medRxivGenetic & Genomic MedicinePreprint
FOG2 coding variant Ser657Gly is associated with Coronary Microvascular Disease through altered hypoxia-mediated gene transcription
Marie A. GuerratyiD, Shefali S. Verma, Y.A. Ko, Michael A. McQuillaniD, Donna ConloniD, John W. TobiasiD, Michael G. LeviniD, William R. HauryiD, C. Zhang, Renae JudyiD, PennMedicine Biobank, Sarah A. TishkoffiD, Scott M. DamraueriD, Zoltan Pierre AranyiD, Daniel James RaderiD
Abstract
RationaleThe coronary microvasculature is crucial for proper cardiac function, and coronary microvascular disease (CMVD) has emerged as an underdiagnosed and undertreated cause of ischemic heart disease. Friend of GATA 2 (FOG2) is a transcriptional co-regulator crucial for coronary development and the maintenance of the coronary microvasculature in adult mice.Little is known about the role of FOG2 in humans or its role in CMVD. ObjectiveHere, we report a genotype-first approach to determine the role of FOG2 in human coronary microvascular disease. FindingsWe performed Phenome-Wide association studies and deep cardiac phenotyping through the Electronic Health record in patients with FOG2 coding variants and identified an association between rs28374544 (A1969G, S657G) and CMVD. Patients with S657G had increased chest pain, smaller burden of obstructive coronary artery disease, and altered coronary blood flow. Differential gene and pathway analysis using several genomic datasets showed that carriers of S657G have increased expression of genes involved in angiogenesis, glycolysis, and the hypoxia-inducible factor (HIF) pathway. In vitro functional studies show that FOG2 S657G promotes angiogenic gene expression and angiogenesis while decreasing oxygen consumption rate. FOG2 also regulates HIF1a occupancy of angiogenic genes. ConclusionsWe identified a human missense variant which is associated with CMVD and established a potential mechanism by which the variant may altered angiogenic gene expression.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 2
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