Plasma fetuin-A is associated with type 2 diabetes, and AHSG, the gene encoding fetuin-A, has been identified as a susceptibility locus for diabetes and metabolic syndrome. Thus far, unbiased investigations of the genetic determinants of plasma fetuin-A concentrations have not been conducted. We searched for single nucleotide polymorphisms (SNPs) related to fetuin-A concentrations by a genome-wide association study in six population-based studies. We examined the association of fetuin-A levels with ∼ 2.5 million genotyped and imputed SNPs in 9,055 participants of European descent and 2,119 African Americans. In both ethnicities, the strongest associations were centered in a region with a high degree of LD near the AHSG locus. Among 136 genome-wide significant (P < 0.05 × 10-8) SNPs near the AHSG locus, the top SNP was rs4917 (P =1.27 × 10-303), a known coding SNP in exon 6 that is associated with a 0.06 g/l (∼13%) lower fetuin-A level. This variant alone explained 14% of the variation in fetuin-A levels. Analyses conditioned on rs4917 indicated that the strong association with the AHSG locus stems from additional independent associations of multiple variants among European Americans. In conclusion, levels of fetuin-A in plasma are strongly associated with SNPs in its encoding gene, AHSG, but not elsewhere in the genome. Given the strength of the associations observed for multiple independent SNPs, the AHSG gene is an example of a candidate locus suitable for additional investigations including fine mapping to elucidate the biological basis of the findings and further functional experiments to clarify AHSG as a potential therapeutic target.

Platelet aggregation at the site of atherosclerotic vascular injury is the underlying pathophysiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes.

Background

Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.

Results

We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.

Conclusions

Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Nonsyndromic mitral valve prolapse (MVP) is a common degenerative cardiac valvulopathy of unknown etiology that predisposes to mitral regurgitation, heart failure and sudden death. Previous family and pathophysiological studies suggest a complex pattern of inheritance. We performed a meta-analysis of 2 genome-wide association studies in 1,412 MVP cases and 2,439 controls. We identified 6 loci, which we replicated in 1,422 cases and 6,779 controls, and provide functional evidence for candidate genes. We highlight LMCD1 (LIM and cysteine-rich domains 1), which encodes a transcription factor and for which morpholino knockdown of the ortholog in zebrafish resulted in atrioventricular valve regurgitation. A similar zebrafish phenotype was obtained with knockdown of the ortholog of TNS1, which encodes tensin 1, a focal adhesion protein involved in cytoskeleton organization. We also showed expression of tensin 1 during valve morphogenesis and describe enlarged posterior mitral leaflets in Tns1(-/-) mice. This study identifies the first risk loci for MVP and suggests new mechanisms involved in mitral valve regurgitation, the most common indication for mitral valve repair.

Although recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.

Background

Use of targeted exome-arrays with common, rare variants and functionally enriched variation has led to discovery of new genes contributing to population variation in risk factors. Plasminogen activator-inhibitor 1 (PAI-1), tissue plasminogen activator (tPA), and the plasma product D-dimer are important components of the fibrinolytic system. There have been few large-scale genome-wide or exome-wide studies of PAI-1, tPA, and D-dimer.

Objectives

We sought to discover new genetic loci contributing to variation in these traits using an exome-array approach.

Methods

Cohort-level analyses and fixed effects meta-analyses of PAI-1 (n = 15 603), tPA (n = 6876,) and D-dimer (n = 19 306) from 12 cohorts of European ancestry with diverse study design were conducted, including single-variant analyses and gene-based burden testing.

Results

Five variants located in NME7, FGL1, and the fibrinogen locus, all associated with D-dimer levels, achieved genome-wide significance (P < 5 × 10^-8 ). Replication was sought for these 5 variants, as well as 45 well-imputed variants with P < 1 × 10^-4 in the discovery using an independent cohort. Replication was observed for three out of the five significant associations, including a novel and uncommon (0.013 allele frequency) coding variant p.Trp256Leu in FGL1 (fibrinogen-like-1) with increased plasma D-dimer levels. Additionally, a candidate-gene approach revealed a suggestive association for a coding variant (rs143202684-C) in SERPINB2, and suggestive associations with consistent effect in the replication analysis include an intronic variant (rs11057830-A) in SCARB1 associated with increased D-dimer levels.

Conclusion

This work provides new evidence for a role of FGL1 in hemostasis.

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

BACKGROUND: Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. OBJECTIVES: To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. METHODS: We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. RESULTS: We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10-7) and EPIC arrays (p < 5.78 × 10-8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. CONCLUSION: We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.