Light exposure at night may have an adverse effect on breast cancer risk through suppression of melatonin,
a hormone that is intimately linked to the circadian system and demonstrates cancer-protective effects.
Observational studies have consistently associated night work with an increase in breast cancer risk. To
date, nine candidate genes for human circadian dysrhythmias have been identified, and common mutations
of four of those were associated with seasonal affective disorder, familial advanced sleep phase syndrome,
and diurnal preference. In mice, loss of mPer2 function results in increased tumor development and
deficiencies in DMAdamage responses. In humans, data, although still sparse, indicate a positive
association between certain clock gene mutations and breast cancer risk. Thus, future investigations of the
associations between breast cancer risk and circadian disruption, such as experienced by night workers,
must take into consideration the role of clock genes. In this study, we propose to draw on the existing data
and DMAsamples from the ongoing Nurses Health Study II (NHS II) to conduct a nested case-control study
that evaluates associations of common variants in candidate genes of the circadian clock with breast cancer
risk, as well as interactions with night shift work. We will assess how the nurses' breast cancer risk is
influenced by different polymorphisms of clock genes and will characterize differences in these associations
according to night work status of nurses. To further study the relationship between molecular rhythmicity and
other markers of the circadian system, we will also assess the association of these genes with variations in
melatonin levels. No other prospective cohort study can provide superior resources to answer these
questions: in the NHSII cohort study, night shift work status has been assessed biennially from 1989
onwards, melatonin levels have been measured in a subgroup of women, and an extensive collection of
DNA is currently under way that will provide DNA from 1,108 breast cancer cases and their 1:3 matched
controls. The results from this study could help identify individuals who are more susceptible to night work
than others, based on their genetic profile.
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