Background: Elevated cardiac troponin levels in blood are associated with increased risk of cardiovascular diseases and mortality. Cardiac troponin levels are heritable, but their genetic... Show moreBackground: Elevated cardiac troponin levels in blood are associated with increased risk of cardiovascular diseases and mortality. Cardiac troponin levels are heritable, but their genetic architecture remains elusive. Methods: We conducted a transethnic genome-wide association analysis on high-sensitivity cTnT (cardiac troponin T; hs-cTnT) and high-sensitivity cTnI (cardiac troponin I; hs-cTnI) levels in 24 617 and 14 336 participants free of coronary heart disease and heart failure from 6 population-based cohorts, followed by a series of bioinformatic analyses to decipher the genetic architecture of hs-cTnT and hs-cTnI. Results: We identified 4 genome-wide significant loci for hs-cTnT including a novel locus rs3737882 in PPFIA4 and 3 previously reported loci at NCOA2, TRAM1, and BCL2. One known locus at VCL was replicated for hs-cTnI. One copy of C allele for rs3737882 was associated with a 6% increase in hs-cTnT levels (minor allele frequency, 0.18; P=2.80x10(-9)). We observed pleiotropic loci located at BAG3 and ANO5. The proportions of variances explained by single-nucleotide polymorphisms were 10.15% and 7.74% for hs-cTnT and hs-cTnI, respectively. Single-nucleotide polymorphisms were colocalized with BCL2 expression in heart tissues and hs-cTnT and with ANO5 expression in artery, heart tissues, and whole blood and both troponins. Mendelian randomization analyses showed that genetically increased hs-cTnT and hs-cTnI levels were associated with higher odds of atrial fibrillation (odds ratio, 1.38 [95% CI, 1.25-1.54] for hs-cTnT and 1.21 [95% CI, 1.06-1.37] for hs-cTnI). Conclusions: We identified a novel genetic locus associated with hs-cTnT in a multiethnic population and found that genetically regulated troponin levels were associated with atrial fibrillation. Show less
Fuentes, L. de las; Sung, Y.J.; Noordam, R.; Winkler, T.; Feitosa, M.F.; Schwander, K.; ... ; Lifelines Cohort Study 2020
Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed... Show moreEducational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 x 10(-8)). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP. Show less
Noordam, R.; Young, W.J.; Salman, R.; Kanters, J.K.; Berg, M.E. van den; Heemst, D. van; ... ; Warren, H.R. 2019
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have... Show moreMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. Show less
