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Published on: April 19, 2013
Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits
Matteo Di Giovannantonio1,2, Benjamin Hl Harris1, Ping Zhang2
1Computational Biology & Integrative Genomics Lab, Department of Oncology, Medical Science Division, University of Oxford, Oxford, UK.
Background:
Height and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic variants in tumour suppressors and oncogenes increase cancer risk, but little is known about their influence on anthropometric traits.
Methods:
By integrating inherited and somatic cancer genetic data from the Genome-Wide Association Study Catalog, expression Quantitative Trait Loci databases and the Cancer Gene Census, we identify SNPs that associate with different cancer types and differential gene expression in at least one tissue type, and explore the potential pleiotropic associations of these SNPs with anthropometric traits through SNP-wise association in a cohort of 500,000 individuals.
Results:
We identify three regulatory SNPs for three important cancer genes, FANCA, MAP3K1 and TP53 that associate with both anthropometric traits and cancer risk. Of particular interest, we identify a previously unrecognised strong association between the rs78378222[C] SNP in the 3' untranslated region (3'-UTR) of TP53 and both increased risk for developing non-melanomatous skin cancer (OR=1.36 (95% 1.31 to 1.41), adjusted p=7.62E-63), brain malignancy (OR=3.12 (2.22 to 4.37), adjusted p=1.43E-12) and increased standing height (adjusted p=2.18E-24, beta=0.073±0.007), lean body mass (adjusted p=8.34E-37, beta=0.073±0.005) and basal metabolic rate (adjusted p=1.13E-31, beta=0.076±0.006), thus offering a novel genetic link between these anthropometric traits and cancer risk.
Conclusion:
Our results clearly demonstrate that heritable variants in key cancer genes can associate with both differential cancer risk and anthropometric traits in the general population, thereby lending support for a genetic basis for linking these human phenotypes.
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