Purpose Systemic Lupus Erythemathosus (SLE) is a prototypic systemic autoimmune disease characterized by a complex aetiology. Epigenetic alterations are known to be mediators of the environmental and genetic factors and to impact transcriptional programs. Here we aim to investigate genetic correlations between SLE and different molecular traits such as DNA methylation, gene expression and protein level by computing genotypic risk scores for the intermediate traits.

Methods We use genotypes for 13,482 European ancestry individuals obtained from pre-existing projects studying SLE genetics, i) 4,174 SLE patients from a collection of SLE cohorts and 4,048 healthy controls from the University of Michigan Health and Retirement Study, ii) 696 SLE patients and 304 healthy controls from the International Consortium for Systemic Lupus Erythematosus Genetics and iii) 397 SLE patients and 561 healthy controls from the PRECISESADS Consortium. We computed genotypic risk scores for biomarkers using the GENOSCORES platform and tested the association between scores and the SLE phenotype using a logistic regression model for each score separately and adjusting for sex and 20 genetic principal components.

Results We computed 1,716 locus-specific genotypic scores for loci affecting human plasma proteins (pQTLs). We detected 7 protein scores significantly associated with the SLE phenotype at Bonferroni correction. One of the 7 proteins, FCGR2B, is already known in SLE pathogenesis. Additionally, 4 protein scores were located within the HLA region in chromosome 6 (AMBN, ATF6, EDA, FIBCD1) and the remaining 2 (AXIN2, TREML4) scores were located in chromosome 14. Furthermore, we computed scores for the gene expression of these 7 proteins in different tissues and showed that scores for the gene expression of the AXIN2 gene were significantly associated with the SLE phenotype.

Conclusions and Ongoing Analyses This study expands the list of candidate proteins associated with SLE and regions that might contain novel genes implicated in the SLE phenotype. Our findings demonstrate how genotypic scores for molecular traits can be used to identify and characterize genetic associations with complex disease traits. We aim to further explore the detected associations by considering DNA methylation traits and their association with SLE.