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Relations between subclinical disease markers and type 2 diabetes, metabolic syndrome, and incident cardiovascular disease: the Jackson Heart Study.
Xanthakis, V, Sung, JH, Samdarshi, TE, Hill, AN, Musani, SK, Sims, M, Ghraibeh, KA, Liebson, PR, Taylor, HA, Vasan, RS, et al
Diabetes care. 2015;(6):1082-8
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Abstract
OBJECTIVE The presence of subclinical disease measures has been directly associated with the development of cardiovascular disease (CVD) in whites. African Americans (AAs) in the U.S. are at higher risk of CVD compared with non-Hispanic whites; however, data on the prevalence of subclinical disease measures in AAs and their association to CVD remain unclear and may explain the higher CVD risk in this group. RESEARCH DESIGN AND METHODS We evaluated 4,416 participants attending the first examination of the Jackson Heart Study (mean age 54 years; 64% women) with available subclinical disease measures. RESULTS There were 1,155 participants (26%) with subclinical disease, defined as the presence of one or more of the following: peripheral arterial disease, left ventricular hypertrophy, microalbuminuria, high coronary artery calcium (CAC) score, and low left ventricular ejection fraction. In cross-sectional analyses using multivariable-adjusted logistic regression, participants with metabolic syndrome (MetS) or diabetes (DM) had higher odds of subclinical disease compared with those without MetS and DM (odds ratios 1.55 [95% CI 1.30-1.85] and 2.86 [95% CI 2.32-3.53], respectively). Furthermore, the presence of a high CAC score and left ventricular hypertrophy were directly associated with the incidence of CVD (265 events) in multivariable-adjusted Cox proportional hazards regression models (P < 0.05). In prospective analyses, having MetS or DM significantly increased the hazard of incident CVD, independent of the presence of subclinical disease (P < 0.001). CONCLUSIONS In our community-based sample of AAs, we observed a moderately high prevalence of subclinical disease, which in turn translated into a greater risk of CVD, especially in people with MetS and DM.
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Analysis of metabolic syndrome components in >15 000 african americans identifies pleiotropic variants: results from the population architecture using genomics and epidemiology study.
Carty, CL, Bhattacharjee, S, Haessler, J, Cheng, I, Hindorff, LA, Aroda, V, Carlson, CS, Hsu, CN, Wilkens, L, Liu, S, et al
Circulation. Cardiovascular genetics. 2014;(4):505-13
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Abstract
BACKGROUND Metabolic syndrome (MetS) refers to the clustering of cardiometabolic risk factors, including dyslipidemia, central adiposity, hypertension, and hyperglycemia, in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. METHODS AND RESULTS Using the Metabochip array in 15 148 African Americans from the Population Architecture using Genomics and Epidemiology (PAGE) study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models that lack power when associations for MetS components are null or have opposite effects, Association-analysis-based-on-subsets uses 1-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With Association-analysis-based-on-subsets, we identify 27 single nucleotide polymorphisms in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, and APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P<2.5e-7, the Bonferroni adjusted P value. Three loci replicate in a Hispanic population, n=5172. A novel African American-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2, and CETP variants, many with opposing effects (eg, the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity). CONCLUSIONS We highlight a method to increase power in large-scale genomic association analyses and report a novel variant associated with all MetS components in African Americans. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications.