The local environment and germline genetic variation predict cancer risk in the UK Biobank prospective cohort.

Cancer Distance to coast Gene-environment interactions Local environment Mediation UK Biobank

Journal

Environmental research
ISSN: 1096-0953
Titre abrégé: Environ Res
Pays: Netherlands
ID NLM: 0147621

Informations de publication

Date de publication:
08 Nov 2023
Historique:
received: 17 07 2023
revised: 27 10 2023
accepted: 30 10 2023
pubmed: 10 11 2023
medline: 10 11 2023
entrez: 9 11 2023
Statut: aheadofprint

Résumé

There is a growing body of evidence on the effect of the local environment exposure on cancer susceptibility. Nonetheless, several of the associations remain controversial. Moreover, our understanding of the possible interaction between the local environment and the genetic variability is still very limited. The aim of this study was to clarify the role of the local environment and its possible interplay with genetics on common cancers development. Using the UK Biobank (UKBB) prospective cohort, we selected 12 local environment exposures: nitrogen oxides, nitrogen dioxides, particulate matter (10 and 2.5 μm), noise pollution, urban traffic, living distance from the coast, percentage of greenspace, natural environment, water, and domestic garden within 1000 m from the residential coordinates of each participant. All these exposures were tested for association with 17 different types of cancer for a total of 53,270 cases and 302,645 controls. Additionally, a polygenic score (PGS) was computed for each cancer, to test possible gene-environment interactions. Finally, mediation analyses were carried out. Thirty-six statistically significant associations considering multiple testing (p < 2.19 × 10 Living close to the coast and air pollution were associated with a decreased risk of prostate cancer and skin melanoma, respectively. These findings from the UKBB support the role of the local environment on cancer development, which is independent from genetics and may be mediated by several lifestyle factors.

Sections du résumé

BACKGROUND BACKGROUND
There is a growing body of evidence on the effect of the local environment exposure on cancer susceptibility. Nonetheless, several of the associations remain controversial. Moreover, our understanding of the possible interaction between the local environment and the genetic variability is still very limited.
OBJECTIVE OBJECTIVE
The aim of this study was to clarify the role of the local environment and its possible interplay with genetics on common cancers development.
METHODS METHODS
Using the UK Biobank (UKBB) prospective cohort, we selected 12 local environment exposures: nitrogen oxides, nitrogen dioxides, particulate matter (10 and 2.5 μm), noise pollution, urban traffic, living distance from the coast, percentage of greenspace, natural environment, water, and domestic garden within 1000 m from the residential coordinates of each participant. All these exposures were tested for association with 17 different types of cancer for a total of 53,270 cases and 302,645 controls. Additionally, a polygenic score (PGS) was computed for each cancer, to test possible gene-environment interactions. Finally, mediation analyses were carried out.
RESULTS RESULTS
Thirty-six statistically significant associations considering multiple testing (p < 2.19 × 10
DISCUSSION CONCLUSIONS
Living close to the coast and air pollution were associated with a decreased risk of prostate cancer and skin melanoma, respectively. These findings from the UKBB support the role of the local environment on cancer development, which is independent from genetics and may be mediated by several lifestyle factors.

Identifiants

pubmed: 37944693
pii: S0013-9351(23)02366-6
doi: 10.1016/j.envres.2023.117562
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

117562

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Alessio Felici (A)

Department of Biology, University of Pisa, Pisa, Italy.

Giulia Peduzzi (G)

Department of Biology, University of Pisa, Pisa, Italy.

Francesca Giorgolo (F)

Kode Solutions s.r.l., Pisa, Italy.

Andrea Spinelli (A)

Kode Solutions s.r.l., Pisa, Italy.

Marco Calderisi (M)

Kode Solutions s.r.l., Pisa, Italy.

Anna Monreale (A)

Department of Computer Science, University of Pisa, Pisa, Italy.

Riccardo Farinella (R)

Department of Biology, University of Pisa, Pisa, Italy.

Roberto Pellungrini (R)

Classe di Scienze, Scuola Normale Superiore, Pisa, Italy.

Federico Canzian (F)

Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Daniele Campa (D)

Department of Biology, University of Pisa, Pisa, Italy. Electronic address: daniele.campa@unipi.it.

Classifications MeSH