An epigenome-wide study of body mass index and DNA methylation in blood using participants from the Sister Study cohort.

BACKGROUND/OBJECTIVES: The relationship between obesity and chronic disease risk is well-established; the underlying biological mechanisms driving this risk increase may include obesity-related epigenetic modifications. To explore this hypothesis, we conducted a genome-wide analysis of DNA methylation and body mass index (BMI) using data from a subset of women in the Sister Study. SUBJECTS/METHODS: The Sister Study is a cohort of 50 884 US women who had a sister with breast cancer but were free of breast cancer themselves at enrollment. Study participants completed examinations which included measurements of height and weight, and provided blood samples. Blood DNA methylation data generated with the Illumina Infinium HumanMethylation27 BeadChip array covering 27,589 CpG sites was available for 871 women from a prior study of breast cancer and DNA methylation. To identify differentially methylated CpG sites associated with BMI, we analyzed this methylation data using robust linear regression with adjustment for age and case status. For those CpGs passing the false discovery rate significance level, we examined the association in a replication set comprised of a non-overlapping group of 187 women from the Sister Study who had DNA methylation data generated using the Infinium HumanMethylation450 BeadChip array. Analysis of this expanded 450 K array identified additional BMI-associated sites which were investigated with targeted pyrosequencing. RESULTS: Four CpG sites reached genome-wide significance (false discovery rate (FDR) q<0.05) in the discovery set and associations for all four were significant at strict Bonferroni correction in the replication set. An additional 23 sites passed FDR in the replication set and five were replicated by pyrosequencing in the discovery set. Several of the genes identified including ANGPT4, RORC, SOCS3, FSD2, XYLT1, ABCG1, STK39, ASB2 and CRHR2 have been linked to obesity and obesity-related chronic diseases. CONCLUSIONS: Our findings support the hypothesis that obesity-related epigenetic differences are detectable in blood and may be related to risk of chronic disease.

Combined effect of low-penetrant SNPs on breast cancer risk.

BACKGROUND: Although many low-penetrant genetic risk factors for breast cancer have been discovered, knowledge about the effect of multiple risk alleles is limited, especially in women <50 years. We therefore investigated the association between multiple risk alleles and breast cancer risk as well as individual effects according to age-approximated pre- and post-menopausal status. METHODS: Ten previously described breast cancer-associated single-nucleotide polymorphisms (SNPs) were analysed in a joint European biobank-based study comprising 3584 breast cancer cases and 5063 cancer-free controls. Genotyping was performed using MALDI-TOF mass spectrometry, and odds ratios were estimated using logistic regression. RESULTS: Significant associations with breast cancer were confirmed for 7 of the 10 SNPs. Analysis of the joint effect of the original 10 as well as the statistically significant 7 SNPs (rs2981582, rs3803662, rs889312, rs13387042, rs13281615, rs3817198 and rs981782) found a highly significant trend for increasing breast cancer risk with increasing number of risk alleles (P-trend 5.6 × 10(-20) and 1.5 × 10(-25), respectively). Odds ratio for breast cancer of 1.84 (95% confidence interval (CI): 1.59-2.14; 10 SNPs) and 2.12 (95% CI: 1.80-2.50; 7 SNPs) was seen for the maximum vs the minimum number of risk alleles. Additionally, one of the examined SNPs (rs981782 in HCN1) had a protective effect that was significantly stronger in premenopausal women (P-value: 7.9 × 10(-4)). CONCLUSION: The strongly increasing risk seen when combining many low-penetrant risk alleles supports the polygenic inheritance model of breast cancer.