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GWASeq: Targeted Re-sequencing Follow Up to GWAS

Abstract

Background: For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS.

Results: We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer.

Conclusions: Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

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References
1.
Haiman C, Le Marchand L, Yamamato J, Stram D, Sheng X, Kolonel L . A common genetic risk factor for colorectal and prostate cancer. Nat Genet. 2007; 39(8):954-6. PMC: 2391283. DOI: 10.1038/ng2098. View

2.
Jaeger E, Webb E, Howarth K, Carvajal-Carmona L, Rowan A, Broderick P . Common genetic variants at the CRAC1 (HMPS) locus on chromosome 15q13.3 influence colorectal cancer risk. Nat Genet. 2007; 40(1):26-8. DOI: 10.1038/ng.2007.41. View

3.
Botstein D, Risch N . Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet. 2003; 33 Suppl:228-37. DOI: 10.1038/ng1090. View

4.
Yang J, Benyamin B, McEvoy B, Gordon S, Henders A, Nyholt D . Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010; 42(7):565-9. PMC: 3232052. DOI: 10.1038/ng.608. View

5.
Zuk O, Hechter E, Sunyaev S, Lander E . The mystery of missing heritability: Genetic interactions create phantom heritability. Proc Natl Acad Sci U S A. 2012; 109(4):1193-8. PMC: 3268279. DOI: 10.1073/pnas.1119675109. View