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1.  Common Variants in 40 Genes Assessed for Diabetes Incidence and Response to Metformin and Lifestyle Intervention in the Diabetes Prevention Program 
Diabetes  2010;59(10):2672-2681.
Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions.
We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates.
We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09–1.40, P = 7 × 10−4). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates.
We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.
PMCID: PMC3279522  PMID: 20682687
2.  Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: The Diabetes Prevention Program 
PLoS Genetics  2012;8(8):e1002895.
Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, Pinteraction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; Pinteraction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, Pinteraction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; Pinteraction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.
Author Summary
The study included 2,993 participants from the Diabetes Prevention Program, a randomized clinical trial of intensive lifestyle intervention, metformin treatment, and placebo control. We examined associations between 32 gene variants that have been reproducibly associated with dyslipidemia and concentrations of lipids and NMR lipoprotein particle sizes and numbers. We also examined whether genetic background influences a person's response to cardioprotective interventions on lipid levels. Our analysis, which focused on determining whether common genetic variants impact the effects of cardioprotective interventions on lipid and lipoprotein particle size, shows that in persons with a high genetic risk score the benefit of intensive lifestyle intervention on LDL and small LDL particle levels is substantially diminished; this information may be informative for the targeted prevention of dyslipidemia, as it suggests that genetics might help identify persons in whom lifestyle intervention is likely to be an effective treatment for elevated lipids and lipoproteins. The NMR subfraction analyses provide novel insight into the biology of dyslipidemia by illustrating how numerous genetic variants that have previously been associated with lipid levels also modulate NMR lipoprotein particle sizes and number. This information may be informative for the targeted prevention of cardiovascular disease.
PMCID: PMC3431328  PMID: 22951888
3.  Maternal Physical Activity and Insulin Action in Pregnancy and Their Relationships With Infant Body Composition 
Diabetes Care  2013;36(2):267-269.
We sought to assess the association between maternal gestational physical activity and insulin action and body composition in early infancy.
At 28–32 weeks' gestation, pregnant women participating in an observational study in Sweden underwent assessments of height, weight, and body composition, an oral glucose tolerance test, and 10 days of objective physical activity assessment. Thirty mothers and infants returned at 11–19 weeks postpartum. Infants underwent assessments of weight, length, and body composition.
Early insulin response was correlated with total physical activity (r = −0.47; P = 0.007). Early insulin response (r = −0.36; P = 0.045) and total physical activity (r = 0.52; P = 0.037) were also correlated with infant fat-free mass. No maternal variable was significantly correlated with infant adiposity.
The relationships between maternal physical activity, insulin response, and infant fat-free mass suggest that physical activity during pregnancy may affect metabolic outcomes in the mother and her offspring.
PMCID: PMC3554315  PMID: 22966095
4.  Dietary Intakes of Individual Flavanols and Flavonols Are Inversely Associated with Incident Type 2 Diabetes in European Populations123 
The Journal of Nutrition  2013;144(3):335-343.
Dietary flavanols and flavonols, flavonoid subclasses, have been recently associated with a lower risk of type 2 diabetes (T2D) in Europe. Even within the same subclass, flavonoids may differ considerably in bioavailability and bioactivity. We aimed to examine the association between individual flavanol and flavonol intakes and risk of developing T2D across European countries. The European Prospective Investigation into Cancer and Nutrition (EPIC)–InterAct case-cohort study was conducted in 8 European countries across 26 study centers with 340,234 participants contributing 3.99 million person-years of follow-up, among whom 12,403 incident T2D cases were ascertained and a center-stratified subcohort of 16,154 individuals was defined. We estimated flavonoid intake at baseline from validated dietary questionnaires using a database developed from Phenol-Explorer and USDA databases. We used country-specific Prentice-weighted Cox regression models and random-effects meta-analysis methods to estimate HRs. Among the flavanol subclass, we observed significant inverse trends between intakes of all individual flavan-3-ol monomers and risk of T2D in multivariable models (all P-trend < 0.05). We also observed significant trends for the intakes of proanthocyanidin dimers (HR for the highest vs. the lowest quintile: 0.81; 95% CI: 0.71, 0.92; P-trend = 0.003) and trimers (HR: 0.91; 95% CI: 0.80, 1.04; P-trend = 0.07) but not for proanthocyanidins with a greater polymerization degree. Among the flavonol subclass, myricetin (HR: 0.77; 95% CI: 0.64, 0.93; P-trend = 0.001) was associated with a lower incidence of T2D. This large and heterogeneous European study showed inverse associations between all individual flavan-3-ol monomers, proanthocyanidins with a low polymerization degree, and the flavonol myricetin and incident T2D. These results suggest that individual flavonoids have different roles in the etiology of T2D.
PMCID: PMC3927546  PMID: 24368432
5.  Telomere length in blood and skeletal muscle in relation to measures of glycaemia and insulinaemia 
Skeletal muscle is a major metabolic organ and plays important roles in glucose metabolism, insulin sensitivity, and insulin action. Muscle telomere length reflects the myocyte's exposure to harmful environmental factors. Leukocyte telomere length is considered a marker of muscle telomere length and is used in epidemiologic studies to assess associations with ageing-related diseases where muscle physiology is important. However, the extent to which leucocyte telomere length and muscle telomere length are correlated is unknown, as are their relative correlations with glucose and insulin concentrations. The purpose of this study was to determine the extent of these relationships.
Leucocyte telomere length and muscle telomere length were measured by quantitative real-time PCR in participants from the Malmö Exercise Intervention (MEI; n=27) and the PPP-Botnia studies (n=31). Participants in both studies were free from type 2 diabetes. We assessed the association between leucocyte telomere length, muscle telomere length and metabolic traits using Spearmen correlations and multivariate linear regression. Bland-Altman analysis was used to assess agreement between leucocyte telomere length and muscle telomere length.
In age-, study-, diabetes family history- and sex-adjusted models, leucocyte telomere length and muscle telomere length were positively correlated (r=0.39, 95% CI: 0.15, 0.59). Leucocyte telomere length was inversely associated with 2hr glucose concentrations (r= -0.58, 95% CI: -1.0, -0.16), but there was no correlation between muscle telomere length and 2 hr glucose concentrations (r=0.05, 95% CI: -0.35, 0.46) or between leucocyte telomere length or muscle telomere length with other metabolic traits.
In summary, the current study supports the use of leucocyte telomere length as a proxy for muscle telomere length in epidemiological studies of type 2 diabetes aetiology.
PMCID: PMC3698879  PMID: 22747879
Leukocyte telomere length; muscle telomere length; cardiometabolic; type 2 diabetes; skeletal muscle physiology
6.  The Complex Interplay of Genetic and Lifestyle Risk Factors in Type 2 Diabetes: An Overview 
Scientifica  2012;2012:482186.
Type 2 diabetes (T2D) is one of the scourges of modern times, with many millions of people affected by the disease. Diabetes occurs most frequently in those who are overweight or obese. However, not all overweight and obese persons develop diabetes, and there are those who develop the disease who are lean and physically active. Certain ethnicities, especially indigenous populations, are at considerably higher risk of obesity and diabetes than those of white European ancestry. The patterns and distributions of diabetes have led some to speculate that the disease is caused by interactions between genetic and obesogenic lifestyle factors. Whilst to many this is a plausible explanation, remarkably little reliable evidence exists to support it. In this review, an overview of published literature relating to genetic and lifestyle risk factors for T2D is provided. The review also describes the concepts and rationale that have motivated the view that gene-lifestyle interactions cause diabetes and overviews the empirical evidence published to date to support this hypothesis.
PMCID: PMC3820646  PMID: 24278702
7.  Diabetes Family History: A Metabolic Storm You Should Not Sit Out 
Diabetes  2010;59(11):2732-2734.
PMCID: PMC2963529  PMID: 20980473
8.  Invited Commentary: Gene × Lifestyle Interactions and Complex Disease Traits—Inferring Cause and Effect From Observational Data, Sine Qua Non 
American Journal of Epidemiology  2010;172(9):992-997.
Observational epidemiology has made outstanding contributions to the discovery and elucidation of relations between lifestyle factors and common complex diseases such as type 2 diabetes. Recent major advances in the understanding of the human genetics of this disease have inspired studies that seek to determine whether the risk conveyed by bona fide risk loci might be modified by lifestyle factors such as diet composition and physical activity levels. A major challenge is to determine which of the reported findings are likely to represent causal interactions and which might be explained by other factors. The authors of this commentary use the Bradford-Hill criteria, a set of tried-and-tested guidelines for causal inference, to evaluate the findings of a recent study on interaction between variation at the cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) locus and total energy intake with respect to prevalent metabolic syndrome and hemoglobin A1c levels in a cohort of 313 Japanese men. The current authors conclude that the study, while useful for hypothesis generation, does not provide overwhelming evidence of causal interactions. They overview ways in which future studies of gene × lifestyle interactions might overcome the limitations that motivated this conclusion.
PMCID: PMC2984255  PMID: 20847104
CDKAL1 protein, human; energy intake; hemoglobin A1c protein, human; Japan; metabolic syndrome X
9.  The prospective association between total and type of fish intake and type 2 diabetes in 8 European countries: EPIC-InterAct Study123 
Background: Epidemiologic evidence of an association between fish intake and type 2 diabetes (T2D) is inconsistent and unresolved.
Objective: The objective was to examine the association between total and type of fish intake and T2D in 8 European countries.
Design: This was a case-cohort study, nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study, with 3.99 million person-years of follow-up, 12,403 incident diabetes cases, and a random subcohort of 16,835 individuals from 8 European countries. Habitual fish intake (lean fish, fatty fish, total fish, shellfish, and combined fish and shellfish) was assessed by country-specific dietary questionnaires. HRs were estimated in each country by using Prentice-weighted Cox regression models and pooled by using a random-effects meta-analysis.
Results: No overall association was found between combined fish and shellfish intake and incident T2D per quartile (adjusted HR: 1.00; 95% CI: 0.94, 1.06; P-trend = 0.99). Total fish, lean fish, and shellfish intakes separately were also not associated with T2D, but fatty fish intake was weakly inversely associated with T2D: adjusted HR per quartile 0.97 (0.94, 1.00), with an HR of 0.84 (0.70, 1.01), 0.85 (0.76, 0.95), and 0.87 (0.78, 0.97) for a comparison of the second, third, and fourth quartiles with the lowest quartile of intake, respectively (P-trend = 0.06).
Conclusions: These findings suggest that lean fish, total fish, and shellfish intakes are not associated with incident diabetes but that fatty fish intake may be weakly inversely associated. Replication of these findings in other populations and investigation of the mechanisms underlying these associations are warranted. Meanwhile, current public health recommendations on fish intake should remain unchanged.
PMCID: PMC3623039  PMID: 22572642
10.  Genetic Predictors of Weight Loss and Weight Regain After Intensive Lifestyle Modification, Metformin Treatment, or Standard Care in the Diabetes Prevention Program 
Diabetes Care  2012;35(2):363-366.
We tested genetic associations with weight loss and weight regain in the Diabetes Prevention Program, a randomized controlled trial of weight loss–inducing interventions (lifestyle and metformin) versus placebo.
Sixteen obesity-predisposing single nucleotide polymorphisms (SNPs) were tested for association with short-term (baseline to 6 months) and long-term (baseline to 2 years) weight loss and weight regain (6 months to study end).
Irrespective of treatment, the Ala12 allele at PPARG associated with short- and long-term weight loss (−0.63 and −0.93 kg/allele, P ≤ 0.005, respectively). Gene–treatment interactions were observed for short-term (LYPLAL1 rs2605100, Plifestyle*SNP = 0.032; GNPDA2 rs10938397, Plifestyle*SNP = 0.016; MTCH2 rs10838738, Plifestyle*SNP = 0.022) and long-term (NEGR1 rs2815752, Pmetformin*SNP = 0.028; FTO rs9939609, Plifestyle*SNP = 0.044) weight loss. Three of 16 SNPs were associated with weight regain (NEGR1 rs2815752, BDNF rs6265, PPARG rs1801282), irrespective of treatment. TMEM18 rs6548238 and KTCD15 rs29941 showed treatment-specific effects (Plifestyle*SNP < 0.05).
Genetic information may help identify people who require additional support to maintain reduced weight after clinical intervention.
PMCID: PMC3263869  PMID: 22179955
11.  Updated Genetic Score Based on 34 Confirmed Type 2 Diabetes Loci Is Associated With Diabetes Incidence and Regression to Normoglycemia in the Diabetes Prevention Program 
Diabetes  2011;60(4):1340-1348.
Over 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes–associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP).
We genotyped 34 type 2 diabetes–associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment.
In multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00–1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93–0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001).
A high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.
PMCID: PMC3064108  PMID: 21378175
12.  Age at Menopause, Reproductive Life Span, and Type 2 Diabetes Risk 
Diabetes Care  2013;36(4):1012-1019.
Age at menopause is an important determinant of future health outcomes, but little is known about its relationship with type 2 diabetes. We examined the associations of menopausal age and reproductive life span (menopausal age minus menarcheal age) with diabetes risk.
Data were obtained from the InterAct study, a prospective case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition. A total of 3,691 postmenopausal type 2 diabetic case subjects and 4,408 subcohort members were included in the analysis, with a median follow-up of 11 years. Prentice weighted Cox proportional hazards models were adjusted for age, known risk factors for diabetes, and reproductive factors, and effect modification by BMI, waist circumference, and smoking was studied.
Mean (SD) age of the subcohort was 59.2 (5.8) years. After multivariable adjustment, hazard ratios (HRs) of type 2 diabetes were 1.32 (95% CI 1.04–1.69), 1.09 (0.90–1.31), 0.97 (0.86–1.10), and 0.85 (0.70–1.03) for women with menopause at ages <40, 40–44, 45–49, and ≥55 years, respectively, relative to those with menopause at age 50–54 years. The HR per SD younger age at menopause was 1.08 (1.02–1.14). Similarly, a shorter reproductive life span was associated with a higher diabetes risk (HR per SD lower reproductive life span 1.06 [1.01–1.12]). No effect modification by BMI, waist circumference, or smoking was observed (P interaction all > 0.05).
Early menopause is associated with a greater risk of type 2 diabetes.
PMCID: PMC3609516  PMID: 23230098
13.  Genetic Predisposition to Long-Term Nondiabetic Deteriorations in Glucose Homeostasis 
Diabetes  2010;60(1):345-354.
To assess whether recently discovered genetic loci associated with hyperglycemia also predict long-term changes in glycemic traits.
Sixteen fasting glucose-raising loci were genotyped in middle-aged adults from the Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk (GLACIER) Study, a population-based prospective cohort study from northern Sweden. Genotypes were tested for association with baseline fasting and 2-h postchallenge glycemia (N = 16,330), and for changes in these glycemic traits during a 10-year follow-up period (N = 4,059).
Cross-sectional directionally consistent replication with fasting glucose concentrations was achieved for 12 of 16 variants; 10 variants were also associated with impaired fasting glucose (IFG) and 7 were independently associated with 2-h postchallenge glucose concentrations. In prospective analyses, the effect alleles at four loci (GCK rs4607517, ADRA2A rs10885122, DGKB-TMEM195 rs2191349, and G6PC2 rs560887) were nominally associated with worsening fasting glucose concentrations during 10-years of follow-up. MTNR1B rs10830963, which was predictive of elevated fasting glucose concentrations in cross-sectional analyses, was associated with a protective effect on postchallenge glucose concentrations during follow-up; however, this was only when baseline fasting and 2-h glucoses were adjusted for. An additive effect of multiple risk alleles on glycemic traits was observed: a weighted genetic risk score (80th vs. 20th centiles) was associated with a 0.16 mmol/l (P = 2.4 × 10−6) greater elevation in fasting glucose and a 64% (95% CI: 33–201%) higher risk of developing IFG during 10 years of follow-up.
Our findings imply that genetic profiling might facilitate the early detection of persons who are genetically susceptible to deteriorating glucose control; studies of incident type 2 diabetes and discrete cardiovascular end points will help establish whether the magnitude of these changes is clinically relevant.
PMCID: PMC3012192  PMID: 20870969
14.  Validity of Electronically Administered Recent Physical Activity Questionnaire (RPAQ) in Ten European Countries 
PLoS ONE  2014;9(3):e92829.
To examine the validity of the Recent Physical Activity Questionnaire (RPAQ) which assesses physical activity (PA) in 4 domains (leisure, work, commuting, home) during past month.
580 men and 1343 women from 10 European countries attended 2 visits at which PA energy expenditure (PAEE), time at moderate-to-vigorous PA (MVPA) and sedentary time were measured using individually-calibrated combined heart-rate and movement sensing. At the second visit, RPAQ was administered electronically. Validity was assessed using agreement analysis.
RPAQ significantly underestimated PAEE in women [median(IQR) 34.1 (22.1, 52.2) vs. 40.6 (32.4, 50.9) kJ/kg/day, 95%LoA: −44.4, 63.4 kJ/kg/day) and in men (43.7 (29.0, 69.0) vs. 45.5 (34.1, 57.6) kJ/kg/day, 95%LoA: −47.2, 101.3 kJ/kg/day]. Using individualised definition of 1MET, RPAQ significantly underestimated MVPA in women [median(IQR): 62.1 (29.4, 124.3) vs. 73.6 (47.8, 107.2) min/day, 95%LoA: −130.5, 305.3 min/day] and men [82.7 (38.8, 185.6) vs. 83.3 (55.1, 125.0) min/day, 95%LoA: −136.4, 400.1 min/day]. Correlations (95%CI) between subjective and objective estimates were statistically significant [PAEE: women, rho = 0.20 (0.15–0.26); men, rho = 0.37 (0.30–0.44); MVPA: women, rho = 0.18 (0.13–0.23); men, rho = 0.31 (0.24–0.39)]. When using non-individualised definition of 1MET (3.5 mlO2/kg/min), MVPA was substantially overestimated (∼30 min/day). Revisiting occupational intensity assumptions in questionnaire estimation algorithms with occupational group-level empirical distributions reduced median PAEE-bias in manual (25.1 kJ/kg/day vs. −9.0 kJ/kg/day, p<0.001) and heavy manual workers (64.1 vs. −4.6 kJ/kg/day, p<0.001) in an independent hold-out sample.
Relative validity of RPAQ-derived PAEE and MVPA is comparable to previous studies but underestimation of PAEE is smaller. Electronic RPAQ may be used in large-scale epidemiological studies including surveys, providing information on all domains of PA.
PMCID: PMC3965465  PMID: 24667343
15.  Evaluation of A2BP1 as an Obesity Gene 
Diabetes  2010;59(11):2837-2845.
A genome-wide association study (GWAS) in Pima Indians (n = 413) identified variation in the ataxin-2 binding protein 1 gene (A2BP1) that was associated with percent body fat. On the basis of this association and the obese phenotype of ataxin-2 knockout mice, A2BP1 was genetically and functionally analyzed to assess its potential role in human obesity.
Variants spanning A2BP1 were genotyped in a population-based sample of 3,234 full-heritage Pima Indians, 2,843 of whom were not part of the initial GWAS study and therefore could serve as a sample to assess replication. Published GWAS data across A2BP1 were additionally analyzed in French adult (n = 1,426) and children case/control subjects (n = 1,392) (Meyre et al. Nat Genet 2009;41:157–159). Selected variants were genotyped in two additional samples of Caucasians (Amish, n = 1,149, and German children case/control subjects, n = 998) and one additional Native American (n = 2,531) sample. Small interfering RNA was used to knockdown A2bp1 message levels in mouse embryonic hypothalamus cells.
No single variant in A2BP1 was reproducibly associated with obesity across the different populations. However, different variants within intron 1 of A2BP1 were associated with BMI in full-heritage Pima Indians (rs10500331, P = 1.9 × 10−7) and obesity in French Caucasian adult (rs4786847, P = 1.9 × 10−10) and children (rs8054147, P = 9.2 × 10−6) case/control subjects. Reduction of A2bp1 in mouse embryonic hypothalamus cells decreased expression of Atxn2, Insr, and Mc4r.
Association analysis suggests that variation in A2BP1 influences obesity, and functional studies suggest that A2BP1 could potentially affect adiposity via the hypothalamic MC4R pathway.
PMCID: PMC2963542  PMID: 20724578
16.  TCF7L2 Polymorphism, Weight Loss and Proinsulin∶Insulin Ratio in the Diabetes Prevention Program 
PLoS ONE  2011;6(7):e21518.
TCF7L2 variants have been associated with type 2 diabetes, body mass index (BMI), and deficits in proinsulin processing and insulin secretion. Here we sought to test whether these effects were apparent in high-risk individuals and modify treatment responses.
We examined the potential role of the TCF7L2 rs7903146 variant in predicting resistance to weight loss or a lack of improvement of proinsulin processing during 2.5-years of follow-up participants (N = 2,994) from the Diabetes Prevention Program (DPP), a randomized controlled trial designed to prevent or delay diabetes in high-risk adults.
We observed no difference in the degree of weight loss by rs7903146 genotypes. However, the T allele (conferring higher risk of diabetes) at rs7903146 was associated with higher fasting proinsulin at baseline (P<0.001), higher baseline proinsulin∶insulin ratio (p<0.0001) and increased proinsulin∶insulin ratio over a median of 2.5 years of follow-up (P = 0.003). Effects were comparable across treatment arms.
The combination of a lack of impact of the TCF7L2 genotypes on the ability to lose weight, but the presence of a consistent effect on the proinsulin∶insulin ratio over the course of DPP, suggests that high-risk genotype carriers at this locus can successfully lose weight to counter diabetes risk despite persistent deficits in insulin production.
PMCID: PMC3144193  PMID: 21814547
17.  Obesity Genotype Score and Cardiovascular Risk in Women with Type 2 Diabetes 
To investigate the associations between obesity-predisposing genetic variants, cardiovascular biomarkers, and cardiovascular disease (CVD) risk in women with preexisting type 2 diabetes.
Methods and Results
We genotyped polymorphisms at nine established obesity loci in 1,395 women with diabetes from the Nurses’ Health Study; 449 of these women developed CVD and 946 did not. A genetic risk score (GRS) was derived by summing risk alleles for each individual. Four polymorphisms, rs9939609 (FTO), rs11084753 (KCTD15), rs10838738 (MTCH2), and rs10938397 (GNPDA2), showed nominally significant associations with CVD. The GRS combining all obesity loci was linearly related to CVD risk (P for trend = 0.013). The OR was 1.08 per risk allele (95% CI: 1.02–1.15; P = 0.01) after adjustment for BMI and other conventional risk factors. Women with the highest quartile of GRS had 53% (6% – 122%) increased CVD risk, compared with those in the lowest quartile (P = 0.024). In addition, higher GRS was associated with lower adiponectin levels (P = 0.02). Further adjustment for BMI and other covariates did not change the association (P = 0.006). Higher GRS was also correlated with lower levels of HDL (P= 0.01).
Obesity-predisposing variants may jointly affect CVD risk among women with diabetes.
PMCID: PMC3061473  PMID: 19910641
Cardiovascular disease; type 2 diabetes; obesity gene; polymorphism
18.  Detailed Investigation of the Role of Common and Low-Frequency WFS1 Variants in Type 2 Diabetes Risk 
Diabetes  2009;59(3):741-746.
Wolfram syndrome 1 (WFS1) single nucleotide polymorphisms (SNPs) are associated with risk of type 2 diabetes. In this study we aimed to refine this association and investigate the role of low-frequency WFS1 variants in type 2 diabetes risk.
For fine-mapping, we sequenced WFS1 exons, splice junctions, and conserved noncoding sequences in samples from 24 type 2 diabetic case and 68 control subjects, selected tagging SNPs, and genotyped these in 959 U.K. type 2 diabetic case and 1,386 control subjects. The same genomic regions were sequenced in samples from 1,235 type 2 diabetic case and 1,668 control subjects to compare the frequency of rarer variants between case and control subjects.
Of 31 tagging SNPs, the strongest associated was the previously untested 3′ untranslated region rs1046320 (P = 0.008); odds ratio 0.84 and P = 6.59 × 10−7 on further replication in 3,753 case and 4,198 control subjects. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2 = 0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (minor allele frequency [MAF] <0.01) nonsynonymous variants between type 2 diabetic case and control subjects (P = 0.79). Two intermediate frequency (MAF 0.01–0.05) nonsynonymous changes also showed no statistical association with type 2 diabetes.
We identified six highly correlated SNPs that show strong and comparable associations with risk of type 2 diabetes, but further refinement of these associations will require large sample sizes (>100,000) or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on type 2 diabetes risk in white U.K. populations, highlighting the complexities of undertaking association studies with low-frequency variants identified by resequencing.
PMCID: PMC2828659  PMID: 20028947
19.  Detailed investigation of the role of common and low frequency WFS1 variants in type 2 diabetes risk 
Diabetes  2009;59(3):741-746.
WFS1 (Wolfram Syndrome 1) SNPs are associated with risk of type 2 diabetes (T2D). Here, we aimed to refine this association and investigate the role of low frequency WFS1 variants in T2D risk.
For fine-mapping, we sequenced WFS1 exons, splice junctions and conserved non-coding sequences in 24 T2D cases and 68 controls, selected tagging SNPs, and genotyped these in 959 UK T2D cases and 1386 controls. The same genomic regions were sequenced in 1235 T2D cases and 1668 controls to compare the frequency of rarer variants between cases and controls.
Of 31 tagging SNPs, the strongest associated was the previously untested 3′ UTR rs1046320 (P=0.008); OR=0.84, P=6.59 × 10−7 on further replication in 3753 cases and 4198 controls. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2=0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (MAF<0.01) non-synonymous variants between T2D cases and controls (P=0.79). Two intermediate frequency (MAF 0.01-0.05) non-synonymous changes also showed no statistical association with T2D.
We identified six highly correlated SNPs that show strong and comparable associations with risk of T2D association but further refinement of these associations will require large sample sizes (>100,000), or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on T2D risk in white UK populations, highlighting the complexities of undertaking association studies with low frequency variants identified by re-sequencing.
PMCID: PMC2828659  PMID: 20028947
20.  In search of quality evidence for lifestyle management and glycemic control in children and adolescents with type 2 diabetes: A systematic review 
BMC Pediatrics  2010;10:97.
Our purpose was to evaluate the impact of lifestyle behavior modification on glycemic control among children and youth with clinically defined Type 2 Diabetes (T2D).
We conducted a systematic review of studies (randomized trials, quasi-experimental studies) evaluating lifestyle (diet and/or physical activity) modification and glycemic control (HbA1c). Our data sources included bibliographic databases (EMBASE, CINAHL®, Cochrane Library, Medline®, PASCAL, PsycINFO®, and Sociological Abstracts), manual reference search, and contact with study authors. Two reviewers independently selected studies that included any intervention targeting diet and/or physical activity alone or in combination as a means to reduce HbA1c in children and youth under the age of 18 with T2D.
Our search strategy generated 4,572 citations. The majority of citations were not relevant to the study objective. One study met inclusion criteria. In this retrospective study, morbidly obese youth with T2D were treated with a very low carbohydrate diet. This single study received a quality index score of < 11, indicating poor study quality and thus limiting confidence in the study's conclusions.
There is no high quality evidence to suggest lifestyle modification improves either short- or long-term glycemic control in children and youth with T2D. Additional research is clearly warranted to define optimal lifestyle behaviour strategies for young people with T2D.
PMCID: PMC3016367  PMID: 21182791
21.  Epigenetics and obesity: the devil is in the details 
BMC Medicine  2010;8:88.
Obesity is a complex disease with multiple well-defined risk factors. Nevertheless, susceptibility to obesity and its sequelae within obesogenic environments varies greatly from one person to the next, suggesting a role for gene × environment interactions in the etiology of the disorder. Epigenetic regulation of the human genome provides a putative mechanism by which specific environmental exposures convey risk for obesity and other human diseases and is one possible mechanism that underlies the gene × environment/treatment interactions observed in epidemiological studies and clinical trials. A study published in BMC Medicine this month by Wang et al. reports on an examination of DNA methylation in peripheral blood leukocytes of lean and obese adolescents, comparing methylation patterns between the two groups. The authors identified two genes that were differentially methylated, both of which have roles in immune function. Here we overview the findings from this study in the context of those emerging from other recent genetic and epigenetic studies, discuss the strengths and weaknesses of the study and speculate on the future of epigenetics in chronic disease research.
See research article:
PMCID: PMC3019199  PMID: 21176136
22.  Childhood Obesity, Other Cardiovascular Risk Factors, and Premature Death 
The New England journal of medicine  2010;362(6):485-493.
The effect of childhood risk factors for cardiovascular disease on adult mortality is poorly understood.
In a cohort of 4857 American Indian children without diabetes (mean age, 11.3 years; 12,659 examinations) who were born between 1945 and 1984, we assessed whether body-mass index (BMI), glucose tolerance, and blood pressure and cholesterol levels predicted premature death. Risk factors were standardized according to sex and age. Proportional-hazards models were used to assess whether each risk factor was associated with time to death occurring before 55 years of age. Models were adjusted for baseline age, sex, birth cohort, and Pima or Tohono O'odham Indian heritage.
There were 166 deaths from endogenous causes (3.4% of the cohort) during a median follow-up period of 23.9 years. Rates of death from endogenous causes among children in the highest quartile of BMI were more than double those among children in the lowest BMI quartile (incidence-rate ratio, 2.30; 95% confidence interval [CI], 1.46 to 3.62). Rates of death from endogenous causes among children in the highest quartile of glucose intolerance were 73% higher than those among children in the lowest quartile (incidence-rate ratio, 1.73; 95% CI, 1.09 to 2.74). No significant associations were seen between rates of death from endogenous or external causes and childhood cholesterol levels or systolic or diastolic blood-pressure levels on a continuous scale, although childhood hypertension was significantly associated with premature death from endogenous causes (incidence-rate ratio, 1.57; 95% CI, 1.10 to 2.24).
Obesity, glucose intolerance, and hypertension in childhood were strongly associated with increased rates of premature death from endogenous causes in this population. In contrast, childhood hypercholesterolemia was not a major predictor of premature death from endogenous causes.
PMCID: PMC2958822  PMID: 20147714
23.  Previously Associated Type 2 Diabetes Variants May Interact With Physical Activity to Modify the Risk of Impaired Glucose Regulation and Type 2 Diabetes 
Diabetes  2009;58(6):1411-1418.
Recent advances in type 2 diabetes genetics have culminated in the discovery and confirmation of multiple risk variants. Two important and largely unanswered questions are whether this information can be used to identify individuals most susceptible to the adverse consequences of sedentary behavior and to predict their response to lifestyle intervention; such evidence would be mechanistically informative and provide a rationale for targeting genetically susceptible subgroups of the population.
Gene × physical activity interactions were assessed for 17 polymorphisms in a prospective population-based cohort of initially nondiabetic middle-aged adults. Outcomes were 1) impaired glucose regulation (IGR) versus normal glucose regulation determined with either fasting or 2-h plasma glucose concentrations (n = 16,003), 2) glucose intolerance (in mmol/l, n = 8,860), or 3) incident type 2 diabetes (n = 2,063 events).
Tests of gene × physical activity interactions on IGR risk for 3 of the 17 polymorphisms were nominally statistically significant:CDKN2A/B rs10811661 (Pinteraction = 0.015), HNF1B rs4430796 (Pinteraction = 0.026), and PPARG rs1801282 (Pinteraction = 0.04). Consistent interactions were observed for the CDKN2A/B (Pinteraction = 0.013) and HNF1B (Pinteraction = 0.0009) variants on 2-h glucose concentrations. Where type 2 diabetes was the outcome, only one statistically significant interaction effect was observed, and this was for the HNF1B rs4430796 variant (Pinteraction = 0.0004). The interaction effects for HNF1B on IGR risk and incident diabetes remained significant after correction for multiple testing (Pinteraction = 0.015 and 0.0068, respectively).
Our observations suggest that the genetic predisposition to hyperglycemia is partially dependent on a person's lifestyle.
PMCID: PMC2682680  PMID: 19324937
24.  Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program 
Diabetes  2008;57(9):2503-2510.
OBJECTIVE— Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and response to preventive interventions in 3,548 subjects at high risk of type 2 diabetes enrolled in the Diabetes Prevention Program (DPP), which examined the effects of lifestyle intervention, metformin, and troglitazone versus placebo.
RESEARCH DESIGN AND METHODS— We genotyped selected single nucleotide polymorphisms (SNPs) in or near diabetes-associated loci, including EXT2, CDKAL1, CDKN2A/B, IGF2BP2, HHEX, LOC387761, and SLC30A8 in DPP participants and performed Cox regression analyses using genotype, intervention, and their interactions as predictors of diabetes incidence. We evaluated their effect on insulin resistance and secretion at 1 year.
RESULTS— None of the selected SNPs were associated with increased diabetes incidence in this population. After adjustments for ethnicity, baseline insulin secretion was lower in subjects with the risk genotype at HHEX rs1111875 (P = 0.01); there were no significant differences in baseline insulin sensitivity. Both at baseline and at 1 year, subjects with the risk genotype at LOC387761 had paradoxically increased insulin secretion; adjustment for self-reported ethnicity abolished these differences. In ethnicity-adjusted analyses, we noted a nominal differential improvement in β-cell function for carriers of the protective genotype at CDKN2A/B after 1 year of troglitazone treatment (P = 0.01) and possibly lifestyle modification (P = 0.05).
CONCLUSIONS— We were unable to replicate the GWAS findings regarding diabetes risk in the DPP. We did observe genotype associations with differences in baseline insulin secretion at the HHEX locus and a possible pharmacogenetic interaction at CDKNA2/B.
PMCID: PMC2518503  PMID: 18544707
25.  Habitual Energy Expenditure Modifies the Association Between NOS3 Gene Polymorphisms and Blood Pressure 
American journal of hypertension  2008;21(3):297-302.
The endothelial nitric-oxide synthase (NOS3) gene encodes the enzyme (eNOS) that synthesizes the molecule nitric oxide, which facilitates endothelium-dependent vasodilation in response to physical activity. Thus, energy expenditure may modify the association between the genetic variation at NOS3 and blood pressure.
To test this hypothesis, we genotyped 11 NOS3 polymorphisms, capturing all common variations, in 726 men and women from the Medical Research Council (MRC) Ely Study (age (mean ± s.d.): 55 ± 10 years, body mass index: 26.4 ± 4.1 kg/m2). Habitual/non-resting energy expenditure (NREE) was assessed via individually calibrated heart rate monitoring over 4 days.
The intronic variant, IVS25+15 [G→A], was significantly associated with blood pressure; GG homozygotes had significantly lower levels of diastolic blood pressure (DBP) (−2.8 mm Hg; P = 0.016) and systolic blood pressure (SBP) (−1.9 mm Hg; P = 0.018) than A-allele carriers. The interaction between NREE and IVS25+15 was also significant for both DBP (P = 0.006) and SBP (P = 0.026), in such a way that the effect of the GG-genotype on blood pressure was stronger in individuals with higher NREE (DBP: −4.9 mm Hg, P = 0.02. SBP: −3.8 mm Hg, P = 0.03 for the third tertile). Similar results were observed when the outcome was dichotomously defined as hypertension.
In summary, the NOS3 IVS25+15 is directly associated with blood pressure and hypertension in white Europeans. However, the associations are most evident in the individuals with the highest NREE. These results need further replication and have to be ideally tested in a trial before being informative for targeted disease prevention. Eventually, the selection of individuals for lifestyle intervention programs could be guided by knowledge of genotype.
PMCID: PMC2714087  PMID: 18246059

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