Posts Tagged ‘brown fat’

brown adipocyte protein CIDEA promotes lipid droplet fusion

Larry H. Bernstein, MD, FCAP, Curator





The brown adipocyte protein CIDEA promotes lipid droplet fusion via a phosphatidic acid-binding

Parker, Nicholas T Ktistakis, Ann M Dixon, Judith Klein-Seetharaman, Susan Henry, Mark Christian Dirk Dormann, Gil-Soo Han, Stephen A Jesch, George M Carman, Valerian Kagan, et al.

eLife 2015;10.7554/eLife.07485


Maintenance of energy homeostasis depends on the highly regulated storage and release of triacylglycerol primarily in adipose tissue and excessive storage is a feature of common metabolic disorders. CIDEA is a lipid droplet (LD)-protein enriched in brown adipocytes promoting the enlargement of LDs which are dynamic, ubiquitous organelles specialized for storing neutral lipids. We demonstrate an essential role in this process for an amphipathic helix in CIDEA, which facilitates embedding in the LD phospholipid monolayer and binds phosphatidic acid (PA). LD pairs are docked by CIDEA trans-complexes through contributions of the N-terminal domain and a C-terminal dimerization region. These complexes, enriched at the LD-LD contact site, interact with the cone-shaped phospholipid PA and likely increase phospholipid barrier permeability, promoting LD fusion by transference of lipids. This physiological process is essential in adipocyte differentiation as well as serving to facilitate the tight coupling of lipolysis and lipogenesis in activated brown fat.


Evolutionary pressures for survival in fluctuating environments that expose organisms to times of both feast and famine have selected for the ability to efficiently store and release energy in the form of triacyclglycerol (TAG). However, excessive or defective lipid storage is a key feature of common diseases such as diabetes, atherosclerosis and the metabolic syndrome (1). The organelles that are essential for storing and mobilizing intracellular fat are lipid droplets (LDs) (2). They constitute a unique cellular structure where a core of neutral lipids is stabilized in the hydrophilic cytosol by a phospholipid monolayer embedding LD-proteins. While most mammalian 46 cells present small LDs (<1 Pm) (3), white (unilocular) adipocytes contain a single giant LD occupying most of their cell volume. In contrast, brown (multilocular) adipocytes hold multiple LDs of lesser size, increasing the LD surface/volume ratio which facilitates the rapid consumption of lipids for adaptive thermogenesis (4).

The exploration of new approaches for the treatment of metabolic disorders has been stimulated by the rediscovery of active brown adipose tissue (BAT) in adult humans (5, 6) and by the induction of multilocular brown-like cells in white adipose tissue (WAT) (7). The multilocular morphology of brown adipocytes is a defining characteristic of these cells along with expression of genes such as Ucp1. The acquisition of a unilocular or multilocular phenotype is likely to be controlled by the regulation of LD growth. Two related proteins, CIDEA and CIDEC promote LD enlargement in adipocytes (8-10), with CIDEA being specifically found in BAT. Together with CIDEB, they form the CIDE (cell death-inducing DFF45-like effector) family of LD-proteins, which have emerged as important metabolic regulators (11).

Different mechanisms have been proposed for LD enlargement, including in situ neutral lipid synthesis, lipid uptake and LD-LD coalescence (12-14). The study of CIDE 62 proteins has revealed a critical role in the LD fusion process in which a donor LD progressively transfers its content to an acceptor LD until it is completely absorbed (15). However, the underlying mechanism by which CIDEC and CIDEA facilitate the interchange of triacylglycerol (TAG) molecules between LDs is not understood. In the present study, we have obtained a detailed picture of the different steps driving this LD enlargement process, which involves the stabilization of LD pairs, phospholipid binding, and the permeabilization of the LD monolayer to allow the transference of lipids.


CIDEA expression mimics the LD dynamics observed during the differentiation of brown adipocytes

Phases of CIDEA activity: LD targeting, LD-LD docking and LD growth

A cationic amphipathic helix in C-term drives LD targeting

The amphipathic helix is essential for LD enlargement

LD-LD docking is induced by the formation of CIDEA complexes

CIDEC differs from CIDEA in its dependence on the N-term domain

CIDEA interacts with Phosphatidic Acid

PA is required for LD enlargement


The Cidea gene is highly expressed in BAT, induced in WAT following cold exposure (46), and is widely used by researchers as a defining marker to discriminate brown or brite adipocytes from white adipocytes (7, 28). As evidence indicated a key role in the LD biology (47) we have characterized the mechanism by which CIDEA promotes LD enlargement, which involves the targeting of LDs, the docking of LD pairs and the transference of lipids between them. The lipid transfer step requires the interaction of CIDEA and PA through a cationic amphipathic helix. Independently of PA-binding, this helix is also responsible for anchoring CIDEA in the LD membrane. Finally, we demonstrate that the docking of LD pairs is driven by the formation of CIDEA complexes involving the N-term domain and a C-term interaction site.

CIDE proteins appeared during vertebrate evolution by the combination of an ancestor N-term domain and a LD-binding C-term domain (35). In spite of this, the full process of LD enlargement can be induced in yeast by the sole exogenous expression of 395 CIDEA, indicating that in contrast to SNARE-triggered vesicle fusion, LD fusion by lipid transference does not require the coordination of multiple specific proteins (48). Whereas vesicle fusion implicates an intricate restructuring of the phospholipid bilayers, LD fusion is a spontaneous process that the cell has to prevent by tightly controlling their phospholipid composition (23). However, although phospholipid-modifying enzymes have been linked with the biogenesis of LDs (49, 50), the implication of phospholipids in physiologic LD fusion processes has not been previously described.

Complete LD fusion by lipid transfer can last several hours, during which the participating LDs remain in contact. Our results indicate that both the N-term domain and a C-term dimerization site (aa 126-155) independently participate in the docking of LD pairs by forming trans interactions (Fig. 7). Certain mutations in the dimerization sites that do not eliminate the interaction result in a decrease on the TAG transference efficiency, reflected on the presence of small LDs docked to enlarged LDs. This suggests that in addition to stabilizing the LD-LD interaction, the correct conformation of the 409 CIDEA complexes is necessary for optimal TAG transfer. Furthermore, the formation of stable LD pairs is not sufficient to trigger LD fusion by lipid transfer. In fact, although LDs can be tightly packed in cultured adipocytes, no TAG transference across neighbour LDs is observed in the absence of CIDE proteins (15), showing that the phospholipid monolayer acts as a barrier impermeable to TAG. Our CG-MD simulations indicate that certain TAG molecules can escape the neutral lipid core of the LD and be integrated within the aliphatic chains of the phospholipid monolayer. This could be a transition state 416 prior to the TAG transference and our data indicates that the docking of the amphipathic helix in the LD membrane could facilitate this process. However, the infiltrated TAGs in LD membranes in the presence of mutant helices, or even in the absence of docking, suggests that this is not enough to complete the TAG transference.

To be transferred to the adjacent LD, the TAGs integrated in the hydrophobic region of the LD membrane should cross the energy barrier defined by the phospholipid polar heads, and the interaction of CIDEA with PA could play a role in this process, as suggested by the disruption of LD enlargement by the mutations preventing PA-binding (K167E/R171E/R175E) and the inhibition of CIDEA after PA depletion. The minor effects observed with more conservative substitutions in the helix, suggests that the presence of positive charges is sufficient to induce TAG transference by attracting anionic phospholipids present in the LD membrane. PA, which requirement is indicated by our PA-depletion experiments, is a cone-shaped anionic phospholipid which could locally destabilize the LD monolayer by favoring a negative membrane curvature incompatible with the spherical LD morphology (51). Interestingly, while the zwitterion PC, the main component of the monolayer, stabilizes the LD structure (23), the negatively charged PA promote their coalescence (29). This is supported by our CD-MD results which resulted in a deformation of the LD shape by the addition of PA. We propose a model in which the C-term amphipathic helix positions itself in the LD monolayer and interacts with PA molecules in its vicinity, which might include trans interactions with PA in the adjacent LD. The interaction with PA disturbs the integrity of the phospholipid barrier at the LD-LD interface, allowing the LD to LD transference of TAG molecules integrated in the LD membrane (Fig. 7). Additional alterations in the LD composition could be facilitating TAG transference, as differentiating adipocytes experience a reduction in saturated fatty acids in the LD phospholipids (52), and in their PC/PE ratio (53) which could increase the permeability of the LD membranes, and we previously observed that a change in the molecular structures of TAG results in an altered migration pattern to the LD surface (32).

During LD fusion by lipid transfer, the pressure gradient experienced by LDs favors TAG flux from small to large LDs (15). However, the implication of PA, a minor component of the LD membrane, could represent a control mechanism, as it is plausible that the cell could actively influence the TAG flux direction by differently regulating the levels of PA in large and small LDs, which could be controlled by the activity of enzymes such as AGPAT3 and LIPIN-1J (13, 30). This is a remarkable possibility, as a switch in the favored TAG flux direction could promote the acquisition of a multilocular phenotype and facilitate the browning of WAT (24). Interestingly, Cidea mRNA is the LD protein- encoding transcript that experiences the greatest increase during the cold-induced process by which multilocular BAT-like cells appear in WAT (24). Furthermore, in BAT, cold exposure instigates a profound increase in CIDEA protein levels that is independent of transcriptional regulation (54). The profound increase in CIDEA is coincident with elevated lipolysis and de novo lipogenesis that occurs in both brown and white adipose tissues after E-adrenergic receptor activation (55). It is likely that CIDEA has a central role in coupling these processes to package newly synthesized TAG in LDs for subsequent lipolysis and fatty acid oxidation. Importantly, BAT displays high levels of glycerol kinase activity (56, 57) that facilitates glycerol recycling rather than release into the blood stream, following induction of lipolysis (58), which occurs in WAT. Hence, the reported elevated glycerol released from cells depleted of CIDEA (28) is likely to be a result of decoupling lipolysis from the ability to efficiently store the products of lipogenesis in LDs and therefore producing a net increase in detected extracellular glycerol. This important role of CIDEA is supported by the marked depletion of TAG in the BAT of Cidea null mice following overnight exposure to 4 °C (28) and our findings that CIDEA-dependent LD enlargement is maintained in a lipase negative yeast strain.

Cidea and the genes that are required to facilitate high rates of lipolysis and lipogenesis are associated with the “browning” of white fat either following cold exposure (46) or in genetic models such as RIP140 knockout WAT (59). The induction of a brown- like phenotype in WAT has potential benefits in the treatment and prevention of metabolic disorders (60). Differences in the activity and regulation of CIDEC and CIDEA could also be responsible for the adoption of unilocular or multilocular phenotypes. In addition to their differential interaction with PLIN1 and 5, we have observed that CIDEC is more resilient to the deletion of the N-term than CIDEA, indicating that it may be less sensitive to regulatory posttranslational modifications of this domain. This robustness of CIDEC activity together with its potentiation by PLIN1, could facilitate the continuity of the LD enlargement in white adipocytes until the unilocular phenotype is achieved. In contrast, in brown adipocytes expressing CIDEA the process would be stopped at the multilocular stage for example due to post-translational modifications that modulate the function or stability of the protein or alteration of the PA levels in LDs.


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Obesity Issues

Larry H. Bernstein, MD, FCAP, Curator



The Changing Face of Obesity

Science tells us obesity is a chronic disease. Why does the outmoded and injurious notion that it is a problem of willpower persist?

By Joseph Proietto | November 1, 2015

In Dante Alighieri’s Divine Comedy the narrator meets a man named Ciacco who had been sent to Hell for the “Damning sin of Gluttony.” According to Catholic theology, in order to end up in Hell one must willfully commit a serious sin. So Dante believed that fat people chose to be fat. This antiquated view of the cause of obesity is still widespread, even among medical professionals. The consequences of this misconception are significant, because it forms the basis for the discrimination suffered by the obese; for the wasting of scarce resources in attempts to change lifestyle habits by public education; and for the limited availability of subsidized obesity treatments.

While obesity is often labeled a lifestyle disease, poor lifestyle choices alone account for only a 6 to 8 kg weight gain. The body has a powerful negative feedback system to prevent excessive weight gain. The strongest inhibitor of hunger, the hormone leptin, is made by fat cells. A period of increased energy intake will result in fat deposition, which will increase leptin production. Leptin suppresses hunger and increases energy expenditure. This slows down weight gain. To become obese, it may be necessary to harbor a genetic difference that makes the individual resistant to the action of leptin.

Evidence from twin and adoption studies suggests that obesity has a genetic basis, and over the past two decades a number of genes associated with obesity have been described. The most common genetic defect in European populations leading to severe obesity is due to mutations in the gene coding for the melanocortin 4 receptor (MCR4). Still, this defect can explain severe obesity in only approximately 6 percent to 7 percent of cases (J Clin Invest, 106:271-79, 2000). Other genes have been discovered that can cause milder increases in weight; for example, variants of just one gene (FTO) can explain up to 3 kg of weight variation between individuals (Science, 316:889-94, 2007).

Genes do not directly cause weight gain. Rather, genes influence the desire for food and the feeling of satiety. In an environment with either poor access to food or access to only low-calorie food, obesity may not develop even in persons with a genetic predisposition. When there is an abundance of food and a sedentary lifestyle, however, an obesity-prone person will experience greater hunger and reduced satiety, increasing caloric intake and weight gain.

Since the 1980s, there has been a rapid rise in the prevalence of obesity worldwide, a trend that likely results from a variety of complex causes. There is increasing evidence, for example, that the development of obesity on individual or familial levels may be influenced by environmental experiences that occur in early life. For example, if a mother is malnourished during early pregnancy, this results in epigenetic changes to genes involved in the set points for hunger and satiety in the developing child. These changes may then become fixed, resulting in a tendency towards obesity in the offspring.

The biological basis of obesity is further highlighted by the vigorous defense of weight following weight loss. There are at least 10 circulating hormones that modulate hunger. Of these, only one has been confirmed as a hunger-inducing hormone (ghrelin), and it is made and released by the stomach. In contrast, nine hormones suppress hunger, including CCK, PYY, GLP-1, oxyntomodulin, and uroguanylin from the small bowel; leptin from fat cells; and insulin, amylin, and pancreatic polypeptide from the pancreas.


After weight loss, regardless of the diet employed, there are changes in circulating hormones involved in the regulation of body weight. Ghrelin levels tend to increase and levels of multiple appetite-suppressing hormones decrease. There is also a subjective increase in appetite. Researchers have shown that even after three years, these hormonal changes persist (NEJM, 365:1597-604, 2011; Lancet Diabetes and Endocrinology, 2:954-62, 2014). This explains why there is a high rate of weight regain after diet-induced weight loss.

Given that the physiological responses to weight loss predispose people to regain that weight, obesity must be considered a chronic disease. Data show that those who successfully maintain their weight after weight loss do so by remaining vigilant and constantly applying techniques to oppose weight regain. These techniques may involve strict diet and exercise practices and/or pharmacotherapy.

It is imperative for society to move away from a view that obesity is simply a lifestyle issue and to accept that it is a chronic disease. Such a change would not only relieve the stigma of obesity but would also empower politicians, scientists and clinicians to tackle the problem more effectively.

Joseph Proietto was the inaugural Sir Edward Dunlop Medical Research Foundation Professor of Medicine in the Department of Medicine, Austin Health at the University of Melbourne in Australia. He is a researcher and clinician investigating and treating obesity and type 2 diabetes.



A Weighty Anomaly

Why do some obese people actually experience health benefits?

By Jyoti Madhusoodanan | November 1, 2015

THE ENDOCRINE THEORY: Some researchers have posited that fat cells may secrete molecules that affect glucose homeostasis in muscle or liver tissue.COURTESY OF MITCHELL LAZAR

In the early 19th century, Belgian mathematician Adolphe Quetelet was obsessed with a shape: the bell curve. While helping with a population census, Quetelet proposed that the spread of human traits such as height and weight followed this trend, also known as a Gaussian or normal distribution. On a quest to define a “normal man,” he showed that human height and weight data fell along his beloved bell curves, and in 1823 devised the “Quetelet Index”—more familiar to us today as the BMI, or body mass index, a ratio of weight to height.

Nearly two centuries later, clinicians, researchers, and fitness instructors continue to rely on this metric to pigeonhole people into categories: underweight, healthy, overweight, or obese. But Quetelet never intended the metric to serve as a way to define obesity. And now, a growing body of evidence suggests these categories fail to accurately reflect the health risks—or benefits—of being overweight.

Although there is considerable debate surrounding the prevalence of metabolically healthy obesity, when obesity is defined in terms of BMI (a BMI of 30 or higher), estimates suggest that about 10 percent of adults in the U.S. are obese yet metabolically healthy, while as many as 80 percent of those with a normal BMI may be metabolically unhealthy, with signs of insulin resistance and poor circulating lipid levels, even if they suffer no obvious ill effects. “If all we know about a person is that they have a certain body weight at a certain height, that’s not enough information to know their health risks from obesity,” says health-science researcher Paul McAuley of Winston-Salem State University. “We need better indicators of metabolic health.”

The dangers of being overweight, such as a higher risk of heart disease, type 2 diabetes, and other complications, are well known. But some obese individuals—dubbed the “fat fit”—appear to fare better on many measures of health when they’re heavier. Studies have found lower mortality rates, better response to hemodialysis in chronic kidney disease, and lower incidence of dementia in such people. Mortality, it’s been found, correlates with obesity in a U-shaped curve (J Sports Sci, 29:773-82, 2011). So does extra heft help or hurt?

To answer that question, researchers are trying to elucidate the metabolic reasons for this obesity paradox.

In a recent study, Harvard University epidemiologist Goodarz Danaei and his colleagues analyzed data from nine studies involving a total of more than 58,000 participants to tease apart how obesity and other well-known metabolic risk factors influence the risk of coronary heart disease. Controlling these other risk factors, such as hypertension or high cholesterol, with medication is simpler than curbing obesity itself, Danaei explains. “If you control a person’s obesity you get rid of some health risks, but if you control hypertension or diabetes, that also reduces health risks, and you can do the latter much more easily right now.”

Danaei’s team assessed BMI and metabolic markers such as systolic blood pressure, total serum cholesterol, and fasting blood glucose. The three metabolic markers only explained half of the increased risk of heart disease across all study participants. In obese individuals, the other half appeared to be mediated by fat itself, perhaps via inflammatory markers or other indirect mechanisms (Epidemiology, 26:153-62, 2015). While Danaei’s study was aimed at understanding how obesity hurts health, the results also uncovered unknown mechanisms by which excess adipose tissue might exert its effects. This particular study revealed obesity’s negative effects, but might these unknown mechanisms hold clues that explain the obesity paradox?

Other researchers have suggested additional possibilities—for example, that inflammatory markers such as TNF-α help combat conditions such as chronic kidney disease, or that obesity makes a body more capable of making changes to, and tolerating changes in, blood flow depending on systemic needs (Am J Clin Nutr, 81:543-54, 2005).

According to endocrinologist Mitchell Lazar at the University of Pennsylvania, the key to explaining the obesity paradox may be two nonexclusive ways fat tissue is hypothesized to function. One mechanism, termed the endocrine theory, suggests that fat cells secrete, or don’t secrete enough of, certain molecules that influence glucose homeostasis in other tissues, such as muscle or liver. The first such hormone to be discovered was leptin; later studies reported several other adipocyte-secreted factors, including adiponectin, resistin, and various cytokines.

The other hypothesis, dubbed the spillover theory, suggests that storing lipids in fat cells has some pluses. Adipose tissue might sequester fat-soluble endotoxins, and produce lipoproteins that can bind to and clear harmful lipids from circulation. When fat cells fill up, however, these endotoxins are stashed in the liver, pancreas, or other organs—and that’s when trouble begins. In “fat fit” people, problems typically linked to obesity such as high cholesterol or diabetes may be avoided simply because their adipocytes mop up more endotoxins.

“In this model, one could imagine that if you could store even more fat in fat cells, you could be even more obese, but you might be protected from problems [associated with] obesity because you’re protecting the other tissues from filling up with lipids that cause problems,” says Lazar. “This may be the most popular current model to explain the fat fit.”

Although obesity greatly increases the risk of type 2 diabetes—up to 93-fold in postmenopausal women, for example—not all obese people suffer from the condition. Similarly, a certain subtype of individuals with “normal” BMIs are at greater risk of developing insulin resistance and type 2 diabetes than others with BMIs in the same range. Precisely what distinguishes these two cohorts is still unclear. “Just as important as explaining why some obese people don’t get diabetes is to explain why other subgroups—normal-weight people or those with lipodystrophy—sometimes get it,” Lazar says. “If there are multiple subtypes of obesity and diabetes, can we figure out genetic aspects or biomarkers that cause one of these phenotypes and not the other?”

To Lazar, McAuley, and other researchers, it’s increasingly evident that BMI may not be that metric. Finding better ways to assess a healthy weight, however, has proven challenging. Researchers have tested measures, such as the body shape index (ABSI) or the waist-hip ratio, which attempt to gauge visceral fat—considered to be more metabolically harmful than fat in other body locations. However, these metrics have yet to be implemented widely in clinics, and few are as simple to understand as the BMI (Science, 341:856-58, 2013).

Independent of metrics, however, the health message regarding weight is still unanimous: exercise and healthy dietary choices benefit everyone. “At a certain point, despite all the so-called fit-fat people, the demographics say that there’s a huge risk of diabetes and heart disease at very high BMI,” notes Lazar. “We can’t assume we’ll be one of the lucky ones who will have a BMI in the obese category but will still be protected from heart disease.”

Correction (November 2): The original version of this article misattributed the pull quote above. The attribution for this quote has been corrected, and The Scientist regrets the error.




 Science 23 Aug 2013;  341(6148): 856858     DOI:
Obesity paradoxes.
In this review, we examine the original obesity paradox phenomenon (i.e. in cardiovascular disease populations, obese patients survive better), as well as three other related paradoxes (pre-obesity, “fat but fit” theory, and “healthy” obesity). An obesity paradox has been reported in a range of cardiovascular and non-cardiovascular conditions. Pre-obesity (defined as a body mass index of 25.0-29.9 kg · m⁻²) presents another paradox. Whereas “overweight” implies increased risk, it is in fact associated with decreased mortality risk compared with normal weight. Another paradox concerns the observation than when fitness is taken into account, the mortality risk associated with obesity is offset. The final paradox under consideration is the presence of a sizeable subset of obese individuals who are otherwise healthy. Consequently, a large segment of the overweight and obese population is not at increased risk for premature death. It appears therefore that low cardiorespiratory fitness and inactivity are a greater health threat than obesity, suggesting that more emphasis should be placed on increasing leisure time physical activity and cardiorespiratory fitness as the main strategy for reducing mortality risk in the broad population of overweight and obese adults.
Obesity, insulin resistance, and cardiovascular disease.
Recent Prog Horm Res. 2004;59:207-23.
The ability of insulin to stimulate glucose disposal varies more than six-fold in apparently healthy individuals. The one third of the population that is most insulin resistant is at greatly increased risk to develop cardiovascular disease (CVD), type 2 diabetes, hypertension, stroke, nonalcoholic fatty liver disease, polycystic ovary disease, and certain forms of cancer. Between 25-35% of the variability in insulin action is related to being overweight. The importance of the adverse effects of excess adiposity is apparent in light of the evidence that more than half of the adult population in the United States is classified as being overweight/obese, as defined by a body mass index greater than 25.0 kg/m(2). The current epidemic of overweight/obesity is most-likely related to a combination of increased caloric intake and decreased energy expenditure. In either instance, the fact that CVD risk is increased as individuals gain weight emphasizes the gravity of the health care dilemma posed by the explosive increase in the prevalence of overweight/obesity in the population at large. Given the enormity of the problem, it is necessary to differentiate between the CVD risk related to obesity per se, as distinct from the fact that the prevalence of insulin resistance and compensatory hyperinsulinemia are increased in overweight/obese individuals. Although the majority of individuals in the general population that can be considered insulin resistant are also overweight/obese, not all overweight/obese persons are insulin resistant. Furthermore, the cluster of abnormalities associated with insulin resistance – namely, glucose intolerance, hyperinsulinemia, dyslipidemia, and elevated plasma C-reactive protein concentrations — is limited to the subset of overweight/obese individuals that are also insulin resistant. Of greater clinical relevance is the fact that significant improvement in these metabolic abnormalities following weight loss is seen only in the subset of overweight/obese individuals that are also insulin resistant. In view of the large number of overweight/obese subjects at potential risk to be insulin resistant/hyperinsulinemic (and at increased CVD risk), and the difficulty in achieving weight loss, it seems essential to identify those overweight/obese individuals who are also insulin resistant and will benefit the most from weight loss, then target this population for the most-intensive efforts to bring about weight loss.
Long-Term Persistence of Hormonal Adaptations to Weight Loss

Priya Sumithran, Luke A. Prendergast, Elizabeth Delbridge, Katrina Purcell, Arthur Shulkes, Adamandia Kriketos, and Joseph Proietto

N Engl J Med 2011; 365:1597-1604   October 27, 2011

After weight loss, changes in the circulating levels of several peripheral hormones involved in the homeostatic regulation of body weight occur. Whether these changes are transient or persist over time may be important for an understanding of the reasons behind the high rate of weight regain after diet-induced weight loss.

Weight loss (mean [±SE], 13.5±0.5 kg) led to significant reductions in levels of leptin, peptide YY, cholecystokinin, insulin (P<0.001 for all comparisons), and amylin (P=0.002) and to increases in levels of ghrelin (P<0.001), gastric inhibitory polypeptide (P=0.004), and pancreatic polypeptide (P=0.008). There was also a significant increase in subjective appetite (P<0.001). One year after the initial weight loss, there were still significant differences from baseline in the mean levels of leptin (P<0.001), peptide YY (P<0.001), cholecystokinin (P=0.04), insulin (P=0.01), ghrelin (P<0.001), gastric inhibitory polypeptide (P<0.001), and pancreatic polypeptide (P=0.002), as well as hunger (P<0.001).

What’s new in endocrinology and diabetes mellitus

Large genome wide association studies have demonstrated that variants in the FTO gene have the strongest association with obesity risk in the general population, but the mechanism of the association has been unclear. However, a nonocoding causal variant in FTO has now been identified that changes the function of adipocytes from energy utilization (beige fat) to energy storage (white fat) with a fivefold decrease in mitochondrial thermogenesis [17]. When the effect of the variant was blocked in genetically engineered mice, thermogenesis increased and weight gain did not occur, despite eating a high-fat diet. Blocking the gene’s effect in human adipocytes also increased energy utilization. This observation has important implications for potential new anti-obesity drugs. (See “Pathogenesis of obesity”, section on ‘FTO variants’.)

Liraglutide for the treatment of obesity (July 2015)

Along with diet, exercise, and behavior modification, drug therapy may be a helpful component of treatment for select patients who are overweight or obese. Liraglutide is a glucagon-like peptide-1 (GLP-1) receptor agonist, used for the treatment of type 2 diabetes, and can promote weight loss in patients with diabetes, as well as those without diabetes.

In a randomized trial in nondiabetic patients who had a body mass index (BMI) of ≥30 kg/m2 or ≥27 kg/m2 with dyslipidemia and/or hypertension, liraglutide 3 mg once daily, compared with placebo, resulted in greater mean weight loss (-8.0 versus -2.6 kg with placebo) [18]. In addition, cardiometabolic risk factors, glycated hemoglobin (A1C), and quality of life improved modestly. Gastrointestinal side effects transiently affected at least 40 percent of the liraglutide group and were the most common reason for withdrawal (6.4 percent). Liraglutide is an option for select overweight or obese patients, although gastrointestinal side effects (nausea, vomiting) and the need for a daily injection may limit the use of this drug. (See “Obesity in adults: Drug therapy”, section on ‘Liraglutide’.)

In a trial designed specifically to evaluate the effect of liraglutide on weight loss in overweight or obese patients with type 2 diabetes (mean weight 106 kg), liraglutide, compared with placebo, resulted in greater mean weight loss (-6.4 kg and -5.0 kg for liraglutide 3 mg and 1.8 mg, respectively, versus -2.2 kg for placebo) [19]. Treatment with liraglutide was associated with better glycemic control, a reduction in the use of oral hypoglycemic agents, and a reduction in systolic blood pressure. Although liraglutide is not considered as initial therapy for the majority of patients with type 2 diabetes, it is an option for select overweight or obese patients with type 2 diabetes who fail initial therapy with lifestyle intervention and metformin.  (See “Glucagon-like peptide-1 receptor agonists for the treatment of type 2 diabetes mellitus”, section on ‘Weight loss’.)

The Skinny on Fat Cells

Bruce Spiegelman has spent his career at the forefront of adipocyte differentiation and metabolism.

By Anna Azvolinsky | November 1, 2015

Bruce Spiegelman
Stanley J. Korsmeyer Professor of Cell Biology
and Medicine
Harvard Medical School
Director, Center for Energy Metabolism
and Chronic
Disease, Dana-Farber Cancer Institute, Boston

It’s hard to know whether you have the right stuff to be a scientist, but I had a passion for the research,” says Bruce Spiegelman, professor of cell biology at Harvard Medical School and the Dana-Farber Cancer Institute. After receiving his PhD in biochemistry from Princeton University in 1978, Spiegelman sent an application to do postdoctoral research to just one lab. “I wasn’t thinking I should apply to five different labs. I just marched forward more or less in a straight line,” he says. Spiegelman did know that he had no financial backup and depended on research fellowships throughout the early phase of his science career. “I thought it was fantastic, and still think so, that a PhD in science is supported by the government. I certainly appreciated that, because many of my friends in the humanities had to support themselves by cobbling together fellowships and teaching every semester, whereas we didn’t face similar challenges in the sciences.”

Since his graduate student days, Spiegelman has realized his potential, pioneering the study of adipose tissue biology and metabolism. He was introduced to the field in Howard Green’s laboratory, then at MIT, where Spiegelman began his one and only postdoc in 1978. Green had recently developed a system for culturing adipose cells and asked Spiegelman if he wanted to study fat cell differentiation. “I knew nothing about adipose tissue, but I was really interested in any model of how one cell switches to another. Whether skin or fat didn’t matter too much to me, because I was not coming at this from the perspective of physiology but from the perspective of how do these switches work at a molecular level?”

Spiegelman has stuck with studying the biology and differentiation of fat cells for more than 30 years. While looking for the master transcriptional regulator of fat development—which his laboratory found in 1994—Spiegelman’s group also discovered one of the first examples of a nuclear oncogene that functions as a transcription factor, and, more recently, the team found that brown fat and white fat come from completely different origins and that brown and beige fat are distinct cell types. Spiegelman was also the first to provide evidence for the connection between inflammation, insulin resistance, and fat tissue.

Here, Spiegelman talks about his strong affinity for the East Coast, his laboratory’s search for molecules that can crank up brown fat production and activity, and the culture of his laboratory’s weekly meeting.

Spiegelman Sets Out

First publication. Spiegelman grew up in Massapequa, New York, a town on Long Island. “Birds, insects, fish, and animals were fascinating to me. As a kid, I imagined I would be a wildlife ranger,” he says. Spiegelman and his brother were the first in their family to attend college; Spiegelman entered the College of William and Mary in 1970 thinking he would major in psychology. But before taking his first psychology course, he had to take a biology course, really loved it, and switched his major. For his senior thesis, he chose one of the few labs that did biochemistry-related research. He studied cultures of the filamentous fungus Aspergillus ornatus in which he induced the upregulation of a metabolic enzyme. Spiegelman applied a calculus transformation that related the age of the culture to the age of individual cells, something that had not been previously done. The work earned him his first first-author publication in 1975. “It was not a great breakthrough, but I think it showed that I was maybe applying myself more than the typical undergraduate.”

Full steam ahead. “My interest in laboratory research was intense. Even though it was not particularly inspired work, the first-author publication in a college where not many of the professors published a lot gave me a lot of confidence. It was probably out of proportion to the quality of the actual work.” That confidence and Spiegelman’s interest in the chemistry of living things led him to pursue a PhD in biochemistry at Princeton University. “Very early on, I felt that I couldn’t understand biology if it didn’t go to the molecular level. To me, just describing how an animal lived without understanding how it worked was very unsatisfying. I think it was one of the best decisions that I made in my life, to do a PhD in biochemistry,” he says, “because if you really want to understand living systems, you are very limited in how you can understand them without having a strong background in biochemistry because these are, essentially, chemical systems.”

Embracing molecular biology. Spiegelman initially joined Arthur Pardee’s laboratory, but switched when Pardee left Princeton for Harvard University in 1975. Because he was already collaborating with Marc Kirschner, a cell biologist and biochemist who studies the regulation of the cell cycle and how the cytoskeleton works, it was an easy transition to transfer to the new laboratory. In Kirschner’s group, Spiegelman became the cell biologist among many protein biochemists working on microtubule assembly in vitro. Rather than understanding how the proteins fit together to form the filamentous structures, Spiegelman wanted to understand what controlled their assembly inside cells. Working in mammalian cells, Spiegelman published three consecutive Cell papers on how microtubule assembly occurs in vivo. The firstpaper, from 1977, demonstrated that a nucleotide functions to stabilize the tubulin molecule rather than to regulate tubulin assembly in vivo.

Spiegelman Simmers

A new tool. For his next move, Spiegelman wanted to marry his background in biochemistry and molecular biology with a good cellular model system. He became interested in differentiation at the end of his PhD, while studying how the cytoskeleton is reorganized during neural differentiation, and settled on Green’s MIT laboratory for his postdoc. Green had developed a way to study both skin and fat cell differentiation. Again, Spiegelman was the odd man out, working on the molecular biology of fat cell differentiation while most of the graduate students and postdocs focused on the cellular biology of skin cell differentiation. While there, Spiegelman learned how to clone cDNA—a new method that some researchers thought was just another new fad, he says. “I thought it was pretty obvious that this was a tool that would be a game changer. I could see how I could clone some of the cDNAs and genes that were regulated in the fat cell lineage and then try to understand the regulation of these genes.”

Setting the stage. Spiegelman demonstrated that cAMP regulates the synthesis of certain enzymes in fat cells during differentiation. But while this was the most influential paper from his postdoc, says Spiegelman, it was his demonstration of cloning mRNAs from adipocytes, published in 1983, that set the stage for cloning fat-selective genes. The work, mostly done when Spiegelman was already a new faculty member at the Dana-Farber Cancer Institute, stemmed from his learning molecular cloning in Phillip Sharp’s lab at MIT and Bryan Roberts’s lab at Harvard. “This was the raw material from which we eventually cloned PPARγ and showed it to be the master regulator of fat [cell] development.”

Roots. Spiegelman became an assistant professor at the Harvard Medical School in 1982, when he was not yet 30. Although he had entertained the idea of moving to the West Coast with his wife, whom he had met at Princeton where she obtained a PhD in French literature, Spiegelman says he is really an East Coaster at heart. “My wife and I came to love Boston and were very comfortable there. Our families were both in New York, which was close, but not too close, and we really enjoyed the culture and pace of Boston; it was more ‘us.’ We really liked to visit California but didn’t particularly want to move there. We’re both real Northeastern people.”

Relating to Sisyphus. The transition from doing a postdoc to setting up his own laboratory was “very exciting and terribly stressful,” says Spiegelman. “When I think back, I always tried to be professional with my laboratory, but I was so stressed at suddenly being on my own with no management training.” The people resources he had encountered in his graduate and postdoctoral training labs were also not there yet, and he says his first publication as a principal investigator was like pushing a rock up a hill. But eventually, Spiegelman’s lab built a reputation and reached a critical mass of talented people who advanced the science. Again in 1983, Spiegelman produced a publication showing that morphological manipulation can affect gene expression and adipose differentiation.

End goal. Spiegelman’s goal was to find a master molecule that  orchestrates the conversion of adipocyte precursor cells into bona fide fat cells. Piece by piece, his lab identified the enhancers, promoters, and other regulatory elements involved in adipocyte differentiation. In 1994, graduate student Peter Tontonoz finallyfound that the PPARγ gene, inserted via a retroviral vector into fibroblasts, could induce the cells to become adipose cells. “It took 10 years,” Spiegelman says. Along the way, the laboratory found that c-fos, the product of a famous nuclear oncogene, bound to the promoters of fat-specific genes and worked as a transcription factor. “It was not really known how nuclear oncogenes worked. This was one of the first papers showing that these oncogenes bound to gene promoters and were transcription factors.”

A wider scope. In 1993, graduate student Gökhan Hotamisligil found that tumor necrosis factor-alpha(TNF-α), is induced in the fat tissue of rodent models of obesity and diabetes. The paper sparked the formation of the field of immunometabolism and resulted in the expansion of Spiegelman’s lab into the physiology arena, partly thanks to the guidance of C. Ronald Kahn and Jeff Flier, who both study metabolism and diabetes. But the work initially encountered pushback, says Spiegelman, partly because it was the merging of two fields.

Spiegelman Scales Up

Fat color palette. Brown fat tissue, abundant in infants but scarce in adults, is a metabolically active form of fat that is chock full of mitochondria and is found in pockets in the body distinct from white fat tissue.Pere Puigserver, then a postdoc in Spiegelman’s lab, found that the coactivator PCG-1, binding to PPARγ and other nuclear receptors, could stimulate mitochondrial biogenesis. The PCG-1 gene is turned on by stimuli such as exercise or a cold environment. Later, postdoc Patrick Seale, Spiegelman, and their colleagues showed brown fat cells derive from the same lineage that gives rise to skeletal muscle. “This was a big surprise, maybe the biggest surprise we ever uncovered in the lab,” says Spiegelman.

A paler shade of brown. More recently, in 2012, Spiegelman’s laboratory showed that within adult white adipose tissue, there are pockets of a yet another type of fat tissue that he called beige fat. “I think the evidence is very good from rodents that if you activate brown and beige fat, you get metabolic benefit both in obesity and diabetes. So the question now is: Can that be done in humans in a way that’s beneficial and not toxic?”  The lab is now looking to identify molecules that can either ramp up the activity of brown and beige fat or increase the production of both cell types as possible therapeutics for metabolic disorders or even cancer-associated cachexia. “Anyone who says that either approach will work better is being foolish. We just don’t know enough to go after just one or the other.”

On the irisin controversy. After reporting in 2012 that a muscle-related hormone called irisin could switch white fat to metabolically active brown fat, Spiegelman became embroiled in a media-covered debate about whether the molecule really exists; he was also the victim of a potential fraud plot. Most recently, Spiegelman provided thorough evidence that irisin does in fact exist. On the controversy, he says it’s a fine line between defending his scientific integrity and not adding more fuel to the fire or engaging with his harassers. “We have a long track record of doing credible and reproducible science and it was not that complicated to address the paper that claimed irisin was ‘a myth.’ That study used very outmoded scientific approaches.”

Raw talent. Many of Spiegelman’s trainees have gone on to become very successful scientists, including Tontonoz, Hotamisligil, Evan Rosen, and Randy Johnson. “It’s a quantum change in the experience of doing science when you get people who have their own visions. I would have thought that interacting with smart people would mainly help me get my scientific vision accomplished. And that was partly true, but also it changed my vision. When you have people challenging you on a day-to-day basis, you learn from them through the questions they ask and the way they challenge you in a constructive way. They made me a much better scientist.”

Rigorous mentorship.  “I feel very passionately that a major part of my job is to prepare the next generation of scientists. Everyone who comes through my lab will tell you that I take that very seriously. We make sure my students give a lot of talks and get critical assessments of their presentations to our lab group. I am very hands-on both scientifically and in developing the way students project their vision. I had a very good mentor, Marc Kirschner, and I’d like to think that I learned how to be a mentor from him. I want to make sure that when people walk out of my lab they are prepared to run independent research programs.”

Greatest Hits

  • Identified the master regulator of adipogenesis, the nuclear receptor PPARγ
  • Was the first to show that a nuclear oncogene, c-fos, codes for a transcription factor that binds to the promoters of genes
  • Demonstrated that adipose tissue synthesizes tumor necrosis factor-alpha (TNF-α), providing the first direct link between obesity, inflammation, insulin resistance, and fat tissue.
  • Showed that brown fat cells are not developmentally related to white fat
  • Identified beige fat as a distinct cell type, different from either white or brown fat


Fanning the Flames

Obesity triggers a fatty acid synthesis pathway, which in turn helps drive T cell differentiation and inflammation.

By Kate Yandell | November 1, 2015


The paper
Y. Endo et al., “Obesity drives Th17 cell differentiation by inducing the lipid metabolic kinase, ACC1,” Cell Reports, 12:1042-55, 2015.

Cell Rep. 2015 Aug 11;12(6):1042-55. Epub 2015 Jul 30.
Obesity Drives Th17 Cell Differentiation by Inducing the Lipid Metabolic Kinase, ACC1.
  • A high-fat diet augments Th17 cell development and the expression of Acaca
  • ACC1 controls Th17 cell development in vitro and Th17 cell pathogenicity in vivo
  • ACC1 modulates RORγt function in developing Th17 cells
  • Obesity in humans induces ACACA and IL-17A expression in CD4 T cells

Chronic inflammation due to obesity contributes to the development of metabolic diseases, autoimmune diseases, and cancer. Reciprocal interactions between metabolic systems and immune cells have pivotal roles in the pathogenesis of obesity-associated diseases, although the mechanisms regulating obesity-associated inflammatory diseases are still unclear. In the present study, we performed transcriptional profiling of memory phenotype CD4 T cells in high-fat-fed mice and identified acetyl-CoA carboxylase 1 (ACC1, the gene product of Acaca) as an essential regulator of Th17 cell differentiation in vitro and of the pathogenicity of Th17 cells in vivo. ACC1 modulates the DNA binding of RORγt to target genes in differentiating Th17 cells. In addition, we found a strong correlation between IL-17A-producing CD45RO(+)CD4 T cells and the expression of ACACA in obese subjects. Thus, ACC1 confers the appropriate function of RORγt through fatty acid synthesis and regulates the obesity-related pathology of Th17 cells.

Figure thumbnail fx1

FEEDING INFLAMMATION: When mice eat a diet high in fat, their CD4 T cells show increased expression of the fatty acid biosynthesis gene Acaca, which encodes the enzyme ACC1 (1). Products of the ACC1 fatty acid synthesis pathway encourage the transcription factor RORγt to bind near the gene encoding the cytokine IL-17A (2). There, RORγt recruits an enzyme called p300 to modify the genome epigenetically and turn on IL-17A. The memory T cells then differentiate into inflammatory T helper 17 cells.
See full infographic: PDF

Obesity often comes with a side of chronic inflammation, causing inflammatory chemicals and immune cells to flood adipose tissue, the hypothalamus, the liver, and other areas of the body. Inflammation is a big part of what makes obesity such an unhealthy condition, contributing to Type 2 diabetes, heart disease, cancers, autoimmune disorders, and possibly even neurodegenerative diseases.

To better understand the relationship between obesity and inflammation, Toshinori Nakayama, Yusuke Endo, and their colleagues at Chiba University in Japan started with what often leads to obesity: a high-fat diet. They fed mice rich meals for a couple of months and looked at how gene expression in the animals’ T cells compared to gene expression in the T cells of mice fed a normal diet. Most notably, they found increased expression ofAcaca, a gene that codes for a fatty acid synthesis enzyme called acetyl coA carboxylase 1 (ACC1). They went on to show that the resulting increase in fatty acid levels pushed CD4 T cells to differentiate into inflammatory T helper 17 (Th17) cells.

Th17 cells help fight off invading fungi and some bacteria. But these immune cells can also spin out of control in autoimmune diseases such as multiple sclerosis. Nakayama’s team showed that either blocking ACC1 activity with a drug called TOFA or deleting a key portion of Acaca in mouse CD4 T cells reduced the generation of pathologic Th17 cells. Overexpressing Acaca increased Th17-cell generation.

The researchers also demonstrated that mice fed a high-fat diet had elevated susceptibility to a multiple sclerosis–like disease, and that TOFA reduced the symptoms.

“This is a very intriguing finding, suggesting not only that obesity can directly induce Th17 differentiation but also indicating that pharmacologic targeting of fatty acid synthesis may help to interfere with obesity-associated inflammation,” Tim Sparwasser of the Twincore Center for Experimental and Clinical Infection Research in Hannover, Germany, says in an email. Sparwasser and his colleagues had previously shown that ACC1 is required for the differentiation of Th17 cells in mice and humans.

Nakayama explains that CD4 T cells must undergo profound metabolic changes as they mature and differentiate. “The intracellular metabolites, including fatty acids, are essential for cell proliferation and cell growth,” he says in an email. When fatty acid levels in T cells increase, the cells are activated and begin to proliferate.

“It’s a nice illustration of how, really, immune response is so highly connected to the metabolic state of the cell,” says Gökhan S. Hotamisligil of Harvard University’s T.H. Chan School of Public Health who was not involved in the study. “The immune system launches its responses commensurate with the sources of nutrients and energy from the environment,” he adds in an email.

There are still missing pieces in the path from high-fat diet to increased Acaca expression to ACC1’s influence on T-cell differentiation. It also remains to be seen how this plays out in obese humans, although Nakayama and colleagues did show that inhibiting ACC1 reduced pathologic Th17 generation in human immune cell cultures, and that the T cells of obese humans contain elevated levels of ACC1 and show signs of increased differentiation into Th17 cells.


The prevalence of obesity has been increasing worldwide, and obesity is now a major public health problem in most developed countries (Gregor and Hotamisligil, 2011, Ng et al., 2014). Obesity-induced inflammation contributes to the development of various chronic diseases, such as autoimmune diseases, metabolic diseases, and cancer (Kanneganti and Dixit, 2012, Kim et al., 2014,Osborn and Olefsky, 2012, Winer et al., 2009a). A number of studies have pointed out the importance of reciprocal interactions between metabolic systems and immune cells in the pathogenesis of obesity-associated diseases (Kaminski and Randall, 2010, Kanneganti and Dixit, 2012, Kim et al., 2014, Mauer et al., 2014, Stienstra et al., 2012, Winer et al., 2011).

Elucidating the molecular mechanisms by which naive CD4 T cells differentiate into effector T cells is crucial for understanding helper T (Th) cell-mediated immune pathogenicity. After antigen stimulation, naive CD4 T cells differentiate into at least four distinct Th cell subsets: Th1, Th2, Th17, and inducible regulatory T (iTreg) cells (O’Shea and Paul, 2010, Reiner, 2007). Several specific master transcription factors that regulate Th1/Th2/Th17/iTreg cell differentiation have been identified, including T-bet for Th1 (Szabo et al., 2000), GATA3 (Yamashita et al., 2004, Zheng and Flavell, 1997) for Th2, retinoic-acid-receptor-related orphan receptor γt (RORγt) for Th17 (Ivanov et al., 2006), and forkhead box protein 3 (Foxp3) for iTreg (Sakaguchi et al., 2008). The appropriate expression and function of these transcription factors is essential for proper immune regulation by each Th cell subset.

Among these Th cell subsets, Th17 cells contribute to the host defense against fungi and extracellular bacteria (Milner et al., 2008). However, the pathogenicity of IL-17-producing T cells has been recognized in various autoimmune diseases, including multiple sclerosis, psoriasis, inflammatory bowel diseases, and steroid-resistant asthma (Bettelli et al., 2006, Coccia et al., 2012, Ivanov et al., 2006,Leonardi et al., 2012, McGeachy and Cua, 2008, Nylander and Hafler, 2012,Stockinger et al., 2007, Sundrud et al., 2009).

An HFD Promotes Th17 Cell Differentiation and Affects the Expression of Fatty Acid Enzymes in Memory CD4 T Cells In Vivo

Inhibition of ACC1 Function Results in Decreased Th17 Cell Differentiation and Ameliorates the Development of Autoimmune Disease

ACC1 Controls the Differentiation of Th17 Cells Both In Vitro and In Vivo

ACC1 Controls the Function, but Not Expression, of RORγt in Differentiating Th17 Cells

Extrinsic Fatty Acid Supplementation Restored Acaca−/− Th17 Cell Differentiation through the Functional Improvement of RORγt

Obese Subjects Show Upregulation of ACACA and Increased Th17 Cells in CD45RO+ Memory CD4 T Cells

We herein identified a critical role that ACC1 plays in Th17 cell differentiation and the pathogenicity of Th17 cells through the control of the RORγt function under obese circumstances. High-fat-induced obesity augments Th17 cell differentiation and the expression of enzymes involved in fatty acid metabolism, including ACC1. Pharmacological inhibition or genetic deletion of ACC1 resulted in impaired Th17 cell differentiation in both mice and humans. In contrast, overexpression of Acaca induced Th17 cells in vivo, leaving the expression ofIfng and Il4 largely unchanged. ACC1 modulated the binding of RORγt to theIl17a gene and the subsequent p300 recruitment in differentiating Th17 cells. Memory CD4 T cells from peripheral blood mononuclear cells (PBMCs) of obese subjects showed increased IL-17A production and ACACA expression. Furthermore, a strong correlation was detected between the proportion of IL-17A-producing cells and the expression level of ACACA in memory CD4 T cells in obese subjects. Thus, our findings provide evidence of a mechanism wherein obesity can exacerbate IL-17-mediated pathology via the induction of ACC1.

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Obesity Variant Circuitry

Larry H. Bernstein, MD, FCAP, Curator



FTO Obesity Variant Circuitry and Adipocyte Browning in Humans

Melina Claussnitzer,  Simon N. Dankel, Kyoung-Han Kim,  Gerald Quon,  Wouter Meuleman,  Christine Haugen,  Viktoria Glunk,  Isabel S. Sousa, et al.

N Engl J Med 2015; 373:895-907  Sept 3, 2015    DOI: http://dx.10.org1/056/NEJMoa1502214


Genomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive.

Full Text of Background…



We examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR–Cas9 genome editing in samples from patients.

Full Text of Methods…



Our data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR–Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7.


Effect of the FTO Locus on IRX3 and IRX5 in Human Adipocyte Progenitor Cells

To identify the cell types in which the causal variant may act, we examined chromatin state maps15,16 of the FTO obesity region across 127 cell types. An unusually long enhancer (12.8 kb) in mesenchymal adipocyte progenitors indicated a major regulatory locus (Figure 1B; and Fig. S1A, S1B, and S1C in the Supplementary Appendix). Haplotype-specific enhancer assays showed activity in association with the risk haplotype that was 2.4 times as high as that associated with the nonrisk haplotype in human SGBS adipocytes (i.e., adipocytes derived from a patient with the Simpson–Golabi–Behmel syndrome), which indicated genetic control of enhancer activity (Figure 1C). Enhancers in brain cells and other cell types were considerably shorter than those in mesenchymal adipocyte progenitors and lacked allelic activity (Fig. S1C and S1D in the Supplementary Appendix).


Figure 1. Activation of a Superenhancer in Human Adipocyte Progenitors by the FTO Obesity Risk Haplotype.

Panel A shows the genetic association with body-mass index (BMI) for all common FTO locus variants,14 including the reported single-nucleotide variant (SNV) rs1558902 (red diamond) and the predicted causal SNV rs1421085 (red square). Gray shading delineates consecutive 10-kb segments. CEU denotes a population of Utah residents with northern and western European ancestry, and LD linkage disequilibrium. Panel B shows chromatin state annotations for the locus across 127 reference epigenomes (rows) for cell and tissue types profiled by the Roadmap Epigenomics Project.15,16 For information on the colors used to denote chromatin states, see Figure S1A in the Supplementary Appendix. Vertical lines delineate the consecutive 10-kb segments shown in Panel A. ESC denotes embryonic stem cell, HSC hematopoietic stem cell, and iPSC induced pluripotent stem cell. Panel C shows human SGBS adipocyte enhancer activity, for 10-kb tiles, of the risk and nonrisk haplotypes with the use of relative luciferase expression. The boxes indicate means from seven triplicate experiments, and T bars indicate standard deviations.

To predict putative target genes, we examined large domains that had long-range three-dimensional chromatin interactions surrounding FTO and identified eight candidate genes (Figure 2A and 2B)



Figure 2. Activation of IRX3 and IRX5 Expression in Human Adipocyte Progenitors by the FTO Obesity Risk Genotype.

Panel A shows gene annotations and LD with array tag variant rs9930506 in a 2.5-Mb window; LD is expressed as r2 values in the CEU population. Arrows indicate the direction of transcription of annotated genes in the locus. Panel B shows chromosome conformation capture (Hi-C) interactions contact probabilities in human IMR90 myofibroblasts,22 revealing a 2-Mb topologically associating domain, and LD mean r2 statistics for all SNV pairs at 40-kb resolution. Panel C shows box plots for expression levels, after 2 days of differentiation, in human adipose progenitors isolated from 20 risk-allele carriers and 18 nonrisk-allele carriers, evaluated by means of a quantitative polymerase-chain-reaction analysis for all genes in the 2.5-Mb locus. The horizontal line within each box represents the median, the top and bottom of each box indicate the 75th and 25th percentile, and I bars indicate the range.

Among them, the developmental regulators IRX3 and IRX5 had genotype-associated expression, which indicated long-range (1.2-Mb) genetic control in primary preadipocytes (Figure 2C). Genotype-associated expression was not observed in whole-adipose tissue, a finding consistent with previous reports23,24; this indicated that the effect was cell type–specific and restricted to preadipocytes, which represent a minority of cells in adipose tissue (Fig. S2A in the Supplementary Appendix).


Effect of the FTO Locus on Mitochondrial Thermogenesis and Lipid Storage

To identify the biologic processes affected by altered IRX3 and IRX5expression in adipocytes, we used genomewide expression patterns in brown adipocyte–containing perirenal adipose tissue from a separate cohort of 10 nongenotyped, healthy kidney donors to identify genes with expression that was positively or negatively correlated with IRX3 and IRX5 expression. Genes that are associated with mitochondrial functions were found to have a negative correlation with IRX3 and IRX5, and genes with FXR and RXR lipid-metabolism functions were found to have a positive correlation, which suggests thatIRX3 and IRX5 may play roles in energy dissipation and storage


Figure 3A


Regulation of Obesity-Associated Cellular Phenotypes in Human Adipocytes by IRX3and IRX5., and Table S1 in the Supplementary Appendix). IRX3 and IRX5 had consistently higher mean expression in white adipose tissue from nine participants, as well as negative correlation with PGC1A and UCP1expression, as assessed with the use of interindividual expression patterns in perithyroid brown adipose tissue (Fig. S2B and S2C in the Supplementary Appendix); these findings indicated potential roles for IRX3 and IRX5 in the repression of thermogenesis.

To examine the trans-eQTL genetic control of energy balance by the FTOobesity locus, we used primary preadipocytes from risk-allele carriers and nonrisk-allele carriers to evaluate the genes with mitochondrial and FXR and RXR functions that had expression patterns most closely correlated with those of IRX3 and IRX5, as well as several known markers of energy-balance regulation (Fig. S2D and S2E in the Supplementary Appendix). As compared with nonrisk-allele carriers, risk-allele carriers had lower expression of mitochondrial, browning, and respiration genes and higher expression of lipid-storage markers, which indicated a shift from energy dissipation to energy storage.

These differences in expression were also reflected in the cellular signatures of obesity. Risk-allele carriers had increased adipocyte size, reduced mitochondrial DNA content, and a loss of UCP1 response to β-adrenergic stimulus or cold exposure (Figure 3B and 3C, and Fig. S2F in theSupplementary Appendix), as well as resistance to isoproterenol-mediated uncoupling, a decreased basal oxygen consumption rate, and a reduction in mitochondrial thermogenesis by a factor of 5 (Fig. S2G in the Supplementary Appendix); this indicated excessive accumulation of triglycerides, reduced mitochondrial oxidative capacity, reduced white adipocyte browning, and reduced thermogenesis.

Adipocyte-Autonomous Effects of IRX3 and IRX5 on Energy Balance

We next quantified the effect that manipulation of IRX3 and IRX5 expression had on thermogenesis in primary preadipocytes that were isolated from both risk-allele carriers and nonrisk-allele carriers. In preadipocytes from risk-allele carriers, IRX3 and IRX5 knockdown restored oxygen consumption and thermogenesis response to nonrisk levels, increased thermogenesis by a factor of 7 (Figure 3D), and restored UCP1 expression levels (Fig. S3A in the Supplementary Appendix). In preadipocytes from nonrisk-allele carriers, IRX3 and IRX5 overexpression reduced basal respiration and thermogenesis to risk-allele levels (with thermogenesis reduced by a factor of 8) (Figure 3D) and decreased the expression of UCP1, other regulators of mitochondrial function and thermogenesis (PGC1A, PGC1B, and PRDM16), and the β-adrenergic receptor (ADRB3), which also regulates UCP1-independent thermogenesis programs (Fig. S3B and S3C in the Supplementary Appendix). These manipulations had no significant effect on preadipocytes from participants with the reciprocal genotypes, which indicated that IRX3 and IRX5 levels recapitulate the effect that the FTO genetic variant has on thermogenesis.

To examine the organism-level effects of the repression of Irx3 in adipose tissue, we used adipose Irx3 dominant-negative (aP2-Irx3DN) mice. These mice had pronounced antiobesity characteristics, including reduced body size, body weight, fat mass, white and brown fat depots, and adipocyte size (Fig. S4A through S4G in the Supplementary Appendix). These aP2-Irx3DN mice also had resistance to weight gain on a high-fat diet, increased energy expenditure both at night and during the day, and increased oxygen consumption both at room temperature (22°C) and in thermoneutral conditions (30°C), but they did not have significant differences from control mice in food intake or locomotor activity (Fig. S4A and S4H through S4L in the Supplementary Appendix). At the molecular and cellular levels, these mice had increased mitochondrial activity and thermogenesis marker expression, reduced lipid-storage marker expression in both white and brown fat compartments, and markedly smaller adipocytes than did control mice (Fig. S4M, S4N, and S4O in the Supplementary Appendix).

Figure 4. Disruption of a Conserved ARID5B Repressor Motif by Causal SNV rs1421085 in Humans.

Panel A shows disruption of an ARID5B repressor motif in the evolutionarily conserved motif module surrounding rs1421085. The sequences shown at the top of the panel indicate the frequencies of each nucleotide, with the size scaled to indicate the information content (measured as entropy) at each position. Panel B shows adapted phylogenetic module complexity analysis (PMCA)25 scores in the FTO region for all 82 noncoding SNPs in LD (r2≥0.8) with tag SNV rs1558902, which was identified in a genomewide association study26; rs1421085 had the maximal score. Chromatin state annotation is shown for Roadmap Epigenomics reference genome E025, which corresponds to adipose-derived mesenchymal stem cells; for information on the colors used to denote chromatin states, see Figure S1A in the Supplementary Appendix. Panel C shows increased endogenous expression of IRX3 and IRX5 on single-nucleotide T-to-C editing of rs1421085 in the nonrisk haplotype of a nonrisk-allele carrier, using CRISPR–Cas9 (five clonal expansions). CRISPR–Cas9 re-editing from the engineered C risk allele back to a T nonrisk allele with the use of an alternative single guide RNA restores low endogenous IRX3 and IRX5 gene expression. Panel D shows reduced expression of IRX3 and IRX5 on C-to-T editing of the risk allele in adipocyte progenitors from a risk-allele carrier. Knockdown of ARID5B increases IRX3 and IRX5 levels, as compared….

We next evaluated the tissue-autonomous versus brain-mediated roles of Irx3 by comparing the aP2-Irx3DN mice with hypothalamus dominant-negative Ins2-Irx3DN mice.19 The aP2-Irx3DN mice had a reduction in fat-mass ratio that was 3 times as great as that in Ins2-Irx3DN mice (a reduction of 57% vs. 19%), despite the fact that transgene expression in the hypothalamus was 3 times lower than that in Ins2-Irx3DN mice (Fig. S4P and S4Q in the Supplementary Appendix), which indicated that Irx3 has a hypothalamus-independent regulatory role in whole-body energy regulation. The phenotypic effects of Irx3 repression in aP2-Irx3DN mice were also stronger than those in whole-body Irx3 knockout mice, which suggested potential dominant repressor effects in adipocytes or other tissues, and were independent of Fto gene expression, which did not change (Fig. S4P and S4R in the Supplementary Appendix).

Our findings indicate that both Irx3 and Irx5 have cell-autonomous roles: manipulation of Irx3 andIrx5 led to energy-balance differences in three mouse cellular models, including mouse embryonic fibroblast–derived adipocytes, white 3T3-L1 preadipocytes, and β-adrenergic–stimulated beige ME3 preadipocytes (Fig. S5 in the Supplementary Appendix). In each case, our results indicated that Irx3 and Irx5 induced adipocyte lipid accumulation and repressed thermogenesis in a cell-autonomous way.


Determination of the Causal Variant and Disruption of Repression by ARID5B

To predict the causal variant, the disruption of which is necessary and sufficient to cause IRX3 andIRX5 dysregulation in human preadipocytes, we used phylogenetic module complexity analysis (PMCA)25

(Figure 4A 


Disruption of a Conserved ARID5B Repressor Motif by Causal SNV rs1421085 in Humans., and Fig. S6A and S6B in the Supplementary Appendix). The highest PMCA score was found for the rs1421085 T-to-C SNV, which is in perfect linkage disequilibrium with the most significant reported SNV, rs1558902, across multiple populations (1000 Genomes Phase 1 data), a finding that is consistent with a potentially causal role.

To evaluate whether rs1421085 plays a causal role in enhancer activity, we introduced the C allele into the nonrisk haplotype in our luciferase reporter assay. The T-to-C single-nucleotide alteration increased enhancer activity levels for 10-kb and 1-kb segments centered on the variant, in both orientations and both upstream and downstream of the transcription start, which indicated a gain of enhancer activity in association with the rs1421085 risk allele (Fig. S6C and S6D in the Supplementary Appendix).

To evaluate the effect of the variant on regulator binding, we used electrophoretic mobility-shift assays (EMSAs) of adipocyte nuclear extract with probes for the risk allele and the nonrisk allele of rs1421085. We found binding for the nonrisk allele, T, which lacked enhancer activity, but no binding for the risk allele, C; this indicated that the increased enhancer activity associated with the risk allele is probably due to a loss of repressor binding rather than to a gain of activator binding (Fig. S6E in the Supplementary Appendix).

We examined disrupted motifs and regulator expression to identify potential upstream regulators. The T-to-C substitution disrupted conserved motifs for NKX6-3, LHX6, and the ARID family of regulators (Figure 4A). Among them, ARID5B had the highest expression in adipose tissue and adipocytes and was bound specifically to the nonrisk allele in EMSA competition experiments (Fig. S6E and S6F in the Supplementary Appendix). ARID5B is known to play both repressive and activating roles and was previously implicated in adipogenesis and lipid metabolism in mice.27,28. Among nonrisk-allele carriers, expression of ARID5B was negatively correlated with expression ofIRX3 and IRX5, a finding consistent with ARID5B having a repressive role. No correlation was found in risk-allele carriers, which indicates a loss of ARID5B regulation (Fig. S6G in the Supplementary Appendix).

To evaluate the causal role of ARID5B, we next examined the effects of its knockdown and overexpression on IRX3 and IRX5. ARID5B knockdown increased IRX3 and IRX5 expression in primary preadipocytes from nonrisk-allele carriers to risk-allele levels, which indicates a loss of repression, but it had no effect on preadipocytes from risk-allele carriers, which indicates epistasis with the obesity-risk haplotype (Fig. S6H in the Supplementary Appendix). Consistent with this finding, in SGBS enhancer assays, ARID5B knockdown increased the activity of preadipocytes with the nonrisk allele to risk-allele levels, which indicates a loss of repression, but had no effect on risk-allele constructs, indicating epistasis with the rs1421085 risk allele (Fig. S6I in the Supplementary Appendix). ARID5B overexpression further reduced IRX3 and IRX5 levels in nonrisk-allele carriers, which indicated that repression was strengthened, but had no significant effect on risk-allele carriers, a finding consistent with impaired ARID5B repression in association with the risk haplotype (Fig. S6J in the Supplementary Appendix).

We also evaluated the cellular effects of ARID5B-directed perturbations in primary preadipocytes from risk-allele carriers and nonrisk-allele carriers. In preadipocytes from nonrisk-allele carriers,ARID5B knockdown reduced basal oxygen consumption and lipolysis (Fig. S6K and S6L in theSupplementary Appendix) and shifted expression patterns from mitochondrial to lipid markers (Fig. S2E in the Supplementary Appendix), which indicated that ARID5B plays causal roles in energy-balance regulation. In contrast, ARID5B knockdown had no effect on preadipocytes from risk-allele carriers, a finding consistent with a loss of ARID5B control.

These results suggest that the FTO obesity variant acts through disruption of ARID5B binding in the risk haplotype, leading to a loss of repression, a gain of enhancer activity, and increases inIRX3 and IRX5 expression (Fig. S6M in the Supplementary Appendix).


C-to-T Editing of the rs1421085 Risk Variant and the Effect on Thermogenesis

Targeted genome editing technology involving CRISPR–Cas929 makes it possible to test the phenotypic effect of altering the predicted causal nucleotide rs1421085 in its endogenous genomic context, in isolation from the other obesity-associated genetic variants in the same haplotype. We used CRISPR–Cas9 in primary preadipocytes with two separate guide RNAs, one for rs1421085 C-to-T rescue of the ARID5B motif disruption in risk-allele carriers and one for rs1421085 T-to-C disruption of the ARID5B motif in nonrisk-allele carriers.

We first evaluated the effect of rs1421085 editing on IRX3 and IRX5 expression levels. Starting from preadipocytes of a nonrisk-allele carrier, T-to-C editing doubled endogenous IRX3 and IRX5expression, to levels seen in risk-allele carriers; starting from the edited preadipocytes, C-to-T re-editing back to the nonrisk allele restored low expression levels (Figure 4C). Starting from the risk haplotype, C-to-T editing reduced IRX3 and IRX5 to nonrisk-allele levels, but only in the presence of ARID5B (Figure 4D); this established that disruption of ARID5B repression by rs1421085 is the mechanistic basis of the IRX3 and IRX5 dysregulatory event that mediates the effects of the FTOlocus on obesity.

Next, we evaluated the role of rs1421085 editing during differentiation of white and beige adipocytes, by studying differences in expression between edited and unedited preadipocytes during differentiation. Unedited adipocytes from a risk-allele carrier had a peak in IRX3 and IRX5expression during days 0 and 2 of preadipocyte differentiation into adipocytes; expression during early differentiation was reduced to nonrisk-allele levels by rs1421085 editing, which indicated a causal role of rs1421085 in developmental gene expression programs.

(Figure 5A


Rescue of Metabolic Effects on Adipocyte Thermogenesis through Editing of SNV rs1421085 in a Risk-Allele Carrier. The causal role of rs1421085 was further reflected in a significant increase in the expression of thermogenesis regulators (ADRB3, DIO2, PGC1A, and UCP1) and mitochondrial markers (NDUFA10, COX7A, and CPT1) in differentiating preadipocytes (Figure 5B), which indicated that C-to-T editing of the risk allele rescued thermogenesis regulatory programs.

Last, we evaluated the role of rs1421085 editing in cellular signatures of obesity by quantifying phenotypic differences between edited and unedited adipocytes. A causal role in the regulation of energy balance was indicated by the fact that C-to-T rescue of rs1421085 in edited adipocytes resulted in a reduction in gene expression for lipid storage and lipolytic markers (Fig. S2E and S8A in the Supplementary Appendix), an increase by a factor of 4 in basal metabolic rate and β-adrenergic oxygen consumption, and an increase by a factor of 7 in thermogenesis (Figure 5C, and Fig. S7B in the Supplementary Appendix). In particular, rescue of the ARID5B motif in C-to-T edited preadipocytes restored the strong dependence of mitochondrial respiration on ARID5B that is seen in nonrisk-allele carriers (Fig. S7C in the Supplementary Appendix).

These results indicate that the rs1421085 T-to-C single-nucleotide alteration underlies the association between FTO and obesity by disrupting ARID5B-mediated repression of IRX3 andIRX5. This disruption leads to a developmental shift from browning to whitening programs and loss of mitochondrial thermogenesis (Figure 5D).


Our work elucidates a potential mechanistic basis for the genetic association between FTO and obesity and indicates that the causal variant rs1421085 can disrupt ARID5B repressor binding; this disruption results in derepression of IRX3 and IRX5 during early adipocyte differentiation. This process could lead to a cell-autonomous shift from white adipocyte browning and thermogenesis to lipid storage, increased fat stores, and body-weight gain.

To translate the results of genomewide association studies into mechanistic insights, we combined public resources (epigenomic annotations, chromosome conformation, and regulatory motif conservation), targeted experiments for risk and nonrisk haplotypes (enhancer tiling, gene expression, and cellular profiling), and directed perturbations in human primary cells and mouse models (regulator–target knockdown and overexpression and CRISPR–Cas9 genome editing). These methods are specific to the elucidation of noncoding variants, which constitute the majority of signals in genomewide association studies; 80% of the trait-associated loci identified in such studies lack protein-altering variants, and 93% of the top hits are noncoding.30

The FTO association with obesity is unusual in many ways. First, rs1421085 has both a high frequency and a strong effect size,31 which suggests positive selection or bottlenecks (e.g., 44% frequency in European populations vs. 5% in African populations). Second, rs1421085 has switchlike behavior in enhancer activity, target-gene expression, and cellular phenotypes, possibly because of selective pressures on energy-balance control for rapid adaptation. Third, rs1421085 acts specifically in the early differentiation of preadipocytes, which emphasizes the importance of profiling diverse tissues, cell types, and developmental stages. Fourth, enhancer activity is found only for the risk allele, which emphasizes the importance of profiling both alleles. Finally, rs1421085 leads to a gain of function (increased enhancer, IRX3, and IRX5 activity); this is a rare property in protein-coding variants but may be common in noncoding variants.

The apparent genetic link between obesity and cell-autonomous adipocyte browning suggests a central role of beige adipocyte thermogenesis in whole-body energy metabolism in humans, a role that is consistent with that suggested in recent reports on PRDM16 in mice.9 IRX3 and IRX5 have evolutionarily conserved roles, and the ARID5B motif lies in a module that is functionally conserved across multiple mammalian species; this indicates that adaptive thermogenesis circuits are conserved, and IRX3 and IRX5 probably play both UCP1-dependent and UCP1-independent roles. Even though IRX3 and IRX5 dysregulation by rs1421085 was restricted to early differentiation, their effects persisted in mature adipocytes, and the targeting of these genes can have broader effects.

Last, we found that direct manipulation of the ARID5B–rs1421085–IRX3/IRX5 regulatory axis in primary cell cultures of adipocytes from patients reversed the signatures of obesity. This indicates that in addition to changes in physical activity and nutrition, manipulation of mitochondrial thermogenesis26 offers a potential third pathway for shifting between energy storage and expenditure in a brain-independent and tissue-autonomous way in humans.

In summary, our work elucidates a mechanistic basis for the strongest genetic association with obesity. Our results indicate that the SNV rs1421085 underlies the genetic association between theFTO locus and obesity. The SNV disrupts an evolutionarily conserved motif for the ARID5B repressor, which leads to loss of binding, derepression of a potent preadipocyte superenhancer, and activation of downstream targets IRX3 and IRX5 during early differentiation of mesenchymal progenitors into adipocyte subtypes. This results in a cell-autonomous shift from white adipocyte browning to lipid-storage gene expression programs and to repression of basal mitochondrial respiration, a decrease in thermogenesis in response to stimulus, and an increase in adipocyte size. Manipulation of the uncovered pathway, including knockdown or overexpression of the upstream regulator ARID5B, genome editing of the predicted causal variant rs1421085, and knockdown or overexpression of target genes IRX3 and IRX5, had a significant effect on obesity phenotypes.

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