Abstract Text |
Compared with array-based, imputation-based, and exome-focused analyses, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants.
To better understand the genetics underlying plasma levels of fibrinogen we utilized data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium and the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. TOPMed phenotypes were centrally harmonized across up to 12 studies of European, African, Asian, or Hispanic ancestry then association analyses were conducted using Freeze 6 deep WGS data (N=32,575). Inverse normalized and rescaled residuals adjusting for age, sex, study, TOPMed phase, study-specific parameters, self-reported ancestry, 11 ancestry informative principal components, and a kinship matrix. Analyses were conducted on the Analysis Commons using the SMMAT function implemented in GENESIS and included all variants with a minor allele count ≥40. Each CHARGE cohort undertook the same analyses using genotypic dosages imputed to the TOPMed backbone (N=75,882). Inverse-variance weighted meta-analysis was undertaken using GWAMA for a final sample size of 108,454.
16 regions were significantly associated with plasma levels of fibrinogen. Most were in loci previously associated with these phenotypes, and the majority were common variants in high linkage disequilibrium with previously reported variants. The most significant association for fibrinogen was a rare missense mutation (rs148685782, p=5.85x10-161, MAF=0.003, FGG) located within the fibrinogen structural genes region.
WGS data provides better resolution of existing and potential detection of novel gene regions. Additional data is anticipated from several more CHARGE cohorts, therefore update results from >150,000 samples will be presented.
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