Autoimmunity最新文献

{"title":"Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in Crohn's disease by integrating bioinformatics and machine learning.","authors":"Xiao-Jun Ren, Man-Ling Zhang, Zhao-Hong Shi, Pei-Pei Zhu","doi":"10.1080/08916934.2024.2422352","DOIUrl":"https://doi.org/10.1080/08916934.2024.2422352","url":null,"abstract":"<p><p>Crohn's disease (CD) presents significant diagnostic and therapeutic challenges due to its unclear etiology, frequent relapses, and limited treatment options. Traditional monitoring often relies on invasive and costly gastrointestinal procedures. This study aimed to identify specific diagnostic markers for CD using advanced computational approaches. Four gene expression datasets from the Gene Expression Omnibus (GEO) were analyzed, identifying differentially expressed genes (DEGs) through gene set enrichment analysis in R. Key biomarkers were selected using machine learning algorithms, including LASSO logistic regression, SVM‑RFE, and Random Forest, and their accuracy was assessed using receiver operating characteristic (ROC) curves and nomogram models. Immune cell infiltration was analyzed using the CIBERSORT algorithm, which helped reveal associations between diagnostic markers and immune cell patterns in CD. From a training set of 605 CD samples and 82 normal controls, we identified eight significant biomarkers: LCN2, FOLH1, CXCL1, FPR1, S100P, IGFBP5, CHP2, and AQP9. The diagnostic model showed high predictive power (AUC=0.954) and performed well in external validation (AUC = 1). Immune cell infiltration analysis highlighted various immune cells involved in CD, with all diagnostic markers strongly linked to immune cell interactions. Our findings propose candidate hub genes and present a nomogram for CD diagnosis, providing potential diagnostic biomarkers for clinical applications in CD.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2422352"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142543384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics and systems-biology approach to identify common pathogenic mechanisms for COVID-19 and systemic lupus erythematosus.","authors":"Yinlan Wu, Yanhong Li, Yu Zhou, Xiufeng Bai, Yi Liu","doi":"10.1080/08916934.2024.2304826","DOIUrl":"10.1080/08916934.2024.2304826","url":null,"abstract":"<p><strong>Background: </strong>The Coronavirus disease 2019 (COVID-19) pandemic has brought a heavy burden to the world, interestingly, it shares many clinical symptoms with systemic lupus erythematosus (SLE). It is unclear whether there is a similar pathological process between COVID-9 and SLE. In addition, we don't know how to treat SLE patients with COVID-19. In this study, we analyse the potential similar pathogenesis between SLE and COVID-19 and explore their possible drug regimens using bioinformatics and systems biology approaches.</p><p><strong>Methods: </strong>The common differentially expressed genes (DEGs) were extracted from the COVID-19 datasets and the SLE datasets for functional enrichment, pathway analysis and candidate drug analysis.</p><p><strong>Result: </strong>Based on the two transcriptome datasets between COVID-19 and SLE, 325 common DEGs were selected. Hub genes were identified by protein-protein interaction (PPI) analysis. few found a variety of similar functional changes between COVID-19 and SLE, which may be related to the pathogenesis of COVID-19. Besides, we explored the related regulatory networks. Then, through drug target matching, we found many candidate drugs for patients with COVID-19 only or COVID-19 combined with SLE.</p><p><strong>Conclusion: </strong>COVID-19 and SLE patients share many common hub genes, related pathways and regulatory networks. Based on these common targets, we found many potential drugs that could be used in treating patient with COVID-19 or COVID-19 combined with SLE.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2304826"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139705973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification the role of necroptosis in rheumatoid arthritis by WGCNA network.","authors":"Feige Nian, Yiwen Wang, Mingfeng Yang, Bin Zhang","doi":"10.1080/08916934.2024.2358069","DOIUrl":"https://doi.org/10.1080/08916934.2024.2358069","url":null,"abstract":"<p><p>Rheumatoid arthritis (RA) is the predominant manifestation of inflammatory arthritis, distinguished by an increasing burden of morbidity and mortality. The intricate interplay of genes and signalling pathways involved in synovial inflammation in patients with RA remains inadequately comprehended. This study aimed to ascertain the role of necroptosis in RA, as along with their associations with immune cell infiltration. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify central genes for RA. In this study, identified total of 28 differentially expressed genes (DEGs) were identified in RA. Utilising WGCNA, two co-expression modules were generated, with one module demonstrating the strongest correlation with RA. Through the integration of differential gene expression analysis, a total of 5 intersecting genes were discovered. These 5 hub genes, namely fused in sarcoma (FUS), transformer 2 beta homolog (TRA2B), eukaryotic translation elongation factor 2 (EEF2), cleavage and polyadenylation specific factor 6 (CPSF6) and signal transducer and activator of transcription 3 (STAT3) were found to possess significant diagnostic value as determined by receiver operating characteristic (ROC) curve analysis. The close association between the concentrations of various immune cells is anticipated to contribute to the diagnosis and treatment of RA. Furthermore, the infiltration of immune cells mentioned earlier is likely to exert a substantial influence on the initiation of this disease.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2358069"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141309930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"iTreg cells-secreted IL10 alleviates lupus nephritis through inactivating lncRNA HAR1A transcription to suppress SMARCD1-mediated iNOS activation.","authors":"Ya Liu, Pei Li, Longkun Wang, Luojia Jiang, Zhengfu Li, Yu Mei, Weijuan Deng","doi":"10.1080/08916934.2024.2423758","DOIUrl":"https://doi.org/10.1080/08916934.2024.2423758","url":null,"abstract":"<p><p>Lupus nephritis (LN) is a highly prevalent complication of systemic lupus erythematosus (SLE). Long non-coding RNAs (lncRNAs) are essential modulators in multiple types of human diseases, including LN. In the current study, we searched on online GEO database to select out lncRNAs that were differentially expressed in blood samples of LN patients. Through further RT-qPCR analysis, we found that lncRNA Highly Accelerated Region 1 A (HAR1A) is most significantly upregulated in blood samples of LN patients. Functionally, we detected that overexpression of HAR1A could aggravate LPS-induced injury and inflammation. According to the results of bioinformatics analysis and mechanism experiments, we determined that HAR1A binds with miR-149-3p to upregulate SMARCD1 through competing endogenous RNA (ceRNA) mechanism. It has been proven that iNOS is an inflammation inducer. Here, we found that HAR1A/miR-149-3p/SMARCD1 upregulates iNOS expression through enhancing H3K27ac level in iNOS promoter. Previously, we proved that CD8⁺CD103⁺ iTreg cells could alleviate glomerular endothelial cell injury. Moreover, we demonstrated that CD8 ⁺ CD103⁺ iTreg cells-secreted IL-10 downregulated HAR1A expression by impeding NF-κB pathway activation. In conclusion, this study provides evidences revealing a novel molecular pathway blocked by CD8⁺CD103⁺ iTreg cells in LN.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2423758"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142581953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CD5L induces inflammation and survival in RA-FLS through ERK1/2 MAPK pathway.","authors":"Huiqing Yang, Yan Luo, Xiaofei Lai","doi":"10.1080/08916934.2023.2201412","DOIUrl":"10.1080/08916934.2023.2201412","url":null,"abstract":"<p><strong>Objective: </strong>To explore the effect of CD5-like molecule (CD5L) on rheumatoid arthritis (RA) fibroblast-like synoviocytes (RA-FLS) and the relative molecular mechanism of CD5L in it.</p><p><strong>Methods: </strong>Recombinant protein CD5L was used to stimulate the cultured RA-FLS cells. The inflammation-related cytokines were determined by real time-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA). The signal molecules and apoptosis-related molecules were detected by western blot assay (WB), and cell counting kit-8 (CCK-8) was used to detect the proliferation.</p><p><strong>Results: </strong>CD5L can increase the production of IL-6, IL-8, and TNF-α and this effect can be inhibited by signal pathway inhibitor. At the same time, CD5L activated ERK1/2 MAPK signal, inhibitor treatment can weaken the intensity of phosphorylation. In addition, CD5L can enhance the proliferation ability of RA-FLS.</p><p><strong>Conclusion: </strong>CD5L induces the production of inflammatory cytokines in RA-FLS through the ERK1/2 MAPK pathway and increases cell survival.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2201412"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139995489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High throughput multiplex immunoassays stratify patients according to symptom burden across the anti-Ro positive systemic autoimmune rheumatic disease spectrum.","authors":"Sarah Dyball, Rudresh Shukla, Anastasia-Vasiliki Madenidou, Maya H Buch, Ian N Bruce, Ben Parker","doi":"10.1080/08916934.2024.2433237","DOIUrl":"https://doi.org/10.1080/08916934.2024.2433237","url":null,"abstract":"<p><p>Anti-Ro/SS-A antibodies are prevalent across systemic autoimmune rheumatic diseases (SARDs) and may signify a distinctive phenotype. This study aimed to identify protein biomarkers associated with symptom burden and health-related quality of life (HR-QoL), and use protein-based stratification to identify clinically meaningful clusters and inflammatory pathways implicated. Anti-Ro positive SARD patients were enrolled in a 6-month pilot study. HR-QoL was determined using a patient-reported visual analogue scale, and symptom burden was assessed with the EULAR Sjögren's Syndrome Patient Reported Index (ESSPRI). Proximity extension immunoassays measured normalized protein expression (NPX) across 92 inflammatory proteins. Linear regression identified proteins linked to patient outcomes. Unsupervised hierarchical clustering of baseline NPX identified patient clusters. Functional protein association networks were visualized using String V.12.0. Diagnostic groups showed no differences in HR-QoL or physician global assessment (PhGA). Poor HR-QoL and high symptom burden correlated with downregulated inflammatory proteins, while PhGA correlated with upregulated proteins. Two distinct clusters were identified; Cluster 1, 'low expression cluster' exhibited higher symptom burden and more impaired HR-QoL, while Cluster 2, 'high expression cluster' correlated with a higher physician global assessment (PhGA). Key hub proteins included TGF-β1, CXCL-8, and CCL-2. This study identified patient clusters across the Ro-positive SARD, linking symptom burden to specific proteomic profiles. Unraveling novel protein networks associated with symptom burden and poor HR-QoL may identify therapeutic targets, which address patient-reported outcome measures (PROMs) across several disease indications.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2433237"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142738277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HLA-transgenic mouse models to study autoimmune central nervous system diseases.","authors":"Kyle R Pressley, Lance Schwegman, Maria Montes De Oca Arena, Carol Chase Huizar, Scott S Zamvil, Thomas G Forsthuber","doi":"10.1080/08916934.2024.2387414","DOIUrl":"10.1080/08916934.2024.2387414","url":null,"abstract":"<p><p>It is known that certain human leukocyte antigen (HLA) genes are associated with autoimmune central nervous system (CNS) diseases, such as multiple sclerosis (MS), but their exact role in disease susceptibility and etiopathogenesis remains unclear. The best studied HLA-associated autoimmune CNS disease is MS, and thus will be the primary focus of this review. Other HLA-associated autoimmune CNS diseases, such as autoimmune encephalitis and neuromyelitis optica will be discussed. The lack of animal models to accurately capture the complex human autoimmune response remains a major challenge. HLA transgenic (<i>tg</i>) mice provide researchers with powerful tools to investigate the underlying mechanisms promoting susceptibility and progression of HLA-associated autoimmune CNS diseases, as well as for elucidating the myelin epitopes potentially targeted by T cells in autoimmune disease patients. We will discuss the potential role(s) of autoimmune disease-associated <i>HLA</i> alleles in autoimmune CNS diseases and highlight information provided by studies using HLA <i>tg</i> mice to investigate the underlying pathological mechanisms and opportunities to use these models for development of novel therapies.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2387414"},"PeriodicalIF":3.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142016208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association of 25(OH)D, interleukin-4, interleukin-5, and interleukin-13 levels with the burden of soil-transmitted helminth infection in stunted children aged 24-59 months.","authors":"Riyadi Adrizain, Monika Verena Nagari, Djatnika Setiabudi, Afiat Berbudi, Budi Setiabudiawan","doi":"10.1080/08916934.2024.2330394","DOIUrl":"10.1080/08916934.2024.2330394","url":null,"abstract":"<p><p>Soil-transmitted helminth (STH) among children aged 24-59 months is one cause of chronic infection that could lead to stunting. The association of 25(OH)D and immune responses during chronic infection in stunted populations has not yet been well established. An association study of case-control data was conducted in Bandung district from October 2019 to January 2023. Sociodemographic factors, stool samples, and serum levels of 25(OH)D, interleukin-4 (IL-4), interleukin-5 (IL-5), and interleukin-13 (IL-13) were assessed. Statistical analysis was performed to evaluate the prevalence and association of 25(OH)D, IL-4, IL-5, and IL-13 with the burden of STH infection in stunted children. In total, 401 stunted children were recruited. A higher burden of STH infection was found for lower levels of IL-5 (<i>r</i> = -0.477; <i>p</i> = 0.004) and IL-13 (<i>r</i> = -0.433; <i>p</i> = 0.028). Thus, 25(OH)D, IL-4, IL-5, and IL-13 play a role in the burden of STH infection.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2330394"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140142657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel peripheral blood mononuclear cell mRNA signature for IFN-beta therapy responsiveness prediction in multiple sclerosis.","authors":"Yang Xue, Pengqi Yin, Hongping Chen, Guozhong Li, Di Zhong","doi":"10.1080/08916934.2024.2332340","DOIUrl":"10.1080/08916934.2024.2332340","url":null,"abstract":"<p><p>Interferon-beta (IFN-<math><mrow><mi>β</mi></mrow></math>) is one of the classical drugs for immunomodulatory therapy in relapsing-remitting multiple sclerosis (RRMS) patients, but the drug responsiveness of different patients varies. Currently, there is no valid model to predict IFN-<math><mrow><mi>β</mi></mrow></math> responsiveness. This research attempted to develop an IFN-<math><mrow><mi>β</mi></mrow></math> responsiveness prediction model based on mRNA expression in RRMS patient peripheral blood mononuclear cells. Peripheral blood mononuclear cell mRNA expression datasets including 50 RRMS patients receiving IFN-<math><mrow><mi>β</mi></mrow></math> treatment were obtained from GEO. Among the datasets, 24 cases from GSE24427 were included in a training set, and 18 and 9 cases from GSE19285 and GSE33464, respectively, were adopted as two independent test sets. In the training set, blood samples were collected immediately before first, second, month 1, 12, and 24 IFN-<math><mrow><mi>β</mi></mrow></math> injection, and the mRNA expression data at four time points, namely, two days, one month, one year and two years after the onset of IFN-<math><mrow><mi>β</mi></mrow></math> treatment, were compared with pre-treatment data to identify IFN-stimulated genes (ISGs). The ISGs at the one-month time point were used to construct the drug responsiveness prediction model. Next, the drug responsiveness model was verified in the two independent test sets to examine the performance of the model in predicting drug responsiveness. Finally, we used CIBERSORTx to estimate the content of cell subtypes in samples and evaluated whether differences in the proportions of cell subtypes were related to differences in IFN-<math><mrow><mi>β</mi></mrow></math> responsiveness. Among the four time points, one month was the time point when the training set GSE24427 and test set GSE33464 had the highest number of ISGs. Functional analysis showed that these one-month ISGs were enriched in biological functions such as the innate immune response, type-I interferon signalling pathway, and other IFN-<math><mrow><mi>β</mi></mrow></math>-associated functions. Based on these ISGs, we obtained a four-factor prediction model for IFN-<math><mrow><mi>β</mi></mrow></math> responsiveness including MX1, MX2, XAF1, and LAMP3. In addition, the model demonstrated favourable predictive performance within the training set and two external test sets. A higher proportion of activated NK cells and lower naive CD4/total CD4 ratio might indicate better drug responsiveness. This research developed a polygene-based biomarker model that could predict RRMS patient IFN-<math><mrow><mi>β</mi></mrow></math> responsiveness in the early treatment period. This model could probably help doctors screen out patients who would not benefit from IFN-<math><mrow><mi>β</mi></mrow></math> treatment early and determine whether a current treatment plan should be continued.</p>","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2332340"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140304557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction.","authors":"","doi":"10.1080/08916934.2024.2331362","DOIUrl":"https://doi.org/10.1080/08916934.2024.2331362","url":null,"abstract":"","PeriodicalId":8688,"journal":{"name":"Autoimmunity","volume":"57 1","pages":"2331362"},"PeriodicalIF":3.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140334586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}