Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( SERPINA1, ZFP36L2 , and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( FGG;FGB;FGA ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation. Key Points ### Competing Interest Statement Laura Raffield is a consultant for the TOPMed Administrative Coordinating Center (through WeStat). Ruifang Li-Gao is a part-time consultant for Metabolon, Inc. Michael Cho has received grant support from Bayer. Bruce Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson and Johnson. In the past three years, Edwin K. Silverman has received grant support from Bayer. ### Funding Statement Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). See the TOPMed Omics Support Table in the Supplemental Data for study specific omics support information. Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. CHARGE is supported by R01HL-105756 and the CHARGE and TOPMed Hemostasis Working Groups by R01HL-134894, R01HL-139553, and R01HL-141291. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award I01-BX004821. The study was supported by the Novo Nordisk Foundation (grant number NNF18CC0034900). D-A.T was supported by the EPIDEMIOM-VT Senior Chair of Excellence from the University of Bordeaux initiative of Excellence (IdEX). Additional study-specific funding and acknowledgements can be found in the Supplemental Data. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. This publication does not represent the views of the Department of Veteran Affairs, the US National Institutes of Health, the National Heart, Lung and Blood Institute, the US Department of Health and Human Service, or the United States Government. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Meta-analysis summary statistics will be available through the CHARGE dbGaP accession (phs000930) or upon request to the corresponding author. Individual-level data for TOPMed studies is available through their relevant dbGaP accessions as listed in the TOPMed Omics Support Table in the Supplemental Data.