TY - JOUR
T1 - Annotation of loci from genome-wide association studies using tissue-specifc quantitative interaction proteomics
AU - Lundby, Alicia
AU - Rossin, Elizabeth J.
AU - Steffensen, Annette B.
AU - Acha, Moshe Rav
AU - Newton-Cheh, Christopher
AU - Pfeufer, Arne
AU - Lynch, Stacey N.
AU - Olesen, S. ren-Peter
AU - Brunak, S. ren
AU - Ellinor, Patrick T.
AU - Jukema, J. Wouter
AU - Trompet, Stella
AU - Ford, Ian
AU - MacFarlane, Peter W.
AU - Krijthe, Bouwe P.
AU - Hofman, Albert
AU - Uitterlinden, André G.
AU - Stricker, Bruno H.
AU - Nathoe, Hendrik M.
AU - Spiering, Wilko
AU - Daly, Mark J.
AU - Asselbergs, Folkert W.
AU - van der Harst, Pim
AU - Milan, David J.
AU - de Bakker, Paul I. W.
AU - Lage, Kasper
AU - Olsen, Jesper V.
PY - 2014
Y1 - 2014
N2 - Genome-wide association studies (GWAs) have identifed thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specifc quantitative interaction proteomics to map a network of fve genes involved in the mendelian disorder long Qt syndrome (lQts). We integrated the lQts network with GWAs loci from the corresponding common complex trait, Qt-interval variation, to identify candidate genes that were subsequently confrmed in Xenopus laevis oocytes and zebrafsh. We used the lQts protein network to flter weak GWAs signals by identifying single-nucleotide polymorphisms (snPs) in proximity to genes in the network supported by strong proteomic evidence. three snPs passing this flter reached genome-wide signifcance after replication genotyping. overall, we present a general strategy to propose candidates in GWAs loci for functional studies and to systematically flter subtle association signals using tissue-specifc quantitative interaction proteomics. © 2014 Nature America, Inc. All rights reserved.
AB - Genome-wide association studies (GWAs) have identifed thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specifc quantitative interaction proteomics to map a network of fve genes involved in the mendelian disorder long Qt syndrome (lQts). We integrated the lQts network with GWAs loci from the corresponding common complex trait, Qt-interval variation, to identify candidate genes that were subsequently confrmed in Xenopus laevis oocytes and zebrafsh. We used the lQts protein network to flter weak GWAs signals by identifying single-nucleotide polymorphisms (snPs) in proximity to genes in the network supported by strong proteomic evidence. three snPs passing this flter reached genome-wide signifcance after replication genotyping. overall, we present a general strategy to propose candidates in GWAs loci for functional studies and to systematically flter subtle association signals using tissue-specifc quantitative interaction proteomics. © 2014 Nature America, Inc. All rights reserved.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84905379444&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/24952909
U2 - https://doi.org/10.1038/nmeth.2997
DO - https://doi.org/10.1038/nmeth.2997
M3 - Article
C2 - 24952909
SN - 1548-7091
VL - 11
SP - 868
EP - 874
JO - Nature methods
JF - Nature methods
IS - 8
ER -