Genetic variants for smoking behaviour and risk of skin cancer.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
06 10 2023
Historique:
received: 01 08 2023
accepted: 04 10 2023
medline: 1 11 2023
pubmed: 7 10 2023
entrez: 6 10 2023
Statut: epublish

Résumé

Observational studies have suggested that smoking may increase the risk of cutaneous squamous cell carcinoma (cSCC) while decreasing the risks of basal cell carcinoma (BCC), and melanoma. However, it remains possible that confounding by other factors may explain these associations. The aim of this investigation was to use Mendelian randomization (MR) to test whether smoking is associated with skin cancer, independently of other factors. Two-sample MR analyses were conducted to determine the causal effect of smoking measures on skin cancer risk using genome-wide association study (GWAS) summary statistics. We used the inverse-variance-weighted estimator to derive separate risk estimates across genetic instruments for all smoking measures. A genetic predisposition to smoking initiation was associated with lower risks of all skin cancer types, although none of the effect estimates reached statistical significance (OR 95% CI BCC 0.91, 0.82-1.01; cSCC 0.82, 0.66-1.01; melanoma 0.91, 0.82-1.01). Results for other measures were similar to smoking initiation with the exception of smoking intensity which was associated with a significantly reduced risk of melanoma (OR 0.67, 95% CI 0.51-0.89). Our findings support the findings of observational studies linking smoking to lower risks of melanoma and BCC. However, we found no evidence that smoking is associated with an elevated risk of cSCC; indeed, our results are most consistent with a decreased risk, similar to BCC and melanoma.

Identifiants

pubmed: 37803080
doi: 10.1038/s41598-023-44144-0
pii: 10.1038/s41598-023-44144-0
pmc: PMC10558453
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

16873

Informations de copyright

© 2023. Springer Nature Limited.

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Auteurs

Jean Claude Dusingize (JC)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

Matthew H Law (MH)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Mathias Seviiri (M)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.

Catherine M Olsen (CM)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Nirmala Pandeya (N)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Maria Teresa Landi (MT)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Mark M Iles (MM)

Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.

Rachel E Neale (RE)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Jue-Sheng Ong (JS)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

Stuart MacGregor (S)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

David C Whiteman (DC)

Departments of Population Health and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. david.whiteman@qimrberghofer.edu.au.
Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia. david.whiteman@qimrberghofer.edu.au.

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