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A systematic SNP selection approach to identify mechanisms underlying disease aetiology: linking height to post-menopausal breast and colorectal cancer risk.


ABSTRACT: Data from GWAS suggest that SNPs associated with complex diseases or traits tend to co-segregate in regions of low recombination, harbouring functionally linked gene clusters. This phenomenon allows for selecting a limited number of SNPs from GWAS repositories for large-scale studies investigating shared mechanisms between diseases. For example, we were interested in shared mechanisms between adult-attained height and post-menopausal breast cancer (BC) and colorectal cancer (CRC) risk, because height is a risk factor for these cancers, though likely not a causal factor. Using SNPs from public GWAS repositories at p-values?

SUBMITTER: Elands RJ 

PROVIDER: S-EPMC5259777 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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A systematic SNP selection approach to identify mechanisms underlying disease aetiology: linking height to post-menopausal breast and colorectal cancer risk.

Elands Rachel J J RJ   Simons Colinda C J M CC   Riemenschneider Mona M   Isaacs Aaron A   Schouten Leo J LJ   Verhage Bas A BA   Van Steen Kristel K   Godschalk Roger W L RW   van den Brandt Piet A PA   Stoll Monika M   Weijenberg Matty P MP  

Scientific reports 20170124


Data from GWAS suggest that SNPs associated with complex diseases or traits tend to co-segregate in regions of low recombination, harbouring functionally linked gene clusters. This phenomenon allows for selecting a limited number of SNPs from GWAS repositories for large-scale studies investigating shared mechanisms between diseases. For example, we were interested in shared mechanisms between adult-attained height and post-menopausal breast cancer (BC) and colorectal cancer (CRC) risk, because h  ...[more]

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