Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Abstract 2611: Role of circadian genes in breast cancer: Analysis of the CECILE study, a population-based case-control study conducted in France

Abstract Breast cancer risk has been associated with shift work and light exposure at night. It has been suggested that disruption of circadian rhythms induced by these exposure may play a role in tumorigenesis. Circadian rhythms regulate diverse physiologic processes, including regulation of sex hormone levels, and genes controlling the circadian rhythm were found to regulate cell proliferation, cell cycle regulation and apoptosis. However, only few studies have investigated the role of these genes in breast cancer. The purpose of this study was to analyze the association between polymorphisms in circadian genes and breast cancer risk. The CECILE study is a population-based case-control study on environmental and genetic factors. A total of 1135 incident cases and 1167 controls provided DNA samples. We genotyped 570 tagging and functional SNPs from the 22 genes in the circadian rhythm pathway defined by KEGG. Preliminary results based on a SNP by SNP analysis using unconditional logistic regression highlighted 36 SNPs with p-value&amp;lt;0.05 in RORA, CUL1, NPAS2, CRY1, CRY2 and CLOCK genes. Of these, 3 SNPs in RORA were significantly associated with breast cancer after Bonferroni correction for multiple testing (p&amp;lt;0.0001). In ongoing analyses, we use the Multilevel Inference for SNP Association (MISA) method, which is a more powerful method that allows estimating associations at the SNP, gene and pathway level. These analyses will be presented. Our results suggest a role of the circadian gene in breast cancer risk. Further analysis on possible interaction between shift work and genetic variants highlighted in this study in relation to breast cancer risk will be conducted in the CECILE study. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2611. doi:1538-7445.AM2012-2611</jats:p

Abstract 3728: Night work and breast cancer risk: CECILE study

Abstract Objectives: Epidemiological studies have suggested that night shift work increases the risk for breast cancer. Disruption of the normal circadian rhythm may explain this association. We investigated the role of night work in the occurrence of breast cancer in a population-based case-control study in France. Methods: The CECILE study was conducted in two French départements (Côte d'Or, Ille-et-Vilaine) between 2005 and 2008. All female residents in these areas aged 25-75 years who were diagnosed with a breast cancer were eligible to the study. Population controls were frequency-matched by 5-year age group to the cases. A total of 1232 incident breast cancer cases and 1317 controls were included. An in-person interview was conducted using a standardized questionnaire to obtain information on recognized or suspected risk factors for breast cancer, as well as on lifetime occupational history. For each job held for more than 6 months, information on night shift work was elicited. Any work shift where the woman had to work for at least one hour between 11 pm and 5 am was defined as night work. Duration (in years) and frequency (times per week) of night shifts were also obtained. Analyses were conducted using unconditional logistic regression adjusting for age and recognized risk factors for breast cancer. Results: Thirteen percent of the cases and eleven percent of the controls had ever worked at night (OR=1.29 [1.00-1.64]). The association was more pronounced for women who had overnight shifts (full-time shift work between 11 pm and 5 am: OR=1.37 [1.03-1.83]) than for women who had late evening shifts (ending after 11 pm: OR=1.29 [0.78-2.15]) or early morning shifts (starting before 5 am: OR=1.19 [0.43-3.31]). Women who worked in overnight shifts for 3 or more years had an OR of 1.49 [1.05-1.89], but no further increase of the OR was observed for longer durations. Overnight shift work of 3 nights or less per week during overnight periods, implying frequent changes between night and day schedules, was associated with an OR of 1.59 [1.08-2.33]). Conclusion: Our results support the hypothesis of a role of overnight work in the occurrence of breast cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3728. doi:10.1158/1538-7445.AM2011-3728</jats:p

Abstract 141: Nonsteroidal anti-inflammatory drugs (NSAIDs), cyclooxygenase-2 polymorphisms, and breast cancer risk.

Abstract Objective: To investigate the role of anti-inflammatory drugs (NSAIDs) in breast cancer occurrence, particularly of selective inhibitors of cyclooxygenase-2 (COX-2), enzyme involved in the immune response to inflammation, as well as the role of genetic polymorphisms in the COX-2 gene and their interactions with NSAIDs in breast cancer risk. Materials and methods: We conducted a population-based case-control study in two French départements (Côte d'Or, Ille-et-Vilaine) between 2005 and 2008 (CECILE study). An in-person interview was conducted using a standardized questionnaire to obtain information on recognized or suspected risk factors for breast cancer. A self-administered questionnaire was used to obtain information on NSAIDs consumption and was returned by mail by 871 cases (71%) and 915 controls (69%). Blood samples were available for 811 cases and 829 controls and allowed genotyping using a dedicated Illumina chip. Seven tagged SNPs selected in COX-2 (rs20417, rs689466, rs2206593, rs5275, rs5277, rs4648261, rs2745557) were included in the analysis. Odds ratios and 95% confidence intervals were calculated using unconditional logistic regression models adjusted for age and département but also for the known risk factors for breast cancer. The analyses were conducted using a dominant genetic model for each SNP. A multiplicative interaction between genetic polymorphisms and NSAIDs use in the risk of breast cancer was also tested. Results: A negative association was observed between NSAIDs use and breast cancer (OR = 0.83 [0.68 to 1.01]). This association was more pronounced among women who consumed selective inhibitors of COX-2 (OR = 0.60 [0.37 to 0.98]). We observed a negative association between breast cancer and the absence of the common allele for rs5275 (OR = 0.73 [0.54 to 0.99]) and a positive association close to statistical significance for women with at least one rare allele for rs5277 (OR = 1.22 [0.99 to 1.52]). Odds ratios for interaction between NSAID use and COX-2 polymorphisms was 1.25 (0.96 to 1.64, p = 0.10) for rs20417 and 1. 16 [0.99 to 1.37, p = 0.07) for rs5275. Conclusion: Our results confirm the negative association between NSAIDs use and the occurrence of breast cancer and reinforce the hypothesis that this association may be more specific to selective inhibitors of COX-2. Our results also indicate that specific polymorphisms of the COX-2 gene may modify the risk of breast cancer associated with NSAIDs use. Citation Format: Florence Menegaux, Thérèse Truong, Florian Ajmia, Antoinette Anger, Claire Mulot, Pierre Laurent-Puig, Emilie Cordina-Duverger, Pascal Guénel. Nonsteroidal anti-inflammatory drugs (NSAIDs), cyclooxygenase-2 polymorphisms, and breast cancer risk. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 141. doi:10.1158/1538-7445.AM2013-141</jats:p

Diagnostic and Prognostic Performance of Blood Plasma Glycan Features in the Women Epidemiology Lung Cancer (WELCA) Study

Lung cancer is the leading cause of cancer death in women living in the United States, which accounts for approximately the same percentage of cancer deaths in women as breast, ovary, and uterine cancers combined. Targeted blood plasma glycomics represents a promising source of noninvasive diagnostic and prognostic biomarkers for lung cancer. Here, 208 samples from lung cancer patients and 207 age-matched controls enrolled in the Women Epidemiology Lung Cancer (WELCA) study were analyzed by a bottom-up glycan “node” analysis approach. Glycan features, quantified as single analytical signals, including 2-linked mannose, α2–6 sialylation, β1–4 branching, β1–6 branching, 4-linked GlcNAc, and antennary fucosylation, exhibited abilities to distinguish cases from controls (ROC AUCs: 0.68–0.92) and predict survival in patients (hazard ratios: 1.99–2.75) at all stages. Notable alterations of glycan features were observed in stages I–II. Diagnostic and prognostic glycan features were mostly independent of smoking status, age, gender, and histological subtypes of lung cancer

Diagnostic and Prognostic Performance of Blood Plasma Glycan Features in the Women Epidemiology Lung Cancer (WELCA) Study

Lung cancer is the leading cause of cancer death in women living in the United States, which accounts for approximately the same percentage of cancer deaths in women as breast, ovary, and uterine cancers combined. Targeted blood plasma glycomics represents a promising source of noninvasive diagnostic and prognostic biomarkers for lung cancer. Here, 208 samples from lung cancer patients and 207 age-matched controls enrolled in the Women Epidemiology Lung Cancer (WELCA) study were analyzed by a bottom-up glycan “node” analysis approach. Glycan features, quantified as single analytical signals, including 2-linked mannose, α2–6 sialylation, β1–4 branching, β1–6 branching, 4-linked GlcNAc, and antennary fucosylation, exhibited abilities to distinguish cases from controls (ROC AUCs: 0.68–0.92) and predict survival in patients (hazard ratios: 1.99–2.75) at all stages. Notable alterations of glycan features were observed in stages I–II. Diagnostic and prognostic glycan features were mostly independent of smoking status, age, gender, and histological subtypes of lung cancer

Carcinogenicity of automotive gasoline and some oxygenated gasoline additives

No abstract availabl