eLifeGenetic & Genomic MedicinePeer-reviewed journal article
Ethnic and region-specific genetic risk variants of stroke and its comorbid conditions may better define the variations in the burden of stroke and its phenotypic traits
Rashmi SukumaraniD, Achuthsankar Sukumaran NairiD, Moinak BanerjeeiD
Abstract
Burden of stroke differs by region, which could be attributed to differences in comorbid conditions and ethnicity. Genomewide variation acts as a proxy marker for ethnicity, and comorbid conditions. We present an integrated approach to understand this variation by considering prevalence and mortality rates of stroke and its comorbid risk for 204 countries from 2009 to 2019, and GWAS risk variant for all these conditions. Global and regional trend analysis of rates using linear regression, correlation and proportion analysis, signify ethnogeographic differences. Interestingly, the comorbid conditions that act as risk drivers for stroke differed by regions, with more of metabolic risk in America and Europe, in contrast to high SBP in Asian and African regions. GWAS risk loci of stroke and its comorbid conditions indicate distinct population stratification for each of these conditions, signifying for population specific risk. Unique and shared genetic risk variants for stroke, and its comorbid and followed up with ethnic specific variation can help in determining regional risk drivers for stroke. Unique ethnic specific risk variants and their distinct patterns of Linkage Disequilibrium further uncover the drivers for phenotypic variation. Therefore, identifying population and comorbidity specific risk variants might help in defining the threshold for risk, and aid in developing population specific prevention strategies for stroke. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/23299453v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@e29e78org.highwire.dtl.DTLVardef@11dee3org.highwire.dtl.DTLVardef@1404396org.highwire.dtl.DTLVardef@1567f7_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
- FWCI
- 0.26
- Field percentile
- 48th percentile
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