Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease

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dc.contributor.authorPal, Lipika R
dc.contributor.authorYu, Chen-Hsin
dc.contributor.authorMount, Stephen M
dc.contributor.authorMoult, John
dc.date.accessioned2021-08-24T14:49:24Z
dc.date.available2021-08-24T14:49:24Z
dc.date.issued2015-06-18
dc.description.abstractThere are now over 2000 loci in the human genome where genome wide association studies (GWAS) have found one or more SNPs to be associated with altered risk of a complex trait disease. At each of these loci, there must be some molecular level mechanism relevant to the disease. What are these mechanisms and how do they contribute to disease? Here we consider the roles of three primary mechanism classes: changes that directly alter protein function (missense SNPs), changes that alter transcript abundance as a consequence of variants close-by in sequence, and changes that affect splicing. Missense SNPs are divided into those predicted to have a high impact on in vivo protein function, and those with a low impact. Splicing is divided into SNPs with a direct impact on splice sites, and those with a predicted effect on auxiliary splicing signals. The analysis was based on associations found for seven complex trait diseases in the classic Wellcome Trust Case Control Consortium (WTCCC1) GWA study and subsequent studies and meta-analyses, collected from the GWAS catalog. Linkage disequilibrium information was used to identify possible candidate SNPs for involvement in disease mechanism in each of the 356 loci associated with these seven diseases. With the parameters used, we find that 76% of loci have at least of these mechanisms. Overall, except for the low incidence of direct impact on splice sites, the mechanisms are found at similar frequencies, with changes in transcript abundance the most common. But the distribution of mechanisms over diseases varies markedly, as does the fraction of loci with assigned mechanisms. Many of the implicated proteins have previously been suggested as relevant, but the specific mechanism assignments are new. In addition, a number of new disease relevant proteins are proposed. The high fraction of GWAS loci with proposed mechanisms suggests that these classes of mechanism play a major role. Other mechanism types, such as variants affecting expression of genes remote in the DNA sequence, will contribute in other loci. Each of the identified putative mechanisms provides a hypothesis for further investigation.en_US
dc.description.urihttps://doi.org/10.1186/1471-2164-16-S8-S4
dc.identifierhttps://doi.org/10.13016/hlxe-ycyn
dc.identifier.citationPal, L.R., Yu, CH., Mount, S.M. et al. Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease. BMC Genomics 16, S4 (2015).en_US
dc.identifier.urihttp://hdl.handle.net/1903/27641
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.isAvailableAtCell Biology & Molecular Geneticsen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtCollege of Computer, Mathematical & Natural Sciencesen_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.subjectGWASen_US
dc.subjectSNPsen_US
dc.subjectcomplex trait diseaseen_US
dc.subjectmissenseen_US
dc.subjectexpressionen_US
dc.subjectsplicingen_US
dc.subjectfunctional annotationen_US
dc.titleInsights from GWAS: emerging landscape of mechanisms underlying complex trait diseaseen_US
dc.typeArticleen_US

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