AUTHOR=Marini Sandro , Lena Umme K. , Crawford Katherine M. , Moomaw Charles J. , Testai Fernando D. , Kittner Steven J. , James Michael L. , Woo Daniel , Langefeld Carl D. , Rosand Jonathan , Anderson Christopher D.
TITLE=Comparison of Genetic and Self-Identified Ancestry in Modeling Intracerebral Hemorrhage Risk
JOURNAL=Frontiers in Neurology
VOLUME=9
YEAR=2018
URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2018.00514
DOI=10.3389/fneur.2018.00514
ISSN=1664-2295
ABSTRACT=Background: We sought to determine whether a small pool of ancestry-informative DNA markers (AIMs) improves modeling of intracerebral hemorrhage (ICH) risk in heterogeneous populations, compared with self-identified race/ethnicity (SIRE) alone.
Methods: We genotyped 15 preselected AIMs to perform principal component (PC) analysis in the ERICH study (a multi-center case-control study of ICH in whites, blacks, and Hispanics). We used multivariate logistic regression and tests for independent samples to compare associations for genetic ancestry and SIRE with ICH-associated vascular risk factors (VRFs). We then compared the performance of models for ICH risk that included AIMs and SIRE alone.
Results: Among 4,935 subjects, 34.7% were non-Hispanic black, 35.1% non-Hispanic white, and 30.2% Hispanic by SIRE. In stratified analysis of these SIRE groups, AIM-defined ancestry was strongly associated with seven of the eight VRFs analyzed (p < 0.001). Within each SIRE group, regression of AIM-derived PCs against VRFs confirmed independent associations of AIMs across at least two race/ethnic groups for seven VRFs. Akaike information criterion (AIC) (6,294 vs. 6,286) and likelihood ratio test (p < 0.001) showed that genetic ancestry defined by AIMs achieved a better ICH risk modeling compared to SIRE alone.
Conclusion: Genetically-defined ancestry provides valuable risk exposure information that is not captured by SIRE alone. Particularly among Hispanics and blacks, inclusion of AIMs adds value over self-reported ancestry in controlling for genetic and environmental exposures that influence risk of ICH. While differences are small, this modeling approach may be superior in highly heterogeneous clinical poulations. Additional studies across other ancestries and risk exposures are needed to confirm and extend these findings.