@article {11319,
	title = {Quantitative and Qualitative Role of Antagonistic Heterogeneity in Genetics of Blood Lipids.},
	journal = {J Gerontol A Biol Sci Med Sci},
	volume = {75},
	year = {2020},
	month = {2020 Sep 25},
	pages = {1811-1819},
	abstract = {<p>Prevailing strategies in genome-wide association studies (GWAS) mostly rely on principles of medical genetics emphasizing one gene, one function, one phenotype concept. Here, we performed GWAS of blood lipids leveraging a new systemic concept emphasizing complexity of genetic predisposition to such phenotypes. We focused on total cholesterol, low- and high-density lipoprotein cholesterols, and triglycerides available for 29,902 individuals of European ancestry from seven independent studies, men and women combined. To implement the new concept, we leveraged the inherent heterogeneity in genetic predisposition to such complex phenotypes and emphasized a new counter intuitive phenomenon of antagonistic genetic heterogeneity, which is characterized by misalignment of the directions of genetic effects and the phenotype correlation. This analysis identified 37 loci associated with blood lipids but only one locus, FBXO33, was not reported in previous top GWAS. We, however, found strong effect of antagonistic heterogeneity that leaded to profound (quantitative and qualitative) changes in the associations with blood lipids in most, 25 of 37 or 68\%, loci. These changes suggested new roles for some genes, which functions were considered as well established such as GCKR, SIK3 (APOA1 locus), LIPC, LIPG, among the others. The antagonistic heterogeneity highlighted a new class of genetic associations emphasizing beneficial and adverse trade-offs in predisposition to lipids. Our results argue that rigorous analyses dissecting heterogeneity in genetic predisposition to complex traits such as lipids beyond those implemented in current GWAS are required to facilitate translation of genetic discoveries into health care.</p>},
	keywords = {blood lipids, genetic, Genetic Heterogeneity, Qualitative Research, Quantitative data},
	issn = {1758-535X},
	doi = {10.1093/gerona/glz225},
	author = {Alexander M Kulminski and Loika, Yury and Nazarian, Alireza and Culminskaya, Irina}
}
