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.

Lupus nephritis or not? A simple and clinically friendly machine learning pipeline to help diagnosis of lupus nephritis.

OBJECTIVE: Diagnosis of lupus nephritis (LN) is a complex process, which usually requires renal biopsy. We aim to establish a machine learning pipeline to help diagnosis of LN. METHODS: A cohort of 681 systemic lupus erythematosus (SLE) patients without LN and 786 SLE patients with LN was established, and a total of 95 clinical, laboratory data and 17 meteorological indicators were collected. After tenfold cross-validation, the patients were divided into training set and test set. The features selected by collective feature selection method of mutual information (MI) and multisurf were used to construct the models of logistic regression, decision tree, random forest, naive Bayes, support vector machine (SVM), light gradient boosting (LGB), extreme gradient boosting (XGB), and artificial neural network (ANN), the models were compared and verified in post-analysis. RESULTS: Collective feature selection method screens out antistreptolysin (ASO), retinol binding protein (RBP), lupus anticoagulant 1 (LA1), LA2, proteinuria and other features, and the hyperparameter optimized XGB (ROC: AUC = 0.995; PRC: AUC = 1.000, APS = 1.000; balance accuracy: 0.990) has the best performance, followed by LGB (ROC: AUC = 0.992; PRC: AUC = 0.997, APS = 0.977; balance accuracy: 0.957). The worst performance is naive Bayes model (ROC: AUC = 0.799; PRC: AUC = 0.822, APS = 0.823; balance accuracy: 0.693). In the composite feature importance bar plots, ASO, RF, Up/Ucr, and other features play important roles in LN. CONCLUSION: We developed and validated a new and simple machine learning pathway for diagnosis of LN, especially the XGB model based on ASO, LA1, LA2, proteinuria, and other features screened out by collective feature selection.

SHP2: its association and roles in systemic lupus erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune inflammatory disease. Src homology 2 domain containing protein tyrosine phosphatase (SHP2) is a member of the protein tyrosine phosphatases (PTPs) family. To date, relationship between SHP2 and SLE pathogenesis is not elucidated. METHOD: We measured plasma levels of SHP2 in 328 SLE patients, 78 RA patients, 80 SS patients and 79 healthy controls by ELISA, and discussed association of SHP2 in SLE patients, potential of plasma SHP2 as a SLE biomarker. Moreover, histological and serological changes were evaluated by flow cytometry, HE/Masson examination, immunofluorescence test in pristane-induced lupus mice after SHP2 inhibitor injection to reveal role of SHP2 in lupus development. RESULTS: Results indicated that SHP2 plasma levels were upregulated in SLE patients and correlated with some clinical, laboratory characteristics such as proteinuria, pyuria, and may be a potential biomarker for SLE. After SHP2 inhibitor treatment, hepatosplenomegaly and histological severity of the kidney in lupus mice were improved. SHP2 inhibitor reversed DCs, Th1, and Th17 cells differentiation and downregulated inflammatory cytokines (IL-4, IL-6, IL-10, IL-17A, IFN-γ and TNF-α) and autoantibodies (ANA, anti-dsDNA) production in pristane-lupus mice. CONCLUSION: In summary, SHP2 correlated with SLE pathogenesis and promoted the development of lupus.

Systemic lupus erythematosus with high disease activity identification based on machine learning.

OBJECTIVE: Clinical evaluation of systemic lupus erythematosus (SLE) disease activity is limited and inconsistent, and high disease activity significantly, seriously impacts on SLE patients. This study aims to generate a machine learning model to identify SLE patients with high disease activity. METHOD: A total of 1014 SLE patients with low disease activity and 453 SLE patients with high disease activity were included. A total of 94 clinical, laboratory data and 17 meteorological indicators were collected. After data preprocessing, we use mutual information and multisurf to evaluate and select the importance of features. The selected features are used for machine learning modeling. Performance of the model is evaluated and verified by a series of binary classification indicators. RESULTS: We screened out hematuria, proteinuria, pyuria, low complement, precipitation, sunlight and other features for model construction by integrated feature selection. After hyperparameter optimization, the LGB has the best performance (ROC: AUC = 0.930; PRC: AUC = 0.911, APS = 0.913; balance accuracy: 0.856), and the worst is the naive bayes (ROC: AUC = 0.849; PRC: AUC = 0.719, APS = 0.714; balance accuracy: 0.705). Finally, the selection of features has good consistency in the composite feature importance bar plot. CONCLUSION: We identify SLE patients with high disease activity by a simple machine learning pipeline, especially the LGB model based on the characteristics of proteinuria, hematuria, pyuria and other feathers screened out by collective feature selection.

Role of miR-155 in inflammatory autoimmune diseases: a comprehensive review.

PURPOSE: MiR-155 is a member of the microRNAs (miRNAs) family and regulates gene expression post-transcriptionally by binding to the 3'UTR of target mRNA. MiR-155 has a critical role in both innate and adaptive immunity. MiR-155 is aberrantly expressed in inflammatory autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, type 1 diabetes, Sjögren's syndrome, systemic sclerosis, and inflammatory bowel disease. Functional studies suggest that miR-155 is involved in development of these diseases. In vitro and in vivo experiments have shown that inhibition of miR-155 can alter disease progression or ameliorate disease symptoms. MATERIALS AND METHODS: A systematic review of relevant literatures published between January 1, 2005, and March 1, 2022 about miR-155 and its role in immune cells, autoimmune diseases was searched on PubMed, EMBASE, Google Scholar. CONCLUSION: In this review, we comprehensively discussed the effects of miR-155, including role of miR-155 in different downstream signaling, which then differently regulate immune cells expression and functions. Furthermore, miR-155-mediated dysfunction of immune cells contributed to development of inflammatory autoimmune diseases. Therefore, miR-155 is expected to be a therapeutic target for inflammatory autoimmune diseases.

IL-38, a potential therapeutic agent for lupus, inhibits lupus progression.

BACKGROUND: Previous studies reported that IL-38 was abnormally expressed in patients with systemic lupus erythematosus (SLE). However, the involvement of IL-38 in the pathophysiology of SLE remains unknown. METHODS: The therapeutic potential of IL-38 was tested in pristane-treated wild-type (WT) and IL-38-/- mice. Thus, SLE was induced via pristane in WT and IL-38-/- mice. Afterwards, the liver, spleen, and kidney of each mouse were obtained. The flow cytometric analysis of the immune cells, serologic expression of inflammatory cytokines and autoantibodies, renal histopathology, and inflammatory signaling were evaluated. RESULTS: WT mice with pristane-induced lupus exhibited hepatomegaly, splenomegaly, severe kidney damages, increased lymphoproliferation, enhanced lymphoproliferation, and upregulated inflammatory cytokines, such as IL-6, IL-13, IL-17A, MIP-3α, IL-12p70, and IFNγ, and elevated levels of autoantibodies, such as ANA IgG, anti-dsDNA IgG, and total IgG. IL-38-/- mice whose lupus progressed, had elevated cells of CD14+, CD19+, CD3+, and Th1, upregulated inflammatory cytokines and autoantibodies, and severe pathological changes in kidney. Administration of recombinant murine IL-38 to pristane-treated IL-38-/- mice improved their renal histopathology, which depended on ERK1/2, JNK1/2, p38, NF-κB p65, and STAT5 signaling pathways. CONCLUSION: IL-38 regulates SLE pathogenesis. Furthermore, targeting IL-38 is critical in the treatment of SLE.

Association between IL-37 and Systemic Lupus Erythematosus Risk.

Interleukin-37 (IL-37) is an anti-inflammatory cytokine. In our former study, we found increased plasma IL-37 levels in systemic lupus erythematosus (SLE) patients. However, relationship between IL-37 levels and clinical laboratory characteristics of SLE patients has not been elucidated. In addition, association of IL37 gene polymorphism with SLE risk needs to be discussed. A group of 580 individuals (220 SLE patients and 360 healthy controls) in a Southern Chinese Han population were recruited. Plasma IL-37 levels were evaluated using enzyme-linked immunosorbent assay (ELISA). Four single-nucleotide polymorphisms (rs3811047, rs2723186, rs2723176 and rs4364030) of IL37 gene were genotyped. Relationship of IL-37 expression, IL37 gene polymorphisms and clinical characteristics was discussed. We found that plasma levels of IL-37 were negatively associated with SLE disease activity index (SLEDAI) (rs = -0.352, P = .001), and were higher in less active patients compared with active patients (P = .003). Decreased levels of IL-37 were found in SLE patients with discoid rash when compared to patients who did not have this symptom (P < .001). Plasma IL-37 levels were significantly lower in patients with hypocomplementemia comparing to those without this feature (P = .009). Levels of IL-37 in SLE with positive proteinuria were lower than patients with negative proteinuria (P = .046). Furthermore, allele distribution of rs2723186, rs4364030 between SLE cases and healthy individuals was significantly different (P = .001, P = .010, respectively). Genotype of rs4364030 was different between SLE cases and controls (P = .015). Haplotype analysis revealed that the frequency of haplotype CG (rs2723176 (C) +rs2723186 (G)) was higher in SLE, as compared with healthy individuals (P = .002). In conclusion, the plasma levels of IL-37 were related to SLE severity, and IL37 gene polymorphisms (rs2723186, rs2723176 and rs4364030) may associate with SLE susceptibility.

Gene polymorphisms of LGALS2, LGALS3 and LGALS9 in patients with rheumatoid arthritis.

Rheumatoid arthritis (RA) is a complicated rheumatic autoimmune disease. Lectin, galactoside-binding soluble, 2 (LGALS2), LGALS3 and LGALS9, three members of the galectin family, play potential roles in autoimmune diseases, including RA. However, association of genetic polymorphisms of LGALS2, LGALS3 and LGALS9 with RA risk in a Southern Chinese Han population has not been elucidated. A case-control study was conducted herein, including 500 RA patients and 650 healthy individuals of Southern Chinese Han origin. Twelve single nucleotide polymorphisms (SNPs), including rs7291467 for the LGALS2 gene, rs4644, rs4652, rs1009977, rs2274273 and rs17128183 for the LGALS3 gene, and rs4795835, rs3763959, rs4239242, rs3751093, rs732222 and rs4794976 for the LGALS9 gene, were genotyped. Polymorphisms were genotyped using the KASP method. Frequencies of rs1009977 genotype TG and rs3751093 genotype GA of LGALS3 gene were significantly different between RA patients and healthy controls (P = 0.049, P = 0.033). Allele T and genotypes TT and TT + TG of rs4794976 for LGALS9 gene were significantly correlated with RA risk (P = 0.017, P = 0.012, P = 0.041). Subgroup analysis revealed that rs1009977, rs2274273 and rs17128183 polymorphisms of LGALS3 gene and rs4795835 polymorphism of LGALS9 gene were correlated with several RA clinical manifestations (all P < 0.05). In addition, haplotype GCGTT showed an increased risk for RA (OR = 1.216, 95% CI: 1.028-1.438, P = 0.023), whereas haplotype GCGTG showed a reduced risk for RA susceptibility (OR = 0.779, 95% CI: 0.625-0.971, P = 0.026). In conclusion, LGALS3 and LGALS9 gene polymorphisms may associate with RA predisposition in a Southern Chinese Han population.

Association of STAT4 Gene Rs7574865, Rs10168266 Polymorphisms and Systemic Lupus Erythematosus Susceptibility: A Meta-analysis.

Association of signal transducer and activator of transcription 4 (STAT4) gene rs7574865, rs10168266 polymorphisms with systemic lupus erythematosus (SLE) risk remains unclear. A meta-analysis was conducted on the correlation between rs7574865, rs10168266 polymorphisms and SLE. Twenty-six studies were recruited in our study (17,389 patients and 29,273 controls). For rs7574865, results showed significant associations between T allele and SLE susceptibility in overall population, Asians and Europeans (OR=1.557, 95%CI: 1.505-1.611, P<0.001; OR=1.557, 95%CI: 1.498-1.661, P<0.001; OR=1.548, 95%CI: 1.474-1.625, P<0.001). Significant associations of genotypes TT, GT, TT+TG and SLE risk were observed in general subjects, Asians and Europeans (all P<0.001). Regarding rs10168266, increased T allele frequencies were detected in overall SLE cases and those from Asian origin (OR=1.532, 95%CI: 1.440-1.631, P<0.001; OR=1.575, 95%CI: 1.445-1.717, P<0.001). The overall data showed that TT genotype, CT genotype and TT+CT genotype were significantly correlated with SLE (all P < 0.001). In conclusion, the present study verified strong association of STAT4 gene rs7574865, rs10168266 polymorphisms and SLE susceptibility.

Association of MASP2 levels and MASP2 gene polymorphisms with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disorder. MASP2 is a mediator that plays an important role in complement system. As dysregulation of the complement system has been demonstrated to correlate with SLE pathogenesis, the role of MASP2 in lupus has not been widely discussed. In the present study, serum levels of MASP2 were evaluated in 61 lupus patients and 98 healthy controls by training cohort, and then a validation cohort including 100 lupus, 100 rheumatoid arthritis, 100 osteoarthritis, 100 gout, 44 Sjogren's syndrome, 41 ankylosing spondylitis patients confirmed the findings. Receiver operating characteristic (ROC) curve analysis determined the discriminatory capacity for serum MASP2. PCR methods tested the association of MASP2 gene polymorphisms (rs7548659, rs17409276, rs2273346, rs1782455 and rs6695096) and SLE risk. Impact of polymorphism on MASP2 serum levels was evaluated as well. Results showed that serum levels of MASP2 were significantly higher in lupus patients and correlated with some clinical, laboratory characteristics in the training cohort, and were much higher as compared to that in different rheumatic diseases patients in the validation cohort. Serum MASP2 showed a good diagnostic ability for lupus. Genotype frequencies and allele frequency of polymorphisms rs7548659, rs2273346 were strongly related to SLE risk, and genotypes of rs17409276, rs1782455, rs76695096 were significantly correlated with lupus genetic susceptibility. Interestingly, patients carrying GA genotype of rs17409276, TT, TC genotype of rs6695096 showed higher levels of serum MASP2. The findings suggested that MASP2 may be a potential disease marker for lupus, and correlate with SLE pathogenesis.

IL-38: A novel cytokine in systemic lupus erythematosus pathogenesis.

IL-38 is a newly identified cytokine that belongs to the IL-1 family. In our previous study, we found elevated plasma levels of IL-38 in patients with systemic lupus erythematosus (SLE). However, the clear relationship of IL-38 expression in plasma, peripheral blood mononuclear cells (PBMCs) and clinical and laboratory features needs elucidation. Additionally, we evaluated the possible role of IL-38 in regulating production of inflammatory cytokines in PBMCs in vitro. A pristane-induced murine lupus model was used to further demonstrate the effects of IL-38 on cytokines in vivo and discuss the significance of IL-38 in lupus development. The results showed that mRNA expression of IL-38 in PBMCs of patients with SLE was elevated compared with volunteers, and expression of IL-38 in both plasma and PBMCs was strongly related to clinical features, such as haematuria and proteinuria, and correlated with a SLEDAI score. Plasma levels of TNF-α, IL-1ß, IL-6 and IL-23 were elevated in patients with SLE and were related to plasma levels of IL-38. In vitro, PBMCs of patients with SLE stimulated with IL-38 showed a decreased expression of the four inflammatory cytokines compared with PBMCs of patients without treatment. Interestingly, IL-38 administration in lupus mice significantly reduced the development of lupus, such as reduced proteinuria, improved histological examinations of the kidneys and down-regulated inflammatory cytokines. In conclusion, IL-38 may suppress synthesis of pro-inflammatory cytokines and therefore regulate lupus pathogenesis.

Insights into IL-29: Emerging role in inflammatory autoimmune diseases.

Interleukin-29 (IL-29) is a newly discovered member of type III interferon. It mediates signal transduction via binding to its receptor complex and activates downstream signalling pathways, and therefore induces the generation of inflammatory components. Recent studies reported that expression of IL-29 is dysregulated in inflammatory autoimmune diseases, such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, Sjögren's syndrome, psoriasis and systemic sclerosis. Furthermore, functional analysis revealed that IL-29 may involve in the pathogenesis of the inflammatory autoimmune disorders. In this review, we will systematically review the current knowledge about IL-29. The information collected revealed the regulatory role of IL-29 and may give important implications for its potential in clinical treatment.

Gene polymorphisms and serum levels of TL1A in patients with rheumatoid arthritis.

Recent findings showed elevated expression of tumor necrosis factor (TNF)-like ligand 1A (TL1A) in rheumatoid arthritis (RA) patients and arthritis mice. However, whether TL1A gene polymorphisms may correlate with RA susceptibility needs to be discussed. This case-control study was performed on 350 RA patients and 556 healthy subjects to identify TL1A genetic variants (rs3810936, rs6478109, and rs7848647) and their possible association with TL1A levels, susceptibility to and severity of RA. Odds ratio and 95% confidence interval were calculated to represent the correlation between TL1A polymorphisms and RA. The TL1A serum levels were evaluated. Results showed that frequencies of TC, TT + TC genotypes of rs3810936, rs7848647 in RA patients were significantly lower in RA patients compared with controls. Patients with C allele showed more severe disease course (disease activity index: erythrocyte sedimentation rate, rheumatoid factor) than in carriers of T allele. However, the allele or genotype frequencies of rs6478109 were not associated with RA. In addition, TL1A genetic variants conferred higher TL1A levels in RA patients compared with controls. In conclusion, these findings indicated an association between TL1A rs3810936, rs7848647 variation and the susceptibility of RA in a sample of Chinese individuals, and TL1A may correlate with severity of RA.

Targeting IL-34 in inflammatory autoimmune diseases.

Interleukin-34 (IL-34) shares a common receptor with macrophage colony-stimulating factor (M-CSF), and can bind to CSF-1R, induces lymphocytes differentiation, proliferation, and regulates the synthesis of inflammatory components. Recent findings reported aberrant expression of IL-34 in several autoimmune disorders, such as lupus, arthritis, systemic sclerosis, inflammatory bowel diseases. The functional analysis further demonstrated that IL-34 may perform significantly in these inflammatory autoimmune disorders. IL-34 might consider as a biomarker for these diseases. I hope this collection of the findings in this review will improve knowledge of the role of IL-34, and targeting IL-34 may give the potential for these autoimmune diseases.

Association between TL1A gene polymorphisms and systemic lupus erythematosus in a Chinese Han population.

Our previous studies showed elevated tumor necrosis factor-like ligand 1 aberrance (TL1A) expression in systemic lupus erythematosus (SLE). However, TL1A polymorphisms with SLE susceptibility remain to be elucidated. In addition, we made meta-analysis to evaluate the relationship of TL1A polymorphisms and autoimmune diseases owing to inconsistent results. The present research was carried out by 404 SLE, 150 primary Sjogren's syndrome (pSS) patients, and 574 healthy individuals. Three TL1A polymorphisms (rs3810936, rs6478109, rs7848647) were genotyped using TaqMan genotyping assay. Then, the meta-analysis was performed by collecting the present case-control study and previously published research. Results showed that genotypes of rs3810936, rs7848647 were different between SLE patients and healthy controls, whereas no significant association was observed in the three polymorphisms and pSS patients. Genotypes distribution of rs6478109, rs7848647 were strongly related to lupus nephritis within SLE (p = 0.004, p = 0.011), respectively. Moreover, combined meta-analysis consisted of ten comparative research involving 4,305 patients and 5,600 controls. An association between autoimmune diseases and rs6478109 polymorphism was found. Our findings indicate that gene polymorphisms (rs3810936, rs7848647) of TL1A might correlate with lupus.

The causal associations of inflammatory cytokines with obesity and systemic lupus erythematosus: A Mendelian randomization study.

OBJECTIVE: Previous studies have partly discussed the roles of inflammatory cytokines in obesity and systemic lupus erythematosus (SLE), but the causal relationship among inflammatory cytokines, obesity, and SLE is unclear. It is challenging to comprehensively evaluate the causal relationship between these variables. This study aimed to investigate the role of cytokines as intermediates between obesity and SLE. METHODS: The inverse-variance weighted method (IVW) of mendelian randomization (MR) is mainly used to explore the causal relationship between exposure and outcome by using the genetic variation of the open large genome-wide association studies (GWAS), namely single-nucleotide polymorphisms (SNPs) related to obesity (more than 600 000 participants), inflammatory cytokines (8293 healthy participants) and SLE (7219 cases). Methods such as weighted median, MR-Egger are used to evaluate the reliability of causality. Reverse analysis is performed for each MR analysis to avoid reverse causality. Cochran's Q statistic and funnel chart are used to detect heterogeneity, MR-Egger intercept test and leave-one-out sensitivity analyses evaluated pleiotropy. RESULTS: Obesity was associated with 25 cytokines, and 3 cytokines were associated with SLE, including CTACK (OR = 1.19, 95% CI: 1.06, 1.33, p = .002), IL-18 (OR = 1.13, 95% CI: 1.01, 1.26, p = .027), SCGFb (OR = 0.89, 95% CI: 0.79, 0.99, p = .044). In the opposite direction, SLE was associated with 18 cytokines, and 2 cytokines were associated with obesity, including IP-10 (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .002), MIP-1B (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .004). CONCLUSION: Our MR study suggested that CTACK, IL-18 and SCGFb may play an intermediary role in obesity to SLE, while IP-10 and MIP-1B may play an intermediary role in SLE to obesity.

An updated advancement of bifunctional IL-27 in inflammatory autoimmune diseases.

Interleukin-27 (IL-27) is a member of the IL-12 family. The gene encoding IL-27 is located at chromosome 16p11. IL-27 is considered as a heterodimeric cytokine, which consists of Epstein-Barr virus (EBV)-induced gene 3 (Ebi3) and IL-27p28. Based on the function of IL-27, it binds to receptor IL-27rα or gp130 and then regulates downstream cascade. To date, findings show that the expression of IL-27 is abnormal in different inflammatory autoimmune diseases (including systemic lupus erythematosus, rheumatoid arthritis, Sjogren syndrome, Behcet's disease, inflammatory bowel disease, multiple sclerosis, systemic sclerosis, type 1 diabetes, Vogt-Koyanagi-Harada, and ankylosing spondylitis). Moreover, in vivo and in vitro studies demonstrated that IL-27 is significantly in3volved in the development of these diseases by regulating innate and adaptive immune responses, playing either an anti-inflammatory or a pro-inflammatory role. In this review, we comprehensively summarized information about IL-27 and autoimmunity based on available evidence. It is hoped that targeting IL-27 will hold great promise in the treatment of inflammatory autoimmune disorders in the future.

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.

Prediction model for developing neuropsychiatric systemic lupus erythematosus in lupus patients.

OBJECTIVE: This study aimed to construct a predictive model for assessing the risk of development of neuropsychiatric systemic lupus erythematosus (NPSLE) among patients with SLE based on clinical, laboratory, and meteorological data. METHODS: A total of 2232 SLE patients were included and were randomly assigned into training and validation sets. Variables such as clinical and laboratory data and local meteorological data were screened by univariate and least absolute shrinkage and selection operator (LASSO) logistic regression modelling. After 10-fold cross-validation, the predictive model was built by multivariate logistic regression, and a nomogram was constructed to visualize the risk of NPSLE. The efficacy and accuracy of the model were assessed by receiver operating characteristic (ROC) curve and calibration curve analysis. Net clinical benefit was assessed by decision curve analysis. RESULTS: Variables that were included in the predictive model were anti-dsDNA, anti-SSA, lymphocyte count, hematocrit, erythrocyte sedimentation rate, pre-albumin, retinol binding protein, creatine kinase isoenzyme MB, Nterminal brain natriuretic peptide precursor, creatinine, indirect bilirubin, fibrinogen, hypersensitive C-reactive protein, CO, and mild contamination. The nomogram showed a broad prediction spectrum; the area under the curve (AUC) was 0.895 (0.858-0.931) for the training set and 0.849 (0.783-0.916) for the validation set. CONCLUSION: The model exhibits good predictive performance and will confer clinical benefit in NPSLE risk calculation. Key Points • Clinical, laboratory, and meteorological data were incorporated into a predictive model for neuropsychiatric systemic lupus erythematosus (NPSLE) in SLE patients. • Anti-dsDNA, anti-SSA, LYM, HCT, ESR, hsCRP, IBIL, PA, RBP, CO, Fib, NT-proBNP, Crea, CO, and mild contamination are predictors of the development of NPSLE and may have potential for research. • The nomogram has good predictive performance and clinical value and can be used to guide clinical diagnosis and treatment.