Evaluating the effect of metabolic traits on oral and oropharyngeal cancer risk using Mendelian randomization

Abstract

A recent World Health Organization report states that at least 40% of all cancer cases may be preventable, with smoking, alcohol consumption and obesity identified as three of the most important modifiable lifestyle factors. Given the significant decline in smoking rates, particularly within developed countries, other potentially modifiable risk factors for head and neck cancer warrant investigation. Obesity and related metabolic disorders such as type 2 diabetes and hypertension have been associated with head and neck cancer risk in multiple observational studies. However, adiposity has also been correlated with smoking, with bias, confounding or reverse causality possibly explaining these findings. To overcome the challenges of observational studies, we conducted two-sample Mendelian randomization (inverse variance weighted (IVW) method) using genetic variants which were robustly associated with adiposity, glycaemic and blood pressure traits in genome-wide association studies (GWAS). Outcome data was taken from the largest available GWAS of 6,034 oral and oropharyngeal cases, with 6,585 controls. We found limited evidence of a causal effect of genetically proxied body mass index (OR IVW = 0.89, 95%CI 0.72-1.09, p = 0.26 per 1 SD in BMI (4.81 kg/m2)) on oral and oropharyngeal cancer risk. Similarly, there was limited evidence for related traits including type 2 diabetes and hypertension.

Data availability

Summary-level analysis was conducted using publicly available GWAS data as cited. Full summary statistics for the GAME-ON outcome data GWAS can be accessed via dbGAP (OncoArray: Oral and Pharynx Cancer; study accession number: phs001202.v1.p1, August 2017) at: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001202.v1.p1) (Lesseur et al., 2016). This data is also available via the IEU OpenGWAS project (https://gwas.mrcieu.ac.uk/).All exposure data used in this study is publicly available from the relevant studies as described below. Data for BMI, WC and WHR GWAS was downloaded from the Genetic Investigation of ANthropometric Traits (GIANT) consortiumhttps://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files (Pulit et al., 2019; Shungin et al., 2015) and UK Biobank (http://www.ukbiobank.ac.uk). T2D data was downloaded from the DIAMANTE (DIAbetes Meta-ANalysis of Trans-Ethnic association studies) consortium from: https://kp4cd.org/node/169 (Vujkovic et al., 2020). Data for FG, FI and HbA1c, were obtained from GWAS published by the MAGIC (Meta-Analyses of Glucose and Insulin-Related Traits) Consortium, available for download from: https://magicinvestigators.org/downloads/ (Lagou et al., 2021),. Finally, data for SBP and DBP were extracted from a GWAS meta-analysis of participants in UK Biobank (and UK Biobank (http://www.ukbiobank.ac.uk) and the International Consortium of Blood Pressure Genome Wide Association Studies (ICBP), available via dbGAP (International Consortium for Blood Pressure (ICBP), study accession number: phs000585.v2.p1, October 2016) at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000585.v2.p1 (Evangelou et al., 2018).Instrument-risk factor analysis outcome summary-level data were derived from the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) and UK Biobank and UK Biobank (http://www.ukbiobank.ac.uk) for alcoholic drinks per week https://conservancy.umn.edu/handle/11299/201564 (Liu et al., 2019) and the comprehensive smoking index (Wootton et al., 2019). Data for risk tolerance and educational attainment were taken from Social Science Genetic Association Consortium (SSGAC) data available from http://www.thessgac.org/data (Karlsson Linner et al., 2019; J. Lee et al., 2018). MR analyses were conducted using the 'TwoSampleMR' package in R (version 3.5.3). A copy of the code and all data files used in this study are available at GitHub (https://github.com/MGormley12/metabolic_trait_hnc_mr.git).

The following previously published data sets were used
    1. Vujkovic M
    2. et al
    (2020) DIAMANTE (European) T2D GWAS
    DIAMANTE (DIAbetes Meta-ANalysis of Trans-Ethnic association studies).

Article and author information

Author details

  1. Mark Gormley

    MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
    For correspondence
    mark.gormley@bristol.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5733-6304
  2. Tom Dudding

    Bristol Dental Hospital and School, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Steven J Thomas

    Bristol Dental Hospital and School, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Jessica Tyrrell

    Medical School, University of Exeter, Exeter, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Andrew R Ness

    University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Miranda Pring

    Bristol Dental Hospital and School, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Danny Legge

    Translational Health Sciences, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3897-5861
  8. George Davey Smith

    MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1407-8314
  9. Rebecca C Richmond

    MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Emma E Vincent

    MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8917-7384
  11. Caroline Bull

    MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2176-5120

Funding

Wellcome Trust (220530/Z/20/Z)

  • Mark Gormley

Diabetes UK (SBF004\1079)

  • Jessica Tyrrell

National Institute for Health and Care Research (RP-PG-0707-10034)

  • Andrew R Ness

Cancer Research UK (C18281/A20919)

  • Andrew R Ness

National Institute of Dental and Craniofacial Research (R01 DE025712 and 1X01HG007780-0)

  • Andrew R Ness

Diabetes UK (17/0005587)

  • Emma E Vincent

World Cancer Research Fund (IIG_2019_2009)

  • Emma E Vincent

Medical Research Council (MC_UU_00011/1,MC_UU_00011/5,MC_UU_00011/6,MC_UU_00011/7)

  • George Davey Smith

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Publicly available summary level data only used in this study. Application entitled "Investigating aetiology, associations and causality in diseases of the head and neck" (Project ID: 40644) covers use of all UK Biobank data in this study and dbGaP application made for accessing OncoArray: Oral and Pharynx Cancer; study accession number: phs001202.v1.p1 data entitled "Investigating risk factors in head and neck cancer using Mendelianrandomization" (Project ID 24266).

Copyright

© 2023, Gormley et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Mark Gormley
  2. Tom Dudding
  3. Steven J Thomas
  4. Jessica Tyrrell
  5. Andrew R Ness
  6. Miranda Pring
  7. Danny Legge
  8. George Davey Smith
  9. Rebecca C Richmond
  10. Emma E Vincent
  11. Caroline Bull
(2023)
Evaluating the effect of metabolic traits on oral and oropharyngeal cancer risk using Mendelian randomization
eLife 12:e82674.
https://doi.org/10.7554/eLife.82674

Share this article

https://doi.org/10.7554/eLife.82674

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