Genetic Overlap Between Diagnostic Subtypes of Ischemic Stroke. Issue 3 (March 2015)

• Record Type: Journal Article
• Authors: Holliday, Elizabeth G.; Traylor, Matthew; Malik, Rainer; Bevan, Steve; Falcone, Guido; Hopewell, Jemma C.; Cheng, Yu-Ching; Cotlarciuc, Ioana; Bis, Joshua C.; Boerwinkle, Eric; Boncoraglio, Giorgio B.; Clarke, Robert; Cole, John W.; Fornage, Myriam; Furie, Karen L.; Ikram, M. Arfan; Jannes, Jim; Kittner, Steven J.; Lincz, Lisa F.; Maguire, Jane M.; Meschia, James F.; Mosley, Thomas H.; Nalls, Mike A.; Oldmeadow, Christopher; Parati, Eugenio A.; Psaty, Bruce M.; Rothwell, Peter M.; Seshadri, Sudha; Scott, Rodney J.; Sharma, Pankaj; Sudlow, Cathie; Wiggins, Kerri L.; Worrall, Bradford B.; Rosand, Jonathan; Mitchell, Braxton D.; Dichgans, Martin; Markus, Hugh S.; Levi, Christopher; Attia, John; Wray, Naomi R.;
• Is Part Of: Stroke. Volume 46:Issue 3(2015)
• Publication Date: 2015-03
• Subjects: atherosclerosis -- genetic epidemiology -- lacunar stroke; Cerebrovascular disease -- Periodicals; Cerebral circulation -- Periodicals; 616.81
• DOI: 10.1161/STROKEAHA.114.007930
• Languages: English
• ISSNs: 0039-2499

Abstract

Abstract : Background and Purpose—: Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses. Methods—: Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA–SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles. Results—: High genetic correlation was identified between LAA and SVD using linear mixed models ( r g =0.96, SE=0.47, P =9×10 −4 ) and profile scores ( r g =0.72; 95% confidence interval, 0.52–0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association ( P =1×10 −7 ) for single nucleotide polymorphisms near the opioid receptor μ1 ( OPRM1 ) gene. Conclusions—: Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes. Abstract : Supplemental Digital Content is available in the text.