Adult body mass index and risk of ovarian cancer by subtype: A Mendelian randomization study

Suzanne C. Dixon, QIMR Berghofer Medical Research Institute
Christina M. Nagle, QIMR Berghofer Medical Research Institute
Aaron P. Thrift, Baylor College of Medicine
Paul D.P. Pharoah, University of Cambridge
Celeste Leigh Pearce, University of Michigan School of Public Health
Wei Zheng, Vanderbilt University Medical Center
Jodie N. Painter, QIMR Berghofer Medical Research Institute
Georgia Chenevix-Trench, QIMR Berghofer Medical Research Institute
Peter A. Fasching, David Geffen School of Medicine at UCLA
Matthias W. Beckmann, Universitätsklinikum Erlangen
Diether Lambrechts, Flanders Interuniversity Institute for Biotechnology
Ignace Vergote, KU Leuven– University Hospital Leuven
Sandrina Lambrechts, KU Leuven– University Hospital Leuven
Els Van Nieuwenhuysen, KU Leuven– University Hospital Leuven
Mary Anne Rossing, Fred Hutchinson Cancer Research Center
Jennifer A. Doherty, Geisel School of Medicine at Dartmouth
Kristine GWicklund, Fred Hutchinson Cancer Research Center
Jenny Chang-Claude, German Cancer Research Center
Anja Rudolph, German Cancer Research Center
Kirsten B. Moysich, Roswell Park Cancer Institute
Kunle Odunsi, Roswell Park Cancer Institute


Background: Observational studies have reported a positive association between body mass index (BMI) and ovarian cancer risk. However, questions remain as to whether this represents a causal effect, or holds for all histological subtypes. The lack of association observed for serous cancers may, for instance, be due to disease-associated weight loss. Mendelian randomization (MR) uses genetic markers as proxies for risk factors to overcome limitations of observational studies. We used MR to elucidate the relationship between BMI and ovarian cancer, hypothesizing that genetically predicted BMI would be associated with increased risk of non-high grade serous ovarian cancers (non-HGSC) but not HGSC. Methods: We pooled data from 39 studies (14 047 cases, 23 003 controls) in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS, partial F-statistic = 172), summing alleles at 87 single nucleotide polymorphisms previously associated with BMI, weighting by their published strength of association with BMI. Applying two-stage predictor-substitution MR, we used logistic regression to estimate study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted BMI and risk, and pooled these using random-effects metaanalysis. Results: Higher genetically predicted BMI was associated with increased risk of non-HGSC (pooled OR=1.29, 95% CI 1.03-1.61 per 5 units BMI) but not HGSC (pooled OR=1.06, 95% CI 0.88-1.27). Secondary analyses stratified by behaviour/subtype suggested that, consistent with observational data, the association was strongest for lowgrade/borderline serous cancers (OR=1.93, 95% CI 1.33-2.81). Conclusions: Our data suggest that higher BMI increases risk of non-HGSC, but not the more common and aggressive HGSC subtype, confirming the observational evidence.