant cardiac hypertrophy, and no differences (with the exception of heart weight; Figure 5A) were observed between LepRS1138 and LepRdb/db mice. Representative M-mode echocardiography tracings are shown in Figure 6 and summarized in Additional file 2: Table S2.

1479-5876-11-170-5  F5 Echocardiography findings

Figure 5.Echocardiography findings in young lean and obese mice before and after chronic β-adrenergic stimulation.
Isoprenaline-filled osmotic minipumps were subcutaneously implanted into 2 months-old WT (n = 12), LepR
S1138 (n = 9) and LepRdb/db (n = 7) mice to examine the cardiac response to a hypertrophic stimulus other than leptin. Echocardiography (A-F) was performed immediately before (open bars) as well as at the time of tissue harvest 14 days later (dotted bars). *P < 0.05, *P < 0.01 and ***P < 0.001 for differences vs. WT mice; §P < 0.05 for differences between LepRdb/db and LepRS1138 mice. Significance levels for differences before and after isoprenaline stimulation (as determined using Student’s t test for paired means) are indicated within the graph.

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Figure 6.Representative M-mode echocardiography recordings.

Additional file 2: Table S2. Echocardiographic parameter in 2 months-old mice before and 14 days after isoprenaline infusion.

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Discussion

The adipocytokine leptin may link obesity with cardiac hypertrophy, an important risk factor for the development of heart failure. Studies in humans [2,3] and rodents [10,11] have shown that obesity is associated with LV hypertrophy, and body mass index was identified as a strong and independent predictor of LV mass [2,3]. Importantly, cardiac hypertrophy is also observed in normotensive obese subjects [6], and plasma leptin levels are associated with increased myocardial wall thickness independent of BW or blood pressure elevations [5], suggesting a causal role for leptin in the pathogenesis of cardiac hypertrophy.

Although the major source of leptin is adipose tissue, cardiomyocytes are also capable of synthesizing leptin [27], and increased cardiac leptin levels have been reported in mice or rats following coronary ligation [13,18] or in patients with heart failure [28]. In this study, elevated circulating as well as cardiac leptin levels were detected in both diet-induced and genetically obese mice, which may have acted on cardiomyocytes as well as other, non-cardiomyocyte cells expressing leptin receptors [29]. Although leptin serum levels were higher than in previous publications [30], we explain this findings with the higher age of the mice, a factor previously found to be associated with increased circulating leptin levels [31]. Leptin has been shown to stimulate the hypertrophy of cardiomyocytes isolated from rats [7,20] or humans [8,19]. Moreover, chronic leptin infusion increased cardiac ANP expression after myocardial infarction (MI) in mice [32], whereas neutralizing LepR antibodies abrogated the hypertrophy of the surviving myocardium after coronary artery ligation in rats [33]. On the other hand and as confirmed in our analysis, cardiac hypertrophy also develops in leptin- and LepR-deficient mice and may be reversed by leptin substitution[12]. Caloric restriction experiments suggested that the anti-hypertrophic effects of leptin had occurred in addition to weight loss [12], which itself may preserve heart function and attenuate LV remodeling [34]. Thus, it is unclear whether the cardiac hypertrophy in obesity is the consequence of pro-hypertrophic effects of the adipokine or rather the result of a resistance towards leptin’s preventive effects on hypertrophic cardiac remodeling. Of note, since body weight is markedly elevated in the diet-induced and particularly, the genetically obese mice, the heart-to-body weight ratio decreases, even though the absolute heart weight is increased (but to a relatively lesser extent).

Obesity is associated with elevated circulating leptin levels and hypothalamic resistance to the weight-reducing effects of the adipokine, whereas the existence of a peripheral (e.g. cardiac) leptin resistance is controversial. For example, reduced cardiac LepR expression has been reported in HFD-fed rats[14], whereas others demonstrated unaltered cardiac STAT3 phosphorylation in diet-induced obese rodents following acute leptin administration [1517]. Our findings also suggest that hearts from diet-induced obese mice continue to respond to leptin in the presence of chronically elevated leptin levels and that the observed elevation of serum and cardiac leptin may thus contribute to the development of cardiac hypertrophy in obesity. For example, hearts of hyperleptinemic obese WT mice (i.e. those with intact leptin receptors) exhibited signs of activated leptin signaling, including elevated levels of phosphorylated LepR and STAT3, while they were unchanged or reduced in mice with mutated or truncated forms of LepR (i.e. LepRS1138 or LepRdb/db mice). Moreover, both lean and obese WT mice responded to a single leptin injection with increased cardiac STAT3 phosphorylation. Of note, we could not spatially dissect the cardiac responsiveness to leptin, since whole heart homogenates were examined. Possible explanations underlying the discrepancy between the present and some previous studies include the animal species, as the absence of a response to leptin in obesity has been so far primarily observed in rats[14]. In addition, age, sex and feeding status of the animals or the time of recombinant leptin administration may have influenced the results. Of note, previous studies in humans have reported the existence of individuals (up to 40%) exhibiting a blunted response to leptin [35], although it is unknown, whether such phenomenon also occurs in rodents.

Interestingly, hearts from LepRS1138 mice exhibited a marked overactivation of STAT3-independent leptin signaling pathways, including Jak2, Src kinase, Akt or p38 MAPK, i.e. factors previously shown to mediate the pro-hypertrophic effects of the adipokine in cardiomyocytes [19,20]. Importantly, overactivation of leptin signaling in hearts of LepRS1138 mice was accompanied by a pronounced cardiac hypertrophy, both at the organ and the single cardiomyocyte level, despite similar adiposity. Although leptin levels were found to be lower in LepRS1138compared to LepRdb/db mice, as previously reported [23], leptin continues to be able to activate LepR signal transduction in these mice, for example via LepR-Tyr985. Similar echocardiographical findings were obtained in young (i.e. 2 months-old) and older (i.e. 7 months-old) mice, arguing against the development of cardiac hypertrophy secondary to hemodynamic or other metabolic changes associated with obesity, although we cannot exclude the possible contribution of a more pronounced hyperinsulinemia [23] to the development of cardiac hypertrophy in LepRS1138 mice. On the other hand, hypertension had not been observed in ob/ob mice [12], and heart weight increase and concentric LV hypertrophy in obese mice and humans also occurs without systolic and diastolic blood pressure elevations [5,6,36].

Although a predominant cardiac expression of the short (i.e. without STAT3 binding site) over the long LepR isoform has been reported [7,29], previous studies have shown that stimulation of neonatal rat cardiomyocytes with leptin increased STAT3 phosphorylation, nuclear translocation and DNA binding activity [32]. Also, cardiac STAT3 activation after MI was blunted in leptin-deficient mice [13]. The observation that increased cardiac STAT3 phosphorylation in hyperleptinemic, diet-induced obese mice was reduced or almost completely abolished in LepRS1138 or LepRdb/db mice suggests that cardiac STAT3 activation in obesity largely occurs downstream of elevated leptin levels and that other cytokines, also elevated in obesity and known to signal via Jak2-STAT3, may be of minor importance. On the other hand, the importance of leptin-mediated STAT3 activation in the heart and its contribution to cardioprotective signaling pathways in vivo have not been directly examined so far.

STAT3 has been implicated in cardioprotection after various injuries. For example, cardiomyocyte-specific STAT3 deletion results in dilatative cardiomyopathy, characterized by increased apoptosis and interstitial fibrosis as well as reduced myocardial capillary density [21,22]. Previous studies suggested that leptin may exert beneficial effects on the heart. For example, administration of leptin was associated with smaller infarct size after ischemia/reperfusion injury [37], whereas ischemic postconditioning failed to induce cardioprotection in mice lacking leptin or its receptor [38]. Also, leptin deficiency was associated with a worsened cardiac function and survival after coronary artery ligation, which could be improved by leptin repletion [13]. Regarding possible mechanisms, increased cardiac myocyte apoptosis was observed in hearts from leptin (receptor)-deficient mice [39,40]. Similar findings were obtained in vitro, showing that leptin protects cardiomyocytes against apoptotic cell death induced by serum starvation [41]. Our analyses also revealed significantly elevated numbers of apoptotic cells in hearts of obese LepRS1138 and LepRdb/dbmice, consistent with a reduced activation of STAT3-responsive anti-apoptotic genes [40]. Although findings in mice with systemic defects in leptin signal transduction may have been confounded by the concomitant presence of obesity and associated metabolic and inflammatory alterations, adverse cardiac remodeling after MI [42] or lethal heart failure [43] were recently reported in mice with cardiomyocyte-specific LepR deletion. On the other hand, the beneficial effects of leptin-mediated STAT3 activation may not be restricted to cardiomyocytes. For example, we and others have shown that leptin promotes the angiogenic properties of endothelial (progenitor) cells [25,44], and cardiac angiogenesis was reduced in LepRS1138 and LepRdb/db mice. In addition, hearts of obese LepRS1138 and LepRdb/db mice exhibited increased interstitial fibrosis, which may have occurred secondary to increased cardiomyocyte loss, although previous studies have shown that leptin may also directly influence myocardial matrix metabolism [45]. On the functional level, the enhanced activation of pro-hypertrophic signaling pathways in the absence of STAT3-mediated cardioprotection may have contributed to the echocardiographic finding of LV cavity dilation in LepRS1138 compared to LepRdb/db mice.

Conclusions

Taken together, our findings suggest that hearts from diet-induced obese mice continue to respond to chronically elevated leptin levels and that increased systemic and/or local leptin and enhanced cardiac LepR activation contribute the development of cardiac hypertrophy. On the other hand, chronic overactivation of hypertrophic signaling mediators together with an inabilitity to activate STAT3-dependent cardioprotective pathways may promote maladaptive cardiac remodeling. Of note, our findings also indicate that leptin signaling is not a prerequisite to develop cardiac hypertrophy in obesity and that additional pathways also contribute to the increase in LV mass associated with higher body weight.

References

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  5. Paolisso G, Tagliamonte MR, Galderisi M, Zito GA, Petrocelli A, Carella C, de Divitiis O, Varricchio M: Plasma leptin level is associated with myocardial wall thickness in hypertensive insulin-resistant men.

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Under Nutrition Early in Life may lead to Obesity

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

With the growing worldwide obesity epidemic, including huge populations in developing countries, such as China, India, Mexico and Brazil, the causes of this health and economic catastrophe have been increasingly studied. It is well known that metabolic syndrome and obesity exhibit a high correlation with low or absent physical exercise practices and the consumption of calorie-rich diets in developing countries; however, although the inhabitants may actually experience a nutrition transition, high levels of overweight and obese individuals could not be justified solely by diet and physical inactivity, other hallmarks, such as metabolic programming by the under nutrition early in life and epigenetic modification could also be underlining the obesity onset.

In addition to the pathophysiological aspects that have emerged from studies on metabolic programming caused by environmental insults during fetal life, another interesting point that is relevant to this issue is the role of epigenetic changes in the increased risk of developing metabolic diseases, such as type 2 diabetes and obesity, later in life. Epigenetic mechanisms, such as DNA methylation and/or nucleoprotein acetylation/methylation, are crucial to the normal/physiological development of several tissues in mammals, and they involve several mechanisms to guarantee fluctuations of enzymes and other proteins that regulate the metabolism. As previously reviewed, the intrauterine phase of development is particularly important for the genomic processes related to genes associated with metabolic pathways. Therefore, this phase of life may be particularly important for nutritional disturbance. In humans who experienced the Dutch famine Winter in 1944–1945 and in rats that were deprived of food in utero, epigenetic modifications were detected in the insulin-like growth factor 2 (IGF2) and pancreatic and duodenal home box 1 (Pdx1), which are the major factors involved in pancreas development and pancreatic β-cell maturation. Although it is known that the pancreas and the pancreatic β-cells develop/maturate during the embryonic phase, the postnatal life is also crucial for the maintenance processes that control the β-cell mass, such as proliferation, neogenesis and apoptosis. Nevertheless, no data on metabolic programming as the result of protein-restricted diet during lactation only have yet been reported, and no direct association with epigenetic modifications has been observed; on the other hand, because stressor insults during the milk suckling phase can lead to disturbances in glucose metabolism, hypothalamic neurons, ANS activity and β-cell mass/function of the pancreatic β-cells in rodents, further studies are needed on this topic.

Two decades ago, it was observed that low birth weight was related to adult chronic, non-transmissible diseases, such as type 2 diabetes, cardiovascular disease and obesity. It has been speculated that a nutritional injury during perinatal growth, including uterine and early postnatal life, may contribute to adapting the adult metabolism toward nutritional restriction. However, if an abundant diet is offered to people who have been undernourished during the perinatal life, this opportunity induces a metabolic shift toward the storage of energy and high fat tissue accumulation, thus leading to high risks of the onset of metabolic/coronary diseases onset. These observations led to the introduction of the term DOHaD (Developmental Origins of Health and Disease) previously known as the Barker thrifty phenotype hypothesis. Currently, the concept of DOHaD is extended to any other insults during perinatal life, pregnancy and/or lactation, such as underweight, overweight, diabetic or hyperplasic mothers. This concept also includes any type of stressful situations that may predispose babies or pups to develop metabolic disorders when they reach adulthood.

Source References:

 

http://www.nutritionandmetabolism.com/content/9/1/80

 

http://www.ncbi.nlm.nih.gov/pubmed/19955786?dopt=Abstract&holding=f1000,f1000m,isrctn

 

http://www.ncbi.nlm.nih.gov/pubmed/12886432?dopt=Abstract&holding=f1000,f1000m,isrctn

 

http://www.ncbi.nlm.nih.gov/pubmed/8733829?dopt=Abstract&holding=f1000,f1000m,isrctn

 

http://www.ncbi.nlm.nih.gov/pubmed/9478036?dopt=Abstract&holding=f1000,f1000m,isrctn

 

 

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Reporter: Aviva Lev-Ari, PhD, RN

 

PTEN Mutations as a Cause of Constitutive Insulin Sensitivity and Obesity

Aparna Pal, M.R.C.P., Thomas M. Barber, D.Phil., M.R.C.P., Martijn Van de Bunt, M.D., Simon A. Rudge, Ph.D., Qifeng Zhang, Ph.D., Katherine L. Lachlan, M.R.C.P.C.H., Nicola S. Cooper, M.R.C.P., Helen Linden, M.R.C.P., Jonathan C. Levy, M.D., F.R.C.P., Michael J.O. Wakelam, Ph.D., Lisa Walker, D.Phil., M.R.C.P.C.H., Fredrik Karpe, Ph.D., F.R.C.P., and Anna L. Gloyn, D.Phil.

N Engl J Med 2012; 367:1002-1011  September 13, 2012DOI: 10.1056/NEJMoa1113966

BACKGROUND

Epidemiologic and genetic evidence links type 2 diabetes, obesity, and cancer. The tumor-suppressor phosphatase and tensin homologue (PTEN) has roles in both cellular growth and metabolic signaling. Germline PTEN mutations cause a cancer-predisposition syndrome, providing an opportunity to study the effect of PTENhaploinsufficiency in humans.

METHODS

We measured insulin sensitivity and beta-cell function in 15 PTENmutation carriers and 15 matched controls. Insulin signaling was measured in muscle and adipose-tissue biopsy specimens from 5 mutation carriers and 5 well-matched controls. We also assessed the effect of PTEN haploinsufficiency on obesity by comparing anthropometric indexes between the 15 patients and 2097 controls from a population-based study of healthy adults. Body composition was evaluated by means of dual-emission x-ray absorptiometry and skinfold thickness.

RESULTS

Measures of insulin resistance were lower in the patients with aPTEN mutation than in controls (e.g., mean fasting plasma insulin level, 29 pmol per liter [range, 9 to 99] vs. 74 pmol per liter [range, 22 to 185]; P=0.001). This finding was confirmed with the use of hyperinsulinemic euglycemic clamping, showing a glucose infusion rate among carriers 2 times that among controls (P=0.009). The patients’ insulin sensitivity could be explained by the presence of enhanced insulin signaling through the PI3K-AKT pathway, as evidenced by increased AKT phosphorylation. The PTEN mutation carriers were obese as compared with population-based controls (mean body-mass index [the weight in kilograms divided by the square of the height in meters], 32 [range, 23 to 42] vs. 26 [range, 15 to 48]; P<0.001). This increased body mass in the patients was due to augmented adiposity without corresponding changes in fat distribution.

CONCLUSIONS

PTEN haploinsufficiency is a monogenic cause of profound constitutive insulin sensitization that is apparently obesogenic. We demonstrate an apparently divergent effect of PTEN mutations: increased risks of obesity and cancer but a decreased risk of type 2 diabetes owing to enhanced insulin sensitivity. (Funded by the Wellcome Trust and others.)

Supported by grants from the Wellcome Trust (095101/Z/10Z, to Dr. Gloyn), the Medical Research Council (G0700222, to Dr. Gloyn; and G0800467, to Drs. Pal and Gloyn), the National Institute for Health Research Oxford Biomedical Research Centre (to Drs. Pal, Karpe, and Gloyn), the Biotechnology and Biological Sciences Research Council (to Drs. Rudge, Zhang, and Wakelam), and the European Union Seventh Framework Program LipodomicNet (202272, for adipocyte signaling work, to Drs. Wakelam and Karpe).

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

We thank the clinicians Trevor R.P. Cole, Louise Izatt, Carole McKeown, Eamonn R. Maher, and Mary Porteous for referring patients for this study; the research nurses Beryl Barrow and Jane Cheeseman for assistance with collecting clinical data; Amy Barrett for analysis of PTEN expression; Sandy Humphries for analysis of apolipoprotein B; Tim James and colleagues at the John Radcliffe Hospital, Oxford, for analysis of glucose and insulin; the NIHR Cambridge Biomedical Research Centre Core Biochemical Assay Laboratory for analysis of leptin and adiponectin; Leanne Hodson and Barbara Fielding for access to control dual-emission x-ray absorptiometry scans and phenotypic data on postmenopausal controls; and Jonathan Clark and Izabella Niewczas for providing lipid standards for the mass-spectrometry analysis.

SOURCE INFORMATION

From the Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford (A.P., T.M.B., M.V.B., J.C.L., F.K., A.L.G.); the Oxford National Institute for Health Research Biomedical Research Centre (A.P., J.C.L., F.K., A.L.G.) and the Oxford Regional Genetics Centre (H.L., L.W.), Churchill Hospital, Oxford; the Inositide Laboratory, the Babraham Institute, Babraham, Cambridge (S.A.R., Q.Z., M.J.O.W.); Wessex Clinical Genetics Service, University Hospital Southampton, Southampton (K.L.L.); the Department of Human Genetics and Genomic Medicine, Faculty of Medicine, University of Southampton, Southampton (K.L.L.); and West Midlands Regional Clinical Genetics Service, Birmingham Women’s Hospital, Birmingham (N.S.C.) — all in the United Kingdom.

Address reprint requests to Dr. Gloyn at the Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford OX3 7LE, United Kingdom, or atanna.gloyn@drl.ox.ac.uk.

 Source:

 

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Reporter: Aviva Lev-Ari, PhD, RN

While a staff nurse at Beth Israel Deaconess Medical Center in Boston, MA in 2008, I provided direct care for Morbid Obese patients, above 400 pounds that were transferred to Farr 9 – the Acute Surgery Unit from the PACU following Bariatric Surgery. The first day after a significant surgical intervention was very tough to the patient and very tough for the nurses, three types of analgesic drugs were used including epidural pumps and PCA. Pain medication diffused in the adipose tissue with just moderate amelioration of pain. Few patients had the operation done 10 years ago and needed a repair. Technology had advanced. More studies are needed to ascertain that in presence of morbid obesity and absence of DM, a Bariatric Surgery is THE Treatment for DM Disease Prevention.

Bariatric Surgery — From Treatment of Disease to Prevention?

Danny O. Jacobs, M.D., M.P.H.

N Engl J Med 2012; 367:764-765  August 23, 2012

Bariatric surgery to treat morbid obesity has improved dramatically over the past 60 years — especially over the past several decades. Today’s methods are far safer than the hazardous intestinal bypass procedures that were introduced in the 1950s. Bariatric-surgery techniques have progressed through various iterations of horizontal and vertical stapling of the stomach with or without banding (e.g., vertical banded gastroplasty) to vertical gastric partitioning or creation of a gastric pouch with proximal bypass into a jejunal loop (i.e., the gastric bypass), which is considered to be a reference standard.

Bariatric Surgery for Morbid Obesity.

Bariatric Surgery for Morbid Obesity.

SOURCE INFORMATION

From the Department of Surgery, Duke University School of Medicine, Durham, NC.

Bariatric Surgery and Prevention of Type 2 Diabetes in Swedish Obese Subjects

Lena M.S. Carlsson, M.D., Ph.D., Markku Peltonen, Ph.D., Sofie Ahlin, M.D., Åsa Anveden, M.D., Claude Bouchard, Ph.D., Björn Carlsson, M.D., Ph.D., Peter Jacobson, M.D., Ph.D., Hans Lönroth, M.D., Ph.D., Cristina Maglio, M.D., Ingmar Näslund, M.D., Ph.D., Carlo Pirazzi, M.D., Stefano Romeo, M.D., Ph.D., Kajsa Sjöholm, Ph.D., Elisabeth Sjöström, M.D., Hans Wedel, Ph.D., Per-Arne Svensson, Ph.D., and Lars Sjöström, M.D., Ph.D.

N Engl J Med 2012; 367:695-704  August 23, 2012

BACKGROUND

Weight loss protects against type 2 diabetes but is hard to maintain with behavioral modification alone. In an analysis of data from a nonrandomized, prospective, controlled study, we examined the effects of bariatric surgery on the prevention of type 2 diabetes.

METHODS

In this analysis, we included 1658 patients who underwent bariatric surgery and 1771 obese matched controls (with matching performed on a group, rather than individual, level). None of the participants had diabetes at baseline. Patients in the bariatric-surgery cohort underwent banding (19%), vertical banded gastroplasty (69%), or gastric bypass (12%); nonrandomized, matched, prospective controls received usual care. Participants were 37 to 60 years of age, and the body-mass index (BMI; the weight in kilograms divided by the square of the height in meters) was 34 or more in men and 38 or more in women. This analysis focused on the rate of incident type 2 diabetes, which was a prespecified secondary end point in the main study. At the time of this analysis (January 1, 2012), participants had been followed for up to 15 years. Despite matching, some baseline characteristics differed significantly between the groups; the baseline body weight was higher and risk factors were more pronounced in the bariatric-surgery group than in the control group. At 15 years, 36.2% of the original participants had dropped out of the study, and 30.9% had not yet reached the time for their 15-year follow-up examination.

RESULTS

During the follow-up period, type 2 diabetes developed in 392 participants in the control group and in 110 in the bariatric-surgery group, corresponding to incidence rates of 28.4 cases per 1000 person-years and 6.8 cases per 1000 person-years, respectively (adjusted hazard ratio with bariatric surgery, 0.17; 95% confidence interval, 0.13 to 0.21; P<0.001). The effect of bariatric surgery was influenced by the presence or absence of impaired fasting glucose (P=0.002 for the interaction) but not by BMI (P=0.54). Sensitivity analyses, including end-point imputations, did not change the overall conclusions. The postoperative mortality was 0.2%, and 2.8% of patients who underwent bariatric surgery required reoperation within 90 days owing to complications.

CONCLUSIONS

Bariatric surgery appears to be markedly more efficient than usual care in the prevention of type 2 diabetes in obese persons. (Funded by the Swedish Research Council and others; ClinicalTrials.gov number, NCT01479452.)

Supported by grants from the Swedish Research Council (K2012-55X-22082-01-3, K2010-55X-11285-13, K2008-65x-20753-01-4), the Swedish Foundation for Strategic Research to Sahlgrenska Center for Cardiovascular and Metabolic Research, the Swedish federal government under the LUA/ALF agreement concerning research and education of doctors, the VINNOVA-VINNMER program, and the Wenner-Gren Foundations. The SOS study has previously been supported by grants to one of the authors from Hoffmann–La Roche, AstraZeneca, Cederroth, Sanofi-Aventis, and Johnson & Johnson.

Dr. Lena Carlsson reports receiving consulting fees from AstraZeneca and owning stock in Sahltech; Dr. Bouchard, receiving consulting fees from New York Obesity Nutrition Research Center, Pathway Genomics, Weight Watchers, and Nike, payment for manuscript preparation from Elsevier and Wiley-Blackwell, royalties from Human Kinetics and Informa Healthcare, honoraria from NaturALPHA, and reimbursement for travel expenses from European College of Sports Sciences, Nordic Physiotherapy, Wingate Congress, and Euro Sci Open Forum; Dr. Björn Carlsson, being employed by and owning stock in AstraZeneca; Dr. Sjöholm, owning stock in Pfizer; Dr. Wedel, receiving consulting fees from AstraZeneca, Pfizer, Roche, and Novartis; and Dr. Lars Sjöström, serving as a member of the board of Lenimen, receiving lecture fees from AstraZeneca and Johnson & Johnson, and providing an expert statement on drug effects and weight-loss effects on obesity for AstraZeneca. No other potential conflict of interest relevant to this article was reported.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

Drs. Carlsson and Peltonen contributed equally to this article.

We thank the staff members at 480 primary health care centers and 25 surgical departments in Sweden that participated in the study; and Gerd Bergmark, Christina Torefalk and Lisbeth Eriksson for administrative support.

SOURCE INFORMATION

From the Institutes of Medicine (L.M.S.C., M.P., S.A., Å.A., B.C., P.J., C.M., C.P., S.R., K.S., E.S., P.-A.S., L.S.) and Surgery (H.L.), Sahlgrenska Academy at the University of Gothenburg, and the Nordic School of Public Health (H.W.), Gothenburg, and the Department of Surgery, University Hospital, Örebro (I.N.) — all in Sweden; the Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki (M.P.); and Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge (C.B.).

Address reprint requests to Dr. Lars Sjöström at the SOS Secretariat, Vita Stråket 15, Sahlgrenska University Hospital, S-413 45 Gothenburg, Sweden, or at lars.v.sjostrom@medfak.gu.se.

N Engl J Med 2012; 367:695-704

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Main health effects of sleep deprivation (See ...

Main health effects of sleep deprivation (See Wikipedia:Sleep deprivation). Model: Mikael Häggström. To discuss image, please see Template talk:Häggström diagrams (Photo credit: Wikipedia)

Reporter: Venkat Karra, Ph.D.

Sleep may influence weight by affecting hormones, glucose metabolism and inflammation, say scientists. A new study has found that sleeping more than nine hours a night appears to suppress genetic factors that lead to weight gain. In contrast, getting too little sleep seems to have the opposite effect. Adding a few hours sleep to your night may prevent you from gaining weight. These new findings reveal a complex interaction between sleep and genetic factors linked to body weight.

The study found heritability of body mass index (BMI) — a measurement relating weight and height — was twice as high for short than for long sleepers.

Thus sleep well and stay healthy.

source

 Article:

Sleep Duration and Body Mass Index in Twins: A Gene-Environment Interaction

by Nathaniel F. Watson, MD, MSc; Kathryn Paige Harden, PhD; Dedra Buchwald, MD; Michael V. Vitiello, PhD; Allan I. Pack, MB ChB, PhD; David S. Weigle, MD; Jack Goldberg, PhD

Sleep, Volume 35/ Issue 05 / Tuesday, May 01, 2012

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