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Pathway-specific Polygenic Risk Scores (PRS) identify OSA-related pathways differentially moderating genetic susceptibility to CAD

By Matthew O. Goodman, Brian E Cade, Neomi Shah, Tianyi Huang, Hassan S Dashti, Richa Saxena, Martin Rutter, Peter Libby, Tamar Sofer, Susan Redline

Posted 30 Apr 2021
medRxiv DOI: 10.1101/2021.04.27.21255520

Background: Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia (IH), may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (e.g. inflammatory) and protective (e.g. increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner. Methods: We selected a cross-sectional sample of 471,877 participants from the UK Biobank, among whom we ascertained 4,974 to have OSA, 25,988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores (PS-PRS) for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (GWAS), annotated to specific genes and pathways using functional genomics databases. Based on evidence of involvement with IH and CAD, we tested PS-PRS for the HIF-1, VEGF, NFkB and TNF signaling pathways. Results: In a multivariable-adjusted logistic generalized additive model, elevated PS-PRSs for the KEGG VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, p = 6E-04). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA. Conclusions: We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner, consistent with the previously studied phenomena whereby features of OSA may have both positive and negative effects on CAD. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. These results can be followed up to study how OSA interacts with genetic risk at the molecular level, and potentially to personalize OSA treatment and reduce CAD risk according to individual pathway-specific genetic risk profiles.

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