Genome-Wide Association Study of Peripheral Artery Disease

Abstract

Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD dependent on diabetic or smoking status. Results: We identified 5 genome-wide significant ( P association ≤5×10 −8 ) associations with PAD in 449 548 (N cases =12 086) individuals of European ancestry near LPA , CDKN2BAS1 , SH2B3-PTPN11 , HDAC9 , and CHRNA5 loci (which overlapped previously reported associations). Meta-analysis with variants previously association with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32–1.74], P diabetes =2.5×10 −9 , P interactionwithdiabetes =5.3×10 −7 ). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11–1.19], P smokers =9.3×10 −10 , P interactionwithsmoking =3.9×10 −5 ). Conclusions: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.

The Genetic Architecture of the Etiology of Lower Extremity Peripheral Artery Disease: Current Knowledge and Future Challenges in the Era of Genomic Medicine

“…GWASs (SNPs) have a low power to identify structural abnormalities (copy number variations (CNVs) caused by translocations, insertions, and deletions), as well as to identify interactions between different genes (epistasis) or between genetic and environmental factors. Exceeding these limits requires different strategies: correctly defining the phenotype for the analyzed cases, increasing the number of analyzed samples and the use of groups with extreme phenotypes; increasing the sensitivity of the detection rate, especially of rare allelic variants, by developing powerful biostatistical tools; taking into account the mechanism of epigenetic regulation of gene expression; fine mapping of SNPs or using next generation sequencing (NGS) for regions of interest to identify rare allelic variants and/or structural variants [ 18 , 22 , 38 , 46 , 97 ].…”

“…The most significant association with LEAD was in the case of the IPO5 gene. The IPO5 gene encodes the IPO5 protein, a member of the importin beta family that plays a role in promoting the excretion of apolipoprotein A-1, a protein that plays an essential role in the regulation of HDL and, therefore, intervenes in the formation of atherosclerotic plaques in the vascular wall [ 17 , 25 , 37 , 38 , 39 ].…”

Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care

“…The identified 443 differentially expressed genes are involved in the cell cycle, DNA replication, metabolic pathways, focal adhesion, regulation of actin cytoskeleton, and nucleotide excision repair in mice. Furthermore, a GWAS study provided evidence for the mechanism underpinning the complication in humans and identified two genomic regions strongly associated with PAD (rs116405693 and coiled-coil serine-rich protein 1 (CCSER1)) confirming the genetic association between the long-term complication and T1D [70].…”

Genomic, transcriptomic and proteomic depiction of iPSC-derived smooth muscle cells as emerging cellular models for arterial diseases

“…Variant enrichment was calculated using rtracklayer (v1.52.1) package as follows. List of lead SNPs were retrieved from GWAS catalog and correspond to individual studies in European populations for coronary artery disease 69 , stroke 70 , blood pressure 71 , intracranial aneurysm 72 , peripheral artery disease 73 , abdominal aortic aneurysm 74 and migraine 75 . Proxies in high linkage disequilibrium (r 2 >0.7) with the lead SNP in the European population of 1000 Genome reference panel were retrieved at each locus using ldproxy function of LDlinkR package (v1.1.2) 76 .…”