{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Usset JL"],"funding":["Cancer Research UK","NCI NIH HHS"],"pagination":["780-90"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4873330"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["25(5)"],"pubmed_abstract":["Background
Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women.Methods
We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed.Results
SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)).Conclusions
We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions.Impact
Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780-90. ©2016 AACR."],"journal":["Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology"],"pubmed_title":["Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity, and Hormone-Related Risk Factors."],"pmcid":["PMC4873330"],"funding_grant_id":["R01 CA076016","16561","P30 CA008748","P30 CA046592","R03 CA115195","R03 CA113148","R13 CA110770","P30 CA071789","P30 CA168524","P30 CA014089","10119","P30 CA016056","R01 CA122443","U01 CA069417","P50 CA136393","R01 CA087538","P30 CA015083","K07 CA143047","R01 CA058598","N01 PC067010","R01 CA058860","10124","R01 CA112523"],"pubmed_authors":["Sieh W","van den Berg DJ","Raghavan R","Pike MC","Larson MC","Gentry-Maharaj A","Yang H","Kiemeney LA","Chang-Claude J","Johnatty SE","Massuger L","Thompson PJ","Modugno F","Pharoah P","Rothstein J","Pearce CL","Berchuck A","Kjaer SK","Rudolph A","Anton-Culver H","Gayther SA","Doherty JA","Ovarian Cancer Association Consortium and the Australian Cancer Study","Usset JL","Tyrer JP","Vierkant RA","Jensen A","Menon U","Lurie G","Ramus SJ","Cunningham JM","Schildkraut JM","DeFazio A","McGuire V","Moysich KB","Edwards RP","Webb P","Song H","Brinton L","Wang-Gohrke S","Goodman MT","Wilkens LR","Ness RB","Hogdall E","Wentzensen N","Whittemore AS","Wu AH","Fridley BL","Rossing MA","Goode EL"],"additional_accession":[]},"is_claimable":false,"name":"Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity, and Hormone-Related Risk Factors.","description":"Background
Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women.Methods
We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed.Results
SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)).Conclusions
We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions.Impact
Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780-90. ©2016 AACR.","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 May","modification":"2024-11-21T03:46:48.441Z","creation":"2019-03-27T02:14:05Z"},"accession":"S-EPMC4873330","cross_references":{"pubmed":["26976855"],"doi":["10.1158/1055-9965.EPI-15-1039","10.1158/1055-9965.epi-15-1039"]}}