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Png, G. ; Gerlini, R. ; Hatzikotoulas, K. ; Barysenska, A. ; Rayner, N.W. ; Klarić, L.* ; Rathkolb, B. ; Aguilar-Pimentel, J.A. ; Rozman, J. ; Fuchs, H. ; Gailus-Durner, V. ; Tsafantakis, E.* ; Karaleftheri, M.* ; Dedoussis, G.* ; Pietrzik, C.U.* ; Wilson, J.F.* ; Hrabě de Angelis, M. ; Becker-Pauly, C.* ; Gilly, A. ; Zeggini, E.

Identifying causal serum protein-cardiometabolic trait relationships using whole genome sequencing.

Hum. Mol. Genet. 32, 1266-1275 (2022)
Postprint DOI PMC
Open Access Hybrid
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 255 serum proteins relevant to cardiometabolic processes in 2893 individuals. Meta-analysing whole-genome sequencing (WGS) data from two Greek cohorts, MANOLIS (n = 1356; 22.5x WGS) and Pomak (n = 1537; 18.4x WGS), we detect 302 independently-associated pQTL variants for 171 proteins, including 12 rare variants (minor allele frequency [MAF] < 1%). We additionally find 15 pQTL variants that are rare in non-Finnish European populations, but have drifted up in frequency in the discovery cohorts here. We identify proteins causally associated with cardiometabolic traits, including MEP1B for high-density lipoprotein levels; and describe a knock-out 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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Metaanalysis; Cholesterol; Expression; Receptors; Discovery; Platform
Sprache englisch
Veröffentlichungsjahr 2022
HGF-Berichtsjahr 2022
ISSN (print) / ISBN 0964-6906
e-ISSN 1460-2083
Zeitschrift Human Molecular Genetics
Quellenangaben Band: 32, Heft: 8, Seiten: 1266-1275 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Great Clarendon St, Oxford Ox2 6dp, England
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)
Institute of Experimental Genetics (IEG)
POF Topic(s) 30205 - Bioengineering and Digital Health
30201 - Metabolic Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-506700-001
G-500692-001
G-500600-001
Förderungen Deutsche Forschungsgemeinschaft (DFG)
German Center for Diabetes Research (DZD)
German Federal Ministry of Education and Research
National Productivity Investment Fund
MRC Human Genetics Unit programme grant, Quantitative traits in health and disease'
European Union
Arthritis Research UK
Chief Scientist Office of the Scottish Government
European Research Council
Wellcome Trust
DOI 10.1093/hmg/ddac275
WOS ID 000908330700001
WOS ID WOS:000908330700001
Scopus ID 85152172014
PubMed ID 36349687
Erfassungsdatum 2022-11-17
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