Occupational and environmental medicine · 2025
Gene-occupational exposure interactions in small airways obstruction in the UK Biobank: a cross-sectional study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Quintero Santofimio Valentina, van der Plaat Diana, Fuertes Elaine, Potts James, Kromhout Hans, Feary Johanna, Amaral Andre F S
Аннотация
OBJECTIVES: Small airways obstruction (SAO) has been associated with lifetime exposure to several agents in the workplace. Whether this association is modified by genetic variants is unknown.
METHODS: Using data from 147 317 adults (33 552 with SAO; 108 762 without SAO) participating in the UK Biobank, we conducted a genome-wide association analysis to identify genetic variants associated with SAO at baseline, defined as the forced expiratory volume in 3 s to 6 s ratio (FEV3/FEV6) below the lower limit of normal. We assigned occupational exposures using the ALOHA+ job exposure matrix. Using cross-sectional data from 38 911 participants (8363 with SAO; 30 548 without SAO), who had complete job histories, we assessed whether the identified genetic variants interacted with occupational exposures on SAO using logistic regression models adjusted for confounders. Additionally, we investigated whether gene-occupational exposure signals were associated with gene expression in lung tissue.
RESULTS: We identified 36 genetic variants significantly associated with SAO. Eight of these significantly modified the association of SAO with pesticides, vapour, gases, dusts, fumes and metals, with participants homozygous for the reference allele being at increased risk of SAO when exposed to these agents. Only two of these genetic variants (rs9273529 and rs644045) appeared to affect gene expression in lung tissue. We found no significant interactions with solvents.
CONCLUSIONS: Using a large population-based cohort, we identified genetic variants that interact and modify the association between SAO and several common workplace exposures. Further research is needed to confirm these effect modification findings and clarify potential biological mechanisms.
METHODS: Using data from 147 317 adults (33 552 with SAO; 108 762 without SAO) participating in the UK Biobank, we conducted a genome-wide association analysis to identify genetic variants associated with SAO at baseline, defined as the forced expiratory volume in 3 s to 6 s ratio (FEV3/FEV6) below the lower limit of normal. We assigned occupational exposures using the ALOHA+ job exposure matrix. Using cross-sectional data from 38 911 participants (8363 with SAO; 30 548 without SAO), who had complete job histories, we assessed whether the identified genetic variants interacted with occupational exposures on SAO using logistic regression models adjusted for confounders. Additionally, we investigated whether gene-occupational exposure signals were associated with gene expression in lung tissue.
RESULTS: We identified 36 genetic variants significantly associated with SAO. Eight of these significantly modified the association of SAO with pesticides, vapour, gases, dusts, fumes and metals, with participants homozygous for the reference allele being at increased risk of SAO when exposed to these agents. Only two of these genetic variants (rs9273529 and rs644045) appeared to affect gene expression in lung tissue. We found no significant interactions with solvents.
CONCLUSIONS: Using a large population-based cohort, we identified genetic variants that interact and modify the association between SAO and several common workplace exposures. Further research is needed to confirm these effect modification findings and clarify potential biological mechanisms.