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.

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.

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.

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.

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.

Metabolic Syndrome and Risk of Gastrointestinal Cancers: An Investigation Using Large-scale Molecular Data.

BACKGROUND & AIMS: Gastrointestinal cancer risk is influenced by the presence of metabolic syndrome (MetS). However, previous epidemiologic studies lacked full serological biomarker data for the classification of MetS, and the interaction of MetS with germline cancer risk variants is unknown. METHODS: We investigated the associations between MetS and gastrointestinal cancer risk (overall, colorectal, pancreatic, esophageal adenocarcinoma, esophageal squamous cell carcinoma, stomach cardia, stomach non-cardia, hepatocellular carcinoma, and intrahepatic bile duct cancer) in 366,016 United Kingdom Biobank participants with comprehensive serum biomarker and genotype data. MetS status was determined by 3 different definitions at baseline, and, in 15,152 participants, at a repeat assessment after a median of 4.3 years of follow-up. Multivariable hazard ratios and 95% confidence intervals for cancer outcomes were estimated using Cox proportional hazards models. Analyses stratified by polygenic risk score were conducted for colorectal and pancreatic cancers. RESULTS: During a median follow-up of 7.1 years, 4238 incident cases of a gastrointestinal cancer occurred. MetS at baseline was associated with higher risk of overall gastrointestinal cancer by any definition (hazard ratio, 1.21; 95% confidence interval, 1.13-1.29, harmonized definition). MetS was associated with increased risks of colorectal cancer, colon cancer, rectal cancer, hepatocellular carcinoma, pancreatic cancer in women, and esophageal adenocarcinoma in men. Associations for colorectal cancer and pancreatic cancer did not differ by polygenic risk score strata (P-heterogeneity 0.70 and 0.69, respectively), and 80% of participants with MetS at baseline retained this status at the repeat assessment. CONCLUSIONS: These findings underscore the importance of maintaining good metabolic health in reducing the burden of gastrointestinal cancers, irrespective of genetic predisposition.

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.

Adapted dietary inflammatory index and differentiated thyroid carcinoma risk in two French population-based case-control studies.

PURPOSE: Thyroid cancer is the most common endocrine cancer and its etiology is still not well understood. The aim of the present study was to assess the association between an adapted dietary inflammatory index and differentiated thyroid cancer (DTC) risk in two population-based case-control studies (CATHY and YOUNG-THYR) conducted in France. METHODS: These studies included a total of 1321 DTC cases and 1502 controls, for which an adapted dietary inflammatory index (ADII) was computed based on food frequency questionnaires in each study separately. The association between ADII and thyroid cancer risk was assessed using logistic regression models controlling for potential confounders. RESULTS: Higher ADII scores, corresponding to a higher pro-inflammatory potential of the diet, were associated with higher DTC risk (odds ratio (OR) for 1 standard deviation (SD) increase: 1.09, 95% confidence interval (CI): 1.01, 1.18, P: 0.03). Associations were stronger in analyses restricted to women (OR for 1-SD increase: 1.14, 95% CI 1.04, 1.25, P: 0.005), as well as in women with lower education level, current smoking, or high body mass index. CONCLUSION: Our study suggests that a pro-inflammatory diet is associated with an increased risk of DTC, especially when combined with other inflammatory conditions such as tobacco smoking or overweight. Our findings will help better understand the role of diet-induced inflammation in DTC etiology.

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.

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.

Penalized partial least squares for pleiotropy.

BACKGROUND: The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. RESULTS: Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. CONCLUSION: The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

Gene- and pathway-level analyses of iCOGS variants highlight novel signaling pathways underlying familial breast cancer susceptibility.

Single-nucleotide polymorphisms (SNPs) in over 180 loci have been associated with breast cancer (BC) through genome-wide association studies involving mostly unselected population-based case-control series. Some of them modify BC risk of women carrying a BRCA1 or BRCA2 (BRCA1/2) mutation and may also explain BC risk variability in BC-prone families with no BRCA1/2 mutation. Here, we assessed the contribution of SNPs of the iCOGS array in GENESIS consisting of BC cases with no BRCA1/2 mutation and a sister with BC, and population controls. Genotyping data were available for 1281 index cases, 731 sisters with BC, 457 unaffected sisters and 1272 controls. In addition to the standard SNP-level analysis using index cases and controls, we performed pedigree-based association tests to capture transmission information in the sibships. We also performed gene- and pathway-level analyses to maximize the power to detect associations with lower-frequency SNPs or those with modest effect sizes. While SNP-level analyses identified 18 loci, gene-level analyses identified 112 genes. Furthermore, 31 Kyoto Encyclopedia of Genes and Genomes and 7 Atlas of Cancer Signaling Network pathways were highlighted (false discovery rate of 5%). Using results from the "index case-control" analysis, we built pathway-derived polygenic risk scores (PRS) and assessed their performance in the population-based CECILE study and in a data set composed of GENESIS-affected sisters and CECILE controls. Although these PRS had poor predictive value in the general population, they performed better than a PRS built using our SNP-level findings, and we found that the joint effect of family history and PRS needs to be considered in risk prediction models.

African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer.

Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.

Multiethnic genome-wide association study of differentiated thyroid cancer in the EPITHYR consortium.

Incidence of differentiated thyroid carcinoma (DTC) varies considerably between ethnic groups, with particularly high incidence rates in Pacific Islanders. DTC is one of the cancers with the highest familial risk suggesting a major role of genetic risk factors, but only few susceptibility loci were identified so far. In order to assess the contribution of known DTC susceptibility loci and to identify new ones, we conducted a multiethnic genome-wide association study (GWAS) in individuals of European ancestry and of Oceanian ancestry from Pacific Islands. Our study included 1554 cases/1973 controls of European ancestry and 301 cases/348 controls of Oceanian ancestry from seven population-based case-control studies participating to the EPITHYR consortium. All participants were genotyped using the OncoArray-500K Beadchip (Illumina). We confirmed the association with the known DTC susceptibility loci at 2q35, 8p12, 9q22.33 and 14q13.3 in the European ancestry population and suggested two novel signals at 1p31.3 and 16q23.2, which were associated with thyroid-stimulating hormone levels in previous GWAS. We additionally replicated an association with 5p15.33 reported previously in Chinese and European populations. Except at 1p31.3, all associations were in the same direction in the population of Oceanian ancestry. We also observed that the frequencies of risk alleles at 2q35, 5p15.33 and 16q23.2 were significantly higher in Oceanians than in Europeans. However, additional GWAS and epidemiological studies in Oceanian populations are needed to fully understand the highest incidence observed in these populations.

Bayesian meta-analysis models for cross cancer genomic investigation of pleiotropic effects using group structure.

An increasing number of genome-wide association studies (GWAS) summary statistics is made available to the scientific community. Exploiting these results from multiple phenotypes would permit identification of novel pleiotropic associations. In addition, incorporating prior biological information in GWAS such as group structure information (gene or pathway) has shown some success in classical GWAS approaches. However, this has not been widely explored in the context of pleiotropy. We propose a Bayesian meta-analysis approach (termed GCPBayes) that uses summary-level GWAS data across multiple phenotypes to detect pleiotropy at both group-level (gene or pathway) and within group (eg, at the SNP level). We consider both continuous and Dirac spike and slab priors for group selection. We also use a Bayesian sparse group selection approach with hierarchical spike and slab priors that enables us to select important variables both at the group level and within group. GCPBayes uses a Bayesian statistical framework based on Markov chain Monte Carlo (MCMC) Gibbs sampling. It can be applied to multiple types of phenotypes for studies with overlapping or nonoverlapping subjects, and takes into account heterogeneity in the effect size and allows for the opposite direction of the genetic effects across traits. Simulations show that the proposed methods outperform benchmark approaches such as ASSET and CPBayes in the ability to retrieve pleiotropic associations at both SNP and gene-levels. To illustrate the GCPBayes method, we investigate the shared genetic effects between thyroid cancer and breast cancer in candidate pathways.

Circadian genes polymorphisms, night work and prostate cancer risk: Findings from the EPICAP study.

Over the past two decades, several studies have attempted to understand the hypothesis that disrupting the circadian rhythm may promote the development of cancer. Some have suggested that night work and some circadian genes polymorphisms are associated with cancer, including prostate cancer. Our study aims to test the hypothesis that prostate cancer risk among night workers may be modulated by genetic polymorphisms in the circadian pathway genes based on data from the EPICAP study, a population-based case-control study including 1511 men (732 cases/779 controls) with genotyped data. We estimated odds ratio (ORs) and P values of the association between prostate cancer and circadian gene variants using logistic regression models. We tested the interaction between circadian genes variants and night work indicators that were significantly associated with prostate cancer at pathway, gene and SNP levels. Analyses were also stratified by each of these night work indicators and by cancer aggressiveness. The circadian pathway was significantly associated with aggressive prostate cancer among night workers (P = .004), particularly for men who worked at night for <20 years (P = .0002) and those who performed long night shift (>10 hours, P = .001). At the gene level, we observed among night workers significant associations between aggressive prostate cancer and ARNTL, NPAS2 and RORA. At the SNP-level, no significant association was observed. Our findings provide some clues of a potential modulating effect of circadian genes in the relationship between night work and prostate cancer. Further investigation is warranted to confirm these findings and to better elucidate the biological pathways involved.

Polyphenol intake and differentiated thyroid cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Polyphenols are bioactive compounds with several anticarcinogenic activities; however, human data regarding associations with thyroid cancer (TC) is still negligible. Our aim was to evaluate the association between intakes of total, classes and subclasses of polyphenols and risk of differentiated TC and its main subtypes, papillary and follicular, in a European population. The European Prospective Investigation into Cancer and Nutrition cohort included 476,108 men and women from 10 European countries. During a mean follow-up of 14 years, there were 748 incident differentiated TC cases, including 601 papillary and 109 follicular tumors. Polyphenol intake was estimated at baseline using validated center/country-specific dietary questionnaires and the Phenol-Explorer database. In multivariable-adjusted Cox regression models, no association between total polyphenol and the risks of overall differentiated TC (HRQ4 vs. Q1 = 0.99, 95% confidence interval [CI] 0.77-1.29), papillary (HRQ4 vs. Q1 = 1.06, 95% CI 0.80-1.41) or follicular TC (HRQ4 vs. Q1 = 1.10, 95% CI 0.55-2.22) were found. No associations were observed either for flavonoids, phenolic acids or the rest of classes and subclasses of polyphenols. After stratification by body mass index (BMI), an inverse association between the intake of polyphenols (p-trend = 0.019) and phenolic acids (p-trend = 0.007) and differentiated TC risk in subjects with BMI ≥ 25 was observed. In conclusion, our study showed no associations between dietary polyphenol intake and differentiated TC risk; although further studies are warranted to investigate the potential protective associations in overweight and obese individuals.

Dietary Inflammatory Index and Differentiated Thyroid Carcinoma Risk: A Population-Based Case-Control Study in New Caledonia.

Despite research efforts, current knowledge of the etiology of thyroid carcinoma remains limited. To explore the potential role of diet-induced inflammation, we examined the association between differentiated thyroid cancer risk and the energy-adjusted Dietary Inflammatory Index (E-DII) in a population-based case-control study conducted in New Caledonia, a Pacific archipelago with one of the highest recorded thyroid cancer incidence rates in the world. The E-DII was computed from food frequency questionnaire information on usual dietary intake. Logistic regression analyses were performed on data from 324 histologically confirmed cases of papillary or follicular carcinoma, diagnosed from 1993 to 1999, and 402 controls. Positive associations between E-DII and thyroid cancer risk were observed (comparing extreme tertiles, odds ratio = 1.67, 95% confidence interval: 1.08, 2.58; P for trend = 0.002), with stronger associations found for larger carcinomas (P for trend = 0.0005). Stratified analyses showed an increased risk of thyroid cancer associated with the E-DII among Southern province residents (P for trend = 0.003), Melanesian women (P for trend = 0.02), obese participants (P for trend = 0.006), and ever-smokers (P for trend = 0.0005). Our results suggest that a proinflammatory diet-especially when concomitant with other inflammation-inducing conditions or habits (e.g., obesity, smoking)-is associated with increased risk of thyroid carcinoma.

Association of breast cancer risk with polymorphisms in genes involved in the metabolism of xenobiotics and interaction with tobacco smoking: A gene-set analysis.

Single nucleotide polymorphisms (SNPs) in genes involved in xenobiotics metabolism (XM) are suspected to play a role in breast cancer risk. However, previous findings based on a SNP by SNP approach need to be replicated taking into account the combined effects of multiple SNPs. We used a gene-set analysis method to study the association between breast cancer risk and genetic variation in XM genes (seen as a set of SNPs) and in the XM pathway (seen as a set of genes). We also studied the interaction between variants in XM genes and tobacco smoking. The analysis was conducted in a case-control study of 1,125 cases and 1,172 controls. Using a dedicated chip, genotyping data of 585 SNPs in 68 XM genes were available. Genetic variation in the whole XM pathway was significantly associated with premenopausal breast cancer risk (p = 0.008). This association was mainly driven by genetic variation in NAT2, CYP2C18, CYP2C19, AKR1C2 and ALDH1A3. The association between the XM gene pathway and breast cancer was observed among current and previous smokers, but not among never smokers (p = 0.013 for interaction between XM genes and tobacco smoking status). The association with breast cancer risk indicates that XM genes variants may play a role in breast carcinogenesis through their detoxification function of environmental pollutants, such as those contained in tobacco smoke.

Circadian genes and risk of prostate cancer: Findings from the EPICAP study.

Circadian rhythms regulate several physiological functions and genes controlling the circadian rhythm were found to regulate cell proliferation, cell cycle and apoptosis. Few studies have investigated the role of those circadian genes in prostate cancer occurrence. We aim to investigate the relationship between circadian genes polymorphisms and prostate cancer risk based on data from the EPICAP study, a population-based case-control study including 1,515 men (732 cases / 783 controls) with genotyped data. Odds Ratios (ORs) for association between prostate cancer and circadian gene variants were estimated for each of the 872 single nucleotide polymorphisms (SNPs) in 31 circadian clock genes. We also used a gene-based and pathway-based approach with a focus on the pathway including 9 core circadian genes. Separate analyses were conducted by prostate cancer aggressiveness. The core-circadian pathway (p = 0.0006) was significantly associated to prostate cancer, for either low (p = 0.002) or high (p = 0.01) grade tumor. At the gene level, we observed significant associations between all prostate cancer and NPAS2 and PER1 after correcting for multiple testing, while only RORA was significant for aggressive tumors. At the SNP-level, no significant association was observed. Our findings provide additional evidence of a potential link between genetic variants in circadian genes and prostate cancer risk. Further investigation is warranted to confirm these findings and to better understand the biological pathways involved.