Synergistic effects of BTN3A1, SHP2, CD274, and STAT3 gene polymorphisms on the risk of systemic lupus erythematosus: a multifactorial dimensional reduction analysis.

OBJECTIVE: Systemic lupus erythematosus is a complex autoimmune disorder, and evidence supports the significance of genetic polymorphisms in SLE genetic susceptibility. The aim of this study was to assess the effects of BTN3A1 (butyrophilin 3A1), SHP2 (Src homology-2 containing protein tyrosine phosphatase), CD274 (programmed cell death 1 ligand 1), and STAT3 (signal transducer-activator of transcription 3) gene interactions on SLE risk. MATERIALS AND METHODS: Two hundred and ninety patients diagnosed with SLE and 370 healthy controls were recruited. A multifactor dimensionality reduction (MDR) approach was used to determine the epistasis among single nucleotide polymorphisms (SNPs) on the BTN3A1 (rs742090), SHP2 (rs58116261), CD174 (rs702275), and STAT3 (rs8078731) genes. The best risk prediction model was identified in terms of precision and cross-validation consistency. RESULTS: Allele A and genotype AA were negatively related to genetic susceptibility of SLE for BTN3A1 rs742090 (OR = 0.788 (0.625-0.993), P = 0.044; OR = 0.604 (0.372-0.981), P = 0.040). For STAT3 rs8078731, allele A and genotype AA were positively related to the risk of SLE (OR = 1.307 (1.032-1.654), P = 0.026; OR = 1.752 (1.020-3.010), P = 0.041). MDR analysis revealed the most significant interaction between BTN3A1 rs742090 and SHP2 rs58116261. The best risk prediction model was a combination of BTN3A1 rs742090, SHP2 rs58116261, and STAT3 rs8078731 (accuracy = 0.5866, consistency = 10/10, OR = 1.9870 (1.5964-2.4731), P = 0.001). CONCLUSION: These data indicate that risk prediction models formed by gene interactions (BTN3A1, SHP2, STAT3) can identify susceptible populations of SLE. Key Points • BTN3A1 rs742090 polymorphism was a protective factor for systemic lupus erythematosus, while STAT3 rs8078731 polymorphism was a risk factor. • There was a strong synergistic effect of BTN3A1 rs742090 and SHP2 rs58116261, and interaction among BTN3A1 rs742090, SHP2 rs58116261, and STAT3 rs8078731 constructed the best model to show association with SLE risk.

Neuropeptide Y, a potential marker for lupus, promotes lupus development.

OBJECTIVE: Relationship between neuropeptide Y (NPY) serum levels, NPY genetic mutation with systemic lupus erythematosus (SLE) pathogenesis is yet to be clarified, and role of NPY in development of SLE needs elucidation. METHOD: This study included 460 SLE patients, 472 non-SLE cases, 500 healthy volunteers. Serum NPY, matrix metalloproteinase-1 (MMP-1) and MMP-8 levels were tested by ELISA. Genotyping 7 NPY single nucleotides polymorphisms (SNPs) (rs5573, rs5574, rs16129, rs16138, rs16140, rs16147, rs16478) was obtained by Kompetitive Allele-Specific PCR (KASP) method. Pristane-induced lupus mice were treated with NPY-Y1 receptor antagonist, and histological analysis, serological changes of the mice were evaluated. RESULTS: NPY serum concentrations were significantly increased in SLE patients when compared to that in healthy volunteers, non-SLE cases. Rs5573 G allele, rs16129 T allele, rs16147 G allele frequencies were significantly different between SLE cases and healthy controls. Rs5574 TT + TC genotypes were related to levels of IgG, C3, C4 and erythrocyte sedimentation rate, and rs16138 GG + GC genotypes correlated with SLE cases with anti-double-stranded deoxyribonucleic acid antibody (anti-dsDNA) (+). Serum MMP-1, MMP-8 concentrations were higher in SLE patients, and NPY levels were significantly related to MMP-1, MMP-8 levels. After treatment of lupus mice with NPY-Y1 receptor antagonist, damage of liver, spleen and kidney was alleviated, production of autoantibodies (anti-nuclear antibody (ANA), total IgG, anti-dsDNA) and MMP-1, MMP-8 was down-regulated, and differentiation of CD3+, CD8+ T cells, B cells, monocytes, macrophages, T helper 1 (Th1), Th2, Th17 cells was reversed. CONCLUSION: NPY may be a biomarker for lupus, which may promote occurrence and development of lupus.

Association between endothelin-1 and systemic lupus erythematosus: insights from a case-control study.

Systemic lupus erythematosus (SLE) is a chronic rheumatic disorder. Endothelin-1, a vasoconstrictor, belongs to the endothelin family and is associated with vascular-related damages. To date, association between ET-1 and pathogenesis of SLE remains unclear. This case-control study was carried out by 314 SLE, 252 non-SLE diseases patients and 500 healthy controls. Serum ET-1, CCN3, IL-28B levels were detected by ELISA, and ET-1 gene polymorphisms (rs5369, rs5370, rs1476046, rs2070699, rs2071942, rs2071943, rs3087459, rs4145451, rs6458155, rs9369217) were genotyped with Kompetitive Allele-Specific PCR. SLE patients had high levels of ET-1, which were correlated with some clinical, laboratory features. Serum CCN3, IL-28B levels were higher in SLE patients, and ET-1 levels were positively correlated with the two cytokines. Rs5370, rs1476046, rs2070699, rs2071942, rs2071943, rs3087459, rs6458155 and rs2070699 were associated with SLE risk. Rs2070699 (T, TT) was related to SLE patients with alopecia. Rs5370 (T, TT, TG), rs1476046 (G,GA), rs2071942 (G,GA) and rs2071943 (G,GA) were associated with SLE patients with pericarditis, pyuria and fever manifestation, respectively. Rs3087459 (CC) and rs9369217 (TC) were related to SLE patients with positive anti-SSB antibody. Rs5369 (AA) was associated with IgG and CRP levels in SLE patients. In conclusion, elevated serum ET-1 in SLE patients may be a potential disease marker, and its gene polymorphisms were related to SLE susceptibility.

Association of STAT3 gene polymorphisms with systemic lupus erythematosus in a Chinese Han population.

OBJECTIVE: Evidence supports the important role of STAT3 in SLE; however, association between STAT3 gene polymorphisms and SLE risk needs discussion. METHODS: Three hundred SLE patients and 380 healthy controls from Chinese Han population were included. DNA is extracted from peripheral blood mononuclear cells and the clinical characteristics of patients are collected. STAT3 gene polymorphisms (rs6503695, rs744166, rs9912773, and rs12601982) were genotyped by the Kompetitive Allele-Specific PCR (KASP) method. SPSS 26.0 was utilized to analyze the genetic susceptibility of SLE and STAT3 gene polymorphisms. RESULTS: Frequencies of genotypes CT, TT, and TT+CT were significantly lower in SLE patients compared with those in healthy controls with respect to rs6503695 (p = .007, p < .001, p = .001). Frequencies of rs744166 genotypes AG, AA, and AA+AG were decreased in SLE patients as compared to those in healthy controls (p = .034, p = .006, p = .009). The recessive models (CC vs GG+GC) for rs9912773 and (AA vs GG+GA) for rs12601982 were significantly related to SLE patients (p = .014, p = .035). Moreover, allele C of rs6503695 was related to optic nerve damage in SLE patients (p = .036). rs744166 allele G was correlated with positive rash and albuminuria in SLE patients (p = .006, p = .014). For rs9912773, SLE patients carrying genotype GG had higher serum C3 and C4 levels compared to genotype GC+CC (p = .029, p = .028). The rs12601982 allele G was strongly associated with positive hypocomplementemia in SLE patients (p = .034). SLE patients carrying genotypes GG, GC, and CC had different SLEDAI score for rs12601982 (GG vs GC vs CC, p = .003). CONCLUSION: STAT3 gene polymorphisms associated with SLE susceptibility.

Exploring machine learning methods for predicting systemic lupus erythematosus with herpes.

OBJECTIVES: To investigate whether machine learning, which is widely used in disease prediction and diagnosis based on demographic data and serological markers, can predict herpes occurrence in patients with systemic lupus erythematosus (SLE). METHODS: A total of 286 SLE patients were included in this study, including 200 SLE patients without herpes and 86 SLE patients with herpes. SLE patients were randomly divided into a training group and a test group, and 18 demographic characteristics and serological indicators were compared between the two groups. RESULTS: We selected basophil, monocyte, white blood cell, age, immunoglobulin E, SLE Disease Activity Index, complement 4, neutrophil, and immunoglobulin G as the basic features of modeling. A random forest model had the best performance, but logistic and decision tree analyses had better clinical decision-making benefits. Random forest had a good consistency between feature importance judgment and feature selection. The 10-fold cross-validation showed the optimization of five model parameters. CONCLUSION: The random forest model may be an excellently performing model, which may help clinicians to identify SLE patients whose disease is complicated by herpes early.

Th1-related transcription factors and cytokines in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an inflammatory disorder related to immunity dysfunction. The Th1 cell family including Th1 cells, transcription factor T-bet, and related cytokines IFNγ, TNFα, IL-2, IL-18, TGF-ß, and IL-12 have been widely discussed in autoimmunity, such as SLE. In this review, we will comprehensively discuss the expression profile of the Th1 cell family in both SLE patients and animal models and clarify how the family members are involved in lupus development. Interestingly, T-bet-related age-associated B cells (ABCs) and low-dose IL-2 treatment in lupus were emergently discussed as well. Collection of the evidence will better understand the roles of the Th1 cell family in lupus pathogenesis, especially targeting IL-2 in lupus.

Emerging role of hypoxia-inducible factor-1α in inflammatory autoimmune diseases: A comprehensive review.

Hypoxia-inducible factor-1α (HIF-1α) is a primary metabolic sensor, and is expressed in different immune cells, such as macrophage, dendritic cell, neutrophil, T cell, and non-immune cells, for instance, synovial fibroblast, and islet ß cell. HIF-1α signaling regulates cellular metabolism, triggering the release of inflammatory cytokines and inflammatory cells proliferation. It is known that microenvironment hypoxia, vascular proliferation, and impaired immunological balance are present in autoimmune diseases. To date, HIF-1α is recognized to be overexpressed in several inflammatory autoimmune diseases, such as systemic lupus erythematosus (SLE), rheumatoid arthritis, and function of HIF-1α is dysregulated in these diseases. In this review, we narrate the signaling pathway of HIF-1α and the possible immunopathological roles of HIF-1α in autoimmune diseases. The collected information will provide a theoretical basis for the familiarization and development of new clinical trials and treatment based on HIF-1α and inflammatory autoimmune disorders in the future.

[Characteristics and contribution of the strengthening units of composite constructed wetland for treating urban sewage].

There are some defects in constructed wetland, including the uneven distribution of flow, easily blocked, lack of oxygen supply systems and the unsatisfactory phosphorus adsorption capacity of the substrates, etc. The research mainly studied the function and contribution of the pool of hydrolysis acidification, the natural reoxygenation/sinking device and strengthen slot for reducing nitrogen and phosphorus. The results showed the removal efficiency of COD and SS in hydrolysis-acidification pool accounted for 38.05% and 34.82% of the total removal efficiency of system. The SS removal efficiency of the natural reoxygenation/sinking device accounted for 22.01% of the total removal efficiency of system, and the concentration of DO kept above 2.5 mg.L-1. The two strengthen slots can ensure the TP, TN, COD up to the standard of the level 1 of GB 18918-2002.