Association of rs780094 in \u3ci\u3eGCKR\u3c/i\u3e with Metabolic Traits and Incident Diabetes and Cardiovascular Disease: The ARIC Study

Objective: The minor T-allele of rs780094 in the glucokinase regulator gene (GCKR) associates with a number of metabolic traits including higher triglyceride levels and improved glycemic regulation in study populations of mostly European ancestry. Using data from the Atherosclerosis Risk in Communities (ARIC) Study, we sought to replicate these findings, examine them in a large population-based sample of African American study participants, and to investigate independent associations with other metabolic traits in order to determine if variation in GKCR contributes to their observed clustering. In addition, we examined the association of rs780094 with incident diabetes, coronary heart disease (CHD), and stroke over up mean follow-up times of 8, 15, and 15 years, respectively. Research Design and Methods: Race-stratified analyses were conducted among 10,929 white and 3,960 black participants aged 45–64 at baseline assuming an additive genetic model and using linear and logistic regression and Cox proportional hazards models. Results: Previous findings replicated among white participants in multivariable adjusted models: the T-allele of rs780094 was associated with lower fasting glucose (p = 10-7) and insulin levels (p = 10-6), lower insulin resistance (HOMA-IR, p=10-9), less prevalent diabetes (p = 10-6), and higher CRP (p = 10-8), 2-h postprandial glucose (OGTT, p = 10-6), and triglyceride levels (p = 10-31). Moreover, the T-allele was independently associated with higher HDL cholesterol levels (p = 0.022), metabolic syndrome prevalence (p = 0.043), and lower beta-cell function measured as HOMA-B (p = 0.011). Among black participants, the T-allele was associated only with higher triglyceride levels (p = 0.004) and lower insulin levels (p = 0.002) and HOMA-IR (p = 0.013). Prospectively, the T-allele was associated with reduced incidence of diabetes (p = 10-4) among white participants, but not with incidence of CHD or stroke. Conclusions: Our findings indicate rs780094 has independent associations with multiple metabolic traits as well as incident diabetes, but not incident CHD or stroke. The magnitude of association between the SNP and most traits was of lower magnitude among African American compared to white participants

The association of α-fibrinogen Thr312Ala polymorphism and venous thromboembolism in the LITE study

The α-fibrinogen Thr312Ala variant has been shown to influence clot structure through increased factor XIII cross-linking and formation of thicker fibrin fibers. However, the effect of this common variant on risk of venous thromboembolism (VTE) is unclear. This paper reports the association between the Thr312Ala variant and VTE in the LITE study

Strength of Association for Incident Diabetes Risk Factors According to Diabetes Case Definitions: The Atherosclerosis Risk in Communities Study

Prospective epidemiologic studies have characterized major risk factors for incident diabetes by a variety of diabetes case definitions. Whether different definitions alter the association of diabetes with risk factors is largely unknown. Using 1987–1998 data from the ongoing Atherosclerosis Risk in Communities (ARIC) Study, the authors assessed the relation of traditional risk factors with 3 different diabetes case definitions and 4 fasting glucose categories. They compared the study protocol case definition with 2 nested case definitions, self-reported diabetes and a multiple-evidence definition. Significant differences in risk factor associations by case definition and by screening cutpoints were observed. Specifically, the magnitude of the association between the risk factors (baseline metabolic syndrome, fasting glucose, blood pressure, body mass index, and serum insulin) and incident diabetes differed by case definition. Associations with these risk factors were weaker with a case definition based on self-report compared with other definitions. These results illustrate the potential limitations of case definitions that rely solely on self-report or those that incorporate measured glucose values to ascertain undiagnosed cases. Although the ability to identify risk factors of diabetes was consistent for the case definitions studied, tests of novel risk factors may result in different estimates of effect sizes depending on the definition used

Impact of repeated measures and sample selection on genome-wide association studies of fasting glucose

Although GWAS have been performed in longitudinal studies, most used only a single trait measure. GWAS of fasting glucose have generally included only normoglycemic individuals. We examined the impact of both repeated measures and sample selection on GWAS in ARIC, a study which obtained four longitudinal measures of fasting glucose and included both individuals with and without prevalent diabetes. The sample included Caucasians and the Affymetrix 6.0 chip was used for genotyping. Sample sizes for GWAS analyses ranged from 8372 (first study visit) to 5782 (average fasting glucose). Candidate SNP analyses with SNPs identified through fasting glucose or diabetes GWAS were conducted in 9133 individuals, including 761 with prevalent diabetes. For a constant sample size, smaller p-values were obtained for the average measure of fasting glucose compared to values at any single visit, and two additional significant GWAS signals were detected. For four candidate SNPs (rs780094, rs10830963, rs7903146, and rs4607517), the strength of association between genotype and glucose was significantly (p-interaction < .05) different in those with and without prevalent diabetes and for all five fasting glucose candidate SNPs (rs780094, rs10830963, rs560887, rs4607517, rs13266634) the association with measured fasting glucose was more significant in the smaller sample without prevalent diabetes than in the larger combined sample of those with and without diabetes. This analysis demonstrates the potential utility of averaging trait values in GWAS studies and explores the advantage of using only individuals without prevalent diabetes in GWAS of fasting glucose

Association of comorbidity burden with abnormal cardiac mechanics: Findings from the HyperGEN study

BACKGROUND: Comorbidities are common in heart failure (HF), and the number of comorbidities has been associated with poor outcomes in HF patients. However, little is known about the effect of multiple comorbidities on cardiac mechanics, which could impact the pathogenesis of HF. We sought to determine the relationship between comorbidity burden and adverse cardiac mechanics. METHODS AND RESULTS: We performed speckle‐tracking analysis on echocardiograms from the HyperGEN study (n=2150). Global longitudinal, circumferential, and radial strain, and early diastolic (e') tissue velocities were measured. We evaluated the association between comorbidity number and cardiac mechanics using linear mixed effects models to account for relatedness among subjects. The mean age was 51±14 years, 58% were female, and 47% were African American. Dyslipidemia and hypertension were the most common comorbidities (61% and 58%, respectively). After adjusting for left ventricular (LV) mass index, ejection fraction, and several potential confounders, the number of comorbidities remained associated with all indices of cardiac mechanics except global circumferential strain (eg, β=−0.32 [95% CI −0.44, −0.20] per 1‐unit increase in number of comorbidities for global longitudinal strain; β=−0.16 [95% CI −0.20, −0.11] for e' velocity; P≤0.0001 for both comparisons). Results were similar after excluding participants with abnormal LV geometry (P<0.05 for all comparisons). CONCLUSIONS: Higher comorbidity burden is associated with worse cardiac mechanics, even in the presence of normal LV geometry. The deleterious effect of multiple comorbidities on cardiac mechanics may explain both the high comorbidity burden and adverse outcomes in patients who ultimately develop HF

Insulin Resistance Exacerbates Genetic Predisposition to Nonalcoholic Fatty Liver Disease in Individuals Without Diabetes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/1/hep41353.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/2/hep41353_am.pd

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them

Transferability and Fine Mapping of Type 2 Diabetes Loci in African Americans: The Candidate Gene Association Resource Plus Study

Type 2 diabetes (T2D) disproportionally affects African Americans (AfA) but, to date, genetic variants identified from genome-wide association studies (GWAS) are primarily from European and Asian populations. We examined the single nucleotide polymorphism (SNP) and locus transferability of 40 reported T2D loci in six AfA GWAS consisting of 2,806 T2D case subjects with or without end-stage renal disease and 4,265 control subjects from the Candidate Gene Association Resource Plus Study. Our results revealed that seven index SNPs at the TCF7L2, KLF14, KCNQ1, ADCY5, CDKAL1, JAZF1, and GCKR loci were significantly associated with T2D (P < 0.05). The strongest association was observed at TCF7L2 rs7903146 (odds ratio [OR] 1.30; P = 6.86 × 10−8). Locus-wide analysis demonstrated significant associations (Pemp < 0.05) at regional best SNPs in the TCF7L2, KLF14, and HMGA2 loci as well as suggestive signals in KCNQ1 after correction for the effective number of SNPs at each locus. Of these loci, the regional best SNPs were in differential linkage disequilibrium (LD) with the index and adjacent SNPs. Our findings suggest that some loci discovered in prior reports affect T2D susceptibility in AfA with similar effect sizes. The reduced and differential LD pattern in AfA compared with European and Asian populations may facilitate fine mapping of causal variants at loci shared across populations

Impact of Common Variation in Bone-Related Genes on Type 2 Diabetes and Related Traits

Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations