Person:

Meigs, James

OBJECTIVE: Whether nicotine leads to a persistent increase in blood glucose levels is not clear. Our objective was to assess the relationship between cotinine, a nicotine metabolite, and glycated hemoglobin (Hb(A_{1c})), an index of recent glycemia. RESEARCH DESIGN AND METHODS: We used cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2008. We limited our analysis to 17,287 adults without diabetes. We created three cotinine categories: <0.05 ng/mL, 0.05–2.99 ng/mL, and ≥3 ng/mL. RESULTS: Using self-report, 25% of the sample were current smokers, 24% were former smokers, and 51% were nonsmokers. Smokers had a higher mean Hb(A_{1c}) (5.36% ± 0.01 SE) compared with never smokers (5.31% ± 0.01) and former smokers (5.31% ± 0.01). In a similar manner, mean Hb(A_{1c}) was higher among participants with cotinine ≥3 ng/mL (5.35% ± 0.01) and participants with cotinine 0.05–2.99 ng/mL (5.34% ± 0.01) compared with participants with cotinine <0.05 ng/mL (5.29% ± 0.01). In multivariable-adjusted analysis, we found that both a cotinine ≥3 ng/mL and self-reported smoking were associated with higher Hb(A_{1c}) compared with a cotinine <0.05 ng/mL or not smoking. People with a cotinine level ≥3 ng/mL had a relative 5% increase in Hb(A_{1c}) compared with people with a cotinine level <0.05 ng/mL, and smokers had a relative 7% increase in Hb(A_{1c}) compared with never smokers. CONCLUSIONS: Our study suggests that cotinine is associated with increased Hb(A_{1c}) in a representative sample of the U.S. population without diabetes.

Objective: 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). Research Design and Methods: 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. Results: 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 (\beta)-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). Conclusions: 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.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = (4.5×10^{−8}–1.2×10^{−43})). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<(3×10^{−4})). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = (4.3×10^{−3}), n = 22,044), increased triglycerides (p = (2.6×10^{−14}), n = 93,440), increased waist-to-hip ratio (p = (1.8×10^{−5}), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = (4.4×10^{−3}), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = (4.5×10^{−13}), n = 96,748) and decreased BMI (p = (1.4×10^{−4}), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

OBJECTIVE: To test the association of family history of diabetes with the adoption of diabetes risk–reducing behaviors and whether this association is strengthened by physician advice or commonly known factors associated with diabetes risk. RESEARCH DESIGN AND METHODS: We used cross-sectional data from the 2005–2008 National Health and Nutrition Examination Survey (NHANES) to examine the effects of family history of diabetes on the adoption of selected risk-reducing behaviors in 8,598 adults (aged ≥20 years) without diabetes. We used multiple logistic regression to model three risk reduction behaviors (controlling or losing weight, increasing physical activity, and reducing the amount of dietary fat or calories) with family history of diabetes. RESULTS: Overall, 36.2% of U.S. adults without diabetes had a family history of diabetes. Among them, ~39.8% reported receiving advice from a physician during the past year regarding any of the three selected behaviors compared with 29.2% of participants with no family history (P < 0.01). In univariate analysis, adults with a family history of diabetes were more likely to perform these risk-reducing behaviors compared with adults without a family history. Physician advice was strongly associated with each of the behavioral changes (P < 0.01), and this did not differ by family history of diabetes. CONCLUSIONS: Familial risk for diabetes and physician advice both independently influence the adoption of diabetes risk–reducing behaviors. However, fewer than half of participants with familial risk reported receiving physician advice for adopting these behaviors.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Aims/hypothesis: The purpose of this study was to examine the association between urbanisation-related factors and diabetes prevalence in China. Methods: Anthropometry, fasting blood glucose (FBG) and community-level data were collected for 7,741 adults (18–90 years) across 217 communities and nine provinces in the 2009 China Health and Nutrition Survey to examine diabetes (FBG ≥7.0 mmol/l or doctor diagnosis). Sex-stratified multilevel models, clustered at the community and province levels and controlling for individual-level age and household income were used to examine the association between diabetes and: (1) a multicomponent urbanisation measure reflecting overall modernisation and (2) 12 separate components of urbanisation (e.g., population density, employment, markets, infrastructure and social factors). Results: Prevalent diabetes was higher in more-urbanised (men 12%; women 9%) vs less-urbanised (men 6%; women 5%) areas. In sex-stratified multilevel models adjusting for residential community and province, age and household income, there was a twofold higher diabetes prevalence in urban vs rural areas (men OR 2.02, 95% CI 1.47, 2.78; women, OR 1.94, 95% CI 1.35, 2.79). All urbanisation components were positively associated with diabetes, with variation across components (e.g. men, economic and income diversity, OR 1.42, 95% CI 1.20, 1.66; women, transportation infrastructure, OR 1.18, 95% CI 1.06, 1.32). Community-level variation in diabetes was comparatively greater for women (intraclass correlation [ICC] 0.03–0.05) vs men (ICC ≤0.01); province-level variation was greater for men (men 0.03–0.04; women 0.02). Conclusions/interpretation: Diabetes prevention and treatment efforts are needed particularly in urbanised areas of China. Community economic factors, modern markets, communications and transportation infrastructure might present opportunities for such efforts. Electronic supplementary material The online version of this article (doi:10.1007/s00125-012-2697-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

Background: Circulating progenitor cells (CPC) contribute to the homeostasis of the vessel wall, and a reduced CPC count predicts cardiovascular morbidity and mortality. We tested the hypothesis that CPC count improves cardiovascular risk stratification and that this is modulated by low-grade inflammation. Methodology/Principal Findings: We pooled data from 4 longitudinal studies, including a total of 1,057 patients having CPC determined and major adverse cardiovascular events (MACE) collected. We recorded cardiovascular risk factors and high-sensitive C-reactive protein (hsCRP) level. Risk estimates were derived from Cox proportional hazard analyses. CPC count and/or hsCRP level were added to a reference model including age, sex, cardiovascular risk factors, prevalent CVD, chronic renal failure (CRF) and medications. The sample was composed of high-risk individuals, as 76.3% had prevalent CVD and 31.6% had CRF. There were 331 (31.3%) incident MACE during an average 1.7±1.1 year follow-up time. CPC count was independently associated with incident MACE even after correction for hsCRP. According to C-statistics, models including CPC yielded a non-significant improvement in accuracy of MACE prediction. However, the integrated discrimination improvement index (IDI) showed better performance of models including CPC compared to the reference model and models including hsCRP in identifying MACE. CPC count also yielded significant net reclassification improvements (NRI) for CV death, non-fatal AMI and other CV events. The effect of CPC was independent of hsCRP, but there was a significant more-than-additive interaction between low CPC count and raised hsCRP level in predicting incident MACE. Conclusions/Significance: In high risk individuals, a reduced CPC count helps identifying more patients at higher risk of MACE over the short term, especially in combination with a raised hsCRP level.

Objective: Vitamin K has a potentially beneficial role in insulin resistance, but evidence is limited in humans. We tested the hypothesis that vitamin K supplementation for 36 months will improve insulin resistance in older men and women. Research Design and Methods: This was an ancillary study of a 36-month, randomized, double-blind, controlled trial designed to assess the impact of supplementation with 500 μg/day phylloquinone on bone loss. Study participants were older nondiabetic men and women (n = 355; aged 60–80 years; 60% women). The primary outcome of this study was insulin resistance as measured by homeostasis model assessment (HOMA-IR) at 36 months. Fasting plasma insulin and glucose were examined as the secondary outcomes. Results: The effect of 36-month vitamin K supplementation on HOMA-IR differed by sex (sex × treatment interaction P = 0.02). HOMA-IR was statistically significantly lower at the 36-month visit among men in the supplement group versus the men in the control group (P = 0.01) after adjustment for baseline HOMA-IR, BMI, and body weight change. There were no statistically significant differences in outcome measures between intervention groups in women. Conclusions: Vitamin K supplementation for 36 months at doses attainable in the diet may reduce progression of insulin resistance in older men.

OBJECTIVE—To examine perceived risk of developing diabetes in primary care patients. RESEARCH DESIGN AND METHODS—We recruited 150 nondiabetic primary care patients. We made standard clinical measurements, collected fasting blood samples, and used the validated Risk Perception Survey for Developing Diabetes questionnaire. RESULTS—Patients with high perceived risk were more likely than those with low perceived risk to have a family history of diabetes (68 vs. 18%; P < 0.0001) and to have metabolic syndrome (53 vs. 35%; P = 0.04). However, patients with high perceived risk were not more likely to have intentions to adopt healthier lifestyle in the coming year (high 26.0% vs. low 29.2%; P = 0.69). CONCLUSIONS—Primary care patients with higher perceived risk of diabetes were at higher actual risk but did not express greater intention to adopt healthier lifestyles. Aspects of health behavior theory other than perceived risk need to be explored to help target efforts in the primary prevention of diabetes.