No abstract

The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex traits. Here we apply dimensionality reduction methods (PCA, t-SNE, PCA-t-SNE, UMAP, and PCA-UMAP) to biobank-derived genomic data of a Japanese population (n = 169,719). Dimensionality reduction reveals fine-scale population structure, conspicuously differentiating adjacent insular subpopulations. We further enluciate the demographic landscape of these Japanese subpopulations using population genetics analyses. Finally, we perform phenome-wide polygenic risk score (PRS) analyses on 67 complex traits. Differences in PRS between the deconvoluted subpopulations are not always concordant with those in the observed phenotypes, suggesting that the PRS differences might reflect biases from the uncorrected structure, in a trait-dependent manner. This study suggests that such an uncorrected structure can be a potential pitfall in the clinical application of PRS.

IntroductionRheumatoid arthritis (RA) is a multifactorial autoimmune disease in which genetic and environmental factors interact in the etiology. In this study, we investigated whether smoking and HLA-DRB1 shared-epitope (SE) alleles interact differently in the development of the two major subgroups of rheumatoid arthritis (RA), anti-citrullinated proteins antibody (ACPA)-positive and ACPA-negative disease, in a multiethnic population of Asian descent.MethodsA case-control study comprising early diagnosed RA cases was carried out in Malaysia between 2005 and 2009. In total, 1,076 cases and 1,612 matched controls participated in the study. High-resolution HLA-DRB1 genotyping was performed for shared-epitope (SE) alleles. All participants answered a questionnaire on a broad range of issues, including smoking habits. The odds ratio (OR) of developing ACPA-positive and ACPA-negative disease was calculated for smoking and the presence of any SE alleles separately. Potential interaction between smoking history (defined as "ever" and "never" smoking) and HLA-DRB1 SE alleles also was calculated.ResultsIn our multiethnic study, both the SE alleles and smoking were associated with an increased risk of developing ACPA-positive RA (OR SE alleles, 4.7; 95% confidence interval (CI), 3.6 to 6.2; OR smoking, 4.1; 95% CI, 1.9 to 9.2). SE-positive smokers had an odds ratio of ACPA-positive RA of 25.6 (95% CI, 10.4 to 63.4), compared with SE-negative never-smokers. The interaction between smoking and SE alleles was significant (attributable proportion due to interaction (AP) was 0.7 (95% CI, 0.5 to 1.0)). The HLA-DRB1*04:05 SE allele, which is common in Asian populations, but not among Caucasians, was associated with an increased risk of ACPA-positive RA, and this allele also showed signs of interaction with smoking (AP, 0.4; 95% CI, -0.1 to 0.9). Neither smoking nor SE alleles nor their combination was associated with an increased risk of ACPA-negative RA.ConclusionsThe risk of developing ACPA-positive RA is associated with a strong gene-environment interaction between smoking and HLA-DRB1 SE alleles in a Malaysian multiethnic population of Asian descent. This interaction seems to apply also between smoking and the specific HLA-DRB1*04:05 SE allele, which is common in Asian populations but not in Caucasians.