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Published on: October 22, 2020
Smoking and Parkinson disease: Evidence for gene-by-smoking interactions
Pei-Chen Lee1, Ismaïl Ahmed1, Marie-Anne Loriot1
1From the Department of Health Care Management (P.-C.L.), College of Health Technology, National Taipei University of Nursing and Health Sciences, Taiwan; Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (I.A.), INSERM, UVSQ, Institut Pasteur, Université Paris-Saclay, Villejuif; Assistance-Publique-Hôpitaux de Paris (M.-A.L.), Hôpital Européen Georges Pompidou, Biochimie, Pharmacogénétique et Oncologie Moléculaire; INSERM UMR-S 1147 (C.M.), CRB EPIGENETEC, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Departments of Epidemiology (K.C.P., B.R.) and Environmental Health (J.M.B., B.R.), Fielding School of Public Health, and Department of Neurology (J.M.B., B.R.), Geffen School of Medicine, University of California at Los Angeles; and Université Paris-Saclay (A.E.), Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France.
Objective:
To investigate whether cigarette smoking interacts with genes involved in individual susceptibility to xenobiotics for the risk of Parkinson disease (PD).
Methods:
Two French population-based case-control studies (513 patients, 1,147 controls) were included as a discovery sample to examine gene-smoking interactions based on 3,179 single nucleotide polymorphisms (SNPs) in 289 genes involved in individual susceptibility to xenobiotics. SNP-by-cigarette smoking interactions were tested in the discovery sample through an empirical Bayes (EB) approach. Nine SNPs were selected for replication in a population-based case-control study from California (410 patients, 845 controls) with standard logistic regression and the EB approach. For SNPs that replicated, we performed pooled analyses including the discovery and replication datasets and computed pooled odds ratios and confidence intervals (CIs) using random-effects meta-analysis.
Results:
Nine SNPs interacted with smoking in the discovery dataset and were selected for replication. Interactions of smoking with rs4240705 in the RXRA gene and rs1900586 in the SLC17A6 gene were replicated. In pooled analyses (logistic regression), the interactions between smoking and rs4240705-G and rs1900586-G were 1.66 (95% CI 1.28-2.14, p = 1.1 × 10-4, p for heterogeneity = 0.366) and 1.61 (95% CI 1.17-2.21, p = 0.003, p for heterogeneity = 0.616), respectively. For both SNPs, while smoking was significantly less frequent in patients than controls in AA homozygotes, this inverse association disappeared in G allele carriers.
Conclusions:
We identified and replicated suggestive gene-by-smoking interactions in PD. The inverse association of smoking with PD was less pronounced in carriers of minor alleles of both RXRA-rs4240705 and SLC17A6-rs1900586. These findings may help identify biological pathways involved in the inverse association between smoking and PD.
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