Polymorphism in STAT4 Increase the Risk of Systemic Lupus Erythematosus: An Updated Meta-Analysis

Genetic polymorphisms in genes involved in the type I interferon system (STAT4 and IRF5): association with Asian SLE patients

Systemic lupus erythematosus (SLE) is a common autoimmune disease with a polymorphic clinical presentation involving multisystem damages with significant differences in prevalence and disease severity among different ethnic groups. Although genetic, hormonal, and environmental factors have been demonstrated to contribute a lot to SLE, the pathogenesis of SLE is still unknown. Numerous evidence revealed that gene variants within the type I interferons (IFN) signaling pathway performed the great genetic associations with autoimmune diseases including SLE. To date, through genome-wide association studies (GWAS), genetic association studies showed that more than 100 susceptibility genes have been linked to the pathogenesis of SLE, among which TYK2, STAT1, STAT4, and IRF5 are important molecules directly connected to the type I interferon signaling system. The review summarized the genetic associations and the detailed risk loci of STAT4 and IRF5 with Asian SLE patients, explored the genotype distributions associated with the main clinical manifestations of SLE, and sorted out the potential reasons for the differences in susceptibility in Asia and Europe. Moreover, the therapies targeting STAT4 and IRF5 were also evaluated in order to propose more personalized and targeted treatment plans in SLE.

Large-scale DNA sequencing identifies rare variants associated with Systemic Lupus Erythematosus susceptibility in known risk genes

The identification of rare genetic variants associated to Systemic Lupus Erythematosus (SLE) could also help to understand the pathogenic mechanisms at the basis of the disease. In this study we have analyzed a cohort of 200 Italian SLE patients in order to explore the rare protein-coding variants in five genes (TNFAIP3, STAT4, IL10, TRAF3IP2, and HCP5) already investigated for commons variants found associated in our previous studies. Genomic DNA of 200 SLE patients was sequenced by whole exome sequencing. The identified variants were filtered by frequency and evaluated by in silico predictions. Allelic association analysis was performed with standard Fisher's exact test. Introducing a cutoff at MAF < 0.01, a total of 19 rare variants were identified. Seven of these variants were ultra-rare (MAF < 0.001) and six were absent in the GnomAD database. For TNFAIP3 gene, the variant c.A1939C was observed in 4 SLE patients and it is located in a region enriched in phosphorylation sites and affects the predict affinity of specific kinases. In TRAF3IP2 gene, we observed 5 different rare variants, including the novel variant c.G410A, located in the region that mediates interaction with TRAF6, and therefore a possible risk factor for SLE development. In STAT4 gene, we identified 6 different rare variants. Among these, three missense variants decrease the stability of this protein. Moreover, 3 novel rare variants were detected in 3 SLE patients. In particular, c.A767T variant was predicted as damaging by six prediction tools. Concluding, we have observed that even in genes whose common variability is associated with SLE susceptibility, it is possible to identify rare variants that could have a strong effect in the disease development and could therefore allow a better understanding of the functional domain involved.

Multiple polygenic risk scores can improve the prediction of systemic lupus erythematosus in Taiwan

OBJECTIVE

To identify new genetic variants associated with SLE in Taiwan and establish polygenic risk score (PRS) models to improve the early diagnostic accuracy of SLE.

METHODS

The study enrolled 2429 patients with SLE and 48 580 controls from China Medical University Hospital in Taiwan. A genome-wide association study (GWAS) and PRS analyses of SLE and other three SLE markers, namely ANA, anti-double-stranded DNA antibody (dsDNA) and anti-Smith antibody (Sm), were conducted.

RESULTS

Genetic variants associated with SLE were identified through GWAS. Some novel genes, which have been previously reported, such as RCC1L and EGLN3, were revealed to be associated with SLE in Taiwan. Multiple PRS models were established, and optimal cut-off points for each PRS were determined using the Youden Index. Combining the PRSs for SLE, ANA, dsDNA and Sm yielded an area under the curve of 0.64 for the optimal cut-off points. An analysis of human leucocyte antigen (HLA) haplotypes in SLE indicated that individuals with HLA-DQA1*01:01 and HLA-DQB1*05:01 were at a higher risk of being classified into the SLE group.

CONCLUSIONS

The use of PRSs to predict SLE enables the identification of high-risk patients before abnormal laboratory data were obtained or symptoms were manifested. Our findings underscore the potential of using PRSs and GWAS in identifying SLE markers, offering promise for early diagnosis and prediction of SLE.