Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels

Jessica Dennis, Alejandra Medina-Rivera, Vinh Truong, Lina Antounians, Nora Zwingerman, Giovana Carrasco, Lisa Strug, Phil Wells, David Alexandre Trégouët, Pierre Emmanuel Morange, Michael D. Wilson, France Gagnon

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI. Our GWAS identified 131 SNPs with suggestive evidence of association (P-value < 5 × 10−8), but no SNPs reached the genome-wide threshold for statistical significance. Hemostasis pathway genes were not enriched for TFPI plasma level associated SNPs (global hypothesis test P-value = 0.147), but EC regulatory regions contained more TFPI plasma level associated SNPs than expected by chance (global hypothesis test P-value = 0.046). We therefore stratified our genome-wide SNPs, prioritizing those in EC regulatory regions via stratified false discovery rate (sFDR) control, and reranked the SNPs by q-value. The minimum q-value was 0.27, and the top-ranked SNPs did not show association evidence in the MARTHA replication sample of 1,033 unrelated VTE cases. Although this study did not result in new loci for TFPI, our work lays out a strategy to utilize epigenomic data in prioritization schemes for future GWAS studies.

Original languageEnglish
Pages (from-to)455-466
Number of pages12
JournalGenetic Epidemiology
Volume41
Issue number5
DOIs
StatePublished - Jul 2017
Externally publishedYes

Keywords

  • epigenetics
  • genetic association studies
  • multiple hypothesis testing
  • thrombosis
  • tissue factor pathway inhibitor

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