Shift work, circadian gene variants and risk of breast cancer.
| Authors | Grundy A, Schuetz JM, Lai AS, Janoo-Gilani R, Leach S, Burstyn I, Richardson H, Brooks-Wilson A, Spinelli JJ & Aronson KJ. |
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| Abstract | Circadian (clock) genes have been linked with several functions relevant to cancer, and epidemiologic research has suggested relationships with breast cancer risk for variants in NPAS2, CLOCK, CRY2 and TIMELESS. Increased breast cancer risk has also been observed among shift workers, suggesting potential interactions in relationships of circadian genes with breast cancer. Relationships with breast cancer of 100 SNPs in 14 clock-related genes, as well as potential interactions with shift work history, were investigated in a case-control study (1042 cases, 1051 controls). Odds ratios in an additive genetic model for European-ancestry participants (645 cases, 806 controls) were calculated, using a two-step correction for multiple testing: within each gene through permutation testing (10,000 permutations), and correcting for the false discovery rate across genes. Interactions of genotypes with ethnicity and shift work (<2 years vs ≥2 years) were evaluated individually. Following permutation analysis, two SNPs (rs3816360 in ARNTL and rs11113179 in CRY1) displayed significant associations with breast cancer and one SNP (rs3027188 in PER1) was marginally significant; however, none were significant following adjustment for the false discovery rate. No significant interaction with shift work history was detected. If shift work causes circadian disruption, this was not reflected in associations between clock gene variants and breast cancer risk in this study. Larger studies are needed to assess interactions with longer durations (>30 years) of shift work that have been associated with breast cancer. |
| Journal Name and Citation | Cancer Epidemiol. pii: S1877-7821(13)00066-0. |
| Date of Publication | 2013/05/28 |
| Publication Link | http://ac.els-cdn.com/S1877782113000660/1-s2.0-S1877782113000660-main.pdf?_tid=4e4445e2-09c5-11e3-a0fd-00000aab0f26&acdnat=1377023057_09d31a52fe65959968ead074c5a46937 |