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

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  • Suzanne C Dixon
  • Christina M Nagle
  • Aaron P Thrift
  • Paul Dp Pharoah
  • Celeste Leigh Pearce
  • Wei Zheng
  • Jodie N Painter
  • Georgia Chenevix-Trench
  • Peter A Fasching
  • Matthias W Beckmann
  • Diether Lambrechts
  • Ignace Vergote
  • Sandrina Lambrechts
  • Els Van Nieuwenhuysen
  • Mary Anne Rossing
  • Jennifer A Doherty
  • Kristine G Wicklund
  • Jenny Chang-Claude
  • Anja Rudolph
  • Kirsten B Moysich
  • Kunle Odunsi
  • Marc T Goodman
  • Lynne R Wilkens
  • Pamela J Thompson
  • Yurii B Shvetsov
  • Thilo Dörk
  • Tjoung-Won Park-Simon
  • Peter Hillemanns
  • Natalia Bogdanova
  • Ralf Butzow
  • Heli Nevanlinna
  • Liisa M Pelttari
  • Arto Leminen
  • Francesmary Modugno
  • Roberta B Ness
  • Robert P Edwards
  • Joseph L Kelley
  • Florian Heitz
  • Beth Y Karlan
  • Susanne K Kjær
  • Estrid Vilma Solyom Høgdall
  • Allan Jensen
  • Ellen L Goode
  • Brooke L Fridley
  • Julie M Cunningham
  • Stacey J Winham
  • Graham G Giles
  • Fiona Bruinsma
  • Claus K Høgdall
  • Lene Lundvall
  • AOCS Group & Australian Cancer Study (Ovarian Cancer)
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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 meta-analysis.

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 low-grade/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.

Original languageEnglish
JournalInternational Journal of Epidemiology
Volume45
Issue number3
Pages (from-to)884-95
Number of pages12
ISSN0300-5771
DOIs
Publication statusPublished - Jun 2016

    Research areas

  • Journal Article

ID: 49500954