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Mediation by differential DNA methylation of known associations between single nucleotide polymorphisms and bladder cancer risk.

BMC Medical Genetics 2020 November 20
BACKGROUND: Though bladder cancer has been the subject of many well-powered genome-wide association studies, the mechanisms involving bladder-cancer-associated single nucleotide polymorphisms (SNPs) remain largely unknown. This study focuses on rs798766, rs401681, rs2294008, and rs8102137, which have been associated with bladder cancer and are also cis-acting methylation quantitative loci (mQTL).

METHODS: Among 412 bladder cancer cases and 424 controls from the Women's Health Initiative (WHI), we assessed whether the effects of these SNPs on bladder cancer are mediated through proximal DNA methylation changes in pre-diagnostic blood at mQTL-associated CpG sites, which we refer to as natural indirect effects (NIEs). We used a multiple-mediator mediation model for each of the four mQTL adjusted for matching variables and potential confounders, including race/ethnicity, smoking status, and pack-years of smoking.

RESULTS: While not statistically significant, our results suggest that substantial proportions of the modest effects of rs401681 (ORNIE  = 1.05, 95% confidence interval (CI) = 0.89 to 1.25; NIE percent = 98.5%) and rs2294008 (ORNIE  = 1.10, 95% CI = 0.90 to 1.33; NIE percent = 77.6%) on bladder cancer risk are mediated through differential DNA methylation at nearby mQTL-associated CpG sites. The suggestive results indicate that rs2294008 may affect bladder cancer risk through a set of genes in the lymphocyte antigen 6 family, which involves genes that bind to and modulate nicotinic acetylcholine receptors. There was no suggestive evidence supporting mediation for rs8102137 and rs798766.

CONCLUSIONS: Though larger studies are necessary, the methylation changes associated with rs401681 and rs2294008 at mQTL-associated CpG sites may be relevant for bladder carcinogenesis, and this study demonstrates how multi-omic data can be integrated to help understand the downstream effects of genetics variants.

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