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 < 1 × 10−5 and a genomic sliding window of 1 mega base pair, we identified SNP clusters including at least one SNP associated with height and one SNP associated with either post-menopausal BC or CRC risk (or both). SNPs were annotated to genes using HapMap and GRAIL and analysed for significantly overrepresented pathways using ConsensuspathDB. Twelve clusters including 56 SNPs annotated to 26 genes were prioritised because these included at least one height- and one BC risk- or CRC risk-associated SNP annotated to the same gene. Annotated genes were involved in Indian hedgehog signalling (p-value = 7.78 × 10−7) and several cancer site-specific pathways. This systematic approach identified a limited number of clustered SNPs, which pinpoint potential shared mechanisms linking together the complex phenotypes height, post-menopausal BC and CRC.

Size matters: height, cell number and a person's risk of cancer

“…While the effect per height locus is generally expected to be small, caution is needed in interpreting the results of ever larger (and hence more powerful) genome-wide association studies (GWAS). Recent genetic analyses have indeed identified loci associated with height variation that link to testicular germcell tumour [49], breast cancer [50], post-menopausal breast cancer and colorectal cancer [51], and prostate cancer [52]. Adherence to the indirect-effect hypothesis suggests that these height effect loci are having a pleiotropic effect on cancer risk; however, the direct-effect hypothesis, which is strongly supported by the present analysis, leads to the expectation that genetic height variation affects cancer risk only through its effect on height, and as such provides little or no new insight into cancer risk.…”

Genetic variants involved in extracellular matrix homeostasis play a role in the susceptibility to frozen shoulder: A case‐control study

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Identification of infectious disease-associated host genes using machine learning techniques

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