|Title||Genetic overlap between diagnostic subtypes of ischemic stroke.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Holliday, EG, Traylor, M, Malik, R, Bevan, S, Falcone, G, Hopewell, JC, Cheng, Y-C, Cotlarciuc, I, Bis, JC, Boerwinkle, E, Boncoraglio, GB, Clarke, R, Cole, JW, Fornage, M, Furie, KL, M Ikram, A, Jannes, J, Kittner, SJ, Lincz, LF, Maguire, JM, Meschia, JF, Mosley, TH, Nalls, MA, Oldmeadow, C, Parati, EA, Psaty, BM, Rothwell, PM, Seshadri, S, Scott, RJ, Sharma, P, Sudlow, C, Wiggins, KL, Worrall, BB, Rosand, J, Mitchell, BD, Dichgans, M, Markus, HS, Levi, C, Attia, J, Wray, NR|
|Corporate Authors||Australian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2, International Stroke Genetics Consortium|
|Date Published||2015 Mar|
|Keywords||Alleles, Atherosclerosis, Cerebral Small Vessel Diseases, Cohort Studies, Data Interpretation, Statistical, Embolism, Genome-Wide Association Study, Genotype, Humans, Ischemia, Linear Models, Meta-Analysis as Topic, Phenotype, Polymorphism, Single Nucleotide, Stroke|
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 (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=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.
|PubMed Central ID||PMC4342266|
|Grant List||095626 / / Wellcome Trust / United Kingdom |
K08 NS045802 / NS / NINDS NIH HHS / United States
L30 DC006823 / DC / NIDCD NIH HHS / United States
OSRP2/1006 / / The Dunhill Medical Trust / United Kingdom
U01 HG005160 / HG / NHGRI NIH HHS / United States
U01 NS069208 / NS / NINDS NIH HHS / United States