Dataset Information

Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228?951 Women of European Descent.

ABSTRACT: BACKGROUND:DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. METHODS:Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n?=?1595). The prediction models were validated using data from the Women's Health Initiative (n?=?883). We applied these models to genomewide association study (GWAS) data of 122?977 breast cancer patients and 105?974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided. RESULTS:Of the 62?938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P?less than?7.94?×?10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. CONCLUSION:Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

SUBMITTER: Yang Y

PROVIDER: S-EPMC7073907 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent.

Yang Yaohua Y Wu Lang L Shu Xiao-Ou XO Cai Qiuyin Q Shu Xiang X Li Bingshan B Guo Xingyi X Ye Fei F Michailidou Kyriaki K Bolla Manjeet K MK Wang Qin Q Dennis Joe J Andrulis Irene L IL Brenner Hermann H Chenevix-Trench Georgia G Campa Daniele D Castelao Jose E JE Gago-Dominguez Manuela M Dörk Thilo T Hollestelle Antoinette A Lophatananon Artitaya A Muir Kenneth K Neuhausen Susan L SL Olsson Håkan H Sandler Dale P DP Simard Jacques J Kraft Peter P Pharoah Paul D P PDP Easton Douglas F DF Zheng Wei W Long Jirong J

Journal of the National Cancer Institute 20200301 3

<h4>Background</h4>DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk.<h4>Methods</h4>Statistical models were built to predict levels of DNA methylation marks using geneti ...[more]

PMID: 31143935

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Project description:BACKGROUND:Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. METHODS:We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases? = ?46,325, controls? = ?42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. RESULTS:In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]? = ?0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32?×?10-10). The associations were similar for both premenopausal (OR?? = ??0.44, 95% CI:0.31-0.62, p? = ?9.91?×?10-8) and postmenopausal breast cancer (OR? = ?0.57, 95%?CI: 0.46-0.71, p? = ?1.88?×?10-8). This association was replicated in the data from the DRIVE consortium (OR? = ?0.72, 95%?CI: 0.60-0.84, p?? = ??1.64?×?10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p?<?0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. CONCLUSIONS:BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.

Project description:BackgroundThe literature on associations of circulating concentrations of minerals and vitamins with risk of colorectal cancer is limited and inconsistent. Evidence from randomized controlled trials (RCTs) to support the efficacy of dietary modification or nutrient supplementation for colorectal cancer prevention is also limited.ObjectivesTo complement observational and RCT findings, we investigated associations of genetically predicted concentrations of 11 micronutrients (β-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B-6, vitamin B-12, and zinc) with colorectal cancer risk using Mendelian randomization (MR).MethodsTwo-sample MR was conducted using 58,221 individuals with colorectal cancer and 67,694 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. Inverse variance-weighted MR analyses were performed with sensitivity analyses to assess the impact of potential violations of MR assumptions.ResultsNominally significant associations were noted for genetically predicted iron concentration and higher risk of colon cancer [ORs per SD (ORSD): 1.08; 95% CI: 1.00, 1.17; P value = 0.05] and similarly for proximal colon cancer, and for vitamin B-12 concentration and higher risk of colorectal cancer (ORSD: 1.12; 95% CI: 1.03, 1.21; P value = 0.01) and similarly for colon cancer. A nominally significant association was also noted for genetically predicted selenium concentration and lower risk of colon cancer (ORSD: 0.98; 95% CI: 0.96, 1.00; P value = 0.05) and similarly for distal colon cancer. These associations were robust to sensitivity analyses. Nominally significant inverse associations were observed for zinc and risk of colorectal and distal colon cancers, but sensitivity analyses could not be performed. None of these findings survived correction for multiple testing. Genetically predicted concentrations of β-carotene, calcium, copper, folate, magnesium, phosphorus, and vitamin B-6 were not associated with disease risk.ConclusionsThese results suggest possible causal associations of circulating iron and vitamin B-12 (positively) and selenium (inversely) with risk of colon cancer.

Project description:BackgroundInflammation plays a pivotal role in the pathogenesis of cancer. Though previous studies have reported a link between several inflammatory biomarkers and risk of certain types of cancer, there is a lack of systematic investigation. Therefore, we aimed to assess the role of circulating cytokines on the risk of cancer using a two-sample Mendelian randomization (MR) approach.MethodWe used genetic variants associated with circulating levels of cytokines from a meta-analysis of genome-wide association studies (GWASs) of 8,293 Finns as instrumental variables. Summary level data of 20 site-specific cancer were obtained from the UK BioBank including up to 456,348 participants of European ancestry. We performed two-sample MR analyses using inverse-variance weighted (IVW) method as the main method, followed by weighted-median and likelihood-based methods as sensitivity analysis. Pleiotropic and outlier variants were assessed by MR-Egger regression and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test.Results224 genetic variants associated with 27 circulating cytokines achieving genome-wide significance (P<5×10-8) were used as IVs. After Bonferroni correction, genetically predicted high levels of interleukin-18 (IL-18) were associated with a decreased risk of acute myeloid leukemia (odds ratio (OR) per 1 standard deviation (SD) increase = 0.55, 95% confidence interval (CI):0.43-0.69, P=5.39×10-7), and circulating levels of IL-17 were associated with altered stomach cancer risk (OR per 1 SD increase = 0.15, 95% CI: 0.07-0.36, P=1.25×10-5) by IVW. Results were stable across sensitivity analyses, and MR-Egger regression did not suggest the presence of directional pleiotropy. Additionally, we found suggestive evidence for 48 cytokine-cancer associations including tumor necrosis factor related apoptosis-inducing ligand (TRAIL) and cutaneous T-cell attracting chemokine (CTACK) with the risk of several types of cancer (9.26×10-5≤P<0.05).ConclusionsBy using a genetic epidemiological approach, our study systematically evaluated the role of circulating cytokines on the risk of cancer, and provided clues for potential therapeutic targets. However, the exact underlying biological mechanism warrants further investigation.

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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228?951 Women of European Descent.

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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent.

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