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Cancer genetics
Original research
Mendelian randomisation study of the effects of known and putative risk factors on pancreatic cancer
  1. Ye Lu1,2,
  2. Manuel Gentiluomo3,
  3. Justo Lorenzo-Bermejo4,
  4. Luca Morelli5,6,
  5. Ofure Obazee1,
  6. Daniele Campa3,
  7. Federico Canzian1
  1. 1 Genomic Epidemiology Group, DKFZ, Heidelberg, Baden-Württemberg, Germany
  2. 2 Medical Faculty Heidelberg, University of Heidelberg, Heidelberg, Baden-Württemberg, Germany
  3. 3 Department of Biology, University of Pisa, Pisa, Toscana, Italy
  4. 4 Statistical Genetics Research Group, Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Baden-Württemberg, Germany
  5. 5 General Surgery, Department of Surgery, Translational and New Technologies, University of Pisa, Pisa, Toscana, Italy
  6. 6 EndoCAS (Center for Computer Assisted Surgery), University of Pisa, Pisa, Toscana, Italy
  1. Correspondence to Professor Daniele Campa, Department of Biology, University of Pisa, Pisa 56126, Italy; daniele.campa{at}unipi.it

Abstract

Background Observational studies have reported multiple risk factors for pancreatic ductal adenocarcinoma (PDAC). Some are well established, like tobacco smoking, alcohol drinking, obesity and type 2 diabetes, whereas some others are putative, such as allergy and dietary factors. Identifying causal risk factors can help establishing those that can be targeted to contribute to prevent PDAC.

Objective We sought to investigate the possible causal effects of established and putative factors on PDAC risk.

Methods We conducted a two-sample Mendelian randomisation (MR) study using publicly available data for genetic variants associated with the factors of interest, and summary genetic data from genome-wide association studies of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including in total 8769 cases and 7055 controls. Causality was assessed using inverse-variance weighted, MR-Egger regression and weighted median methods, complemented with sensitivity and radial MR analyses.

Results We found evidence for a causal effect of body mass index (BMI) on PDAC risk (OR 1.43, 95% CI 1.20 to 1.71, p=8.43×10−5). Fasting insulin (OR 2.84, 95% CI 1.23 to 6.56, p=0.01), low-density lipoprotein cholesterol (OR 1.16, 95% CI 1.02 to 1.32, p=0.03) and type 2 diabetes (OR 1.09, 95% CI 1.01 to 1.17, p=0.02) were also causally associated with PDAC risk. BMI showed both direct and fasting insulin-mediated causal effects.

Conclusion We found strong evidence that BMI is causally associated with PDAC risk, providing support that obesity management may be a potential prevention strategy for reducing pancreatic cancer risk while fasting insulin and type 2 diabetes showed a suggestive association that should be further investigated.

  • pancreatic cancer
  • Mendelian randomization
  • genetic polymorphisms
  • risk factors

https://doi.org/10.1136/jmedgenet-2019-106200

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    Footnotes

    • YL and MG are joint first authors.

    • DC and FC are joint senior authors.

    • Twitter @gentiluomo_m

    • YL and MG contributed equally.

    • DC and FC contributed equally.

    • Contributors DC and FC conceived the study. MG and YL performed data analysis. YL, MG, JL-B, LM, DC and FC drafted the manuscript. JL-B revised the statistical analysis. All the authors critically read, commented and approved the manuscript.

    • Funding This work was supported by intramural funding of DKFZ, by Fondazione Tizzi and by Fondazione Arpa (www.fondazionearpa.it).

    • Competing interests None declared.

    • Patient consent for publication Obtained.

    • Ethics approval Each participating study obtained approval from the responsible institutional review board (IRB) and IRB certification permitting data sharing in accordance with the NIH Policy for Sharing of Data Obtained in NIH-Supported or NIH-Conducted Genome Wide Association Studies.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available in a controlled-access repository, under the NIH Genomic Data Sharing (GDS) Policy open access repository.