Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics
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Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics. / Lundby, Alicia; Rossin, Elizabeth J; Steffensen, Annette B; Acha, Moshe Rav; Newton-Cheh, Christopher; Pfeufer, Arne; Lynch, Stacey N; Olesen, Søren-Peter; Brunak, Søren; Ellinor, Patrick T; Jukema, J Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W; Krijthe, Bouwe P; Hofman, Albert; Uitterlinden, André G; Stricker, Bruno H; Nathoe, Hendrik M; Spiering, Wilko; Daly, Mark J; Asselbergs, Folkert W; van der Harst, Pim; Milan, David J; de Bakker, Paul I W; Hansen, Kasper Lage; Olsen, Jesper V; The QT Interval International GWAS Consortium (QT-IGC).
I: Nature Methods, Bind 11, Nr. 8, 22.06.2014, s. 868-874.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › fagfællebedømt
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T1 - Annotation of loci from genome-wide association studies using tissue-specific 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, Søren-Peter
AU - Brunak, Søren
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 - Hansen, Kasper Lage
AU - Olsen, Jesper V
AU - The QT Interval International GWAS Consortium (QT-IGC)
PY - 2014/6/22
Y1 - 2014/6/22
N2 - Genome-wide association studies (GWAS) have identified 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-specific quantitative interaction proteomics to map a network of five 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 confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter 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 filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.
AB - Genome-wide association studies (GWAS) have identified 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-specific quantitative interaction proteomics to map a network of five 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 confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter 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 filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.
U2 - 10.1038/nmeth.2997
DO - 10.1038/nmeth.2997
M3 - Journal article
C2 - 24952909
VL - 11
SP - 868
EP - 874
JO - Nature Methods
JF - Nature Methods
SN - 1548-7091
IS - 8
ER -
ID: 117564096