Polygenic risk scores stratify breast cancer risk among women with benign breast disease.

PURPOSE: Most breast biopsies are diagnosed as benign breast disease (BBD), with 1.5- to fourfold increased breast cancer (BC) risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in BC risk assessment of these patients. We assessed whether a 313-SNP polygenic risk score (PRS) stratifies risk of BBD patients. PATIENTS AND METHODS: We pooled data from five Breast Cancer Association Consortium case-control studies (mean age = 59.9 years), including 6,706 cases and 8,488 controls. Using logistic regression, we estimated BC risk associations by self-reported BBD history and strata of PRS, with median PRS category among women without BBD as the referent. We assessed interactions and mediation of BBD and PRS with BC risk. RESULTS: BBD history was associated with increased BC risk (OR = 1.48, 95% CI: 1.37-1.60; p < .001). PRS increased BC risk, irrespective of BBD history (p-interaction = 0.48), with minimal evidence of mediation of either factor by the other. Women with BBD and PRS in the highest tertile had over 2-fold increased odds of BC (OR = 2.73, 95% CI: 2.41-3.09) and those with BBD and PRS in the lowest tertile experienced reduced BC risk (OR = 0.79, 95% CI: 0.70-0.91), compared to the reference group. Women with BBD and PRS in the highest decile had a 3.7- fold increase (95% CI: 3.00-4.61) compared to those with median PRS without BBD. CONCLUSION: BC risks are elevated among women with BBD and increase progressively with PRS, suggesting that optimal combinations of these factors may improve risk stratification.

Circulating inflammatory and immune response proteins and endometrial cancer risk: a nested case-control study and Mendelian randomization analyses.

BACKGROUND: Inflammation and immune dysregulation are hypothesized contributors to endometrial carcinogenesis; however, the precise underlying mechanisms remain unclear. METHODS: We measured pre-diagnostically 152 plasma protein biomarkers in 624 endometrial cancer case-control pairs nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Odds ratios (ORs) were estimated using conditional logistic regression, accounting for confounding and multiple comparisons. Proteins considered as associated with endometrial cancer risk were further tested in a two-sample Mendelian randomization (MR) analysis using summary data from the UK Biobank (n = 52,363) and the Endometrial Cancer Association Consortium (12,270 cases and 46,126 controls). FINDINGS: In the EPIC nested case-control study, IL-6 [OR per NPX (doubling of concentration) = 1.28 (95% confidence interval (CI) 1.03-1.57)], HGF [1.48 (1.06-2.07)], PIK3AP1 [1.22 (1.00-1.50)] and CLEC4G [1.52 (1.00-2.32)] were positively associated; HSD11B1 [0.67 (0.49-0.91)], SCF [0.68 (0.49-0.94)], and CCL25 [0.80 (0.65-0.99)] were inversely associated with endometrial cancer risk; all estimates had multiple comparisons adjusted P-value > 0.05. In complementary MR analysis, IL-6 [OR per inverse-rank normalized NPX = 1.19 (95% CI 1.04-1.36)] and HSD11B1 [0.91 (0.84-0.99)] were associated with endometrial cancer risk. INTERPRETATION: Altered IL-6 signalling and reduced glucocorticoid activity via HSD11B1 might play important roles in endometrial carcinogenesis. FUNDING: Funding for IIG_FULL_2021_008 was obtained from Wereld Kanker Onderzoek Fonds (WKOF), as part of the World Cancer Research Fund International grant programme; Funding for INCA_15849 was obtained from Institut National du Cancer (INCa).

Circulating endogenous sex steroids and risk of differentiated thyroid carcinoma in men and women.

Thyroid cancer (TC) is substantially more common in women than in men, pointing to a possible role of sex steroid hormones. We investigated the association between circulating sex steroid hormones, sex hormone binding globulin (SHBG) and the risk of differentiated TC in men and women within the European Prospective Investigation into Cancer and nutrition (EPIC) cohort. During follow-up, we identified 333 first primary incident cases of differentiated TC (152 in pre/peri-menopausal women, 111 in post-menopausal women, and 70 in men) and 706 cancer-free controls. Women taking exogenous hormones at blood donation were excluded. Plasma concentrations of testosterone, androstenedione, dehydroepiandrosterone, estradiol, estrone and progesterone (in pre-menopausal women only) were performed using liquid chromatography/mass spectrometry method. SHBG concentrations were measured by immunoassay. Odds ratios (ORs) were estimated using conditional logistic regression models adjusted for possible confounders. No significant associations were observed in men and postmenopausal women, while a borderline significant increase in differentiated TC risk was observed with increasing testosterone (adjusted OR T3 vs T1: 1.68, 95% CI: 0.96-2.92, ptrend = .06) and androstenedione concentrations in pre/perimenopausal women (adjusted OR T3 vs T1: 1.78, 95% CI: 0.96-3.30, ptrend = .06, respectively). A borderline decrease in risk was observed for the highest progesterone/estradiol ratio (adjusted OR T3 vs T1: 0.54, 95% CI: 0.28-1.05, ptrend = .07). Overall, our results do not support a major role of circulating sex steroids in the etiology of differentiated TC in post-menopausal women and men but may suggest an involvement of altered sex steroid production in pre-menopausal women.

Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer.

Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483R ∧ rs1473473D ∧ rs3729931D: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.

Investigation of common genetic risk factors between thyroid traits and breast cancer.

Breast cancer (BC) risk is suspected to be linked to thyroid disorders, however observational studies exploring the association between BC and thyroid disorders gave conflicting results. We proposed an alternative approach by investigating the shared genetic risk factors between BC and several thyroid traits. We report a positive genetic correlation between BC and thyroxine (FT4) levels (corr = 0.13, p-value = 2.0 × 10-4) and a negative genetic correlation between BC and thyroid-stimulating hormone (TSH) levels (corr = -0.09, p-value = 0.03). These associations are more striking when restricting the analysis to estrogen receptor-positive BC. Moreover, the polygenic risk scores (PRS) for FT4 and hyperthyroidism are positively associated to BC risk (OR = 1.07, 95%CI: 1.00-1.13, p-value = 2.8 × 10-2 and OR = 1.04, 95%CI: 1.00-1.08, p-value = 3.8 × 10-2, respectively), while the PRS for TSH is inversely associated to BC risk (OR = 0.93, 95%CI: 0.89-0.97, p-value = 2.0 × 10-3). Using the PLACO method, we detected 49 loci associated to both BC and thyroid traits (p-value < 5 × 10-8), in the vicinity of 130 genes. An additional colocalization and gene-set enrichment analyses showed a convincing causal role for a known pleiotropic locus at 2q35 and revealed an additional one at 8q22.1 associated to both BC and thyroid cancer. We also found two new pleiotropic loci at 14q32.33 and 17q21.31 that were associated to both TSH levels and BC risk. Enrichment analyses and evidence of regulatory signals also highlighted brain tissues and immune system as candidates for obtaining associations between BC and TSH levels. Overall, our study sheds light on the complex interplay between BC and thyroid traits and provides evidence of shared genetic risk between those conditions.

GCPBayes pipeline: a tool for exploring pleiotropy at the gene level.

Cross-phenotype association using gene-set analysis can help to detect pleiotropic genes and inform about common mechanisms between diseases. Although there are an increasing number of statistical methods for exploring pleiotropy, there is a lack of proper pipelines to apply gene-set analysis in this context and using genome-scale data in a reasonable running time. We designed a user-friendly pipeline to perform cross-phenotype gene-set analysis between two traits using GCPBayes, a method developed by our team. All analyses could be performed automatically by calling for different scripts in a simple way (using a Shiny app, Bash or R script). A Shiny application was also developed to create different plots to visualize outputs from GCPBayes. Finally, a comprehensive and step-by-step tutorial on how to use the pipeline is provided in our group's GitHub page. We illustrated the application on publicly available GWAS (genome-wide association studies) summary statistics data to identify breast cancer and ovarian cancer susceptibility genes. We have shown that the GCPBayes pipeline could extract pleiotropic genes previously mentioned in the literature, while it also provided new pleiotropic genes and regions that are worthwhile for further investigation. We have also provided some recommendations about parameter selection for decreasing computational time of GCPBayes on genome-scale data.

Genetic factors for differentiated thyroid cancer in French Polynesia: new candidate loci.

Background: Populations of French Polynesia (FP), where France performed atmospheric tests between 1966 and 1974, experience a high incidence of differentiated thyroid cancer (DTC). However, up to now, no sufficiently large study of DTC genetic factors in this population has been performed to reach definitive conclusion. This research aimed to analyze the genetic factors of DTC risk among the native FP populations. Methods: We analyzed more than 300 000 single nucleotide polymorphisms (SNPs) genotyped in 283 DTC cases and 418 matched controls born in FP, most being younger than 15 years old at the time of the first nuclear tests. We analyzed the genetic profile of our cohort to identify population subgroups. We then completed a genome-wide analysis study on the whole population. Results: We identified a specific genetic structure in the FP population reflecting admixture from Asian and European populations. We identified three regions associated with increased DTC risk at 6q24.3, 10p12.2, and 17q21.32. The lead SNPs at these loci showed respective p-values of 1.66 × 10-7, 2.39 × 10-7, and 7.19 × 10-7 and corresponding odds ratios of 2.02, 1.89, and 2.37. Conclusion: Our study results suggest a role of the loci 6q24.3, 10p12.2 and 17q21.32 in DTC risk. However, a whole genome sequencing approach would be better suited to characterize these factors than genotyping with microarray chip designed for the Caucasian population. Moreover, the functional impact of these three new loci needs to be further explored and validated.

Association of Mediterranean diet with survival after breast cancer diagnosis in women from nine European countries: results from the EPIC cohort study.

BACKGROUND: The Mediterranean diet has been associated with lower risk of breast cancer (BC) but evidence from prospective studies on the role of Mediterranean diet on BC survival remains sparse and conflicting. We aimed to investigate whether adherence to Mediterranean diet prior to diagnosis is associated with overall and BC-specific mortality. METHODS: A total of 13,270 incident breast cancer cases were identified from an initial sample of 318,686 women in 9 countries from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Adherence to Mediterranean diet was estimated through the adapted relative Mediterranean diet (arMED), a 16-point score that includes 8 key components of the Mediterranean diet and excludes alcohol. The degree of adherence to arMED was classified as low (score 0-5), medium (score 6-8), and high (score 9-16). Multivariable Cox proportional hazards models were used to analyze the association between the arMED score and overall mortality, and Fine-Gray competing risks models were applied for BC-specific mortality. RESULTS: After a mean follow-up of 8.6 years from diagnosis, 2340 women died, including 1475 from breast cancer. Among all BC survivors, low compared to medium adherence to arMED score was associated with a 13% higher risk of all-cause mortality (HR 1.13, 95%CI 1.01-1.26). High compared to medium adherence to arMED showed a non-statistically significant association (HR 0.94; 95% CI 0.84-1.05). With no statistically significant departures from linearity, on a continuous scale, a 3-unit increase in the arMED score was associated with an 8% reduced risk of overall mortality (HR3-unit 0.92, 95% CI: 0.87-0.97). This result sustained when restricted to postmenopausal women and was stronger among metastatic BC cases (HR3-unit 0.81, 95% CI: 0.72-0.91). CONCLUSIONS: Consuming a Mediterranean diet before BC diagnosis may improve long-term prognosis, particularly after menopause and in cases of metastatic breast cancer. Well-designed dietary interventions are needed to confirm these findings and define specific dietary recommendations.

Associations between dietary inflammatory scores and biomarkers of inflammation in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

BACKGROUND: Since the first version of the dietary inflammatory index (DII®) developed in the past decade, several other versions have been developed. However, to date no study has attempted to compare these versions with respect to their associations with biomarkers of inflammation. OBJECTIVE: We aimed to investigate the relationship between four dietary inflammatory scores [DII, two energy-adjusted derivatives (E-DII and E-DIIr), and the Inflammatory Score of the Diet (ISD)], and circulating levels of several inflammatory markers and adipokines. METHODS: This study included 17 637 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with at least one marker of inflammation measured in blood. Associations between the four scores and C-reactive protein (CRP), interleukin (IL)6, IL10, IL1RA, tumor necrosis factor-α (TNFα), soluble tumor necrosis factor receptor-1 (sTNFR1), sTNFR2, leptin, soluble leptin receptor (sLeptin R), adiponectin, and High Molecular Weight (HMW) adiponectin were evaluated using multivariable linear regressions adjusted for potential confounders. RESULTS: Positive associations were observed between the four dietary inflammatory scores and levels of CRP, IL6, sTNFR1, sTNFR2 and leptin. However, only the DII and the ISD were positively associated with IL1RA levels and only the DII and the E-DIIr were positively associated with TNFα levels. The proportion of variance of each biomarker explained by the scores was lower than 2%, which was equivalent to the variance explained by smoking status but much lower than that explained by body mass index. CONCLUSIONS: Our results suggest that the four dietary inflammatory scores were associated with some biomarkers of inflammation and could be used to assess the inflammatory potential of diet in European adults but are not sufficient to capture the inflammatory status of an individual. These findings can help to better understand the inflammatory potential of diet, but they need to be replicated in studies with repeated dietary measurements.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer.

BACKGROUND: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS: Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding. INTERPRETATION: The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease. FUNDING: Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease.

BACKGROUND: Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors. OBJECTIVE: To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study. RESULTS: All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS313 in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively). CONCLUSION: Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.

Blood cell DNA methylation biomarkers in preclinical malignant pleural mesothelioma: The EPIC prospective cohort.

Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer mainly caused by asbestos exposure. Specific and sensitive noninvasive biomarkers may facilitate and enhance screening programs for the early detection of cancer. We investigated DNA methylation (DNAm) profiles in MPM prediagnostic blood samples in a case-control study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) cohort, aiming to characterise DNAm biomarkers associated with MPM. From the EPIC cohort, we included samples from 135 participants who developed MPM during 20 years of follow-up and from 135 matched, cancer-free, controls. For the discovery phase we selected EPIC participants who developed MPM within 5 years from enrolment (n = 36) with matched controls. We identified nine differentially methylated CpGs, selected by 10-fold cross-validation and correlation analyses: cg25755428 (MRI1), cg20389709 (KLF11), cg23870316, cg13862711 (LHX6), cg06417478 (HOOK2), cg00667948, cg01879420 (AMD1), cg25317025 (RPL17) and cg06205333 (RAP1A). Receiver operating characteristic (ROC) analysis showed that the model including baseline characteristics (age, sex and PC1wbc) along with the nine MPM-related CpGs has a better predictive value for MPM occurrence than the baseline model alone, maintaining some performance also at more than 5 years before diagnosis (area under the curve [AUC] < 5 years = 0.89; AUC 5-10 years = 0.80; AUC >10 years = 0.75; baseline AUC range = 0.63-0.67). DNAm changes as noninvasive biomarkers in prediagnostic blood samples of MPM cases were investigated for the first time. Their application can improve the identification of asbestos-exposed individuals at higher MPM risk to possibly adopt more intensive monitoring for early disease identification.

Design and quality control of large-scale two-sample Mendelian randomization studies.

Background: Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods: We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results: We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions: In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women.

Background: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. Methods: We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. Results: After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). Conclusion: In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Impact: Our study suggests a limited role of gene-environment interactions in breast cancer risk.

Adherence to mediterranean diet and the risk of differentiated thyroid cancer in a European cohort: The EPIC study.

Background: The Mediterranean diet (MD) has been proposed as a healthy diet with a potential to lower the incidence of several types of cancer, but there is no data regarding thyroid cancer (TC). We investigated the association between MD adherence, and its components, and the differentiated TC risk within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: Over 450,000 men and women from nine European countries were followed up for a mean of 14.1 years, during which 712 differentiated TC cases were identified. Adherence to MD was estimated using the relative MD (rMED) score, an 18-point scale including alcohol, and the adapted rMED (arMED) score, a 16-point scale excluding alcohol. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression models adjusted for potential confounding factors. Results: Adherence to the arMED score was not associated with the risk of differentiated TC (HRhigh vs. low adherence = 0.94, 95% CI: 0.70-1.25; p-trend 0.27), while a suggestive, but non-statistically significant inverse relationship was observed with rMED (HRhigh vs. low adherence = 0.88, 95% CI: 0.68-1.14; p-trend 0.17). Low meat (HRlow vs. high meat intake = 0.81, 95% CI: 0.67-0.99; p-trend = 0.04) and moderate alcohol (HRmoderate vs. non-moderate intake = 0.88, 95% CI: 0.75-1.03) intake were related with lower differentiated TC risk. Conclusions: Our study shows that a high adherence to MD is not strongly related to differentiated TC risk, although further research is required to confirm the impact of MD and, especially, meat intake in TC risk.

Cigarette Smoking and Endometrial Cancer Risk: Observational and Mendelian Randomization Analyses.

BACKGROUND: Current epidemiologic evidence indicates that smoking is associated with a lower endometrial cancer risk. However, it is unknown if this association is causal or confounded. To further elucidate the role of smoking in endometrial cancer risk, we conducted complementary observational and Mendelian randomization (MR) analyses. METHODS: The observational analyses included 286,415 participants enrolled in the European Prospective Investigation into Cancer and Nutrition and 179,271 participants in the UK Biobank, and multivariable Cox proportional hazards models were used. In two-sample MR analyses, genetic variants robustly associated with lifetime amount of smoking (n = 126 variants) and ever having smoked regularly (n = 112 variants) were selected and their association with endometrial cancer risk (12,906 cancer/108,979 controls from the Endometrial Cancer Association Consortium) was examined. RESULTS: In the observational analysis, lifetime amount of smoking and ever having smoked regularly were associated with a lower endometrial cancer risk. In the MR analysis accounting for body mass index, a genetic predisposition to a higher lifetime amount of smoking was not associated with endometrial cancer risk (OR per 1-SD increment: 1.15; 95% confidence interval: 0.91-1.44). Genetic predisposition to ever having smoked regularly was not associated with risk of endometrial cancer. CONCLUSIONS: Smoking was inversely associated with endometrial cancer in the observational analyses, although unsupported by the MR. Additional studies are required to better understand the possible confounders and mechanisms underlying the observed associations between smoking and endometrial cancer. IMPACT: The results from this analysis indicate that smoking is unlikely to be causally linked with endometrial cancer risk.

Inflammatory potential of the diet and association with risk of differentiated thyroid cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

PURPOSE: Chronic inflammation is thought to initiate or promote differentiated thyroid cancer (DTC) and previous studies have shown that diet can modulate this inflammatory process. We aimed to evaluate the association of several dietary scores reflecting the inflammatory potential of the diet with DTC risk. METHODS: Within the EPIC cohort, 450,063 participants were followed during a mean period of 14 years, and 712 newly incident DTC cases were identified. Associations between four dietary inflammatory scores [the dietary inflammatory index (DII®) and two energy-adjusted derivatives (the E-DIIr and the E-DIId), and the Inflammatory Score of the Diet (ISD)] and DTC risk were evaluated in the EPIC cohort using multivariable Cox regression models. RESULTS: Positive associations were observed between DTC risk and the DIIs (HR for 1 SD increase in DII: 1.11, 95%CI: 1.01, 1.23, similar results for its derivatives), but not with the ISD (HR for 1 SD increase: 1.04, 95% CI 0.93, 1.16). CONCLUSION: Diet-associated inflammation, as estimated by the DII and its derivatives, was weakly positively associated with DTC risk in a European adult population. These results suggesting that diet-associated inflammation acts in the etiology of DTC need to be validated in independent studies.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women.

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

Associations between plasma levels of brominated flame retardants and methylation of DNA from peripheral blood: A cross-sectional study in a cohort of French women.

BACKGROUND: Brominated flame retardants (BFRs) are organic compounds that are widespread in the environment. Because of their persistence, they are able to bioaccumulate with major impacts on human health. It has been hypothesized that the effect of BFRs on human health is mediated by alterations of DNA methylation. OBJECTIVE: The aim of this study was to examine the association between methylation of DNA extracted from peripheral blood and circulating levels of BFRs measured in plasma. METHODS: We conducted a methylation wide association study on 336 blood samples from a study within the E3N (Etude Epidémiologique auprès de femmes de l'Education Nationale) cohort, a long-term longitudinal cohort of French women. DNA methylation at more than 850 000 cytosine-guanine dinucleotide (CpG) sites was measured with the Illumina Infinium HumanMethylation - EPIC BeadChip. Circulating levels of seven BFRs (BDE-28, BDE-47, BDE-99, BDE-100, BDE-153, BDE-154 and PBB-153) were measured by gas chromatography coupled to high-resolution mass spectrometry in plasma samples. The association between DNA methylation and BFRs plasma levels was assessed through linear mixed-effects models followed by gene-set enrichment analyses (GSEA). RESULTS: We identified 253 CpG sites whose methylation levels were significantly associated with exposure to BFRs after Bonferroni correction. For 50 of these CpGs the p-values were less than 2.2x10-9 with the strongest association being between BDE-154 and cg23619365 (4.32x10-13). GSEA of CpG sites associated with exposure to BFRs identified significant enrichment of genes involved in hypoxia, glycolysis and adipogenesis. CONCLUSIONS: Exposure to BFRs appears to be related to numerous alterations in DNA methylation. These findings, if replicated in independent studies, provide insights into the biological and health effects of BFRs.

Leveraging pleiotropic association using sparse group variable selection in genomics data.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants associated with multiple complex diseases. We can leverage this phenomenon, known as pleiotropy, to integrate multiple data sources in a joint analysis. Often integrating additional information such as gene pathway knowledge can improve statistical efficiency and biological interpretation. In this article, we propose statistical methods which incorporate both gene pathway and pleiotropy knowledge to increase statistical power and identify important risk variants affecting multiple traits. METHODS: We propose novel feature selection methods for the group variable selection in multi-task regression problem. We develop penalised likelihood methods exploiting different penalties to induce structured sparsity at a gene (or pathway) and SNP level across all studies. We implement an alternating direction method of multipliers (ADMM) algorithm for our penalised regression methods. The performance of our approaches are compared to a subset based meta analysis approach on simulated data sets. A bootstrap sampling strategy is provided to explore the stability of the penalised methods. RESULTS: Our methods are applied to identify potential pleiotropy in an application considering the joint analysis of thyroid and breast cancers. The methods were able to detect eleven potential pleiotropic SNPs and six pathways. A simulation study found that our method was able to detect more true signals than a popular competing method while retaining a similar false discovery rate. CONCLUSION: We developed feature selection methods for jointly analysing multiple logistic regression tasks where prior grouping knowledge is available. Our method performed well on both simulation studies and when applied to a real data analysis of multiple cancers.