A Gene-Environment Interaction Between Smoking and Gene polymorphisms Provides a High Risk of Two Subgroups of Sarcoidosis.

Rivera NV, Patasova K, Kullberg S, Diaz-Gallo LM, Iseda T, Bengtsson C, Alfredsson L, Eklund A, Kockum I, Grunewald J, Padyukov L

Sci Rep 9 (1) 18633 [2019-12-09; online 2019-12-09]

The influence and effect of cigarette smoking in sarcoidosis is unclear. Here, we evaluated gene-environment interaction between multiple genetic variants including HLA genes and smoking in sarcoidosis defined by two clinical phenotypes, Löfgren's syndrome (LS) and patients without Löfgren's syndrome (non-LS). To quantify smoking effects in sarcoidosis, we performed a gene-environment interaction study in a Swedish population-based case-control study consisting of 3,713 individuals. Cases and controls were classified according to their cigarette smoking status and genotypes by Immunochip platform. Gene-smoking interactions were quantified by an additive interaction model using a logistic regression adjusted by sex, age and first two principal components. The estimated attributable proportion (AP) was used to quantify the interaction effect. Assessment of smoking effects with inclusion of genetic information revealed 53 (in LS) and 34 (in non-LS) SNP-smoking additive interactions at false discovery rate (FDR) below 5%. The lead signals interacting with smoking were rs12132140 (AP = 0.56, 95% CI = 0.22-0.90), p = 1.28e-03) in FCRL1 for LS and rs61780312 (AP = 0.62, 95% CI = 0.28-0.90), p = 3e-04) in IL23R for non-LS. We further identified 16 genomic loci (in LS) and 13 (in non-LS) that interact with cigarette smoking. These findings suggest that sarcoidosis risk is modulated by smoking due to genetic susceptibility. Therefore, patients having certain gene variants, are at a higher risk for the disease. Consideration of individual's genetic predisposition is crucial to quantify effects of smoking in sarcoidosis.

Bioinformatics Support for Computational Resources [Service]

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

National Genomics Infrastructure [Service]

PubMed 31819081

DOI 10.1038/s41598-019-54612-1

Crossref 10.1038/s41598-019-54612-1

pii: 10.1038/s41598-019-54612-1