Abstract
Background Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease with diverse heterogeneous phenotypes. Impact of complex genetic variants on the clinical manifestations of SLE was not fully understood. The aim of this study is to identify the cumulative effect of SLE-risk variants on clinical manifestations and autoantibody profiles in patients with SLE.
Methods A total of 781 Korean patients from the Hanyang BAE lupus cohort were genotyped by Immunochip and genome-wide association study (GWAS) using Illumina HumanOmni1-Quad array. Weighted genetic risk score (GRS) were calculated from 45 well-validated non-HLA SNPs and HLA SLE-risk loci. Individual GRS was tested for associations with the clinical subphenotypes based on 1997 ACR criteria of SLE and the development of autoantibody by using a linear regression or a logistic regression adjusting for the top 10 PCs as covariates, respectively.
Results We identified weighted GRS calculated from non-HLA and HLA SLE-risk loci with significant associations in various SLE subphenotypes defined by the ACR criteria (mean number 5.74) among 11 criteria. Individuals weighted GRS showed significantly positive correlation with the number of ACR criteria in a linear regression model (coefficient=0.128, p=9.00×103). Consistently, a significant positive correlation with the number of ACR in both non-HLA GRS (coefficient=0.110, p=0.027) and HLA GRS (coefficient=0.06, p=0.021) was observed, respectively.
In a clinical subphenotype analysis, weighted GRS from non-HLA and HLA risk loci were significantly related to malar rash (OR 1.23, p=2.68×103), renal disorder (OR 1.15, p=4.41×102), and thrombocytopenia (OR 1.21, p=7.55×103) using a multivariable logistic regression. Weighted GRS were strongly associated with production of anti-DNA antibody (OR 1.38, p=2.18×103).
Conclusions In conclusion, a high cumulative SLE-risk effect promoted diverse clinical manifestations and influenced the production of auto-antibodies including anti-DNA, that could provide clues to identifying distinctive mechanisms in SLE.
Funding Source(s): None
