Feeds:
Posts
Comments

Posts Tagged ‘type 2 diabetes’


Metformin and vitamin B12 deficiency?

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Years of taking popular diabetes drug tied to risk of B12 deficiency

 

Long-term Metformin Use and Vitamin B12 Deficiency in the Diabetes Prevention Program Outcomes Study

 

Metformin linked to vitamin B12 deficiency

David Holmes   Nature Reviews Endocrinology(2016)    http://dx.doi.org:/10.1038/nrendo.2016.39

Secondary analysis of data from the Diabetes Prevention Program Outcomes Study (DPPOS), one of the largest and longest studies of metformin treatment in patients at high risk of developing type 2 diabetes mellitus, shows that long-term use of metformin is associated with vitamin B12deficiency.

Aroda, V. R. et al. Long-term metformin use and vitamin B12 deficiency in the Diabetes Prevention Program Outcomes Study. J. Clin. Endocrinol. Metab. http://dx.doi.org/10.1210/jc.2015-3754 (2016)

 

Long-term Follow-up of Diabetes Prevention Program Shows Continued Reduction in Diabetes Development

http://www.diabetes.org/newsroom/press-releases/2014/long-term-follow-up-of-diabetes-prevention-program-shows-reduction-in-diabetes-development.html

San Francisco, California
June 16, 2014

Treatments used to decrease the development of type 2 diabetes continue to be effective an average of 15 years later, according to the latest findings of the Diabetes Prevention Program Outcomes Study, a landmark study funded by the National Institutes of Health (NIH).

The results, presented at the American Diabetes Association’s 74th Scientific Sessions®, come more than a decade after the Diabetes Prevention Program, or DPP, reported its original findings. In 2001, after an average of three years of study, the DPP announced that the study’s two interventions, a lifestyle program designed to reduce weight and increase activity levels and the diabetes medicinemetformin, decreased the development of type 2 diabetes in a diverse group of people, all of whom were at high risk for the disease, by 58 and 31 percent, respectively, compared with a group taking placebo.

The Diabetes Prevention Program Outcomes Study, or DPPOS, was conducted as an extension of the DPP to determine the longer-term effects of the two interventions, including further reduction in diabetes development and whether delaying diabetes would reduce the development of the diabetes complications that can lead to blindness, kidney failure, amputations and heart disease. Funded largely by the NIH’s National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the new findings show that the lifestyle intervention and metformin treatment have beneficial effects, even years later, but did not reduce microvascular complications.

Delaying Type 2 Diabetes

Participants in the study who were originally assigned to the lifestyle intervention and metformin during DPP continued to have lower rates of type 2 diabetes development than those assigned to placebo, with 27 percent and 17 percent reductions, respectively, after 15 years.

“What we’re finding is that we can prevent or delay the onset of type 2 diabetes, a chronic disease, through lifestyle intervention or with metformin, over a very long period of time,” said David M. Nathan, MD, Chairman of the DPP/DPPOS and Professor of Medicine at Harvard Medical School. “After the initial randomized treatment phase in DPP, all participants were offered lifestyle intervention and the rates of diabetes development fell in the metformin and former placebo groups, leading to a reduction in the treatment group differences over time.  However, the lifestyle intervention and metformin are still quite effective at delaying, if not preventing, type 2 diabetes,” Dr. Nathan said. Currently, an estimated 79 million American adults are at high-risk for developing type 2 diabetes.

Microvascular Complications
The DPPOS investigators followed participants for an additional 12 years after the end of the DPP to determine both the extent of diabetes prevention over time and whether the study treatments would also decrease the small vessel -or microvascular- complications, such as eye, nerve and kidney disease. These long-term results did not demonstrate significant differences among the lifestyle intervention, metformin or placebo groups on the microvascular complications, reported Kieren Mather, MD, Professor of Medicine at Indiana University School of Medicine and a study investigator.

“However, regardless of type of initial treatment, participants who didn’t develop diabetes had a 28 percent lower occurrence of the microvascular complications than those participants who did develop diabetes. These findings show that intervening in the prediabetes phase is important in reducing early stage complications,” Dr. Mather noted. The absence of differences in microvascular complications among the intervention groups may be explained by the small differences in average glucose levels among the groups at this stage of follow-up.

Risk for Cardiovascular Disease

The DPP population was relatively young and healthy at the beginning of the study, and few participants had experienced any severe cardiovascular events, such as heart attack or stroke, 15 years later. The relatively small number of events meant that the DPPOS researchers could not test the effects of interventions on cardiovascular disease. However, the research team did examine whether the study interventions, or a delay in the onset of type 2 diabetes, improved cardiovascular risk factors.

“We found that cardiovascular risk factors, such as hypertension, are generally improved by the lifestyle intervention and somewhat less by metformin,” said Ronald Goldberg, MD, Professor of Medicine at the University of Miami and one of the DPPOS investigators. “We know that people with type 2 diabetes are at much higher risk for heart disease and stroke than those who do not have diabetes, so a delay in risk factor development or improvement in risk factors may prove to be beneficial.”

Long-term Results with Metformin

The DPP/DPPOS is the largest and longest duration study to examine the effects of metformin, an inexpensive, well-known and generally safe diabetes medicine, in people who have not been diagnosed with diabetes. For DPPOS participants, metformin treatment was associated with a modest degree of long-term weight loss. “Other than a small increase in vitamin B-12 deficiency, which is a recognized consequence of metformin therapy, it has been extremely safe and well-tolerated over the 15 years of our study,” said Jill Crandall, MD, Professor of Medicine at Albert Einstein College of Medicine and a DPPOS investigator. “Further study will help show whether metformin has beneficial effects on heart disease and cancer, which are both increased in people with type 2 diabetes.”

Looking to the Future

In addition to the current findings, the DPPOS includes a uniquely valuable population that can help researchers understand the clinical course of type 2 diabetes.  Since the participants did not have diabetes at the beginning of the DPP, for those who have developed diabetes, the data show precisely when they developed the disease, which is rare in previous studies. “The DPP and DPPOS have given us an incredible wealth of information by following a very diverse group of people with regard to race and age as they have progressed from prediabetes to diabetes,” said Judith Fradkin, MD, Director of the NIDDK Division of Diabetes, Endocrinology and Metabolic Diseases. “The study provides us with an opportunity to make crucial discoveries about the clinical course of type 2 diabetes.”

Dr. Fradkin noted that the study population held promise for further analyses because researchers would now be able to examine how developing diabetes at different periods of life may cause the disease to progress differently. “We can look at whether diabetes behaves differently if you develop it before the age of 50 or after the age of 60,” she said. “Thanks to the large and diverse population of DPPOS that has remained very loyal to the study, we will be able to see how and when complications first develop and understand how to intervene most effectively.”

She added that NIDDK had invited the researchers to submit an application for a grant to follow the study population for an additional 10 years.

The Diabetes Prevention Program Outcomes Study was funded under NIH grant U01DK048489 by the NIDDK; National Institute on Aging; National Cancer Institute; National Heart, Lung, and Blood Institute; National Eye Institute; National Center on Minority Health and Health Disparities; and the Office of the NIH Director; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Office of Research on Women’s Health; and Office of Dietary Supplements, all part of the NIH, as well as the Indian Health Service, Centers for Disease Control and Prevention and American Diabetes Association. Funding in the form of supplies was provided by Merck Sante, Merck KGaA and LifeScan.

The American Diabetes Association is leading the fight to Stop Diabetes® and its deadly consequences and fighting for those affected by diabetes. The Association funds research to prevent, cure and manage diabetes; delivers services to hundreds of communities; provides objective and credible information; and gives voice to those denied their rights because of diabetes. Founded in 1940, our mission is to prevent and cure diabetes and to improve the lives of all people affected by diabetes. For more information please call the American Diabetes Association at 1-800-DIABETES (1-800-342-2383) or visit http://www.diabetes.org. Information from both these sources is available in English and Spanish.

Association of Biochemical B12Deficiency With Metformin Therapy and Vitamin B12Supplements  

The National Health and Nutrition Examination Survey, 1999–2006

Lael ReinstatlerYan Ping QiRebecca S. WilliamsonJoshua V. Garn, and Godfrey P. Oakley Jr.
Diabetes Care February 2012 vol. 35 no. 2 327-333 
     http://dx.doi.org:/10.2337/dc11-1582

OBJECTIVE To describe the prevalence of biochemical B12deficiency in adults with type 2 diabetes taking metformin compared with those not taking metformin and those without diabetes, and explore whether this relationship is modified by vitamin B12supplements.

RESEARCH DESIGN AND METHODS Analysis of data on U.S. adults ≥50 years of age with (n = 1,621) or without type 2 diabetes (n = 6,867) from the National Health and Nutrition Examination Survey (NHANES), 1999–2006. Type 2 diabetes was defined as clinical diagnosis after age 30 without initiation of insulin therapy within 1 year. Those with diabetes were classified according to their current metformin use. Biochemical B12 deficiency was defined as serum B12concentrations ≤148 pmol/L and borderline deficiency was defined as >148 to ≤221 pmol/L.

RESULTS Biochemical B12 deficiency was present in 5.8% of those with diabetes using metformin compared with 2.4% of those not using metformin (P = 0.0026) and 3.3% of those without diabetes (P = 0.0002). Among those with diabetes, metformin use was associated with biochemical B12 deficiency (adjusted odds ratio 2.92; 95% CI 1.26–6.78). Consumption of any supplement containing B12 was not associated with a reduction in the prevalence of biochemical B12deficiency among those with diabetes, whereas consumption of any supplement containing B12 was associated with a two-thirds reduction among those without diabetes.

CONCLUSIONS Metformin therapy is associated with a higher prevalence of biochemical B12 deficiency. The amount of B12recommended by the Institute of Medicine (IOM) (2.4 μg/day) and the amount available in general multivitamins (6 μg) may not be enough to correct this deficiency among those with diabetes.

It is well known that the risks of both type 2 diabetes and B12deficiency increase with age (1,2). Recent national data estimate a 21.2% prevalence of diagnosed diabetes among adults ≥65 years of age and a 6 and 20% prevalence of biochemical B12 deficiency (serum B12<148 pmol/L) and borderline deficiency (serum B12 ≥148–221 pmol/L) among adults ≥60 years of age (3,4).

The diabetes drug metformin has been reported to cause a decrease in serum B12 concentrations. In the first efficacy trial, DeFronzo and Goodman (5) demonstrated that although metformin offers superior control of glycosylated hemoglobin levels and fasting plasma glucose levels compared with glyburide, serum B12 concentrations were lowered by 22% compared with placebo, and 29% compared with glyburide therapy after 29 weeks of treatment. A recent, randomized control trial designed to examine the temporal relationship between metformin and serum B12 found a 19% reduction in serum B12 levels compared with placebo after 4 years (6). Several other randomized control trials and cross-sectional surveys reported reductions in B12ranging from 9 to 52% (716). Although classical B12 deficiency presents with clinical symptoms such as anemia, peripheral neuropathy, depression, and cognitive impairment, these symptoms are usually absent in those with biochemical B12 deficiency (17).

Several researchers have made recommendations to screen those with type 2 diabetes on metformin for serum B12 levels (6,7,1416,1821). However, no formal recommendations have been provided by the medical community or the U.S. Prevention Services Task Force. High-dose B12 injection therapy has been successfully used to correct the metformin-induced decline in serum B12 (15,21,22). The use of B12supplements among those with type 2 diabetes on metformin in a nationally representative sample and their potentially protective effect against biochemical B12 deficiency has not been reported. It is therefore the aim of the current study to use the nationally representative National Health and Nutrition Examination Survey (NHANES) population to determine the prevalence of biochemical B12deficiency among those with type 2 diabetes ≥50 years of age taking metformin compared with those with type 2 diabetes not taking metformin and those without diabetes, and to explore how these relationships are modified by B12 supplement consumption.

Design overview

NHANES is a nationally representative sample of the noninstitutionalized U.S. population with targeted oversampling of U.S. adults ≥60 years of age, African Americans, and Hispanics. Details of these surveys have been described elsewhere (23). All participants gave written informed consent, and the survey protocol was approved by a human subjects review board.

Setting and participants

Our study included adults ≥50 years of age from NHANES 1999–2006. Participants with positive HIV antibody test results, high creatinine levels (>1.7 mg/dL for men and >1.5 mg/dL for women), and prescription B12 injections were excluded from the analysis. Participants who reported having prediabetes or borderline diabetes (n = 226) were removed because they could not be definitively grouped as having or not having type 2 diabetes. We also excluded pregnant women, those with type 1 diabetes, and those without diabetes taking metformin. Based on clinical aspects described by the American Diabetes Association and previous work in NHANES, those who were diagnosed before the age of 30 and began insulin therapy within 1 year of diagnosis were classified as having type 1 diabetes (24,25). Type 2 diabetes status in adults was dichotomized as yes/no. Participants who reported receiving a physician’s diagnosis after age 30 (excluding gestational diabetes) and did not initiate insulin therapy within 1 year of diagnosis were classified as having type 2 diabetes.

Outcomes and follow-up

The primary outcome was biochemical B12 deficiency determined by serum B12 concentrations. Serum B12 levels were quantified using the Quantaphase II folate/vitamin B12 radioassay kit from Bio-Rad Laboratories (Hercules, CA). We defined biochemical B12 deficiency as serum levels ≤148 pmol/L, borderline deficiency as serum B12 >148 to ≤221 pmol/L, and normal as >221 pmol/L (26).

The main exposure of interest was metformin use. Using data collected in the prescription medicine questionnaire, those with type 2 diabetes were classified as currently using metformin therapy (alone or in combination therapy) versus those not currently using metformin. Length of metformin therapy was used to assess the relationship between duration of metformin therapy and biochemical B12 deficiency. In the final analysis, two control groups were used to allow the comparison of those with type 2 diabetes taking metformin with those with type 2 diabetes not taking metformin and those without diabetes.

To determine whether the association between metformin and biochemical B12 deficiency is modified by supplemental B12 intake, data from the dietary supplement questionnaire were used. Information regarding the dose and frequency was used to calculate average daily supplemental B12 intake. We categorized supplemental B12 intake as 0 μg (no B12 containing supplement), >0–6 μg, >6–25 μg, and >25 μg. The lower intake group, >0–6 μg, includes 6 μg, the amount of vitamin B12 typically found in over-the-counter multivitamins, and 2.4 μg, the daily amount the IOM recommends for all adults ≥50 years of age to consume through supplements or fortified food (1). The next group, >6–25 μg, includes 25 μg, the amount available in many multivitamins marketed toward senior adults. The highest group contains the amount found in high-dose B-vitamin supplements.

 

In the final analysis, there were 575 U.S. adults ≥50 years of age with type 2 diabetes using metformin, 1,046 with type 2 diabetes not using metformin, and 6,867 without diabetes. The demographic and biological characteristics of the groups are shown in Table 1. Among metformin users, mean age was 63.4 ± 0.5 years, 50.3% were male, 66.7% were non-Hispanic white, and 40.7% used a supplement containing B12. The median duration of metformin use was 5 years. Compared with those with type 2 diabetes not taking metformin, metformin users were younger (P < 0.0001), reported a lower prevalence of insulin use (P < 0.001), and had a shorter duration of diabetes (P = 0.0207). Compared with those without diabetes, metformin users had a higher proportion of nonwhite racial groups (P< 0.0001), a higher proportion of obesity (P < 0.0001), a lower prevalence of macrocytosis (P = 0.0017), a lower prevalence of supplemental folic acid use (P = 0.0069), a lower prevalence of supplemental vitamin B12 use (P = 0.0180), and a lower prevalence of calcium supplement use (P = 0.0002). There was a twofold difference in the prevalence of anemia among those with type 2 diabetes versus those without, and no difference between the groups with diabetes.    

Association of Biochemical B12Deficiency With Metformin Therapy and Vitamin B12Supplements

Demographic and biological characteristics of U.S. adults ≥50 years of age: NHANES 1999–2006

Table 1
The geometric mean serum B12 concentration among those with type 2 diabetes taking metformin was 317.5 pmol/L. This was significantly lower than the geometric mean concentration in those with type 2 diabetes not taking metformin (386.7 pmol/L; P = 0.0116) and those without diabetes (350.8 pmol/L; P = 0.0011). As seen in Fig. 1, the weighted prevalence of biochemical B12 deficiency adjusted for age, race, and sex was 5.8% for those with type 2 diabetes taking metformin, 2.2% for those with type 2 diabetes not taking metformin (P = 0.0002), and 3.3% for those without diabetes (P = 0.0026). Among the three aforementioned groups, borderline deficiency was present in 16.2, 5.5, and 8.8%, respectively (P < 0.0001). Applying the Fleiss formula for calculating attributable risk from cross-sectional data (27), among all of the cases of biochemical B12 deficiency, 3.5% of the cases were attributable to metformin use; and among those with diabetes, 41% of the deficient cases were attributable to metformin use. When the prevalence of biochemical B12 deficiency among those with diabetes taking metformin was analyzed by duration of metformin therapy, there was no notable increase in the prevalence of biochemical B12 deficiency as the duration of metformin use increased. The prevalence of biochemical B12 deficiency was 4.1% among those taking metformin <1 year, 6.3% among those taking metformin ≥1–3 years, 4.1% among those taking metformin >3–10 years, and 8.1% among those taking metformin >10 years (P = 0.3219 for <1 year vs. >10 years). Similarly, there was no clear increase in the prevalence of borderline deficiency as the duration of metformin use increased (15.9% among those taking metformin >10 years vs. 11.4% among those taking metformin <1 year; P = 0.4365).
Figure 1
Weighted prevalence of biochemical B12 deficiency and borderline deficiency adjusted for age, race, and sex in U.S. adults ≥50 years of age: NHANES 1999–2006. Black bars are those with type 2 diabetes on metformin, gray bars are those with type 2 diabetes not on metformin, and the white bars are those without diabetes. *P = 0.0002 vs. type 2 diabetes on metformin. †P < 0.0001 vs. type 2 diabetes on metformin. ‡P = 0.0026 vs. type 2 diabetes on metformin.
Table 2 presents a stratified analysis of the weighted prevalence of biochemical B12 deficiency and borderline deficiency by B12supplement use. For those without diabetes, B12 supplement use was associated with an ∼66.7% lower prevalence of both biochemical B12deficiency (4.8 vs. 1.6%; P < 0.0001) and borderline deficiency (16.6 vs. 5.5%; P < 0.0001). A decrease in the prevalence of biochemical B12deficiency was seen at all levels of supplemental B12 intake compared with nonusers of supplements. Among those with type 2 diabetes taking metformin, supplement use was not associated with a decrease in the prevalence of either biochemical B12 deficiency (5.6 vs. 5.3%; P= 0.9137) or borderline deficiency (15.5 vs. 8.8%; P = 0.0826). Among the metformin users who also used supplements, those who consumed >0–6 μg of B12 had a prevalence of biochemical B12 deficiency of 14.1%. However, consumption of a supplement containing >6 μg of B12 was associated with a prevalence of biochemical B12 deficiency of 1.8% (P = 0.0273 for linear trend). Similar trends were seen in the association of supplemental B12 intake and the prevalence of borderline deficiency. For those with type 2 diabetes not taking metformin, supplement use was also not associated with a decrease in the prevalence of biochemical B12 deficiency (2.1 vs. 2.0%; P = 0.9568) but was associated with a 54% reduction in the prevalence of borderline deficiency (7.8 vs. 3.4%; P = 0.0057 for linear trend).
Table 2
Comparison of average daily B12 supplement intake by weighted prevalence of biochemical B12 deficiency (serum B12 ≤148 pmol/L) and borderline deficiency (serum B12 >148 to ≤221 pmol/L) among U.S. adults ≥50 years of age: NHANES 1999–2006.
Table 3 demonstrates the association of various risk factors with biochemical B12 deficiency. Metformin therapy was associated with biochemical B12 deficiency (odds ratio [OR] 2.89; 95% CI 1.33–6.28) and borderline deficiency (OR 2.32; 95% CI 1.31–4.12) in a crude model (results not shown). After adjusting for age, BMI, and insulin and supplement use, metformin maintained a significant association with biochemical B12 deficiency (OR 2.92; 95% CI 1.28–6.66) and borderline deficiency (OR 2.16; 95% CI 1.22–3.85). Similar to Table 2, B12 supplements were protective against borderline (OR 0.43; 95% CI 0.23–0.81), but not biochemical, B12 deficiency (OR 0.76; 95% CI 0.34–1.70) among those with type 2 diabetes. Among those without diabetes, B12 supplement use was ∼70% protective against biochemical B12 deficiency (OR 0.26; 95% CI 0.17–0.38) and borderline deficiency (OR 0.27; 95% CI 0.21–0.35).
Table 3
Polytomous logistic regression for potential risk factors of biochemical B12 deficiency and borderline deficiency among U.S. adults ≥50 years of age: NHANES 1999–2006, OR (95% CI)

The IOM has highlighted the detection and diagnosis of B12 deficiency as a high-priority topic for research (1). Our results suggest several findings that add to the complexity and importance of B12 research and its relation to diabetes, and offer new insight into the benefits of B12 supplements. Our data confirm the relationship between metformin and reduced serum B12 levels beyond the background prevalence of biochemical B12 deficiency. Our data demonstrate that an intake of >0–6 μg of B12, which includes the dose most commonly found in over-the-counter multivitamins, was associated with a two-thirds reduction of biochemical B12 deficiency and borderline deficiency among adults without diabetes. This relationship has been previously reported with NHANES and Framingham population data (4,29). In contrast, we did not find that >0–6 μg of B12 was associated with a decrease in the prevalence of biochemical B12 deficiency or borderline deficiency among adults with type 2 diabetes taking metformin. This observation suggests that metformin reduces serum B12 by a mechanism that is additive to or different from the mechanism in older adults. It is also possible that metformin may exacerbate the deficiency among older adults with low serum B12. Our sample size was too small to determine which amount >6 μg was associated with maximum protection, but we did find a dose-response trend.

We were surprised to find that those with type 2 diabetes not using metformin had the lowest prevalence of biochemical B12 deficiency. It is possible that these individuals may seek medical care more frequently than the general population and therefore are being treated for their biochemical B12 deficiency. Or perhaps, because this population had a longer duration of diabetes and a higher proportion of insulin users compared with metformin users, they have been switched from metformin to other diabetic treatments due to low serum B12 concentrations or uncontrolled glucose levels and these new treatments may increase serum B12 concentrations. Despite the observed effects of metformin on serum B12 levels, it remains unclear whether or not this reduction is a public health concern. With lifetime risks of diabetes estimated to be one in three and with metformin being a first-line intervention, it is important to increase our understanding of the effects of oral vitamin B12 on metformin-associated biochemical deficiency (20,21).

The strengths of this study include its nationally representative, population-based sample, its detailed information on supplement usage, and its relevant biochemical markers. This is the first study to use a nationally representative sample to examine the association between serum B12 concentration, diabetes status, and metformin use as well as examine how this relationship may be modified by vitamin B12 supplementation. The data available regarding supplement usage provided specific information regarding dose and frequency. This aspect of NHANES allowed us to observe the dose-response relationship in Table 2 and to compare it within our three study groups.

This study is also subject to limitations. First, NHANES is a cross-sectional survey and it cannot assess time as a factor, and therefore the results are associations and not causal relationships. A second limitation arises in our definition of biochemical B12 deficiency. There is no general consensus on how to define normal versus low serum B12levels. Some researchers include the functional biomarker methylmalonic acid (MMA) in the definition, but this has yet to be agreed upon (3034). Recently, an NHANES roundtable discussion suggested that definitions of biochemical B12 deficiency should incorporate one biomarker (serum B12 or holotranscobalamin) and one functional biomarker (MMA or total homocysteine) to address problems with sensitivity and specificity of the individual biomarkers. However, they also cited a need for more research on how the biomarkers are related in the general population to prevent misclassification (34). MMA was only measured for six of our survey years; one-third of participants in our final analysis were missing serum MMA levels. Moreover, it has recently been reported that MMA values are significantly greater among the elderly with diabetes as compared with the elderly without diabetes even when controlling for serum B12 concentrations and age, suggesting that having diabetes may independently increase the levels of MMA (35). This unique property of MMA in elderly adults with diabetes makes it unsuitable as part of a definition of biochemical B12 deficiency in our specific population groups. Our study may also be subject to misclassification bias. NHANES does not differentiate between diabetes types 1 and 2 in the surveys; our definition may not capture adults with type 2 diabetes exclusively. Additionally, we used responses to the question “Have you received a physician’s diagnosis of diabetes” to categorize participants as having or not having diabetes. Therefore, we failed to capture undiagnosed diabetes. Finally, we could only assess current metformin use. We cannot determine if nonmetformin users have ever used metformin or if they were not using it at the time of the survey.

Our data demonstrate several important conclusions. First, there is a clear association between metformin and biochemical B12 deficiency among adults with type 2 diabetes. This analysis shows that 6 μg of B12 offered in most multivitamins is associated with two-thirds reduction in biochemical B12 deficiency in the general population, and that this same dose is not associated with protection against biochemical B12 deficiency among those with type 2 diabetes taking metformin. Our results have public health and clinical implications by suggesting that neither 2.4 μg, the current IOM recommendation for daily B12 intake, nor 6 μg, the amount found in most multivitamins, is sufficient for those with type 2 diabetes taking metformin.

This analysis suggests a need for further research. One research design would be to identify those with biochemical B12 deficiency and randomize them to receive various doses of supplemental B12chronically and then evaluate any improvement in serum B12concentrations and/or clinical outcomes. Another design would use existing cohorts to determine clinical outcomes associated with biochemical B12 deficiency and how they are affected by B12supplements at various doses. Given that a significant proportion of the population ≥50 years of age have biochemical B12 deficiency and that those with diabetes taking metformin have an even higher proportion of biochemical B12 deficiency, we suggest that support for further research is a reasonable priority.

 

Discussion:
One research design would be to identify those with biochemical B12 deficiency and randomize them to receive various doses of supplemental B12chronically and then evaluate any improvement in serum B12concentrations and/or clinical outcomes. Another design would use existing cohorts to determine clinical outcomes associated with biochemical B12 deficiency and how they are affected by B12supplements at various doses.
This is of considerable interest.  As far as I can see, there is insufficient data presented to discern all of the variables entangled.  In a study of 8000 hemograms several years ago, it was of some interest that there were a large percentage of patients who were over age 75 years having a MCV of 94 – 100, not considered indicative of macrocytic anemia.  It would have been interesting to explore that set of the data further.

Read Full Post »


Adipocyte Derived Stroma Cells: Their Usage in Regenerative Medicine and Reprogramming into Pancreatic Beta-Like Cells

Curator: Evelina Cohn, Ph.D.

The following presentation can be dowloaded in PowerPoint form by clicking on the link below:

adipocytes (1)

 

In Summary:

There are different results related to betatrophin and its characteristic to induce insulin and/or expand the pancreas beta cells. All the experiments so far were performed in mice. Some of the authors like Elisabeth Kugelberg from Harvard University agrees that betatrophin can induce insulin and expansion of secreting beta cells in mice (E. Kugelberg , 2014). Levitsky et al., 2014, come to the conclusion that betatrophin stimulate growth of beta cells in mice, while Gusarova et al., 2014, said that Betatrophin doesn’t control cell expansion in mice ( Gusarova et al., 2014) All three results are based on experiments on mice.

To make sure what are the characteristics of betatrophin in human pancreatic beta cells I suggest to try to determine the concentration and effect on those concentrations on immortal beta cells from human, CM cell line (insulinoma-obtained from ascitic fluid of cancer patients ) ( they are not producing any insulin under the glucose stimulation, therefore they may be a good for our model if they respond to betatrophin) TRM-1 (foetal Human SV40 T antigen)-Express small amount of insulin, not responsive to glucose stimulation) and finally Blox5 ( foetal Human SV40 T –antigen) which Exhibit glucose responsive. and Low insulin content. Blox5 may be the second good cell line to experiment, because they are responsive to glucose and they may be responsive to betatrophin as well.

If we found that those cell lines are inducing insulin then we may try primary beta cells. There is an article of 2013 (Ilie and Ilie, 2013) in which there is a possibility of regeneration of beta cells in vivo by neogenesis from adult pancreas. We can use their model to see if betatrophin indeed induce insulin in those cells. ( see the article attached)

On the other hand there are possibilities of growing beta cells directly onto pancreatic duct as it shows below:

pharmacoogicalapproaches to islet regeneration

 

 

 

 

 

 

 

 

 

 

From: https://infodiabet.wordpress.com/2010/08/31/new-sources-of-pancreatic-beta-cells/

Therefore, I suggest of producing pancreatic duct by using 3D printing and grow the cells by neogenesis

directly on the pancreatic duct.

References:

Gusarova V, Alexa CA, Na E, Stevis PE, Xin Y, Bonner-Weir S,

Cohen JC, Hobbs HH, Murphy AJ, Yancopoulos GD, Gromada J (2014), ANGPTL8/Betatrophin Does Not Control Pancreatic Beta Cell Expansion. Cell 159: 691-696.

Kugelberg E. (2013) Diabetes: Betatrophin—inducing β-cell expansion to treat diabetes mellitus? Nature Reviews Endocrinology 9: 379

Levitsky LL, Ardestani G, Rhoads DB (2014). Role of growth factors in control of pancreatic beta cell mass: focus on betatrophin. Curr Opin Pediatr. August 26 (4):475-9

 

 

 

Slide1Slide2Slide3Slide4Slide5Slide6Slide7Slide8Slide9Slide10Slide11Slide12Slide13Slide14

 

 

 

 

 

Read Full Post »


Drug utilization, safety, and effectiveness of exenatide, sitagliptin, and vildagliptin for type 2 diabetes

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

Drug utilization, safety, and effectiveness of exenatide, sitagliptin, and vildagliptin for type 2 diabetes in the real world: Data from the Italian AIFA Anti-diabetics Monitoring Registry

S. Montilla, G. Marchesini, A. Sammarco, M.P. Trotta, P.D. Siviero, C. Tomino, D. Melchiorri, L. Pani for the AIFA Anti-Diabetes Monitoring Registry
Nutrition Diabetes and Cardiovasc Dis  Dec 2014; 24(12):1346–1353     http://dx.doi.org/10.1016/j.numecd.2014.07.014

Background and aims

In Italy, the reimbursed use of incretin mimetics and incretin enhancers was subject to enrollment of patients into a web-based system recording the general demographic and clinical data of patients. We report the utilization data of glucagon-like peptide 1 (GLP1) receptor agonists and dipeptidylpeptidase-4 (DPP4) inhibitors in clinical practice as recorded by the Italian Medicines Agency (AIFA) Monitoring Registry.

Methods and results

From February 2008 to August 2010, 75,283 patients with type 2 diabetes were entered into the registry and treated with exenatide, sitagliptin, or vildagliptin. The treatment was administered to patients in a wide range of ages (≥75 years, n = 6125 cases), body mass index (BMI) (≥35 kg/m2, n = 22,015), and metabolic control (HbA1c ≥ 11% ((96 mmol/mol), n = 3151). Overall, 1116 suspected adverse drug reactions were registered, including 12 cases of acute pancreatitis (six on exenatide). Hypoglycemic episodes mainly occurred in combination with sulfonylureas. Treatment discontinuation for the three drugs (logistic regression analysis) was negatively associated with the male gender and positively with baseline HbA1c, diabetes duration, and, limitedly to DPP-4 inhibitors, with BMI. Treatment discontinuation (including loss to follow-up, accounting for 21–26%) was frequent. Discontinuation for treatment failure occurred in 7.7% of cases (exenatide), 3.8% (sitagliptin), and 4.1% (vildagliptin), respectively, corresponding to 27–40% of all discontinuations, after excluding lost to follow-up. HbA1c decreased on average by 0.9–1.0% (9 mmol/mol). Body weight decreased by 3.5% with exenatide and by 1.0–1.5% with DPP-4 inhibitors.

Conclusions

In the real world of Italian diabetes centers, prescriptions of incretins have been made in many cases outside the regulatory limits. Nevertheless, when appropriately utilized, incretins may grant results at least in line with pivotal trials.

 

Article Outline

  1. Introduction
  2. Methods
    1. The AIFA Anti-diabetics Monitoring registry
    2. Statistical analysis
  3. Results
    1. Patient population and baseline characteristics
    2. Adverse drug reactions
    3. Treatment switching and discontinuation
    4. Effect on glycemic control and body weight
  4. Discussion
  5. Author contributions
  6. Funding
  7. Guarantor’s name
  8. Conflicts of interest
  9. Appendix A. Supplementary data
  10. Reference

 

A progressive intensification of treatment is mandatory in type 2 diabetes whenever lifestyle intervention fails to maintain metabolic control [1]. All major guidelines agree on administering metformin as the initial treatment, when tolerated and not contraindicated, but there is no consensus on second-line add-on treatment, in the case of unsatisfactory metabolic control. [[2], [3], [4], [5]].

In the past decade, injectable glucagon-like peptide-1 receptor agonists (GLP-1RAs) and orally administered inhibitors of dipeptidylpeptidase-4 (DPP-4Is) entered the diabetes arena [[6], [7]]. Since the initial marketing authorization as add-on therapies, these drugs have been granted extension of indications to include first-line monotherapy and combination with insulin. However, their best place in therapy remains uncertain [8]. In controlled clinical trials, both GLP-1RAs and DPP-4Is, combined with metformin, produce similar improvements in glycemic control as other second-line treatments, with no negative effects on body weight and overall hypoglycemia [[9], [10]]. However, only a few systematic analyses of long-term clinical data are available on large patients’ cohorts [[11], [12]], capturing treatment effects and prescription trends in the community.

In February 2008, the Italian Medicines Agency (AIFA) approved the reimbursed use of exenatide, sitagliptin, and vildagliptin, subject to enrollment of patients into a web-based system to monitor the appropriateness of use, safety profile, and effects on metabolic control and body weight. We report the results of the first 30-month monitoring, as derived from the AIFA Monitoring Registry. Of note, fixed-dose associations of sitagliptin and vildagliptin with metformin were made available along the years; in the present report, their use is considered equivalent to the combination use of the individual compounds. Focus is given to the clinical characteristics of patients, drug safety, and reasons for treatment discontinuation. An analysis of the percentage of patients reaching HbA1c targets over time is also provided, to help clinicians tailor treatment on patients’ characteristics.

Patient population and baseline characteristics

A total of 77,864 records (38,811 on sitagliptin, 21,064 on exenatide, and 17,989 on vildagliptin), corresponding to 75,283 patients, were registered by 3741 diabetes specialists in 1278 centers, either hospital (n = 790) or community based (n = 488), distributed throughout Italy. On average, 16.5/10,000 inhabitants aged ≥18 were included (from 8.2 to 28.8 in different Italian regions).

The patients belonged to a fairly heterogeneous group, including a high proportion of cases scarcely represented in the trials supporting the marketing authorization of the three medicinal products. Over 50% of cases on exenatide and approximately 20% on DPP4-Is had severe obesity (BMI ≥ 35 kg/m2); exenatide patients exhibited higher median HbA1c and a greater percentage of cases with very poor metabolic control (HbA1c ≥ 11%, ≥97 mmol/mol). Elderly patients (≥75 years, n = 6125) constituted approximately 10% of the DPP-4I-treated cases (Table 1A; Supplemental Figure S2).

Table 1ABaseline demographic/clinical data of the population with diabetes enrolled in the AIFA Anti-diabetics Monitoring Registry with glucose-lowering agents.
Exenatide (n = 21,064) Sitagliptin (n = 38,811) Vildagliptin (n = 17,989)
Mean SD Mean SD Mean SD
Age (years) 58.9 9.9 61.7 10.4 61.9 10.4
Duration of diabetes (years) 10.0 15.4 9.1 7.1 8.2 6.5
Body mass index (kg/m2) 36.1 6.8 30.8 5.7 30.5 5.5
Waist circumference (cm) 115.9 14.4 104.6 13.1 104.4 12.6
Fasting glucose (mg/dL) 187.8 49.8 170.8 41.6 171.9 41.1
HbA1c (%) [mmol/mol] 8.8 [73] 1.3 [14] 8.3 [67] 1.1 [12] 8.2 [66] 1.1 [12]
Fasting C-peptide (ng/mL) 3.2 1.6 3.0 1.6 3.3 1.7
N % N % N %
Male gender 10,109 48.0 20,446 52.7 9741 54.1
Age > 75 years 723 3.4 3666 9.4 1736 9.7
BMI > 35 10,835 51.4 7870 20.3 3300 18.3
HbA1c > 11% (>97 mmol/mol) 1496 7.1 1139 2.9 516 2.9

Metformin was the background therapy in most cases, with/without concomitant sulfonylureas. Glitazones were rarely used, reflecting the Italian market. Monotherapy with sitagliptin was registered in <1% of cases (Table 1B).

Table 1BAssociation with other glucose-lowering agents.
Exenatide

(n = 21,064)

Sitagliptin

(n = 38,811)

Vildagliptin

(n = 17,989)

N % N % N %
No associationa 0 0 3.87 0.1 0
Metformin 10,691 50.8 25,116 64.7 15,289 85
Sulfonylureas 1323 6.3 1843 4.7 2062 11.5
Sulfonylureas + metformin 9050 43.0 9824 25.3 a a
Glitazones a a 1624 4.2 638 3.5
Repaglinide 1450 6.9 276 0.7 a a
Acarbose 260 1.2 225 0.5 72 0.4

In individual cases, background therapy could vary in the course of the observation. Please note that patients could be treated with more than one active principle; therefore, the sum of the percentages of cases may exceed 100%.

aOff-label according to marketing authorization.
Adverse drug reactions

During the 30-month observation period, 1116 ADRs were registered. The median time to ADR was 2.06, 2.85, and 3.87 months on exenatide, sitagliptin, and vildagliptin, respectively. Complete and partial recovery was observed in 717 and 179 cases, respectively; 103 cases did not recover, and late complications were registered in 13. No follow-up was available in 102 cases and two patients died. ADRs did not lead to treatment discontinuation only in 90 cases; after stopping the treatment, drug use was restarted in 100 cases.

ADRs were classified as severe in 77 cases (6.9%), particularly with exenatide (six acute pancreatitis, seven vomiting/nausea, and four renal failures, corresponding to an IR of 0.334, 0.390, and 0.223/1000 person-years, respectively) (Table 2). Three cases of acute pancreatitis occurred on sitagliptin and three more on vildagliptin (IRs: 0.097 and 0.221/1000 person-years, respectively). In addition, non-severe pancreatitis/elevated pancreatic enzymes were recorded in 48 cases (19 with exenatide, 16 with sitagliptin, and 13 with vildagliptin).

Table 2List of all severe ADRs and corresponding IR (in 1000 person-years) reported in the AIFA Anti-diabetics Monitoring Registry.
Event Exenatide Sitagliptin Vildagliptin
No. IRa 95% CI No. IRa 95% CI No. IRa 95% CI
Acute pancreatitis 6 0.334 (0.157–0.650) 3 0.097 (0.035–0.234) 3 0.221 (0.080–0.533)
Vomiting/nausea 7 0.390 (0.192–0.727) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Renal failure 4 0.223 (0.090–0.488) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Colon cancer 1 0.056 (0.013–0.205) 2 0.065 (0.020–0.180) 1 0.074 (0.018–0.272)
Epileptic convulsions 2 0.111 (0.034–0.310) 0 (0.000–0.081) 0 (0.000–0.185)
Abdominal pain 2 0.111 (0.034–0.310) 0 (0.000–0.081) 0 (0.000–0.185)
Severe hypoglycemia 1 0.056 (0.013–0.205) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Pneumonia 0 (0.000–0.140) 2 0.065 (0.020–0.180) 0 (0.000–0.185)
Breast cancer 1 0.056 (0.013–0.205) 2 0.065 (0.020–0.180) 0 (0.000–0.185)
Visual loss 0 (0.000–0.140) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Colon adenoma 0 (0.000–0.140) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Anaphylactic reaction/shock 1 0.056 (0.013–0.205) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Anemia 0 (0.000–0.140) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Cardiac failure 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Atrioventricular block 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Renal carcinoma 2 0.111 (0.034–0.310) 0 (0.000–0.081) 0 (0.000–0.185)
Cervix carcinoma 1 0.056 (0.013–0.205) 0 (0.001–0.081) 0 (0.000–0.185)
Coronary disease/Infarction 2 0.111 (0.034–0.310) 0 (0.000–0.081) 0 (0.000–0.185)
Cholecystitis 0 (0.000–0.140) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Cholestasis 0 (0.000–0.140) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Acute dermatitis 1 0.056 (0.013–0.205) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Gastric hemorrhage 0 (0.000–0.140) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Abdominal hernia 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Atrial fibrillation 1 0.056 (0·013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Liver dysfunction 0 (0.000–0.140) 0 (0.000–0.081) 2 0.147 (0.046–0.411)
Acute gastroenteritis 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Congestive gastropathy 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Ictus/cerebral hemorrhage/ischemia 1 0.056 (0.013–0.205) 1 0.032 (0.008–0.119) 1 0.074 (0.018–0.272)
Leukemia/lymphoma 0 (0.000–0.140) 2 0.065 (0.020–0.180) 1 0.074 (0.018–0.272)
Urticaria 2 0.111 (0.034–0.310) 0 (0.000–0.081) 0 (0.000–0.185)
Bladder cancer 0 (0.000–0.140) 0 (0.000–0.081) 1 0.074 (0.018–0.272)
Pericardial effusion 0 (0.000–0.140) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Gastric ulcer 1 0.056 (0.013–0.205) 0 (0.000–0.081) 0 (0.000–0.185)
Other 2 0.111 (0.034–0.310) 1 0.032 (0.008–0.119) 0 (0.000–0.185)
Total 43 2.397 (1.7813.162) 20 0.645 (0.4210.960) 14 1.034 (0.6191.639)
aIncidence rate (IR) = # event (N)/person-time at risk (T).

Hypoglycemic episodes were reported in 1085 exenatide-treated patients, 608 on sitagliptin, and 207 on vildagliptin, with IRs of 20.6, 6.3, and 4.6/1000 person-years, respectively. Sulfonylureas, either alone or combined with metformin, increased the risk of hypoglycemia. The RR during add-on to sulfonylureas, compared with add-on to metformin, was 2.96 (95% confidence interval (CI), 2.33–3.50) on exenatide, 2.99 (95% CI, 2.45–3.64) on sitagliptin, and 1.84 (95% CI, 1.20–2.69) on vildagliptin. In add-on to sulfonylurea + metformin, the RRs further increased to 3.76 (95% CI, 3.24–4.36) and 2.94 (95% CI, 2.39–3.61) for exenatide and sitagliptin, respectively (not authorized for vildagliptin).

……………..

Effect on glycemic control and body weight

On exenatide, absolute HbA1c decreased on average by 0.99% (0.9 mmol/mol) and body weight by 3.5% from baseline to the last available follow-up. The corresponding variations for sitagliptin and vildagliptin were −0.88% and −0.94% (0.8–0.9 mmol/mol) for HbA1c, and around −1.0% for body weight. The probability of reaching the HbA1c target of 7% (53 mmol/mol) or the secondary target of 8% (64 mmol/mol), after 3–4 or 8–9 months, decreased rapidly with increasing baseline HbA1c, with <20% probability for baseline values >9% (>75 mmol/mol) (Fig. 1). The number of cases at target with baseline HbA1c >11% was much lower for sitagliptin and vildagliptin than for exenatide, and the confidence interval of the estimate much larger.

Thumbnail image of Figure 1. Opens large image

Figure 1

Probability of achieving the targets of metabolic control (HbA1c <7%, lower lines; <8%, upper lines) at 3–4 months (continuous lines) or 8–9 months (broken lines) as function of entry HbA1c values.

In the subset of centers compliant to follow-up, the probability of achieving the desired target was not dependent on age or BMI, but it was inversely related to baseline HbA1c and to the use of incretin mimetics/DPP-4Is as third-line therapy. The add-on to metformin and treatment duration (not on vildagliptin) increased the probability of reaching the target (Supplementary Table 2).

The AIFA Monitoring Registry of exenatide, sitagliptin, and vildagliptin, collecting data on the use, safety, and effectiveness of incretin mimetics/DPP-4Is, represents a significant step forward in the post-marketing evaluation of new or innovative medicines.

The safety profiles of exenatide, sitagliptin, and vildagliptin in Italian clinical practice were similar to those recorded in registration trials and recently reviewed [12]. Although favored by online registration, the total number of ADRs was relatively low – but much higher than that usually observed in post-marketing surveillance – despite the old age of the population, and no unexpected ADRs were registered, with only one case of heart failure with DPP-4Is [13]. The decision of the regulatory Italian Agency (AIFA) to limit the reimbursement of incretin-based therapies to diabetes specialists in a well-defined monitoring system might have favored an accurate selection of patients also in the community setting, limiting adverse reactions.

Two ADRs are of particular significance: pancreatitis and hypoglycemia. The association of exenatide and sitagliptin with pancreatitis was documented since 2006 and prompted close monitoring [[14], [15]]. Later, the potential risk appeared to be increased by diabetes per se; post-approval studies have documented cases associated with incretin use, but a causal relationship between treatment and pancreatitis was neither proved nor excluded [[16], [17], [18], [19], [20]]. In the registry, a few additional reports of non-severe pancreatitis or simply raised levels of pancreatic enzymes were also recorded, without differences between drugs. When these non-adjudicated ADRs were summed up to severe pancreatitis, the total incidence of pancreatic events was in the range reported in the general population with diabetes and should be considered in the context of the notoriety bias generated by alerts. A 2013 comprehensive review of preclinical and clinical data on pancreatic safety by the European Medicines Agency concluded that the concerns on the risk of pancreatitis should not be minimized [21]. Later, the publication of two large cardiovascular outcome DPP-Is trials [[13], [22]] and epidemiological data [23] stifled the debate; a 2014 joint Food and Drug Administration (FDA)–European Medicines Agency (EMA) assessment concluded with a low-risk [24] but suggested continuous capture of data.

As expected, exenatide and DPP4-I add-ons to metformin were accompanied by low rates of hypoglycemia [25]. On the contrary, a two-to threefold increase in hypoglycemia was observed in combination with sulfonylureas, both with and without metformin, but very few cases were recorded as severe ADRs, requiring hospital admission. These data are in keeping with registration studies and with recent clinical trials showing that DPP4-Is are associated with very low rates of hypoglycemia when combined with metformin [26], despite similar or only moderately inferior glucose-lowering efficacy compared to sulfonylureas.

The analysis of discontinuation rates and metabolic effects may give hints for an appropriate use of these drugs in the community. This approach seems sound, as confirmed by a sensitivity analysis in a subset of selected centers with adherence to follow-up ≥80% (Supplementary Tables 1 and 2). As expected, the discontinuation rates of all drugs increased systematically with higher baseline HbA1c. They also increased with age for exenatide, not for gliptins, indicating a preferential use of oral agents in elderly subjects for whom a less strict metabolic target may be preferred [[3], [4], [27]]. On the contrary, weight loss might be the reason for the lower discontinuation rates of exenatide with increasing BMI, despite injections and higher baseline HbA1c.

Two subpopulations, with limited safety data in registration studies, deserve particular attention. The AIFA Registry included many patients aged ≥70; in a few of them, gastrointestinal symptoms associated with exenatide were the precipitating factors of acute renal failure, a side effect to be considered in frail patients. DPP-4Is were demonstrated to be safe in a meta-analysis on patients aged ≥65, as well as in a systematic review, and vildagliptin was shown to be effective and safe also in subjects with diabetes aged ≥75 [[6], [9],[27]]. Future analyses of the elderly Italian cohort will throw light on the efficacy of DPP-4I in the elderly. Similarly, the very large group with morbid obesity in the AIFA Registry will offer a unique opportunity to test the effects of incretin-based therapies in these patients, where metabolic control remains difficult and the use of insulin may be critical, because it further increases body weight.

In our database, the effectiveness of incretin-based add-on therapies on HbA1c and body weight was similar to that reported in a review of head-to-head trials [28], but these results should be taken with caution, considering that the high rate of L-FUs inflates effectiveness. HbA1c was reduced on average by 0.9–1.0% (9 mmol/mol) in the general dataset, also in relation to HbA1c at baseline, with much larger effects in subjects with poor metabolic control. In the AIFA Registry, exenatide and DPP-4Is were also prescribed to subjects with very poor metabolic control, above the levels where insulin is recommended by international guidelines [4]. Such prescribing approach may be explained by the opportunity to test these new drugs across the whole spectrum of disease, or as an extreme attempt before prescribing insulin. Fig. 1 provides an immediate picture of the possibility of attaining specific HbA1c targets with incretin-based therapies in clinical practice, emphasizing the predictive value of baseline metabolic control. This figure may help clinicians forecast the results of treatment in their next patient, as modulated by other variables (i.e., age, BMI, diabetes duration, and background treatment), as reported in Supplementary Table 2. The observation that several patients with HbA1c in the range 9–11% (75–97 mmol/mol) may reach an acceptable metabolic control with a low incidence of adverse reactions, including hypoglycemic events, is clinically relevant. Drug effectiveness should always be considered in the context of existing therapies [29], safety, cost, therapeutic inertia [30], and the beneficial effects of intensive lifestyle counseling, which remains mandatory at any step of intensified treatment. Notably, in frail patients, a patient-centered approach and progressively less challenging targets are proposed by international guidelines, to avoid the risk of adverse events. [4].

Our study presents limitations and strengths. First, the major limitation is an observation period of only 30 months, too short to draw definite conclusions on long-term efficacy (i.e., effects on diabetic complications). Second, due to its observational nature, baseline differences, and high rates of L-FU, any comparisons of safety, discontinuation, and effect on metabolic and weight control among the three drugs should be made with extreme caution. Third, given the purpose of the AIFA Registry, there was no comparator-treated group. Conversely, the main strength is the very large and heterogeneous diabetes cohort, including the complete dataset from an entire European nation, where drugs were used under strict regulatory access, requiring online registration for reimbursement.

In conclusion, data on the compliance, safety, and effectiveness of incretin-based therapies derived from the AIFA Registry, while not capturing any new safety signal, provide a comprehensive framework for health-care providers to regulate the use of these drugs in the community. These data might be useful to address several important points, including the independent effect of baseline HbA1c on its decline, the safety and effectiveness in subjects with diabetes over 75, and the effectiveness of incretins – also including liraglutide and saxagliptin from August 2010 – in the large cohort of obese subjects with BMI >35. These analyses will be carried out when the monitoring data will be available in the new and updated in-house web platform currently being developed. Whenever effective strategies of lifestyle changes preliminary to any further step in treatment intensification fail, the implementation of new treatments, including incretin-based therapies, should be dictated by solid data on long-term safety and effectiveness in the context of available drugs for type 2 diabetes, favoring a patient-centered approach. [4].

Read Full Post »


HDL oxidation in type 2 diabetic patients

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

 

 

High-density lipoprotein oxidation in type 2 diabetic patients and young patients with premature myocardial infarction

G. SartoreaR. SeragliabS. Burlinaa, , A. BolisaR. MarinaE. ManzatoaE. RagazzicP. TraldibA. Lapollaa
N
utr Metab Cardiovasc Dis April 2015; 25(4): 418–425       http://dx.doi.org:/10.1016/j.numecd.2014.12.004

Highlights

•  Oxidative damage can generate dysfunctional HDL reducing its anti-atherogenic role.
•  Increased MetO levels in ApoA-I in patients with premature MI and in type 2 DM.
•  An increase in MetO levels in ApoA-I could result in HDL dysfunction.

 

Background and aims

ApoA-I can undergo oxidative changes that reduce anti-atherogenic role of HDL. The aim of this study was to seek any significant differences in methionine sulfoxide (MetO) content in the ApoA-I of HDL isolated from young patients with coronary heart disease (CHD), type 2 diabetics and healthy subjects.

Methods and results

We evaluated the lipid profile of 21 type 2 diabetic patients, 23 young patients with premature MI and 21 healthy volunteers; we determined in all patients the MetO content of ApoA-I in by MALDI/TOF/TOF technique. The typical MALDI spectra of the tryptic digest obtained from HDL plasma fractions all patients showed a relative abundance of peptides containing Met112O in ApoA-I in type 2 diabetic and CHD patients. This relative abundance is given as percentages of oxidized ApoA-I (OxApoA-I). OxApoA-I showed no significant correlations with lipoproteins in all patients studied, while a strong correlation emerged between the duration of diabetic disease and OxApoA-I levels in type 2 diabetic patients.

Conclusions

The most remarkable finding of our study lies in the evidence it produced of an increased HDL oxidation in patients highly susceptible to CHD. Levels of MetO residues in plasma ApoA-I, measured using an accurate, specific method, should be investigated and considered in prospective future studies to assess their role in CHD.

 

No more than 25% of the risk of coronary heart disease (CHD) can be explained by known risk factors, despite their high prevalence [1].

High-density lipoprotein (HDL) protects artery wall from atherosclerosis, in particular they remove excess cholesterol from artery wall macrophages and carries it back to the liver for excretion in bile [2]. Apolipoprotein A-I (ApoA-I) is the main protein of HDL and it plays a crucial part in the first cholesterol transport reversal step by enhancing sterol efflux from macrophages [3].

Epidemiological studies have demonstrated that plasma HDL independently predict the risk of developing atherosclerosis and cardiovascular disease [4]. More recently, however, it has emerged that HDL quality also seems to be an important parameter in atheroprotection, though there is little data in the literature to support it [5].

An increasing body of evidence shows that HDL isolated from atheromas and the plasma of patients with established CHD lacks these anti-atherogenic properties [6]. HDL can be functionally deficient in populations at high risk of CHD, as in type 2 diabetes mellitus, due to glycation and oxidative changes in their HDL, apolipoproteins, and/or enzymes[7].

ApoA-I in particular can undergo oxidative changes that reduce its anti-atherogenic role[8]. Oxidation of the Tyr and Met residues in ApoA-I by myeloperoxidase drastically impairs the protein’s ability to promote cholesterol efflux via the ABCA1 pathway [9]. Levine and colleagues [10] suggested that Met residues in protein serve as endogenous antioxidants, protecting functionally important amino acids against oxidation. In ApoA-I in particular, Met86 and Met112 are thought to be important for cholesterol efflux, and Met148is believed to be involved in LCAT activation [11].

Brock et al. recently examined the extent and sites of methionine sulfoxide (MetO) formation in the ApoA-I of HDL isolated from the plasma of healthy controls and type 1 diabetic subjects, demonstrating that MetO formation was significantly greater in diabetic patients than in a control group at all three sites considered (Met86, Met112, and Met148)[12].

Considering the relevant role of HDL oxidation in the onset of atherosclerotic processes, we ran a pilot study on a small group of type 2 diabetic patients and young people prematurely experiencing acute myocardial infarction (MI): in both these groups we found higher levels of Met112O than in healthy controls [13]. That investigation was carried out by microfluidic-LC/ESI-MS measurements. In a further study the determination of MetO content of ApoA-I in type 2 diabetic patients was performed by MALDI/MS [14] and the results obtained perfectly overlap those achieved in the previous LC/MS investigation. These results proved that possible oxidation phenomena, sometimes observed in MALDI conditions [15], are in this case absent.

The aim of this study was to assess larger study groups to seek any significant differences in MetO between patients with premature MI, type 2 diabetics and healthy subjects, and to identify any correlations with these individuals’ lipoproteins. A secondary aim was to see whether the duration of the diabetic patients’ disease correlated with HDL oxidation.

MALDI/MS

MALDI/time of flight (TOF) and MALDI/TOF/TOF measurements were performed using a MALDI/TOF/TOF UltrafleXtreme instrument (Bruker Daltonics, Bremen, Germany), equipped with a 1 kHz smartbeam II laser (λ = 355 nm) and operating in the positive reflectron ion mode. The instrumental conditions were: IS1 = 25 kV; IS2 = 21.65 kV; reflectron potential = 26.3 kV; delay time = 0 nsec. The matrix was α-cyano-4-hydroxycinnamic acid (HCCA) (saturated solution in H2O/acetonitrile (50:50; v/v) containing 0.1% TFA). Five μL of purified tryptic digest and 5 μL of matrix solution were mixed together, then 1 μL of the resulting mixture was deposited on the stainless steel sample holder and allowed to dry before placing it in the mass spectrometer. External mass calibration (Peptide Calibration Standard) was based on monoisotopic values of [M+H]+ of angiotensin II, angiotensin I, substance P, bombesin, ACTH clip [1], [2], [3], [4],[5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16] and [17], ACTH clip (18–39), somatostatin 28 at m/z 1046.5420, 1296.6853, 1347.7361, 1619.8230, 2093.0868, 2465.1990 and 3147.4714. TOF/TOF experiments were performed using the LIFT device in the following experimental conditions: IS1: 7.5 kV; IS2: 6.75 kV; Lift1: 19 kV; Lift2: 3.7 kV; Reflector1: 29.5 kV; delay time: 70 ns.

Table 1 shows the demographic and clinical characteristics of patients and controls. The three groups were matched for age and smoke; the controls and diabetics were also matched for gender, while the premature MI group consisted almost entirely of men, with only one female patient. Type 2 diabetic patients were not in a situation of good metabolic control, their HbA1c levels being a mean 8.22 ± 0.84% and their FPG 156.7 ± 29.7 mg/dl.

Table 1.Clinical characteristics of type 2 diabetic patients, young patients with premature CHD and controls. Data are expressed as mean ± standard deviation. To assess statistical differences between groups, ANOVA followed by Tukey’spost-hoc test was used. ●●● p < 0.001; ●● p < 0.01; ● p < 0.05; ns: not significant;:not applied. Abbreviations: FPG = fasting plasma glucose; TC = total cholesterol; LDL = low-density lipoprotein; HDL = high-density lipoprotein; OxApoAI = oxidized Apolipoprotein AI; MI = myocardial infarction.

Control subjects (C)
(n = 21)
CHD patients (CHD)
(n = 23)
Type 2 diabetic patients (D)
(n = 21)
P


C vsCHD CvsD CHDvs D
Gender (M/F) 6/15 22/1 10/11
Age (yrs) 41.4 ± 2.8 40.7 ± 3.4 51.8 ± 3.5 ns ns ns
Diabetes duration (yrs) 8.5 ± 3.9
FPG (mg/dl) 83.5 ± 4.8 89.1 ± 7.4 156.7 ± 29.7 ns ●●● ●●●
HbA1c (%) 5.2 ± 0.2 5.3 ± 0.2 8.2 ± 0.8 ns ●●● ●●●
TC (mg/dl) 203.2 ± 33.3 205.3 ± 26.3 203.2 ± 37.0 ns ns ns
LDL (mg/dl) 117.5 ± 30.6 143.7 ± 24.7 118.3 ± 30.6 ●● ns
HDL (mg/dl) 68.7 ± 11.2 38.3 ± 10.4 49.7 ± 14.0 ●●● ●●● ●●
Triglycerides (mg/dl) 85.4 ± 21.6 146.3 ± 55.9 178.0 ± 91.8 ●● ●●● ns
ApoA1 (mg/dl) 148.2 ± 31.3 117.2 ± 14.5 128.9 ± 14.7 ns
OX ApoA1 (%) 1.7 ± 1.3 4.8 ± 2.6 10.6 ± 5.3 ●●● ●●●
MI (no/yes) 21/0 0/23 21/0
Statin therapy (yes/no) 0/21 23/0 18/3 ns
Anti-platelet agents (yes/no) 0/21 23/0 17/4 ns
Antihypertensive drugs (yes/no) 0/21 23/0 20/1 ns
Smokers (yes/no/ex) 4/15/2 5/16/2 6/14/1 ns ns ns

The three groups had similar total cholesterol levels. The group of patients with a premature MI had the highest levels of LDL cholesterol and the lowest levels of HDL cholesterol. Their triglycerides were also higher than in the healthy controls, but lower than in the diabetic patients.

Characterization of Met112 and Met112-O containing peptides

The typical MALDI spectra of the tryptic digest obtained from HDL plasma fractions of healthy subjects, diabetics and CHD patients are given in Fig. 1. MS/MS experiments performed on the two ions at m/z 1283.6 and 2645.4 showed that the sequences of the corresponding peptides are W108QEEM112ELYR and V97QPYLDDFQKKWQEEM112ELYR, both of which contain the methionine residue in position 112 (Met112). Looking at selected regions of the spectra related to the two above-mentioned ions, some differences appear between the healthy controls vs the diabetic patients and CHD patients. In the case of the diabetics and CHD patients, the two peaks at m/z 1299 and 2661 become more evident than those detected in the case of healthy subjects. These two peptides, differing from the above-described species by 16 Da, can be justified by the presence of the previously-mentioned peptides containing a Met112O moiety (see Fig. 2). MS/MS experiments performed on these two ions confirms this hypothesis, based on the presence of a fragment ion due to the loss of CH3SOH. This result confirms that oxidation occurs at Met112 in both the peptides. The above-described relative abundance of peptides containing Met112O- and Met112 was ascertained for all samples. The percentages of OxApoA-I were calculated dividing the sum of the abundances of the peaks at m/z 1299 and 2661 (originating from oxidation of Met112) to the sum of the abundances of the four peaks of interest: the results so obtained are shown in Table 1. Both the diabetic and the CHD patients showed significantly higher OxApoA-I levels than controls. We did not observe any significant correlation between the levels of ApoA-I and OxApoA-I in all groups (controls: r = −0.031; diabetics: r = 0.092; CHD patients: r = 0.20, respectively).

The typical MALDI spectra of the tryptic digest obtained from HDL plasma ...
Figure 1.

The typical MALDI spectra of the tryptic digest obtained from HDL plasma fractions of healthy subjects, diabetic and CHD patients.

Expanded view (A: m/z 1283–1299; B: m/z 2635–2690) of the MALDI mass spectra of ...
Figure 2.

Expanded view (A: m/z 1283–1299; B: m/z 2635–2690) of the MALDI mass spectra of tryptic digests from healthy subjects, diabetic patients and CHD patients.

It is to underline that the possible ex-vivo oxidation of methionine residue was checked analyzing the lyophilized HDL samples after two and four months of storage at −30 °C. No significant variation in the content of Met112O was observed, indicating that ex-vivo oxidation is inhibited at storage temperature.

Correlations

OxApoA-I showed no significant correlations with lipoproteins, while there were inverse significant correlations between HDL cholesterol and triglycerides in both the diabetic and the CHD patients (p < 0.02), but not in the healthy controls, as shown in Table 2. No correlation emerged between the OxApoA-I and HbA1c levels in the diabetic patients (r = 0.0344).

Table 2.Linear correlation between oxidized ApoA-I (Ox-ApoA-I) and serum cholesterol in the three groups of patients. Data are the Pearson product–moment correlation coefficient (Pearson’s r) with the lower and upper 95% confidence intervals (in parentheses).*p < 0.02.

Correlation between variables Control subjects, n = 21
(Lower and upper 95% C.I.)
CHD patients, n = 23
(Lower and upper 95% C.I.)
Diabetic patients, n = 21
(Lower and upper 95% C.I.)
Ox-ApoA-1 vs total cholesterol 0.3757
(−0.0669 ÷ 0.6947)
0.0519
(−0.3681 ÷ 0.4544)
−0.3287
(−0.6659 ÷ 0.1200)
Ox-ApoA-1 vs LDL-cholesterol 0.3557
(−0.0897 ÷ 0.6826)
−0.1688
(−0.5432 ÷ 0.2616)
−0.3193
(−0.6600 ÷ 0.1303)
Ox-ApoA-1 vs HDL-cholesterol 0.0745
(−0.3690 ÷ 0.4904)
0.3130
(−0.1139 ÷ 0.6423)
0.0839
(−0.3608 ÷ 0.4976)
Ox-ApoA-1vs triglycerides 0.1965
(−0.2570 ÷ 0.5790)
0.0434
(−0.3755 ÷ 0.4476)
−0.1953
(−0.5782÷0.2581)
Triglycerides vs HDL-cholesterol −0.3973
(−0.7076 ÷ 0.0415)
−0.4898*
(−0.7505 ÷ −0.0972)
−0.5413*
(−0.7887 ÷ −0.1431)

In order to evaluate with a more integrated approach the presence of interrelationships among variables, the non-parametric technique of PCA was considered. The analysis was extended to the three groups as a whole, in order to check any distribution among the individuals, and the respective role of the considered variables. As the biplot of Fig. 3shows, it was confirmed the previously found lack of any relationship between the OxApoA-I levels and HDL cholesterol or triglycerides, and it was confirmed also the presence of an inverse correlation between HDL cholesterol or triglycerides; moreover, from this analysis a strong direct correlation between the duration of diabetic disease and OxApoA-I levels emerged.

In order to evaluate with a more integrated approach the presence of interrelationships among variables, the non-parametric technique of PCA was considered. The analysis was extended to the three groups as a whole, in order to check any distribution among the individuals, and the respective role of the considered variables. As the biplot of Fig. 3shows, it was confirmed the previously found lack of any relationship between the OxApoA-I levels and HDL cholesterol or triglycerides, and it was confirmed also the presence of an inverse correlation between HDL cholesterol or triglycerides; moreover, from this analysis a strong direct correlation between the duration of diabetic disease and OxApoA-I levels emerged.

Biplot of the first two principal components (PC1 and PC2) obtained by PCA ...
Figure 3.

Biplot of the first two principal components (PC1 and PC2) obtained by PCA conducted on the most representative variables from diabetic patients, CHD patients and controls.

In the present, small cross-sectional study, our data analyses support the impression that the atheroprotective effect of HDL may be deficient in patients experiencing a premature MI and in cases of type 2 DM, both models of accelerated atherosclerosis [23]. This HDL dysfunction could be due to an increase in MetO levels in ApoA-I. We demonstrated, not only that type 2 diabetic patients and young patients with premature acute MI share the same ApoA-I oxidation, but also and more importantly they both have a greater HDL oxidation than controls, irrespective of their HDL levels. This feature was recently observed in type 1 diabetic patients compared with healthy controls, and it may contribute to an accelerated atherosclerosis [12]. These findings provide a new clinical perspective compared to preliminary results obtained by microfluidic-LC/ESI-MS [13], this time using an alternative technique (MALDI/MS), that makes the analysis far less time-consuming, as we previously showed in type 2 diabetic patients and healthy controls [14]. Our group of type 2 diabetic patients showed no signs of CHD despite their more severely oxidized HDL. We surmise that they offset the higher levels of oxidized HDL with higher levels of HDL, so the ratio of HDL to oxidized HDL might be a better marker of CHD than low HDL levels. Unfortunately, since our method only allowed for a semiquantitative assessment of the oxidation of the above-described peptides, these data cannot be used to calculate the HDL/oxidized-HDL ratio.

It is worth noting that no correlation emerged between MetO levels in ApoA-I and HbA1c, indicating that ApoA-I oxidation appears unrelated to the degree of glycemic control. This finding is in agreement with previous observations that have shown no correlation between glyco-oxidation products, such as glyoxal and methylglyoxal, which better represent the real glyco-oxidative stress experienced by patients [24].

On the other hand, our data suggest that duration of disease might be the parameter most closely related to MetO levels in ApoA-I in type 2 diabetes. In this contest, the antioxidant system could play an important part in the onset of cardiovascular complications by counter-regulating the increased oxidative stress, as we found in various phenotypes of type 2 diabetic patients with and without micro- and macrovascular complications [25] and [26]. Several studies have also demonstrated that decreased levels of antioxidants favor cardiovascular disease in subjects without diabetes [27]. As regards our data on HDL oxidation, we hypothesized that the increase of Apo-AI oxidation could be due to the decreased levels of antioxidant defenses that characterized type 2 diabetic patients with long duration of disease and patient with premature MI. Recent observations, in fact, showed that serum myeloperoxidase/paraoxonase 1 ratio is a potential indicator of dysfunctional HDL and risk stratification in CHD [28]. At the end HDL oxidation process could be partially independent from oxidative stress burden, but affected by decreased antioxidant capacity.

As for the higher triglyceride levels found in our type 2 DM and CHD patients, we surmise that hypertriglyceridemia could be a prognostic marker even in young patients with premature MI, irrespective of other cardiovascular risk factors, as previously reported[29]. Both our groups of patients showed a strong inverse relationship between their HDL and triglyceride levels, a situation typical of insulin resistance and found associated with MI occurring before 40 years of age [30].

As regards LDL cholesterol, we found the highest level in young CHD patients who were all in statin therapy. Considering the very short period of statin therapy and knowing that to reach the full effect it needs at still a month, CHD patients showed LDL cholesterol levels not still at target. On the other side, statin therapy hardly have had an impact on the oxidation of HDL. In any case statin protective effect on the oxidation strengthen our conclusions.

All these quantitative and qualitative lipoprotein features (higher oxidized HDL, higher triglycerides and lower HDL levels) suggest the feasibility of characterizing patients at high risk of CHD in terms of their lipid profile, as illustrated in the integrated biplot ofFig. 3.

In conclusion, the most remarkable finding of our study lies in the evidence it produced of an increased HDL oxidation in patients highly susceptible to CHD. Levels of MetO residues in plasma ApoA-I, measured using an accurate, specific method, should be investigated and considered in prospective future studies in order to assess their possible role as a novel risk factor – and eventually as a therapeutic target – to reduce the burden of cardiovascular complications.

Read Full Post »


Glucokinase target for type 2 diabetes

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

Pfizer’s PF 04991532 a Hepatoselective Glucokinase Activator Clinical Candidate for Treating Type 2 Diabetes Mellitus
DR ANTHONY MELVIN CRASTO, WORLD DRUG TRACKER
http://newdrugapprovals.org/2015/11/27/pfizers-pf-04991532-a-hepatoselective-glucokinase-activator-clinical-candidate-for-treating-type-2-diabetes-mellitus/

 

PF 04991532

GKA PF-04991532

(S)-6-{3-cyclopentyl-2-[4-(trifluoromethyl)-1H-imidazol-1-yl]propanamido}nicotinic acid

(S)-6-(3-Cyclopentyl-2-(4-(trifluoromethyl)-1H-imidazol-1-yl)propanamido)nicotinic Acid

(S)-6-(3-cyclopentyl-2-(4-(trifluoromethyl)-1H-imidazol-1-yl)propanamido)nicotinic acid

MW 396.36, MF C18 H19 F3 N4 O3

CAS 1215197-37-7

3-​Pyridinecarboxylic acid, 6-​[[(2S)​-​3-​cyclopentyl-​1-​oxo-​2-​[4-​(trifluoromethyl)​-​1H-​imidazol-​1-​yl]​propyl]​amino]​-

http://www.biochemj.org/content/441/3/881

 

Type 2 diabetes mellitus (T2DM) is a rapidly expanding public epidemic affecting over 300 million people worldwide. This disease is characterized by elevated fasting plasma glucose (FPG), insulin resistance, abnormally elevated hepatic glucose production (HGP), and reduced glucose-stimulated insulin secretion (GSIS). Moreover, long-term lack of glycemic control increases risk of complications from neuropathic, microvascular, and macrovascular diseases.

The standard of care for T2DM is metformin followed by sulfonylureas, dipeptidyl peptidase-4 (DPP-IV) inhibitors, and thiazolidinediones (TZD) as second line oral therapies. As disease progression continues, patients typically require injectable agents such as glucagon-like peptide-1 (GLP-1) analogues and, ultimately, insulin to help maintain glycemic control. Despite these current therapies, many patients still remain unable to safely achieve and maintain tight glycemic control, placing them at risk of diabetic complications and highlighting the need for novel therapeutic options.

 

Glucokinase (hexokinase IV) continues to be a compelling target for the treatment of type 2 diabetes given the wealth of supporting human genetics data and numerous reports of robust clinical glucose lowering in patients treated with small molecule allosteric activators. Recent work has demonstrated the ability of hepatoselective activators to deliver glucose lowering efficacy with minimal risk of hypoglycemia.

While orally administered agents require a considerable degree of passive permeability to promote suitable exposures, there is no such restriction on intravenously delivered drugs. Therefore, minimization of membrane diffusion in the context of an intravenously agent should ensure optimal hepatic targeting and therapeutic index.

 

Diabetes is a major public health concern because of its increasing prevalence and associated health risks. The disease is characterized by metabolic defects in the production and utilization of carbohydrates which result in the failure to maintain appropriate blood glucose levels. Two major forms of diabetes are recognized. Type I diabetes, or insulin-dependent diabetes mellitus (IDDM), is the result of an absolute deficiency of insulin. Type II diabetes, or non-insulin dependent diabetes mellitus (NIDDM), often occurs with normal, or even elevated levels of insulin and appears to be the result of the inability of tissues and cells to respond appropriately to insulin. Aggressive control of NIDDM with medication is essential; otherwise it can progress into IDDM.

As blood glucose increases, it is transported into pancreatic beta cells via a glucose transporter. Intracellular mammalian glucokinase (GK) senses the rise in glucose and activates cellular glycolysis, i.e. the conversion of glucose to glucose-6-phosphate, and subsequent insulin release. Glucokinase is found principally in pancreatic β-cells and liver parenchymal cells. Because transfer of glucose from the blood into muscle and fatty tissue is insulin dependent, diabetics lack the ability to utilize glucose adequately which leads to undesired accumulation of blood glucose (hyperglycemia). Chronic hyperglycemia leads to decreases in insulin secretion and contributes to increased insulin resistance. Glucokinase also acts as a sensor in hepatic parenchymal cells which induces glycogen synthesis, thus preventing the release of glucose into the blood. The GK processes are thus critical for the maintenance of whole body glucose homeostasis.

It is expected that an agent that activates cellular GK will facilitate glucose-dependent secretion from pancreatic beta cells, correct postprandial hyperglycemia, increase hepatic glucose utilization and potentially inhibit hepatic glucose release. Consequently, a GK activator may provide therapeutic treatment for NIDDM and associated complications, inter alia, hyperglycemia, dyslipidemia, insulin resistance syndrome, hyperinsulinemia, hypertension, and obesity.

Several drugs in five major categories, each acting by different mechanisms, are available for treating hyperglycemia and subsequently, NIDDM (Moller, D. E., “New drug targets for Type II diabetes and the metabolic syndrome” Nature414; 821-827, (2001)): (A) Insulin secretogogues, including sulphonyl-ureas (e.g., glipizide, glimepiride, glyburide) and meglitinides (e.g., nateglidine and repaglinide) enhance secretion of insulin by acting on the pancreatic beta-cells. While this therapy can decrease blood glucose level, it has limited efficacy and tolerability, causes weight gain and often induces hypoglycemia. (B) Biguanides (e.g., metformin) are thought to act primarily by decreasing hepatic glucose production. Biguanides often cause gastrointestinal disturbances and lactic acidosis, further limiting their use. (C) Inhibitors of alpha-glucosidase (e.g., acarbose) decrease intestinal glucose absorption. These agents often cause gastrointestinal disturbances. (D) Thiazolidinediones (e.g., pioglitazone, rosiglitazone) act on a specific receptor (peroxisome proliferator-activated receptor-gamma) in the liver, muscle and fat tissues. They regulate lipid metabolism subsequently enhancing the response of these tissues to the actions of insulin. Frequent use of these drugs may lead to weight gain and may induce edema and anemia. (E) Insulin is used in more severe cases, either alone or in combination with the above agents.

Ideally, an effective new treatment for NIDDM would meet the following criteria: (a) it would not have significant side effects including induction of hypoglycemia; (b) it would not cause weight gain; (c) it would at least partially replace insulin by acting via mechanism(s) that are independent from the actions of insulin; (d) it would desirably be metabolically stable to allow less frequent usage; and (e) it would be usable in combination with tolerable amounts of any of the categories of drugs listed herein.

Substituted heteroaryls, particularly pyridones, have been implicated in mediating GK and may play a significant role in the treatment of NIDDM. For example, U.S. Patent publication No. 2006/0058353 and PCT publication Nos. WO2007/043638, WO2007/043638, and WO2007/117995 recite certain heterocyclic derivatives with utility for the treatment of diabetes. Although investigations are on-going, there still exists a need for a more effective and safe therapeutic treatment for diabetes, particularly NIDDM.

 

s1

s1

 

s1

 

PATENT

US 20100063063

http://www.google.com/patents/US20100063063

SYNTHESIS CONSTRUCTION

6-aminonicotinic acid

 

BENZYL BROMIDE

 

Figure US20100063063A1-20100311-C00076

FIRST KEY INTERMEDIATE

 

SECOND SERIES FOR NEXT INTERMEDIATE

CONDENSED WITH

4-Trifluoromethyl-1H-imidazole

TO  GIVE PRODUCT SHOWN BELOW

 

Figure US20100063063A1-20100311-C00025

(S)-methyl 3-cyclopentyl-2-(4-(trifluoromethyl)-1H-imidazol-1-yl)propanoate (I-8a)

 

CONVERTED TO ACID CHLORIDE, (S)-3-cyclopentyl-2-(4-(trifluoromethyl)-1H-imidazol-1-yl)propanoyl chloride (I-8c)

AND CONDENSED WITH

Figure US20100063063A1-20100311-C00076

WILL GIVE BENZYL DERIVATIVE

THEN DEBENZYLATION TO FINAL PRODUCT

 

 

 

1H NMR (400 MHz, DMSO-d6) δ 13.10-13.25 (1H), 11.44 (1H), 8.83 (1H), 8.23-8.26 (1H), 8.09-8.12 (1H), 7.94-7.95 (2H), 5.22-5.26 (1H), 2.06-2.17 (2H), 1.29-1.64 (8H), 1.04-1.07 (1H); m/z 397.3 (M+H)+.

 

Organic Process Research & Development (2012), 16(10), 1635-1645

http://pubs.acs.org/doi/abs/10.1021/op300194c

Abstract Image

This work describes the process development and manufacture of early-stage clinical supplies of a hepatoselective glucokinase activator, a potential therapy for type 2 diabetes mellitus. Critical issues centered on challenges associated with the synthesis of intermediates and API bearing a particularly racemization-prone α-aryl carboxylate functionality. In particular, a T3P-mediated amidation process was optimized for the coupling of a racemization-prone acid substrate and a relatively non-nucleophilic amine. Furthermore, an unusually hydrolytically-labile amide in the API also complicated the synthesis and isolation of drug substance. The evolution of the process over multiple campaigns is presented, resulting in the preparation of over 110 kg of glucokinase activator.

(S)-6-(3-Cyclopentyl-2-(4-(trifluoromethyl)-1H-imidazol-1-yl)propanamido)nicotinic Acid (1)

 

Journal of Medicinal Chemistry (2012), 55(3), 1318-1333

http://pubs.acs.org/doi/abs/10.1021/jm2014887

Abstract Image

Glucokinase is a key regulator of glucose homeostasis, and small molecule allosteric activators of this enzyme represent a promising opportunity for the treatment of type 2 diabetes. Systemically acting glucokinase activators (liver and pancreas) have been reported to be efficacious but in many cases present hypoglycaemia risk due to activation of the enzyme at low glucose levels in the pancreas, leading to inappropriately excessive insulin secretion. It was therefore postulated that a liver selective activator may offer effective glycemic control with reduced hypoglycemia risk. Herein, we report structure–activity studies on a carboxylic acid containing series of glucokinase activators with preferential activity in hepatocytes versus pancreatic β-cells. These activators were designed to have low passive permeability thereby minimizing distribution into extrahepatic tissues; concurrently, they were also optimized as substrates for active liver uptake via members of the organic anion transporting polypeptide (OATP) family. These studies lead to the identification of 19 as a potent glucokinase activator with a greater than 50-fold liver-to-pancreas ratio of tissue distribution in rodent and non-rodent species. In preclinical diabetic animals, 19 was found to robustly lower fasting and postprandial glucose with no hypoglycemia, leading to its selection as a clinical development candidate for treating type 2 diabetes.

Bioorganic & Medicinal Chemistry Letters (2013), 23(24), 6588-6592

http://www.sciencedirect.com/science/article/pii/S0960894X13012638

Image for unlabelled figure

 

Structure of Hepatoselective GKA PF-04991532 (1).

Figure 1.

Structure of Hepatoselective GKA PF-04991532 (1).

 

Pfizer’s PF 04937319 glucokinase activators for the treatment of Type 2 diabetes
DR ANTHONY MELVIN CRASTO, WORLD DRUG TRACKER
http://newdrugapprovals.org/2015/11/27/pfizers-pf-04937319-glucokinase-activators-for-the-treatment-of-type-2-diabetes/

Graphical abstract: Designing glucokinase activators with reduced hypoglycemia risk: discovery of N,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide as a clinical candidate for the treatment of type 2 diabetes mellitus

PF 04937319

N,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide

MW 432.43

MF C22 H20 N6 O4
CAS 1245603-92-2
2-​Pyrimidinecarboxamid​e, N,​N-​dimethyl-​5-​[[2-​methyl-​6-​[[(5-​methyl-​2-​pyrazinyl)​amino]​carbonyl]​-​4-​benzofuranyl]​oxy]​-
N,N-Dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)carbamoyl)-benzofuran-4- yloxy)pyrimidine-2-carboxamide
Pfizer Inc. clinical candidate currently in Phase 2 development.
CLINICAL TRIALS

A trial to assess the safety, tolerability, pharmacokinetics, and pharmacodynamics of single doses of PF-04937319 in subjects with type 2 diabetes mellitus (NCT01044537)

Multiple dose study of PF-04937319 in patients with type 2 diabetes (NCT01272804)
Phase 2 study to evaluate safety and efficacy of investigational drug – PF04937319 in patients with type 2 diabetes (NCT01475461)

 

SYNTHESIS

PF 319 SYN

Glucokinase is a key regulator of glucose homeostasis and small molecule activators of this enzyme represent a promising opportunity for the treatment of Type 2 diabetes. Several glucokinase activators have advanced to clinical studies and demonstrated promising efficacy; however, many of these early candidates also revealed hypoglycemia as a key risk. In an effort to mitigate this hypoglycemia risk while maintaining the promising efficacy of this mechanism, we have investigated a series of substituted 2-methylbenzofurans as “partial activators” of the glucokinase enzyme leading to the identification ofN,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide as an early development candidate.

 

It is expected that an agent that activates cellular GK will facilitate glucose-dependent secretion from pancreatic beta cells, correct postprandial hyperglycemia, increase hepatic glucose utilization and potentially inhibit hepatic glucose release. Consequently, a GK activator may provide therapeutic treatment for NIDDM and associated complications, inter alia, hyperglycemia, dyslipidemia, insulin resistance syndrome, hyperinsulinemia, hypertension, and obesity. Several drugs in five major categories, each acting by different mechanisms, are available for treating hyperglycemia and subsequently, NIDDM (Moller, D. E., “New drug targets for Type 2 diabetes and the metabolic syndrome” Nature 414; 821 -827, (2001 )): (A) Insulin secretogogues, including sulphonyl-ureas (e.g., glipizide, glimepiride, glyburide) and meglitinides (e.g., nateglidine and repaglinide) enhance secretion of insulin by acting on the pancreatic beta-cells. While this therapy can decrease blood glucose level, it has limited efficacy and tolerability, causes weight gain and often induces hypoglycemia. (B) Biguanides (e.g., metformin) are thought to act primarily by decreasing hepatic glucose production. Biguanides often cause gastrointestinal disturbances and lactic acidosis, further limiting their use. (C) Inhibitors of alpha-glucosidase (e.g., acarbose) decrease intestinal glucose absorption. These agents often cause gastrointestinal disturbances. (D) Thiazolidinediones (e.g., pioglitazone, rosiglitazone) act on a specific receptor (peroxisome proliferator-activated receptor-gamma) in the liver, muscle and fat tissues. They regulate lipid metabolism subsequently enhancing the response of these tissues to the actions of insulin. Frequent use of these drugs may lead to weight gain and may induce edema and anemia. (E) Insulin is used in more severe cases, either alone or in combination with the above agents. Ideally, an effective new treatment for NIDDM would meet the following criteria: (a) it would not have significant side effects including induction of hypoglycemia; (b) it would not cause weight gain; (c) it would at least partially replace insulin by acting via mechanism(s) that are independent from the actions of insulin; (d) it would desirably be metabolically stable to allow less frequent usage; and (e) it would be usable in combination with tolerable amounts of any of the categories of drugs listed herein.

Substituted heteroaryls, particularly pyridones, have been implicated in mediating GK and may play a significant role in the treatment of NIDDM. For example, U.S. Patent publication No. 2006/0058353 and PCT publication No’s. WO2007/043638, WO2007/043638, and WO2007/117995 recite certain heterocyclic derivatives with utility for the treatment of diabetes. Although investigations are on-going, there still exists a need for a more effective and safe therapeutic treatment for diabetes, particularly NIDDM.

 

Designing glucokinase activators with reduced hypoglycemia risk: discovery of N,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide as a clinical candidate for the treatment of type 2 diabetes mellitus

*Corresponding authors
aPfizer Worldwide Research & Development, Eastern Point Road, Groton
E-mail: jeffrey.a.pfefferkorn@pfizer.com
Tel: +860 686 3421
Med. Chem. Commun., 2011,2, 828-839

DOI: 10.1039/C1MD00116G

http://pubs.rsc.org/en/content/articlelanding/2011/md/c1md00116g/unauth#!divAbstract

http://www.rsc.org/suppdata/md/c1/c1md00116g/c1md00116g.pdf

Glucokinase is a key regulator of glucose homeostasis and small molecule activators of this enzyme represent a promising opportunity for the treatment of Type 2 diabetes. Several glucokinase activators have advanced to clinical studies and demonstrated promising efficacy; however, many of these early candidates also revealed hypoglycemia as a key risk. In an effort to mitigate this hypoglycemia risk while maintaining the promising efficacy of this mechanism, we have investigated a series of substituted 2-methylbenzofurans as “partial activators” of the glucokinase enzyme leading to the identification ofN,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide as an early development candidate.

Graphical abstract: Designing glucokinase activators with reduced hypoglycemia risk: discovery of N,N-dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)-carbamoyl)benzofuran-4-yloxy)pyrimidine-2-carboxamide as a clinical candidate for the treatment of type 2 diabetes mellitus

N,N-Dimethyl-5-(2-methyl-6-((5-methylpyrazin-2-yl)carbamoyl)-benzofuran-4- yloxy)pyrimidine-2-carboxamide (28).

 

PAPER

 

http://pubs.rsc.org/en/content/articlelanding/2013/md/c2md20317k#!divAbstract

 

PAPER

Bioorganic & Medicinal Chemistry Letters (2013), 23(16), 4571-4578

http://www.sciencedirect.com/science/article/pii/S0960894X13007452

Glucokinase activators 1 and 2.

Figure 1.

Glucokinase activators 1 and 2.

 

PATENT

Pfizer Inc.

WO 2010103437

https://www.google.co.in/patents/WO2010103437A1?cl=en

Scheme I outlines the general procedures one could use to provide compounds of the present invention having Formula (I).

Figure imgf000011_0001
PF 319 SYN

Preparations of Starting Materials and Key Intermediates

 

 

Beebe, D.A.; Ross, T.T.; Rolph, T.P.; Pfefferkorn, J.A.; Esler, W.P.
The glucokinase activator PF-04937319 improves glycemic control in combination with exercise without causing hypoglycemia in diabetic rats
74th Annu Meet Sci Sess Am Diabetes Assoc (ADA) (June 13-17, San Francisco) 2014, Abst 1113-P

 

Amin, N.B.; Aggarwal, N.; Pall, D.; Paragh, G.; Denney, W.S.; Le, V.; Riggs, M.; Calle, R.A.
Two dose-ranging studies with PF-04937319, a systemic partial activator of glucokinase, as add-on therapy to metformin in adults with type 2 diabetes
Diabetes Obes Metab 2015, 17(8): 751

 

Study to compare single dose of three modified release formulations of PF-04937319 with immediate release material-sparing-tablet (IR MST) formulation previously studied in adults with type 2 diabetes mellitus (NCT02206607)

Read Full Post »


Finding the Genetic Links in Common Disease:  Caveats of Whole Genome Sequencing Studies

Writer and Reporter: Stephen J. Williams, Ph.D.

In the November 23, 2012 issue of Science, Jocelyn Kaiser reports (Genetic Influences On Disease Remain Hidden in News and Analysis)[1] on the difficulties that many genomic studies are encountering correlating genetic variants to high risk of type 2 diabetes and heart disease.  At the recent American Society of Human Genetics annual 2012 meeting, results of several DNA sequencing studies reported difficulties in finding genetic variants and links to high risk type 2 diabetes and heart disease.  These studies were a part of an international effort to determine the multiple genetic events contributing to complex, common diseases like diabetes.  Unlike Mendelian inherited diseases (like ataxia telangiectasia) which are characterized by defects mainly in one gene, finding genetic links to more complex diseases may pose a problem as outlined in the article:

  • Variants may be so rare that massive number of patient’s genome would need to be analyzed
  • For most diseases, individual SNPs (single nucleotide polymorphisms) raise risk modestly
  • Hard to find isolated families (hemophilia) or isolated populations (Ashkenazi Jew)
  • Disease-influencing genes have not been weeded out by natural selection after human population explosion (~5000 years ago) resulted in numerous gene variants
  • What percentage variants account for disease heritability (studies have shown this is as low as 26% for diabetes with the remaining risk determined by environment)

Although many genome-wide-associations studies have found SNPs that have causality to increasing risk diseases such as cancer, diabetes, and heart disease, most individual SNPs for common diseases raise risk by about only 20-40% and would be useless for predicting an individual’s chance they will develop disease and be a candidate for a personalized therapy approach.  Therefore, for common diseases, investigators are relying on direct exome sequencing and whole-genome sequencing to detect these medium-rare risk variants, rather than relying on genome-wide association studies (which are usually fine for detecting the higher frequency variants associated with common diseases).

Three of the many projects (one for heart risk and two for diabetes risk) are highlighted in the article:

1.  National Heart, Lung and Blood Institute Exome Sequencing Project (ESP)[2]: heart, lung, blood

  • Sequenced 6,700 exomes of European or African descent
  • Majority of variants linked to disease too rare (as low as one variant)
  • Groups of variants in the same gene confirmed link between APOC3 and higher risk for early-onset heart attack
  • No other significant gene variants linked with heart disease

2.  T2D-GENES Consortium: diabetes

Sequenced 5,300 exomes of type 2 diabetes patients and controls from five ancestry groups
SNP in PAX4 gene associated with disease in East Asians
No low-frequency variant with large effect though

3.  GoT2D: diabetes

  • After sequencing 2700 patient’s exomes and whole genome no new rare variants above 1.5% frequency with a strong effect on diabetes risk

A nice article by Dr. Sowmiya Moorthie entitled Involvement of rare variants in common disease can be found at the PGH Foundation site http://www.phgfoundation.org/news/5164/ further discusses this conundrum,  and is summarized below:

“Although GWAs have identified many SNPs associated with common disease, they have as yet had little success in identifying the causative genetic variants. Those that have been identified have only a weak effect on disease risk, and therefore only explain a small proportion of the heritable, genetic component of susceptibility to that disease. This has led to the common disease-common variant hypothesis, which predicts that common disease-causing genetic variants exist in all human populations, but each individual variant will necessarily only have a small effect on disease susceptibility (i.e. a low associated relative risk).

An alternative hypothesis is the common disease, many rare variants hypothesis, which postulates that disease is caused by multiple strong-effect variants, each of which is only found in a few individuals. Dickson et al. in a paper in PLoS Biology postulate that these rare variants can be indirectly associated with common variants; they call these synthetic associations and demonstrate how further investigation could help explain findings from GWA studies [Dickson et al. (2010) PLoS Biol. 8(1):e1000294][3].  In simulation experiments, 30% of synthetic associations were caused by the presence of rare causative variants and furthermore, the strength of the association with common variants also increased if the number of rare causative variants increased. “

one_of_many rare variants

Figure from Dr. Moorthie’s article showing the problem of “finding one in many”.

(please   click to enlarge)

Indeed, other examples of such issues concerning gene variant association studies occur with other common diseases such as neurologic diseases and obesity, where it has been difficult to clearly and definitively associate any variant with prediction of risk.

For example, Nuytemans et. al.[4] used exome sequencing to find variants in the vascular protein sorting 3J (VPS35) and eukaryotic transcription initiation factor 4  gamma1 (EIF4G1) genes, tow genes causally linked to Parkinson’s Disease (PD).  Although they identified novel VPS35 variants none of these variants could be correlated to higher risk of PD.   One EIF4G1 variant seemed to be a strong Parkinson’s Disease risk factor however there was “no evidence for an overall contribution of genetic variability in VPS35 or EIF4G1 to PD development”.

These negative results may have relevance as companies such as 23andme (www.23andme.com) claim to be able to test for Parkinson’s predisposition.  To see a description of the LLRK2 mutational analysis which they use to determine risk for the disease please see the following link: https://www.23andme.com/health/Parkinsons-Disease/. This company and other like it have been subjects of posts on this site (Personalized Medicine: Clinical Aspiration of Microarrays)

However there seems to be more luck with strategies focused on analyzing intronic sequence rather than exome sequence. Jocelyn Kaiser’s Science article notes this in a brief interview with Harry Dietz of Johns Hopkins University where he suspects that “much of the missing heritability lies in gene-gene interactions”.  Oliver Harismendy and Kelly Frazer and colleagues’ recent publication in Genome Biology  http://genomebiology.com/content/11/11/R118 support this notion[5].  The authors used targeted resequencing of two endocannabinoid metabolic enzyme genes (fatty-acid-amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal weight and 142 extremely obese patients.

These patients were enrolled in the CRESCENDO trial and patients analyzed were of European descent. However, instead of just exome sequencing, the group resequenced exome AND intronic sequence, especially focusing on promoter regions.   They identified 1,448 single nucleotide variants but using a statistical filter (called RareCover which is referred to as a collapsing method) they found 4 variants in the promoters and intronic areas of the FAAH and MGLL genes which correlated to body mass index.  It should be noted that anandamide, a substrate for FAAH, is elevated in obese patients. The authors did note some issues though mentioning that “some other loci, more weakly or inconsistently associated in the original GWASs, were not replicated in our samples, which is not too surprising given the sample size of our cohort is inadequate to replicate modest associations”.

PLEASE WATCH VIDEO on the National Heart, Lung and Blood Institute Exome Sequencing Project

https://www.youtube.com/watch?v=-Qr5ahk1HEI

REFERENCES

http://www.phgfoundation.org/news/5164/  PHG Foundation

1.            Kaiser J: Human genetics. Genetic influences on disease remain hidden. Science 2012, 338(6110):1016-1017.

2.            Tennessen JA, Bigham AW, O’Connor TD, Fu W, Kenny EE, Gravel S, McGee S, Do R, Liu X, Jun G et al: Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 2012, 337(6090):64-69.

3.            Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB: Rare variants create synthetic genome-wide associations. PLoS biology 2010, 8(1):e1000294.

4.            Nuytemans K, Bademci G, Inchausti V, Dressen A, Kinnamon DD, Mehta A, Wang L, Zuchner S, Beecham GW, Martin ER et al: Whole exome sequencing of rare variants in EIF4G1 and VPS35 in Parkinson disease. Neurology 2013, 80(11):982-989.

5.            Harismendy O, Bansal V, Bhatia G, Nakano M, Scott M, Wang X, Dib C, Turlotte E, Sipe JC, Murray SS et al: Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level. Genome biology 2010, 11(11):R118.

Other posts on this site related to Genomics include:

Cancer Biology and Genomics for Disease Diagnosis

Diagnosis of Cardiovascular Disease, Treatment and Prevention: Current & Predicted Cost of Care and the Promise of Individualized Medicine Using Clinical Decision Support Systems

Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

Genomics-based cure for diabetes on-the-way

Personalized Medicine: Clinical Aspiration of Microarrays

Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Genetics of Disease: More Complex is How to Creating New Drugs

Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

Centers of Excellence in Genomic Sciences (CEGS): NHGRI to Fund New CEGS on the Brain: Mental Disorders and the Nervous System

Cancer Genomic Precision Therapy: Digitized Tumor’s Genome (WGSA) Compared with Genome-native Germ Line: Flash-frozen specimen and Formalin-fixed paraffin-embedded Specimen Needed

Mitochondrial Metabolism and Cardiac Function

Pancreatic Cancer: Genetics, Genomics and Immunotherapy

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Quantum Biology And Computational Medicine

Personalized Cardiovascular Genetic Medicine at Partners HealthCare and Harvard Medical School

Centers of Excellence in Genomic Sciences (CEGS): NHGRI to Fund New CEGS on the Brain: Mental Disorders and the Nervous System

LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2

Consumer Market for Personal DNA Sequencing: Part 4

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

Whole-Genome Sequencing Data will be Stored in Coriell’s Spin off For-Profit Entity

 

Read Full Post »


Liver Endoplasmic Reticulum Stress and Hepatosteatosis

Larry H Bernstein, MD, FCAP

 

1. Absence of adipose triglyceride lipase protects from hepatic endoplasmic reticulum stress in mice.

Fuchs CD, Claudel T, Kumari P, Haemmerle G, et al.
LabExpMol Hepatology, Medical Univ of Graz, Austria.
Hepatology. 2012 Jul;56(1):270-80.   http://dx.doi.org/10.1002/hep.25601. Epub 2012 May 29.

Nonalcoholic fatty liver disease (NAFLD) is characterized by

  • triglyceride (TG) accumulation and
  • endoplasmic reticulum (ER) stress.

Fatty acids (FAs) may trigger ER stress, therefore,

  •  the absence of adipose triglyceride lipase (ATGL/PNPLA2)-
    • the main enzyme for intracellular lipolysis,
  • releasing FAs, and
  • closest homolog to adiponutrin (PNPLA3)

recently implicated in the pathogenesis of NAFLD-

  • could protect against hepatic ER stress.

Wild-type (WT) and ATGL knockout (KO) mice

  •  were challenged with tunicamycin (TM) to induce ER stress.

Markers of hepatic

  •  lipid metabolism,
  • ER stress, and
  • inflammation were explored
    • for gene expression by
    •  serum biochemistry,
    • hepatic TG and FA profiles,
    • liver histology,
    • cell-culture experiments were performed in Hepa1.6 cells
  • after the knockdown of ATGL before FA and TM treatment.

TM increased hepatic TG accumulation in ATGL KO, but not in WT mice. Lipogenesis and β-oxidation
were repressed at the gene-expression level
(sterol regulatory element-binding transcription factor 1c,
fatty acid synthase, acetyl coenzyme A carboxylase 2, and carnitine palmitoyltransferase 1 alpha) in
both WT and ATGL KO mice. Genes for very-low-density lipoprotein (VLDL) synthesis (microsomal
triglyceride transfer protein and apolipoprotein B)

  •  were down-regulated by TM in WT
  • and even more in ATGL KO mice,
  • which displayed strongly reduced serum VLDL cholesterol levels.

ER stress markers were induced exclusively in TM-treated WT, but not ATGL KO, mice:

  •  glucose-regulated protein,
  • C/EBP homolog protein,
  • spliced X-box-binding protein,
  • endoplasmic-reticulum-localized DnaJ homolog 4, and
  • inflammatory markers Tnfα and iNos.

Total hepatic FA profiling revealed a higher palmitic acid/oleic acid (PA/OA) ratio in WT mice.
Phosphoinositide-3-kinase inhibitor-

  • known to be involved in FA-derived ER stress and
  • blocked by OA-
  • was increased in TM-treated WT mice only.

In line with this, in vitro OA protected hepatocytes from TM-induced ER stress. Lack of ATGL may protect from
hepatic ER stress through alterations in FA composition. ATGL could constitute a new therapeutic strategy
to target ER stress in NAFLD.
PMID: 22271167 Diabetes Obes Metab. 2010 Oct;12 Suppl 2:83-92.
http://dx.doi.org/10.1111/j.1463-1326.2010.01275.x.

2. Hepatic steatosis: a role for de novo lipogenesis and the transcription factor SREBP-1c.
Ferré P, Foufelle F. INSERM, and Université Pierre et Marie Curie-Paris, Paris, France.    PMID: 21029304

Excessive availability of plasma fatty acids and lipid synthesis from glucose (lipogenesis) are important determinants of steatosis.
Lipogenesis is an insulin- and glucose-dependent process that is under the control of specific transcription factors,

Insulin induces the maturation of SREBP-1c in the endoplasmic reticulum (ER).

  • SREBP-1c in turn activates glycolytic gene expression,
    • allowing glucose metabolism, and
    • lipogenic genes in conjunction with ChREBP.

Lipogenesis activation in the liver of obese markedly insulin-resistant steatotic rodents is then paradoxical.
It appears the activation of SREBP-1c and thus of lipogenesis is

  •  secondary in the steatotic liver to an ER stress.

The ER stress activates the

  •  cleavage of SREBP-1c independent of insulin,
  • explaining the paradoxical stimulation of lipogenesis
  • in an insulin-resistant liver.

Inhibition of the ER stress in obese rodents

  •  decreases SREBP-1c activation and lipogenesis and
  • improves markedly hepatic steatosis and insulin sensitivity.
  • ER is thus worth considering as a potential therapeutic target for steatosis and metabolic syndrome.

3. SREBP-1c transcription factor and lipid homeostasis: clinical perspective
Ferré P, Foufelle F
Inserm, Centre de Recherches Biomédicales des Cordeliers, Paris, France.
Horm Res. 2007;68(2):72-82. Epub 2007 Mar 5. PMID:17344645

Insulin has long-term effects on glucose and lipid metabolism through its control on the expression of specific genes.
In insulin sensitive tissues and particularly in the liver,

  •  the transcription factor sterol regulatory element binding protein-1c (SREBP-1c) transduces the insulin signal, which is
  • synthetized as a precursor in the membranes of the endoplasmic reticulum
  • which requires post-translational modification to yield its transcriptionally active nuclear form.

Insulin activates the transcription and the proteolytic maturation of SREBP-1c, which induces the

  •  expression of a family of genes
  • involved in glucose utilization and fatty acid synthesis and
  • can be considered as a thrifty gene.

Since a high lipid availability is

  •  deleterious for insulin sensitivity and secretion,
  • a role for SREBP-1c in dyslipidaemia and type 2 diabetes
  • has been considered in genetic studies.

SREBP-1c could also participate in

  •  hepatic steatosis observed in humans
  • related to alcohol consumption and
  • hyperhomocysteinemia
  • concomitant with a ER-stress and
  • insulin-independent SREBP-1c activation.

4. Hepatic steatosis: a role for de novo lipogenesis and the transcription factor SREBP-1c
Ferré P, Foufelle F
INSERM, Centre de Recherches des Cordeliers and Université Pierre et Marie Curie-Paris, Paris, France.
Diabetes Obes Metab. 2010 Oct;12 Suppl 2:83-92. PMID: 21029304
http://dx.doiorg/10.1111/j.1463-1326.2010.01275.x.

Lipogenesis in liver steatosis is

  •  an insulin- and glucose-dependent process
  • under the control of specific transcription factors,
  • sterol regulatory element binding protein 1c (SREBP-1c),
  • activated by insulin and carbohydrate response element binding protein (ChREBP)

Insulin induces the maturation of SREBP-1c in the endoplasmic reticulum (ER).
SREBP-1c in turn activates glycolytic gene expression, allowing –

  •  glucose metabolism in conjunction with ChREBP.

activation of SREBP-1c and lipogenesis is secondary in the steatotic liver to ER stress, which

  •  activates the cleavage of SREBP-1c independent of insulin,
  • explaining the stimulation of lipogenesis in an insulin-resistant liver.
  • Inhibition of the ER stress in obese rodents decreases SREBP-1c activation and improves
  • hepatic steatosis and insulin sensitivity.

ER is thus a new partner in steatosis and metabolic syndrome

5. Pharmacologic ER stress induces non-alcoholic steatohepatitis in an animal model
Jin-Sook Leea, Ze Zhenga, R Mendeza, Seung-Wook Hac, et al.
Wayne State University SOM, Detroit, MI
Toxicology Letters 20 May 2012; 211(1):29–38      http://dx.doi.org/10.1016/j.toxlet.2012.02.017

Endoplasmic reticulum (ER) stress refers to a condition of

  •  accumulation of unfolded or misfolded proteins in the ER lumen, which is known to
  • activate an intracellular stress signaling termed
  • Unfolded Protein Response (UPR).

A number of pharmacologic reagents or pathophysiologic stimuli

  •  can induce ER stress and activation of the UPR signaling,
  • leading to alteration of cell physiology that is
  • associated with the initiation and progression of a variety of diseases.

Non-alcoholic steatohepatitis (NASH), characterized by hepatic steatosis and inflammation, has been considered the
precursor or the hepatic manifestation of metabolic disease. In this study, we delineated the

  • toxic effect and molecular basis
  • by which pharmacologic ER stress,
  • induced by a bacterial nucleoside antibiotic tunicamycin (TM),
  • promotes NASH in an animal model.

Mice of C57BL/6J strain background were challenged with pharmacologic ER stress by intraperitoneal injection of TM. Upon TM injection,

  •  mice exhibited a quick NASH state characterized by
  • hepatic steatosis and inflammation.

TM-treated mice exhibited an increase in –

  •  hepatic triglycerides (TG) and a –
  • decrease in plasma lipids, including
  • plasma TG,
  • plasma cholesterol,
  • high-density lipoprotein (HDL), and
  • low-density lipoprotein (LDL),

In response to TM challenge,

  •  cleavage of sterol responsive binding protein (SREBP)-1a and SREBP-1c,
  •  the key trans-activators for lipid and sterol biosynthesis,
  • was dramatically increased in the liver.

Consistent with the hepatic steatosis phenotype, expression of

  •  some key regulators and enzymes in de novo lipogenesis and lipid droplet formation was up-regulated,
  • while expression of those involved in lipolysis and fatty acid oxidation was down-regulated
  • in the liver of mice challenged with TM.

TM treatment also increased phosphorylation of NF-κB inhibitors (IκB),

  •  leading to the activation of NF-κB-mediated inflammatory pathway in the liver.

Our study not only confirmed that pharmacologic ER stress is a strong “hit” that triggers NASH, but also demonstrated

  •  crucial molecular links between ER stress,
  • lipid metabolism, and
  • inflammation in the liver in vivo.

Highlights
► Pharmacologic ER stress induced by tunicamycin (TM) induces a quick NASH state in vivo.
► TM leads to dramatic increase in cleavage of sterol regulatory element-binding protein in the liver.
► TM up-regulates lipogenic genes, but down-regulates the genes in lipolysis and FA oxidation.
► TM activates NF-κB and expression of genes encoding pro-inflammatory cytokines in the liver.
Abbreviations
ER, endoplasmic reticulum; TM, tunicamycin; NASH, non-alcoholic steatohepatitis; NAFLD,
non-alcoholic fatty liver disease; TG, triglycerides; SREBP, sterol responsive binding protein;
NF-κB, activation of nuclear factor-kappa B; IκB, NF-κB inhibitor
Keywords: ER stress; Non-alcoholic steatohepatitis; Tunicamycin; Lipid metabolism; Hepatic inflammation
Figures and tables from this article:

Fig. 1. TM challenge alters lipid profiles and causes hepatic steatosis in mice. (A) Quantitative real-time RT-PCR analysis of liver mRNA isolated from mice challenged with TM or vehicle control. Total liver mRNA was isolated at 8 h or 30 h after injection with vehicle or TM (2 μg/g body weight) for real-time RT-PCR analysis. Expression values were normalized to β-actin mRNA levels. Fold changes of mRNA are shown by comparing to one of the control mice. Each bar denotes the mean ± SEM (n = 4 mice per group); **P < 0.01. Edem1, ER degradation enhancing, mannosidase alpha-like 1. (B) Oil-red O staining of lipid droplets in the livers of the mice challenged with TM or vehicle control (magnification: 200×). (C) Levels of TG in the liver tissues of the mice challenged with TM or vehicle control. (D) Levels of plasma lipids in the mice challenged with TM or vehicle control. TG, triglycerides; TC, total plasma cholesterol; HDL, high-density lipoproteins; VLDL/LDL, very low and low density lipoproteins. For C and D, each bar denotes mean ± SEM (n = 4 mice per group); *P < 0.05; **P < 0.01.

 Fhttp://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr1.jpgigure options

Fig. 2. TM challenge leads to a quick NASH state in mice. (A) Histological examination of liver tissue sections of the mice challenged with TM (2 μg/g body weight) or vehicle control. Upper panel, hematoxylin–eosin (H&E) staining of liver tissue sections; the lower panel, Sirius staining of collagen deposition of liver tissue sections (magnification: 200×). (B) Histological scoring for NASH activities in the livers of the mice treated with TM or vehicle control. The grade scores were calculated based on the scores of steatosis, hepatocyte ballooning, lobular and portal inflammation, and Mallory bodies. The stage scores were based on the liver fibrosis. Number of mice examined is given in parentheses. Mean ± SEM values are shown. P-values were calculated by Mann–Whitney U-test.

 http://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr2.jpg

Fig. 3. TM challenge significantly increases levels of cleaved/activated forms of SREBP1a and SREBP1c in the liver. Western blot analysis of protein levels of SREBP1a (A) and SREBP1c (B) in the liver tissues from the mice challenged with TM (2 μg/g body weight) or vehicle control. Levels of GAPDH were included as internal controls. For A and B, the values below the gels represent the ratios of mature/cleaved SREBP signal intensities to that of SREBP precursors. The graph beside the images showed the ratios of mature/cleaved SREBP to precursor SREBP in the liver of mice challenged with TM or vehicle. The protein signal intensities shown by Western blot analysis were quantified by NIH imageJ software. Each bar represents the mean ± SEM (n = 3 mice per group); **P < 0.01. SREBP-p, SREBP precursor; SREBP-m, mature/cleaved SREBP.

 http://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr3.jpg

Fig. 4. TM challenge up-regulates expression of genes involved in lipogenesis but down-regulates expression of genes involved in lipolysis and FA oxidation. Quantitative real-time RT-PCR analysis of liver mRNAs isolated from the mice challenged with TM (2 μg/g body weight) or vehicle control, which encode regulators or enzymes in: (A) de novo lipogenesis: PGC1α, PGC1β, DGAT1 and DGAT2; (B) lipid droplet production: ADRP, FIT2, and FSP27; (C) lipolysis: ApoC2, Acox1, and LSR; and (D) FA oxidation: PPARα. Expression values were normalized to β-actin mRNA levels. Fold changes of mRNA are shown by comparing to one of the control mice. Each bar denotes the mean ± SEM (n = 4 mice per group); **P < 0.01. (E and F) Isotope tracing analysis of hepatic de novo lipogenesis. Huh7 cells were incubated with [1-14C] acetic acid for 6 h (E) or 12 h (F) in the presence or absence of TM (20 μg/ml). The rates of de novo lipogenesis were quantified by determining the amounts of [1-14C]-labeled acetic acid incorporated into total cellular lipids after normalization to cell numbers.

 http://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr4.jpg

Fig. 5. TM activates the inflammatory pathway through NF-κB, but not JNK, in the liver. Western blot analysis of phosphorylated Iκ-B, total Iκ-B, phosphorylated JNK, and total JNK in the liver tissues from the mice challenged with TM (2 μg/g body weight) or vehicle control. Levels of GAPDH were included as internal controls. The values below the gels represent the ratios of phosphorylated protein signal intensities to that of total proteins.

 http://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr5.jpg

Fig. 6. TM induces expression of pro-inflammatory cytokines and acute-phase responsive proteins in the liver. Quantitative real-time RT-PCR analyses of liver mRNAs isolated from the mice challenged with TM (2 μg/g body weight) or vehicle control, which encode: (A) pro-inflammatory cytokine TNFα and IL6; and (B) acute-phase protein SAP and SAA3. Expression values were normalized to β-actin mRNA levels. Fold changes of mRNA are shown by comparing to one of the control mice. (C–E) ELISA analyses of serum levels of TNFα, IL6, and SAP in the mice challenged with TM or vehicle control for 8 h ELISA. Each bar denotes the mean ± SEM (n = 4 mice per group); *P < 0.05, **P < 0.01.

http://ars.els-cdn.com/content/image/1-s2.0-S0378427412000732-gr6.jpg

Corresponding author at: Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, 540 E. Canfield Avenue, Detroit, MI 48201, USA. Tel.: +1 313 577 2669; fax: +1 313 577 5218.

The SREBP regulatory pathway. Brown MS, Goldst...

The SREBP regulatory pathway. Brown MS, Goldstein JL (1997). “The SREBP pathway: regulation of cholesterol metabolism by proteolysis of a membrane-bound transcription factor”. Cell 89 (3) : 331–340. doi:10.1016/S0092-8674(00)80213-5. PMID 9150132. (Photo credit: Wikipedia)

English: Structure of the SREBF1 protein. Base...

English: Structure of the SREBF1 protein. Based on PyMOL rendering of PDB 1am9. (Photo credit: Wikipedia)

The SREBP regulatory pathway

The SREBP regulatory pathway (Photo credit: Wikipedia)

English: Diagram of rough endoplasmic reticulu...

English: Diagram of rough endoplasmic reticulum by Ruth Lawson, Otago Polytechnic. (Photo credit: Wikipedia)

Micrograph demonstrating marked (macrovesicula...

Micrograph demonstrating marked (macrovesicular) steatosis in non-alcoholic fatty liver disease. Masson’s trichrome stain. (Photo credit: Wikipedia)

 

Read Full Post »

Older Posts »