Person:

De Vivo, Immaculata

Background: Recent evidence suggests a role for progesterone in breast cancer development and tumorigenesis. Progesterone exerts its effect on target cells by interacting with its receptor; thus, genetic variations, which might cause alterations in the biological function in the progesterone receptor (PGR), can potentially contribute to an individual's susceptibility to breast cancer. It has been reported that the PROGINS allele, which is in complete linkage disequilibrium with a missense substitution in exon 4 (G/T, valine→leucine, at codon 660), is associated with a decreased risk for breast cancer. Methods: Using a nested case-control study design within the Nurses' Health Study cohort, we genotyped 1252 cases and 1660 matched controls with the use of the Taqman assay. Results: We did not observe any association of breast cancer risk with carrying the G/T (Val660→Leu) polymorphism (odds ratio 1.10, 95% confidence interval 0.93–1.30). In addition, we did not observe an interaction between this allele and menopausal status and family history of breast cancer as reported previously. Conclusion: Overall, our study does not support an association between the Val660→Leu PROGINS polymorphism and breast cancer risk.

Introduction: Rheumatoid arthritis (RA) is more common in females than males and sex steroid hormones may in part explain this difference. We conducted a case–control study nested within two prospective studies to determine the associations between plasma steroid hormones measured prior to RA onset and polymorphisms in the androgen receptor (AR), estrogen receptor 2 (ESR2), aromatase (CYP19) and progesterone receptor (PGR) genes and RA risk. Methods: We genotyped AR, ESR2, CYP19, PGR SNPs and the AR CAG repeat in RA case–control studies nested within the Nurses' Health Study (NHS), NHS II (449 RA cases, 449 controls) and the Women's Health Study (72 cases, and 202 controls). All controls were matched on cohort, age, Caucasian race, menopausal status, and postmenopausal hormone use. We measured plasma dehydroepiandrosterone sulfate (DHEAS), testosterone, and sex hormone binding globulin in 132 pre-RA samples and 396 matched controls in the NHS cohorts. We used conditional logistic regression models adjusted for potential confounders to assess RA risk. Results: Mean age of RA diagnosis was 55 years in both cohorts; 58% of cases were rheumatoid factor positive at diagnosis. There was no significant association between plasma DHEAS, total testosterone, or calculated free testosterone and risk of future RA. There was no association between individual variants or haplotypes in any of the genes and RA or seropositive RA, nor any association for the AR CAG repeat. Conclusions: Steroid hormone levels measured at a single time point prior to RA onset were not associated with RA risk in this study. Our findings do not suggest that androgens or the AR, ESR2, PGR, and CYP19 genes are important to RA risk in women.

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×(10^{−106})), PRMT6 (rs17496332, 1p13.3, p = 1.4×(10^{−11})), GCKR (rs780093, 2p23.3, p = 2.2×(10^{−16})), ZBTB10 (rs440837, 8q21.13, p = 3.4×(10^{−9})), JMJD1C (rs7910927, 10q21.3, p = 6.1×(10^{−35})), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×(10^{−08})), NR2F2 (rs8023580, 15q26.2, p = 8.3×(10^{−12})), ZNF652 (rs2411984, 17q21.32, p = 3.5×(10^{−14})), TDGF3 (rs1573036, Xq22.3, p = 4.1×(10^{−14})), LHCGR (rs10454142, 2p16.3, p = 1.3×(10^{−07}), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×(10^{−08})), and UGT2B15 (rs293428, 4q13.2, p = 5.5×(10^{−06})). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×(10^{−08}), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Genome-wide association studies (GWAS) have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG) levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS) data from the Nurses’ Health Study (NHS), and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ∼1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint (\beta) = -0.126; joint P = 2.09×10–16), downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10–5), several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ∼900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10–5 was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.

Recent genome-wide scans identified several novel breast cancer risk alleles, including variants of the FGFR2, MAP3K1, and LSP1 genes, and a study of associations between these alleles and characteristics of breast cancer patients reported a borderline significant correlation between the number of FGFR2 minor alleles and family history of breast/ovarian cancer. Given these results and similarities in the etiology of breast and ovarian cancer, we examined the association between seven novel breast cancer susceptibility alleles and epithelial ovarian cancer risk in two large study populations. Our analysis included 1,173 cases and 1,201 controls from a New England-based case-control study and 210 cases and 603 controls from the prospective Nurses’ Health Study. We used logistic regression to estimate the odds ratio (OR) for individuals heterozygous or homozygous for the minor allele at each locus, compared to individuals with the wild-type genotype. We examined the associations separately in each population and, after testing for heterogeneity in the results, pooled the estimates using a random effects model. There was no clear association between these polymorphisms and ovarian cancer risk in either population. The pooled, per allele OR for FGFR2 was 1.06 (95% confidence interval [CI]=0.95–1.18) for rs1219648 and 1.04 (95%CI=0.93–1.15) for rs2981582. We had over 80% power to detect a log-additive OR of 1.16–1.18 per allele at the alpha=0.05 level in the pooled analysis. Our results do not provide strong support for an association between these breast cancer susceptibility alleles and epithelial ovarian cancer risk.

Background: Although cross-sectional studies have linked higher body mass index (BMI) and type 2 diabetes (T2D) to shortened telomeres, whether these metabolic conditions play a causal role in telomere biology is unknown. We therefore examined whether genetic predisposition to higher BMI or T2D was associated with shortened leukocyte telomere length (LTL). Methodology: We conducted an analysis of 3,968 women of European ancestry aged 43–70 years from the Nurses' Health Study, who were selected as cases or controls in genome-wide association studies and studies of telomeres and disease. Pre-diagnostic relative telomere length in peripheral blood leukocytes, collected in 1989–1990, was measured by quantitative PCR. We combined information from multiple risk variants by calculating genetic risk scores based on 32 polymorphisms near 32 loci for BMI, and 36 polymorphisms near 35 loci for T2D. Findings: After adjustment for age and case-control status, there was no association between the BMI genetic risk score and LTL (β per standard deviation increase: −0.01; SE: 0.02; P = 0.52). Similarly, the T2D genetic score was not associated with LTL (β per standard deviation increase: −0.006; SE: 0.02; P = 0.69). Conclusions: In this population of middle-aged and older women of European ancestry, those genetically predisposed to higher BMI or T2D did not possess shortened telomeres. Although we cannot exclude weak or modest effects, our findings do not support a causal relation of strong magnitude between these metabolic conditions and telomere dynamics.

Endometrial cancer (EC) contributes substantially to total burden of cancer morbidity and mortality in the United States. Family history is a known risk factor for EC, thus genetic factors may play a role in EC pathogenesis. Three previous genome-wide association studies (GWAS) have found only one locus associated with EC, suggesting that common variants with large effects may not contribute greatly to EC risk. Alternatively, we hypothesize that rare variants may contribute to EC risk. We conducted an exome-wide association study (EXWAS) of EC using the Infinium HumanExome BeadChip in order to identify rare variants associated with EC risk. We successfully genotyped 177,139 variants in a multiethnic population of 1,055 cases and 1,778 controls from four studies that were part of the Epidemiology of Endometrial Cancer Consortium (E2C2). No variants reached global significance in the study, suggesting that more power is needed to detect modest associations between rare genetic variants and risk of EC.

Endometrial cancer (EC), a neoplasm of the uterine epithelial lining, is the most common gynecological malignancy in developed countries and the fourth most common cancer among US women. Women with a family history of EC have an increased risk for the disease, suggesting that inherited genetic factors play a role. We conducted a two-stage genome-wide association study of Type I EC. Stage 1 included 5,472 women (2,695 cases and 2,777 controls) of European ancestry from seven studies. We selected independent single-nucleotide polymorphisms (SNPs) that displayed the most significant associations with EC in Stage 1 for replication among 17,948 women (4,382 cases and 13,566 controls) in a multiethnic population (African America, Asian, Latina, Hawaiian and European ancestry), from nine studies. Although no novel variants reached genome-wide significance, we replicated previously identified associations with genetic markers near the HNF1B locus. Our findings suggest that larger studies with specific tumor classification are necessary to identify novel genetic polymorphisms associated with EC susceptibility. Electronic supplementary material The online version of this article (doi:10.1007/s00439-013-1369-1) contains supplementary material, which is available to authorized users.

We evaluated whether genetic variability, as well as menopausal status, modify the association between coffee intake and risk of ovarian cancer. Risk factor information and biologic specimens from three large epidemiological studies, the Nurses’ Health Study (NHS), NHSII, and the New England based Case-Control study of ovarian cancer (NECC) were pooled resulting in 1354 ovarian cancer cases and 1851 controls for analysis. Odds ratios (ORs) and 95% confidence intervals (CI) were estimated using conditional (NHS/NHSII) and unconditional (NECC) logistic regression. Coffee consumption was not associated with risk overall (OR = 0.99; 95% CI 0.77–1.28); however, there was a suggested increased risk of ovarian cancer among premenopausal women in the NECC only and an inverse association among postmenopausal women. Carrying one or both of the variant CYP19013 A or CYP19027 G alleles was associated with an 18% increased (P for trend = 0.02) and 15% decreased (P for trend = 0.05) risk of ovarian cancer, respectively. Variation in CYP1A1, CYP1A2, or CYP2A6, did not explain the inconsistent reports of coffee intake and risk. Furthermore, we did not observe any clear gene-environment interactions between caffeine metabolizing genes and ovarian cancer. Future studies evaluating mechanisms by which coffee mediates this relationship are warranted.

Epidemiologic evidence suggests a possible association between genital use of talcum powder and risk of epithelial ovarian cancer; however, the biological basis for this association is not clear. We analyzed interactions between talc use and genes in detoxification pathways [glutathione S-transferase M1 (GSTM1), glutathione S-transferase T1 (GSTT1), and N-acetyltransferase 2 (NAT2)] to assess whether the talc/ovarian cancer association is modified by variants of genes potentially involved in the response to talc. Our analysis included 1,175 cases and 1,202 controls from a New England-based case-control study and 210 cases and 600 controls from the prospective Nurses' Health Study. We genotyped participants for the GSTM1 and GSTT1 gene deletions and three NAT2 polymorphisms. We used logistic regression to analyze the main effect of talc use, genotype, and gene-talc interactions in each population and pooled the estimates using a random-effects model. Regular talc use was associated with increased ovarian cancer risk in the combined study population (RR, 1.36; 95% CI, 1.14-1.63; P(trend) < 0.001). Independent of talc, the genes examined were not clearly associated with risk. However, the talc/ovarian cancer association varied by GSTT1 genotype and combined GSTM1/GSTT1 genotype. In the pooled analysis, the association with talc was stronger among women with the GSTT1-null genotype (P(interaction) = 0.03), particularly in combination with the GSTM1-present genotype (P(interaction) = 0.03). There was no clear evidence of an interaction with GSTM1 alone or NAT2. These results suggest that women with certain genetic variants may have a higher risk of ovarian cancer associated with genital talc use. Additional research is needed on these interactions and the underlying biological mechanisms.