Big Data Transforms Discovery-Utilization Therapeutics Continuum.

Enabling omic technologies adopt a holistic view to produce unprecedented insights into the molecular underpinnings of health and disease, in part, by generating massive high-dimensional biological data. Leveraging these systems-level insights as an engine driving the healthcare evolution is maximized through integration with medical, demographic, and environmental datasets from individuals to populations. Big data analytics has accordingly emerged to add value to the technical aspects of storage, transfer, and analysis required for merging vast arrays of omic-, clinical-, and eco-datasets. In turn, this new field at the interface of biology, medicine, and information science is systematically transforming modern therapeutics across discovery, development, regulation, and utilization

Genetic Architecture of Plasma Adiponectin Overlaps With the Genetics of Metabolic Syndrome–Related Traits

OBJECTIVE - Adiponectin, a hormone secreted by adipose tissue, is of particular interest in metabolic syndrome, because it is inversely correlated with obesity and insulin sensitivity. However, it is not known to what extent the genetics of plasma adiponectin and the genetics of obesity and insulin sensitivity are interrelated. We aimed to evaluate the heritability of plasma adiponectin and its genetic correlation with the metabolic syndrome and metabolic syndrome-related traits and the association between these traits and 10 ADIPOQ single nucleotide polymorphisms (SNPs). RESEARCH DESIGN AND METHODS - We made use of a family-based population, the Erasmus Rucphen Family study (1,258 women and 967 men). Heritability analysis was performed using a polygenic model. Genetic correlations were estimated using bivariate heritability analyses. Genetic association analysis was performed using a mixed model. RESULTS - Plasma adiponectin showed a heritability of 55.1%. Genetic correlations between plasma adiponectin HDL cholesterol and plasma insulin ranged from 15 to 24% but were not significant for fasting glucose, triglycerides, blood pressure, homeostasis model assessment of insulin resistance (HOMA-IR), and C-reactive protein. A significant association with plasma adiponectin was found for ADIPOQ variants rs17300539 and rs182052. A nominally significant association was found with plasma insulin and HOMA-IR and ADIPOQ variant rs17300539 after adjustment for plasma adiponectin. CONCLUSIONS - The significant genetic correlation between plasma adiponectin and HDL cholesterol and plasma insulin should be taken into account in the interpretation of genome-wide association studies. Association of ADIPOQ SNPs with plasma adiponectin was replicated, and we showed association between one ADIPOQ SNP and plasma insulin and HOMA-IR

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

Association of a Fasting Glucose Genetic Risk Score With Subclinical Atherosclerosis: The Atherosclerosis Risk in Communities (ARIC) Study

Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT. The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually. The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third. The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways

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

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

Polygenic type 2 diabetes prediction at the limit of common variant detection.

Genome-wide association studies (GWAS) may have reached their limit of detecting common type 2 diabetes (T2D)-associated genetic variation. We evaluated the performance of current polygenic T2D prediction. Using data from the Framingham Offspring (FOS) and the Coronary Artery Risk Development in Young Adults (CARDIA) studies, we tested three hypotheses: 1) a 62-locus genotype risk score (GRSt) improves T2D prediction compared with previous less inclusive GRSt; 2) separate GRS for \u3b2-cell (GRS\u3b2) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRS\u3b2, or GRSIR do not differ between blacks and whites. Among 1,650 young white adults in CARDIA, 820 young black adults in CARDIA, and 3,471 white middle-aged adults in FOS, cumulative T2D incidence was 5.9%, 14.4%, and 12.9%, respectively, over 25 years. The 62-locus GRSt was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRSt improved the model C statistic (0.698 and 0.726 for models without and with GRSt, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRS\u3b2 but not GRSIR predicted incident T2D among FOS and CARDIA whites. At the end of the era of common variant discovery for T2D, polygenic scores can predict T2D in whites and blacks but do not outperform clinical models. Further optimization of polygenic prediction may require novel analytic methods, including less common as well as functional variants

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

Overweight across the life course and adipokines, inflammatory and endothelial markers at age 60-64 years: evidence from the 1946 birth cohort.

BACKGROUND/OBJECTIVES: There is growing evidence that early development of obesity increases cardiovascular risk later in life, but less is known about whether there are effects of long-term excess body weight on the biological drivers associated with the atherosclerotic pathway, particularly adipokines, inflammatory and endothelial markers. This paper therefore investigates the influence of overweight across the life course on levels of these markers at retirement age. SUBJECTS/METHODS: Data from the Medical Research Council National Survey of Health and Development (n=1784) were used to examine the associations between overweight status at 2, 4, 6, 7, 11, 15, 20, 26, 36, 43, 53 and 60-64 years (body mass index (BMI)⩾25 kg m(-2) for adult ages and gender-specific cut-points for childhood ages equivalent to BMI⩾25 kg m(-2)) and measurements of adipokines (leptin and adiponectin), inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6)) and endothelial markers (E-selectin, tissue plasminogen activator (t-PA) and von Willebrand factor) at 60-64 years. In addition, the fit of different life course models (sensitive periods/accumulation) were compared using partial F-tests. RESULTS: In age- and sex-adjusted models, overweight at 11 years and onwards was associated with higher leptin, CRP and IL-6 and lower adiponectin; overweight at 15 years and onwards was associated with higher E-selectin and t-PA. Associations between overweight at all ages earlier than 60-64 with leptin, adiponectin, CRP and IL-6 were reduced but remained apparent after adjustment for overweight at 60-64 years; whereas those with E-selectin and t-PA were entirely explained. An accumulation model best described the associations between overweight across the life course with adipokines and inflammatory markers, whereas for the endothelial markers, the sensitive period model for 60-64 years provided a slightly better fit than the accumulation model. CONCLUSIONS: Overweight across the life course has a cumulative influence on adipokines, inflammatory and possibly endothelial markers. Avoidance of overweight from adolescence onwards is likely important for cardiovascular disease prevention