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Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics.

ABSTRACT: 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.

SUBMITTER: Lundby A

PROVIDER: S-EPMC4117722 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics.

Lundby Alicia A Rossin Elizabeth J EJ Steffensen Annette B AB Acha Moshe Rav MR Newton-Cheh Christopher C Pfeufer Arne A Lynch Stacey N SN Olesen Søren-Peter SP Brunak Søren S Ellinor Patrick T PT Jukema J Wouter JW Trompet Stella S Ford Ian I Macfarlane Peter W PW Krijthe Bouwe P BP Hofman Albert A Uitterlinden André G AG Stricker Bruno H BH Nathoe Hendrik M HM Spiering Wilko W Daly Mark J MJ Asselbergs Folkert W FW van der Harst Pim P Milan David J DJ de Bakker Paul I W PI Lage Kasper K Olsen Jesper V JV

Nature methods 20140622 8

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 gene ...[more]

PMID: 24952909

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Project description:ObjectiveTo explore the relationship between sleep habits (sleep duration, sleep efficiency, sleep onset timing) and ischemic stroke, and whether there is an interaction between sleep habits and ischemic stroke susceptibility gene loci.MethodsA questionnaire survey, physical examination, blood biochemical testing and genotyping were conducted among rural residents in Beijing, and the gene loci of ischemic stroke suggested by previous genome-wide association studies (GWAS) were screened. Multivariable generalized linear model was used to analyze the correlation between sleep habits, sleep-gene interaction and ischemic stroke.ResultsA total of 4 648 subjects with an average age of (58.5±8.7) years were enrolled, including 1 316 patients with ischemic stroke. Compared with non-stroke patients, stroke patients with sleep duration ≥9 hours, sleep efficiency < 80%, and sleep onset timing earlier than 22:00 accounted for a higher proportion (P < 0.05). There was no significant association between sleep duration and risk of ischemic stroke (OR=1.04, 95%CI: 0.99-1.10, P=0.085). Sleep efficiency was inversely associated with the risk of ischemic stroke (OR=0.18, 95%CI: 0.06-0.53, P=0.002). The risk of ischemic stroke in the subjects with sleep efficiency < 80% was 1.47-fold (95%CI: 1.03-2.10, P=0.033) of that in the subjects with sleep efficiency ≥80%. Falling asleep earlier than 22:00 was associated with 1.26 times greater risk of stroke than falling asleep between 22:00 and 22:59 (95%CI: 1.04-1.52, P=0.017). Multifactorial adjustment model showed that rs579459 on ABO gene had an interaction with sleep time (P for interaction =0.040). When there were two T alleles for rs579459 on the ABO gene, those who fell asleep before 22:00 had 1.56 times (95%CI: 1.20-2.04, P=0.001) the risk of stroke compared with those who fell asleep between 22:00 and 22:59, and there was no significant difference when the number of pathogenic alleles was 0 or 1. In the model adjusted only for gender, age and family structure, sleep duration and the number of T allele rs2634074 on PITX2 gene had an interaction with ischemic stroke (P for interaction=0.033).ConclusionDecreased sleep efficiency is associated with increased risk of ischemic stroke, and falling asleep earlier than 22:00 is associated with higher risk of ischemic stroke. Sleep onset timing interacted with rs579459 in ABO gene and the risk of ischemic stroke. Sleep duration and PITX2 rs2634074 may have a potential interaction with ischemic stroke risk.

Project description:BACKGROUND:To identify loci associated with abdominal fat and replicate prior findings, we performed genome-wide association (GWA) studies of abdominal fat traits: subcutaneous adipose tissue (SAT); visceral adipose tissue (VAT); total adipose tissue (TAT) and visceral to subcutaneous adipose tissue ratio (VSR). SUBJECTS AND METHODS:Sex-combined and sex-stratified analyses were performed on each trait with (TRAIT-BMI) or without (TRAIT) adjustment for body mass index (BMI), and cohort-specific results were combined via a fixed effects meta-analysis. A total of 2513 subjects of European descent were available for the discovery phase. For replication, 2171 European Americans and 772 African Americans were available. RESULTS:A total of 52 single-nucleotide polymorphisms (SNPs) encompassing 7 loci showed suggestive evidence of association (P<1.0 × 10(-6)) with abdominal fat in the sex-combined analyses. The strongest evidence was found on chromosome 7p14.3 between a SNP near BBS9 gene and VAT (rs12374818; P=1.10 × 10(-7)), an association that was replicated (P=0.02). For the BMI-adjusted trait, the strongest evidence of association was found between a SNP near CYCSP30 and VAT-BMI (rs10506943; P=2.42 × 10(-7)). Our sex-specific analyses identified one genome-wide significant (P<5.0 × 10(-8)) locus for SAT in women with 11 SNPs encompassing the MLLT10, DNAJC1 and EBLN1 genes on chromosome 10p12.31 (P=3.97 × 10(-8) to 1.13 × 10(-8)). The THNSL2 gene previously associated with VAT in women was also replicated (P=0.006). The six gene/loci showing the strongest evidence of association with VAT or VAT-BMI were interrogated for their functional links with obesity and inflammation using the Biograph knowledge-mining software. Genes showing the closest functional links with obesity and inflammation were ADCY8 and KCNK9, respectively. CONCLUSIONS:Our results provide evidence for new loci influencing abdominal visceral (BBS9, ADCY8, KCNK9) and subcutaneous (MLLT10/DNAJC1/EBLN1) fat, and confirmed a locus (THNSL2) previously reported to be associated with abdominal fat in women.

Dataset Information

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics.

Publications

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics.

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