Associations of carotid intima media thickness with gene expression in whole blood and genetically predicted gene expression across 48 tissues.

Castaneda, Andy B; Petty, Lauren E; Scholz, Markus; Jansen, Rick; Weiss, Stefan; Zhang, Xiaoling; Schramm, Katharina; Beutner, Frank; Kirsten, Holger; Schminke, Ulf; Hwang, Shih-Jen; Marzi, Carola; Dhana, Klodian; Seldenrijk, Adrie; Krohn, Knut; Homuth, Georg; Wolf, Petra; Peters, Marjolein J; Dörr, Marcus; Peters, Annette; ... (2022). Associations of carotid intima media thickness with gene expression in whole blood and genetically predicted gene expression across 48 tissues. Human molecular genetics, 31(7), pp. 1171-1182. Oxford University Press 10.1093/hmg/ddab236

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Carotid intima media thickness (cIMT) is a biomarker of subclinical atherosclerosis and a predictor of future cardiovascular events. Identifying associations between gene expression levels and cIMT may provide insight to atherosclerosis etiology. Here, we use two approaches to identify associations between mRNA levels and cIMT: differential gene expression analysis in whole blood and S-PrediXcan. We used microarrays to measure genome-wide whole blood mRNA levels of 5647 European individuals from four studies. We examined the association of mRNA levels with cIMT adjusted for various potential confounders. Significant associations were tested for replication in three studies totaling 3943 participants. Next, we applied S-PrediXcan to summary statistics from a cIMT genome-wide association study of 71 128 individuals to estimate the association between genetically determined mRNA levels and cIMT and replicated these analyses using S-PrediXcan on an independent genome-wide association study on cIMT that included 22 179 individuals from the UK Biobank. mRNA levels of TNFAIP3, CEBPD, and METRNL were inversely associated with cIMT, but these associations were not significant in the replication analysis. S-PrediXcan identified associations between cIMT and genetically determined mRNA levels for 36 genes, of which six were significant in the replication analysis, including TLN2, which had not been previously reported for cIMT. There was weak correlation between our results using differential gene expression analysis and S-PrediXcan. Differential expression analysis and S-PrediXcan represent complementary approaches for the discovery of associations between phenotypes and gene expression. Using these approaches, we prioritize TNFAIP3, CEBPD, METRNL, and TLN2 as new candidate genes whose differential expression might modulate cIMT.

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