Identifying causal serum protein-cardiometabolic trait relationships using whole genome sequencing - Png, Grace; Gerlini, Raffaele; Hatzikotoulas, Konstantinos; Barysenka, Andrei; Rayner, N William; Klarić, Lucija; Rathkolb, Birgit; Aguilar-Pimentel, Juan A; Rozman, Jan; Fuchs, Helmut; Gailus-Durner, Valerie; Tsafantakis, Emmanouil; et al. (Human molecular genetics, 2023)
Cardiometabolic diseases, such as type 2 diabetes and cardiovascular disease, have a high public health burden. Understanding the genetically determined regulation of proteins that are dysregulated in disease can help to dissect the complex biology underpinning them. Here, we perform a protein quantitative trait locus (pQTL) analysis of 248 serum proteins relevant to cardiometabolic processes in 2893 individuals. Meta-analyzing whole-genome sequencing (WGS) data from two Greek cohorts, MANOLIS (n = 1356; 22.5× WGS) and Pomak (n = 1537; 18.4× WGS), we detect 301 independently associated pQTL variants for 170 proteins, including 12 rare variants (minor allele frequency < 1%). We additionally find 15 pQTL variants that are rare in non-Finnish European populations but have drifted up in the frequency in the discovery cohorts here. We identify proteins causally associated with cardiometabolic traits, including Mep1b for high-density lipoprotein (HDL) levels, and describe a knock-out (KO) Mep1b mouse model. Our findings furnish insights into the genetic architecture of the serum proteome, identify new protein-disease relationships and demonstrate the importance of isolated populations in pQTL analysis.
Keywords: kardiovaskulární nemoci; Animals; Diabetes Mellitus, Type 2; Blood Proteins; krevní proteiny; Phenotype; fenotyp; zvířata; Mice; Genome-Wide Association Study; Cardiovascular Diseases; sekvenování celého genomu; diabetes mellitus 2. typu; Whole Genome Sequencing; celogenomová asociační studie; myši