Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting predominantly females. To discover additional genetic risk variants for SLE on the X chromosome, we performed a follow-up study of our previously published genome-wide association study (GWAS) data set in this study. Twelve single nucleotide polymorphisms (SNPs) within novel or unpublished loci with P-value < 1.00 × 10−02 were selected for genotype with a total of 2,442 cases and 2,798 controls(including 1,156 cases and 2,330 controls from central China, 1,012 cases and 335 controls from southern China and 274 cases and 133 controls from northern China) using Sequenom Massarry system. Associaton analyses were performed using logistic regression with sample region as a covariate through PLINK 1.07 software. Combined analysis in discovery and central validation dataset discovered a novel locus rs5914778 within LINC01420 associated with SLE at genome-wide significance (P = 1.00 × 10−08; odds ratio (OR) = 1.32). We also confirmed rs5914778 in the southern Chinese sample cohort (P = 5.31 × 10−05; OR = 1.51), and meta-analysis of the samples from the discovery, central and southern validations regions provided robust evidence for the association of rs5914778 (P = 5.26 × 10−12; OR = 1.35). However, this SNP did not show association with SLE in the northern sample (P = 0.33). Further analysis represent the association of northern was significantly heterogeneous compared to central and southern respectively. Our study increases the number of established susceptibility loci for SLE in Han Chinese population and has further demonstrated the important role of X-linked genetic risk variants in the pathogenesis of SLE in Chinese Han population.

Introduction: Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by the production of autoantibodies, immune complex deposition, and tissue/organ damage. In this study, we aimed to identify molecular features and signaling pathways associated with SLE severity using RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), and clinical parameters.Methods: We analyzed transcriptome profiles of 45 SLE patients, grouped into mild (mSLE, SLEDAI ≤ 9) and severe (sSLE, SLEDAI > 9) based on SLE Disease Activity Index (SLEDAI) scores. We also collected clinical data on anti-dsDNA, ANA, ESR, CRP, snRNP, AHA, and anti-Smith antibody status for each patient.Results: By comparing gene expression across groups, we identified 12 differentially expressed genes (DEGs), including 7 upregulated (CEACAM6, UCHL1, ARFGEF3, AMPH, SERPINB10, TACSTD2, and OTX1) and 5 downregulated (SORBS2, TRIM64B, SORCS3, DRAXIN, and PCDHGA10) DEGs in sSLE compared to mSLE. Furthermore, using the CIBERSORT algorithm, we found that Treg cells were significantly decreased in sSLE and negatively correlated with AMPH expression, which was mainly expressed in Treg cells from SLE patients according to public scRNA-seq data (GSE135779).Discussion: Overall, our findings shed light on the molecular mechanisms underlying SLE severity and provide insight into potential therapeutic targets.

Purpose: Systemic lupus erythematosus (SLE) is a typical autoimmune disease characterized by the involvement of multiple organs and the production of antinuclear antibodies. This study aimed to investigate the molecular mechanism of SLE. Patients and Methods: We retrieved genome-wide gene expression levels from five public datasets with relatively large sample sizes from the Gene Expression Omnibus (GEO), and we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from SLE patients and healthy controls (HCs). The expression of seven target genes in PBMCs from 25 cases and 3 HCs was further validated by reverse-transcription quantitative PCR (RT‒qPCR). Flow cytometry was used for verifying the proportion of naive CD4(+) T cells and M2 macrophages in PBMCs from 5 cases and 4 HCs. Results: We found 14 genes (TRIM5, FAM8A1, SHFL, LHFPL2, PARP14, IFIT5, PARP12, DDX60, IRF7, IF144, OAS1, OAS3, RHBDF2, and RSAD2) that were differentially expressed among all five datasets. The heterogeneity test under the fixed effect model showed no obvious heterogeneity of TRIM5, FAM8A1, and SHFL across different populations. TRIM5 was positively correlated with the remaining 13 genes. By separating patient samples into TRIM5-high and TRIM5-low groups, we found that up-regulated genes in the TRIM5-high group were mainly enriched in virus-related pathways. Immune cell proportion analysis and flow cytometry revealed that naive CD4(+) T cells were significantly decreased while M2 macrophages were increased in the SLE group. TRIM5 expression levels were negatively correlated with naive CD4(+) T cells but positively correlated with M2 macrophages. Conclusion: Our data indicated that TRIM5 might be a key factor that modulates SLE etiology, possibly through naive CD4(+) T cells and M2 macrophages.