Details

Autor(en) / Beteiligte

• Ferkingstad, Egil
• Sulem, Patrick
• Atlason, Bjarni A
• Sveinbjornsson, Gardar
• Magnusson, Magnus I
• Styrmisdottir, Edda L
• Gunnarsdottir, Kristbjorg
• Helgason, Agnar
• Oddsson, Asmundur
• Halldorsson, Bjarni V
• Jensson, Brynjar O
• Zink, Florian
• Halldorsson, Gisli H
• Masson, Gisli
• Arnadottir, Gudny A
• Katrinardottir, Hildigunnur
• Juliusson, Kristinn
• Magnusson, Magnus K
• Magnusson, Olafur Th
• Fridriksdottir, Run
• Saevarsdottir, Saedis
• Gudjonsson, Sigurjon A
• Stacey, Simon N
• Rognvaldsson, Solvi
• Eiriksdottir, Thjodbjorg
• Olafsdottir, Thorunn A
• Steinthorsdottir, Valgerdur
• Tragante, Vinicius
• Ulfarsson, Magnus O
• Stefansson, Hreinn
• Jonsdottir, Ingileif
• Holm, Hilma
• Rafnar, Thorunn
• Melsted, Pall
• Saemundsdottir, Jona
• Norddahl, Gudmundur L
• Lund, Sigrun H
• Gudbjartsson, Daniel F
• Thorsteinsdottir, Unnur
• Stefansson, Kari

Titel

Large-scale integration of the plasma proteome with genetics and disease

Ist Teil von

• Nature genetics, 2021-12, Vol.53 (12), p.1712-1721

Ort / Verlag

United States: Nature Publishing Group

Erscheinungsjahr

2021

Quelle

MEDLINE

Beschreibungen/Notizen

• The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF) < 1%). We tested plasma protein levels for association with 373 diseases and other traits and identified 257,490 associations. We integrated pQTL and genetic associations with diseases and other traits and found that 12% of 45,334 lead associations in the GWAS Catalog are with variants in high linkage disequilibrium with pQTL. We identified 938 genes encoding potential drug targets with variants that influence levels of possible biomarkers. Combining proteomics, genomics and transcriptomics, we provide a valuable resource that can be used to improve understanding of disease pathogenesis and to assist with drug discovery and development.