An Examination of the Relationship between Lipid Levels and Associated Genetic Markers across Racial/Ethnic Populations in the Multi-Ethnic Study of Atherosclerosis

• Published in: PloS one Vol. 10; no. 5; p. e0126361
• Main Authors: Johnson, Lucia, Zhu, Jonathan, Scott, Erick R, Wineinger, Nathan E
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.05.2015; Public Library of Science (PLoS)
• Subjects: Analysis; Arteriosclerosis; Asian Americans; Atherosclerosis; Atherosclerosis - blood; Atherosclerosis - genetics; Cardiovascular disease; Cohort Studies; Ethnicity - genetics; Genetic aspects; Genetic counseling; Genetic diversity; Genetic Loci; Genetic markers; Genetic Markers - genetics; Genetic Predisposition to Disease; Genetic screening; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genomics; Genotype; Health risk assessment; Humans; Lipids; Lipids - blood; Lipids - genetics; Loci; Markers; Meta-analysis; Methods; Minority & ethnic groups; Physiological aspects; Polymorphism, Single Nucleotide; Population studies; Populations; Studies; United States; White People - genetics; United States
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0126361

Large genome-wide association studies have reported hundreds of genetic markers associated with lipid levels. However, the discovery and estimated effect of variants at these loci, derived from samples of exclusively European descent, may not generalize to the majority of the world populations. We examined the collective strength of association among these loci in a diverse set of U.S. populations from the Multi-Ethnic Study of Atherosclerosis. We constructed a genetic risk score for each lipid outcome based on previously identified lipid-associated genetic markers, and examined the relationship between the genetic risk scores and corresponding outcomes. We discover this relationship was often moderated by race/ethnicity. Our findings provide insight into the generalizability and predictive utility of large sample size meta-analyses results when leveraging data from a single population. We hope these findings will encourage researchers to investigate genetic susceptibility in more diverse populations and explore the source of such discrepancies. Until then, we caution clinicians, genetic counselors, and genetic testing consumers when interpreting genetic data on complex traits.