Risk Of Systemic Lupus Erythematosus Research Articles

Gut microbiota landscape and potential biomarker identification in female patients with systemic lupus erythematosus using machine learning.

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease that disproportionately affects women. Early diagnosis and prevention are crucial for women's health, and the gut microbiota has been found to be strongly associated with SLE. This study aimed to identify potential biomarkers for SLE by characterizing the gut microbiota landscape using feature selection and exploring the use of machine learning (ML) algorithms with significantly dysregulated microbiotas (SDMs) for early identification of SLE patients. Additionally, we used the SHapley Additive exPlanations (SHAP) interpretability framework to visualize the impact of SDMs on the risk of developing SLE in females. Stool samples were collected from 54 SLE patients and 55 Negative Controls (NC) for microbiota analysis using 16S rRNA sequencing. Feature selection was performed using Elastic Net and Boruta on species-level taxonomy. Subsequently, four ML algorithms, namely logistic regression (LR), Adaptive Boosting (AdaBoost), Random Forest (RF), and eXtreme gradient boosting (XGBoost), were used to achieve early identification of SLE with SDMs. Finally, the best-performing algorithm was combined with SHAP to explore how SDMs affect the risk of developing SLE in females. Both alpha and beta diversity were found to be different in SLE group. Following feature selection, 68 and 21 microbiota were retained in Elastic Net and Boruta, respectively, with 16 microbiota overlapping between the two, i.e., SDMs for SLE. The four ML algorithms with SDMs could effectively identify SLE patients, with XGBoost performing the best, achieving Accuracy, Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, and AUC values of 0.844, 0.750, 0.938, 0.923, 0.790, and 0.930, respectively. The SHAP interpretability framework showed a complex non-linear relationship between the relative abundance of SDMs and the risk of SLE, with Escherichia_fergusonii having the largest SHAP value. This study revealed dysbiosis in the gut microbiota of female SLE patients. ML classifiers combined with SDMs can facilitate early identification of female patients with SLE, particularly XGBoost. The SHAP interpretability framework provides insight into the impact of SDMs on the risk of SLE and may inform future scientific treatment for SLE.

Genetically predicted 486 blood metabolites concerning risk of systemic lupus erythematosus: a Mendelian randomization study

Metabolic abnormalities constitute a significant characteristic of systemic lupus erythematosus (SLE). We utilised a two-sample Mendelian randomisation (MR) study to evaluate the potential causal association between 486 blood metabolites and SLE. Exposure data at the metabolite level were extracted from 7824 European Genome-wide association studies (GWAS). Preliminary analysis utilised SLE GWAS data from FinnGen. The primary method for causal analysis relied on random inverse variance weighting (IVW). To ensure robustness, sensitivity analyses included the Cochran Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Steiger testing and linkage disequilibrium score regression were employed to validate the identified metabolites. This study identified 12 metabolites, comprising six known chemical structures: 1,5-anhydroglucitol(1,5-AG) [odds ratio (OR) = 0.100, 95% confidence interval (CI): 0.015–0.773, P = 0.027), gamma-glutamylthreonine (OR = 0.077, 95% CI: 0.010–0.574, P = 0.012), 5-dodecenoate(12:1n7) (OR = 0.205, 95% CI: 0.061–0.685, P = 0.010), linoleoylglycerophosphoethanolamine * (OR = 0.159, 95% CI: 0.027–0.933, P = 0.044), erythrose (OR = 88.331,95% CI:1.098–63.214, P = 0.040) and 1-, adrenate (22:4n6) (OR = 9.876, 95% CI: 1.753–55.639, P = 0.001)]. Additionally, we found associations between SLE and six unknown chemical structures: X-06351 (OR = 0.071, 95% CI: 0.006–0.817, P = 0.034), X-10810 (OR = 4.268 95% CI: 1.260–14.459, P = 0.020), X-11412 (OR = 5.418 95% CI: 1.068–27.487, P = 0.041), X-11905 (OR = 0.551, 95%CI: 0.304–0.997, P = 0.049), X-12038 (OR = 0.178 95%CI: 0.032–0.988, P = 0.045), X-12217 (OR = 0.174 95%CI: 0.044–0.680, P = 0.014). This study offers evidence supporting a causal relationship between SLE and 12 circulating metabolites, six of which have known chemical structures and six that remain unidentified. These findings introduce a new perspective for further exploration of SLE mechanisms.

Managing Cardiovascular Risk in Systemic Lupus Erythematosus: Considerations for the Clinician

Managing Cardiovascular Risk in Systemic Lupus Erythematosus: Considerations for the Clinician

Evaluation of causal associations between interleukin-18 levels and immune-mediated inflammatory diseases: a Mendelian randomization study

BackgroundAltered interleukin (IL)-18 levels are associated with immune-mediated inflammatory diseases (IMIDs), but no studies have investigated their causal relationship. This study aimed to examine the causal associations between IL-18 and IMIDs.MethodsWe performed a two-sample Mendelian randomization (MR) analysis. Genetic variants were selected from genome-wide association study datasets following stringent assessments. We then used these variants as instrumental variables to estimate the causal effects of IL-18 levels on the risk of developing five common IMIDs: rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), ankylosing spondylitis (AS), and psoriasis. We used the inverse variance-weighted (IVW) method as the primary analysis, with sensitivity analyses performed to avoid potential bias. Reverse-direction MR analyses were performed to rule out the possibility of reverse associations.ResultsWe found that genetically determined higher circulating IL-18 levels were causally associated with a higher risk for SLE (PIVW = 0.009; OR, 1.214; 95% CI, 1.049 − 1.404) and IBD (PIVW < 0.001; OR, 1.142; 95% CI, 1.062 − 1.228), but found no significant associations of IL-18 with RA (PIVW = 0.496; OR, 1.044; 95% CI, 0.923 − 1.180), AS (PIVW = 0.021; OR, 1.181; 95% CI, 1.025 − 1.361), or psoriasis (PIVW = 0.232; OR, 1.198; 95% CI, 0.891 − 1.611). In the reverse direction, no causal relationship existed between SLE or IBD and IL-18 levels. Globally, sensitivity studies using alternative MR methods supported the results that were robust and reliable. The Cochran’s Q test, MR-Egger intercept, and MR-Pleiotropy RESidual Sum and Outlier excluded the influence of heterogeneity, horizontal pleiotropy, and outliers.ConclusionsWe have demonstrated that elevated IL-18 levels increase the risk of SLE and IBD but not RA, AS, or psoriasis. The results enhanced our understanding of IL-18 in the pathology of IMIDs.

Nationwide analysis of neuromyelitis optica in systemic lupus erythematosus and Sjogren's syndrome.

Neuromyelitis optica (NMO), also known as Devic's disease, is a rare inflammatory demyelinating disorder causing myelitis and optic neuritis. While there have been reports of systemic lupus erythematosus (SLE) and primary Sjogren's syndrome (SS) occurring with NMO, a formal association is not established. We aimed to investigate the occurrence of NMO in SLE and SS patients and study the clinical characteristics and outcomes of NMO and SLE/SS hospitalizations utilizing the national inpatient sample (NIS) database. The NIS database from 2016 to 2019 was used to extract data. Adult hospitalizations with the principal or secondary diagnosis of NMO were included. We classified NMO patients with and without concomitant diagnosis of SLE or Sjogren's syndrome. We evaluated and compared the clinical characteristics and outcomes of NMO hospitalizations with and without SLE or Sjogren's syndrome. STATA17 was used for data analysis. We also calculated the odds ratio of NMO in SLE and Sjogren's syndrome. There were a total of 16,360 adult hospitalizations with the principal or secondary discharge diagnosis of NMO. Among all NMO hospitalizations, 1425 (8.71%) had the primary or secondary diagnosis of SLE or SS. The odds of NMO in SLE and Sjogren's syndrome were noted to be 12.29 and 5.56, respectively. NMO with SLE/SS group had higher proportion of females (89.82% vs 79%, P value < 0.001), African Americans (56.63% vs 38.28, P value < 0.001), and Asians (5.73% vs 3.25, P value 0.04). The Charlson comorbidity index was higher for NMO-SLE/SS overlap (2.44 vs 1.28, P value < 0.001). There was no significant difference in overall mortality rates of both groups (2.11% vs 1.2%, P value 0.197). There were significantly higher reported seizures (14.73% vs 6.05, P value < 0.001) and paraplegia (21.75% vs 13.93%, P value < 0.001) in NMO-SLE/SS patients. These patients also had a longer length of stay in comparison to the reference group (7 vs 5 days, P value < 0.001) as well as higher total charges. NMO patients had a 12-fold higher risk of SLE and 5-fold higher risk of Sjogren's disease when compared to general population. Patients with overlap of NMO and SLE or Sjogren's were predominantly women and were more likely to be African-American. Co-existence of these autoimmune disorders was associated with poor prognosis in terms of higher morbidity for patients and increased health care burden. Key Points • NMO is a rare autoimmune disease seen predominantly in women in the middle age group with low overall mortality. • SLE and Sjogren's have increased odds of NMO in comparison to general population. • NMO patients have high rates of several complications such as paraplegia, quadriplegia, seizures, blindness, sepsis, and respiratory failure with even higher rates of seizures and paraplegia in those with concomitant SLE or Sjogren's.

Crucial Role of Foxp3 Gene Expression and Mutation in Systemic Lupus Erythematosus, Inferred from Computational and Experimental Approaches.

The impaired suppressive function of regulatory T cells is well-understood in systemic lupus erythematosus. This is likely due to changes in Foxp3 expression that are crucial for regulatory T-cell stability and function. There are a few reports on the correlation between the Foxp3 altered expression level and single-nucleotide polymorphisms within the Foxp3 locus. Moreover, some studies showed the importance of Foxp3 expression in the same diseases. Therefore, to explore the possible effects of single-nucleotide polymorphisms, here, we evaluated the association of IVS9+459/rs2280883 (T>C) and -2383/rs3761549 (C>T) Foxp3 polymorphisms with systemic lupus erythematosus. Moreover, through machine-learning and deep-learning methods, we assessed the connection of the expression level of the gene with the disease. Single-nucleotide polymorphisms of Foxp3 (IVS9+459/rs2280883 (T>C) and -2383/rs3761549 (C>T)) were, respectively, genotyped using allele-specific PCR and direct sequencing and polymerase chain reaction-restriction fragment length polymorphism, in 199 systemic lupus erythematosus patients and 206 healthy age- and sex-matched controls. The Statistical Package for the Social Sciences version 19 and Fisher's exact and chi-square tests were used to analyze the data. Moreover, six machine-learning models and two sequential deep-learning models were designed to classify patients from normal people in the E-MTAB-11191 dataset through the expression level of Foxp3 and its correlated genes. The allele and genotype frequencies of both polymorphisms in question were found to be significantly associated with an increased risk of systemic lupus erythematosus. Furthermore, both of the two single-nucleotide polymorphisms were associated with some systemic-lupus-erythematosus-related risk factors. Three SVM models and the logistic regression model showed an 81% accuracy in classification problems. In addition, the first deep-learning model showed an 83% and 89% accuracy for the training and validation data, respectively, while the second model had an 85% and 79% accuracy for the training and validation datasets. In this study, we are prompted to represent the predisposing loci for systemic lupus erythematosus pathogenesis and strived to provide evidence-based support to the application of machine learning for the identification of systemic lupus erythematosus. It is predicted that the recruiting of machine-learning algorithms with the simultaneous measurement of the applied single nucleotide polymorphisms will increased the diagnostic accuracy of systemic lupus erythematosus, which will be very helpful in providing sufficient predictive value about individual subjects with systemic lupus erythematosus.

Association of Perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposures and the risk of systemic lupus erythematosus: a case–control study in China

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) may have a role in impaired health. However, the data on the association between PFASs and Systemic lupus erythematosus (SLE) have been limited. We designed a population-based case–control study in China and evaluated the association. 100 normal persons (Control) and 100 SLE patients (Case) were obtained from 113 controls and 125 cases according to matching conditions. Serum samples were collected by venipuncture for UHPLC-MRM-MS Analysis to obtain the concentration of five PFASs in participants. Demographic characterization description was performed for the two groups of participants, the PFASs concentration distribution of the two groups was described and compared, then divided into three tiers (< 50th, 50th ~ 75th, > 75th) for subsequent analysis. Conditional logistic regression models were utilized to calculate the odds ratios (ORs) and 95% CIs for SLE. Relationship between changes in the concentration of PFASs and the risk of SLE assessed by restricted cubic spline. As the highest serum levels of the five PFASs tested in this study population, the highest perfluoroundecanoic acid (PFUnA) quartile had a 2.78-fold (95%CI: 1.270, 6.10) compared with the lowest quartile of PFUnA exposure, other types of PFASs also showed high association with SLE as well as PFASs mixture. Additionally, the exposure of PFASs exist a dose–response relationship (ptrend < 0.05). This risk association remained be found after adjusting the covariates in model 1 (adjustment of BMI) and in model 2(adjustment of BMI, smoking, drinking, hypertension and leukocyte). The restricted cubic spline illustrated a gradual increase in the possible risk of SLE with the increasing exposure of PFASs components levels. Our study firstly revealed that PFASs are risk factors for SLE and PFASs exposures are associated with SLE risk in a dose − response manner. Evidence from larger and more adequately powered cohort studies is needed to confirm our results.

Association of lipid lowering drugs and the risk of systemic lupus erythematosus: a drug target Mendelian randomization.

Background and objective: An interaction between low-density lipoprotein level, lipid-lowering drugs, and systemic lupus erythematosus (SLE) was reported by previous studies. However, whether lipid-lowering drugs provided protective effect for reducing the risk of SLE was unclear. We aimed to clarify this causal relationship through a drug-target Mendelian randomization (MR) study. Methods: Genetic instruments-single nucleotide polymorphism (SNPs)-were utilized to proxy inhibition of the three genes-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-Like 1(NPC1L1), which was corresponded to three lipid-lowering drugs-statins, evolocumab, and ezetimibe. Low-density lipoprotein (LDL) cholesterol was selected as the biomarker for the measurement of the inhibitors of HMGCR, PCSK9, and NPC1L1, and the genetic data were acquired from the Global Lipids Genetics Consortium, which consisted of 1.3 million participants of European ancestry and 146.5 thousand participants of East Asian ancestry. The genetic dataset of SLE was acquired from two large-scale GWAS studies; one recruited 23,210 participants (7,219 SLE cases and 15,991 controls) of European ancestry and the other one recruited 12,653 participants (4,222 SLE cases and 8,431 controls) of Chinese ancestry. The primary analysis used the inverse variance weighted (IVW) method. Four additional sensitivity analyses, colocalization analysis, and stratification analysis were performed. Results: The primary analysis showed that inhibition of PCSK9 (evolocumab) was associated with a significantly lower risk of SLE [odds ratio (OR) 0.51, 95%CI 0.34 to 0.76, p = 0.001] in the European population. The secondary analyses had similar findings. Stratification analysis demonstrated that the preventive effect of PCSK9 inhibition for SLE was similar in both males and females. However, the results were not replicated in the East Asian population. The inhibition of HMGCR (statins) and NPC1L1 (ezetimibe) did not cause a lower risk of SLE. Conclusion: Evolocumab might provide a protective effect on the risk of SLE in the European population, but statins and ezetimibe might not have the protective effect. Further research is necessary to elucidate the specific mechanisms and potential therapeutic applications of PCSK9 inhibitors (evolocumab) in the context of SLE protection.

Assessing the causal relationship between immune traits and systemic lupus erythematosus by bi-directional Mendelian randomization analysis.

Previous studies have observed relationships between immune cells and systemic lupus erythematosus (SLE), but their causal links remain undetermined. Based on the public available genome-wide association studies (GWAS) summary statistics, we conducted two-sample Mendelian randomization (MR) to evaluate the associations between 731 immune phenotypes and SLE pairs. Pairwise pleiotropy analysis was performed to identify pleiotropic genes for significant immunophenotype-SLE pairs. A comprehensive gene function analysis was undertaken to explore the mechanisms of immune cells in SLE. By using the instrumental variables extracted from GWAS data, we observed that increased levels of five immune phenotypes were causally associated with SLE risk (FDR < 0.05), that were CD20 on IgD+ CD38- naïve, BAFF-R on IgD+ CD38dim, CD39+ secreting Treg AC, CD14- CD16+ monocyte AC, and HLA DR on CD14+ monocyte. Pairwise gene-based analyses identified a total of 38 pleiotropic genes for 5 significant pairs identified and gene set enrichment analysis revealed the involvement of the identified pleiotropic genes in complex pathways (i.e., systemic lupus erythematosus, an integral component of luminal side of endoplasmic reticulum membrane, C-type lectin receptor signaling pathway and regulation of hormone secretion). This study demonstrates that the immune response influences the progression of SLE in a complex pattern. These findings greatly improve our understanding of the interaction between immune response and SLE risk and also aid in the design of therapeutic strategies from an immunological perspective.

N-terminal pro-brain natriuretic peptide is a biomarker for cardiovascular damage in systemic lupus erythematous: a cross-sectional study.

Prediction models based on traditional risk factors underestimate cardiovascular (CV) risk in systemic lupus erythematosus (SLE). In a large sample of unselected SLE patients, we investigated cross-sectional associations of NT-proBNP with cardiovascular damage (CVD). Serum NT-proBNP was measured in SLE patients enrolled in the MUHC Lupus Clinic registry. Serum was collected between March 2022 and April 2023 at annual research visits. The primary outcome was CVD identified on the SLICC Damage Index. Factors associated with CVD and NT-proBNP levels were determined. Overall, 270 SLE patients [female 91%, median age 50.7 (first quartile to third quartile: 39.6-62.1) years] were analysed for the primary outcome. Among them, 33 (12%) had CVD. The ROC curve for NT-proBNP demonstrated strong associations with CVD (AUC 0.78, 95% CI 0.69-0.87) with a threshold of 133 pg/ml providing the best discrimination for those with/without CVD. Hypertension (OR 3.3, 95% CI 1.2-9.0), dyslipidaemia (OR 3.6, 95% CI 1.3-9.6) and NT-proBNP >133 pg/ml (OR 7.0, 95% CI, 2.6-19.1) were associated with CVD in the multivariable logistic regression model. Increased NT-proBNP levels were associated with age (OR 4.2, 95% CI 2.2-8.3), ever smoking (OR 1.9, 95% CI 1.0-3.5), reduced eGFR (4.1, 95% CI 1.3-13.1), prior pericarditis/pleuritis (OR 2.5, 95% CI 1.4-4.5) and aPL antibodies (OR 2.6, 95% CI 1.4-4.9). NT-proBNP is a biomarker for CV damage in SLE. The novel associations of NT-proBNP levels with prior pericarditis/pleuritis and aPL antibodies suggest new avenues for research to better understand what drives CV risk in SLE.

Identification of monocyte-associated biomarkers in systemic lupus erythematosus and their pan-cancer analysis.

Immune dysregulation is not only a pathogenic mechanism in systemic lupus erythematosus (SLE) but also a potential cause of the link between SLE and cancer. The current understanding of SLE monocyte-associated biomarkers is limited, and the precise mechanism behind the link between SLE and cancer is uncertain. By using WGCNA and immune infiltration to analyze the GSE72326 dataset, we determined the most pertinent modules for monocytes and discovered eight candidate hub genes from them. The limma software was used to find genes that were differently expressed in SLE. The genes that overlapped between the two were chosen using a Venn diagram as the essential genes related to monocytes in SLE, and the essential genes were verified by several datasets. Correlation analysis and GSEA analysis were used to examine the probable immunological pathways connected to key genes. We examined the expression of hub genes in cancer and their interaction with monocytes using the GEPIA and TIMER databases to understand the significance of essential genes in tumorigenesis. In addition, we performed transcription factor identification. We discovered three biomarkers (IFI30, BLVRA, and RIN2) that are mostly involved in interferon-related signaling pathways and are associated with monocyte-mediated immune responses in SLE. The three important genes are also strongly expressed in a number of malignancies and have a relationship with monocytes. As a result, IFI30, BLVRA, and RIN2 may act as SLE-associated biomarkers of monocytes and as a bridge between SLE and tumors. We proposed that interferon-related signaling pathways might function as possible mediators of cancer risk in SLE.

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.

Pervasive Sharing of Causal Genetic Risk Factors Contributes to Clinical and Molecular Overlap between Sjögren's Disease and Systemic Lupus Erythematosus.

SjD (Sjögren's Disease) and SLE (Systemic Lupus Erythematosus) are similar diseases. There is extensive overlap between the two in terms of both clinical features and pathobiologic mechanisms. Shared genetic risk is a potential explanation of this overlap. In this study, we evaluated whether these diseases share causal genetic risk factors. We compared the causal genetic risk for SLE and SjD using three complementary approaches. First, we examined the published GWAS results for these two diseases by analyzing the predicted causal gene protein-protein interaction networks of both diseases. Since this method does not account for overlapping risk intervals, we examined whether such intervals also overlap. Third, we used two-sample Mendelian randomization (two sample MR) using GWAS summary statistics to determine whether risk variants for SLE are causal for SjD and vice versa. We found that both the putative causal genes and the genomic risk intervals for SLE and SjD overlap 28- and 130-times more than expected by chance (p < 1.1 × 10-24 and p < 1.1 × 10-41, respectively). Further, two sample MR analysis confirmed that alone or in aggregate, SLE is likely causal for SjD and vice versa. [SjD variants predicting SLE: OR = 2.56; 95% CI (1.98-3.30); p < 1.4 × 10-13, inverse-variance weighted; SLE variants predicting SjD: OR = 1.36; 95% CI (1.26-1.47); p < 1.6 × 10-11, inverse-variance weighted]. Notably, some variants have disparate impact in terms of effect size across disease states. Overlapping causal genetic risk factors were found for both diseases using complementary approaches. These observations support the hypothesis that shared genetic factors drive the clinical and pathobiologic overlap between these diseases. Our study has implications for both differential diagnosis and future genetic studies of these two conditions.

Long Non-Coding RNA TUG1 Gene Polymorphism and TUG1 Expression Level as Molecular Biomarkers of Systemic Lupus Erythematosus and Lupus Nephritis.

Long non-coding RNA (lncRNA) TUG1 acts as a proto-oncogene, allowing the proliferation of tumor cells, and it has been related to inflammation. Therefore, we aimed in this study to investigate for the first time the role of TUG1 gene polymorphism and the TUG1 level as biomarkers in systemic lupus erythematosus (SLE) and their link to lupus nephritis 145 SLE. A total of 145 healthy controls were subjected to clinical and laboratory evaluation. The disease activity was assessed by the SLE disease activity index (SLEDAI) score. SLE patients were divided into two subgroups according to the presence of lupus nephritis. The TUG1 gene polymorphisms rs5749201 and rs886471 were determined by Sanger sequencing, and TUG1 expression was assessed by qRT-PCR. There was a significant increase in the risk of SLE AA, TA, dominant genotypes, and the A allele of rs5749201 (p < 0.001) by 4.9-, 10.1-, 6.5-, and 2.5-fold in comparison to the relative control. GG and TG, dominant genotypes and the G allele of rs886471 (p < 0.01) increased the risk by 5.09-, 11.9-, 6.5-, and 2.6-fold. AA, A allele, dominant and recessive rs5749201genotypes increased the risk of lupus nephritis by 16.6-, 7.4-, 7.1-, and 12.2-fold, respectively (p < 0.05). GG, dominant and recessive genotypes, and the G allele of rs886471 increased the risk of lupus nephritis by 17.04-, 7.8-, 9.4-, and 6.08-fold, respectively (p < 0.05). Additionally, the AG haplotype increased the risk of SLE and lupus nephritis by 2.7- and 7.8-fold, respectively. The AA rs5749201 and GG rs886471 variants are significantly associated with more severe disease (p < 0.001). TUG1 expression was significantly higher in SLE than in the control and in the lupus nephritis than in non-lupus nephritis cases (p < 0.05). Interestingly, AA rs5749201 and GG rs886471 were significantly associated with higher TUG1 levels (p < 0.001). It was also found that AA rs5749201 and high SLEDAI were predictors of lupus nephritis. Overall, our findings illustrated for the first time that TUG1 gene rs5749201 and rs886471 variants were associated with increased risk of SLE, more severe disease, and lupus nephritis, and the TUG1 level could be used as a diagnostic biomarker of SLE and lupus nephritis.

Quality of life, fatigue, sleep quality, and mental health in systemic lupus erythematosus patients with a high cardiovascular risk profile.

Systemic lupus erythematosus (SLE) patients report worse health-related quality of life (HRQL), fatigue, anxiety, depression, and sleep quality, when compared to the general population and other chronic diseases. Furthermore, cardiometabolic diseases are highly prevalent in SLE and are also associated with these parameters. Thus, it is plausible to suggest that SLE patients with a high cardiovascular risk may report worse results for these parameters. The aim of the study is to describe HRQL, fatigue, anxiety and depression symptoms, and sleep quality in a sample of SLE patients with a high cardiovascular risk profile (i.e., BMI between 25 and 40kg/m2 and/or dyslipidemia, hypertension, or diabetes). This was a cross-sectional study where patients were assessed for (i) demographic, anthropometric, and disease-related parameters, (ii) HRQL, (iii) fatigue, (iv) anxiety and depression symptoms, and (v) sleep quality. One-hundred patients completed the study; however, only 87 patients were assessed for sleep quality data. Patients averaged 41.7 ± 9years, and most patients were classified as overweight/obese (87%). SF-36 scores for physical and mental components summary were 51.3 ± 9.6 and 54.2 ± 15.6, respectively, with "bodily pain" and "role emotional" presenting the lower scores. The total SLEQOL score was 105.1 ± 42.0, with lower scores reported for "self-image" and "mood." Fatigue score was 30.8 ± 8.9, and 78% and 93% reported severe symptoms of anxiety and depression, respectively. The average sleep effectiveness was 82.9 ± 6.6%. Sleep latency, total time in bed (TTiB), and total sleep time (TST) were 8.4 ± 8.9, 495.8 ± 79.7, and 409.7 ± 69.9min, respectively. Patients reported an average of 17.8 ± 6.2 WE, with 4.5 ± 1.5min duration and a WASO of 77.7 ± 36.6min. Despite similar HRQL, fatigue, and sleep quality parameters to those reported by other SLE populations, SLE patients with a high cardiovascular risk had a higher prevalence of depression and anxiety. Understanding SLE patients' quality of life and psychological symptoms is of utmost importance to improve disease management. The findings of this study highlight the need for more intensive and global care regarding mental health when considering a high cardiovascular risk in SLE.

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

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. 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. 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). 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.

Systemic Lupus Erythematosus Risk Probability Index: ready for routine use? Results from a Chinese cohort

ObjectivesTo evaluate the performance of Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in patients with SLE using a Chinese cohort.MethodsThe Chinese cohort included 352 patients with and 385 without SLE...

TP53 and p21 (CDKN1A) polymorphisms and the risk of systemic lupus erythematosus

BackgroundThe p53 and p21 proteins are important regulators of cell cycle and apoptosis and may contribute to autoimmune diseases, such as systemic lupus erythematosus (SLE). As genetic polymorphisms may cause changes in protein levels and functions, we investigated associations of TP53 and p21 (CDKN1A) polymorphisms (p53 72 G > C—rs1042522; p53 PIN3—rs17878362; p21 31 C > A—rs1801270; p21 70 C > T—rs1059234) with the development of systemic lupus erythematosus (SLE) in a Southeastern Brazilian population.MethodsGenotyping of 353 female volunteers (cases, n = 145; controls, n = 208) was performed by polymerase chain reaction, restriction fragment length polymorphism and/or DNA sequencing. Associations between TP53 and p21 polymorphisms and SLE susceptibility and clinical manifestations of SLE patients were assessed by logistic regression analysis.ResultsProtective effect was observed for the genotype combinations p53 PIN3 A1/A1-p21 31 C/A, in the total study population (OR 0.45), and p53 PIN3 A1/A2-p21 31 C/C, in non-white women (OR 0.28). In Whites, p53 72 C-containing (OR 3.06) and p53 PIN3 A2-containing (OR 6.93) genotypes were associated with SLE risk, and higher OR value was observed for the combined genotype p53 72 G/C-p53 PIN3 A1/A2 (OR 9.00). Further, p53 PIN3 A1/A2 genotype was associated with serositis (OR 2.82), while p53 PIN3 A2/A2 and p53 72 C/C genotypes were associated with neurological disorders (OR 4.69 and OR 3.34, respectively).ConclusionsOur findings showed that the TP53 and p21 polymorphisms included in this study may have potential to emerge as SLE susceptibility markers for specific groups of patients. Significant interactions of the TP53 polymorphisms with serositis and neurological disorders were also observed in SLE patients.

Telomere length and its association with systemic lupus erythematosus in an Asian population: A Mendelian randomization study.

To investigate whether shorter telomere length is a causal risk factor for systemic lupus erythematosus (SLE) in the Asian population. We applied the two-sample Mendelian randomization (MR) method to the pooled statistics from a genome-wide association study (GWAS) of 6,707 SLE cases and 16,047 controls. We selected nine single-nucleotide polymorphisms (SNPs) with genome-wide significance as instrumental variables for telomere length. The main analysis was carried out by the random-effects inverse-variance weighted (IVW) method. Horizontal pleiotropy was evaluated by the intercept of MR-Egger regression. A potentially causal relationship between longer genetically predicted telomere length and increased risk of systemic lupus erythematosus (OR = 1.72, 95%CI: 1.21, 2.46, p = 0.01) was observed. The MR-Egger regression demonstrated an intercept proximal to zero (intercept = 0.017, p = 0.69), which does not provide evidence of the presence of horizontal pleiotropy. Our findings provided evidence supporting a potential causal relationship between longer telomere length and increased risk of systemic lupus erythematosus.

Recent positive selection signatures reveal phenotypic evolution in the Han Chinese population

Characterizing natural selection signatures and relationships with phenotype spectra is important for understanding human evolution and both biological and pathological mechanisms. Here, we identified 24 genetic loci under recent selection by analyzing rare singletons in 3946 high-depth whole-genome sequencing data of Han Chinese. The loci include immune-related gene regions (MHC cluster, IGH cluster, STING1, and PSG), alcohol metabolism-related gene regions (ADH1B, ALDH2, and ALDH3B2), and the olfactory perception gene OR4C16, in which the MHC cluster, ADH1B, and ALDH2 were also identified by TOPMed and WestLake Biobank. Among the signals, the IGH cluster is particularly interesting, in which the favored allele of variant 14_105737776_C_T (rs117518546, IgG1-G396R) promotes immune response, but also increases the risk of an autoimmune disease systemic lupus erythematosus (SLE). It is also surprising that our newly discovered ALDH3B2 evolved in the opposite direction to ALDH2 for alcohol metabolism. Besides monogenic traits, we found that multiple complex traits experienced polygenic adaptation. Particularly, multi-methods consistently revealed that lower blood pressure was favored in natural selection. Finally, we built a database named RePoS (recent positive selection, http://bigdata.ibp.ac.cn/RePoS/) to integrate and display multi-population selection signals. Our study extended our understanding of natural evolution and phenotype adaptation in Han Chinese as well as other populations.