Integrated Bioinformatics and Validation Reveal Potential Biomarkers Associated With Progression of Primary Sjögren's Syndrome

Primary Sjögren's syndrome independently promotes premature subclinical atherosclerosis

OBJECTIVES

Cardiovascular comorbidities are common in patients with autoimmune diseases. This study investigates the extent of subclinical atherosclerosis in patients with primary Sjögren's syndrome (pSS). Correlations with clinical factors such as organ involvement (OI) or disease activity were analysed and oxLDL antibodies (oxLDL ab) were measured as potential biomarkers of vascular damage.

METHODS

Patients with pSS were consecutively included from the rheumatology outpatient clinic. Age- and sex-matched controls were recruited (2:1 ratio). Data collection was performed by a standardised questionnaire and Doppler ultrasound to evaluate the plaque extent and carotid intima-media thickness (cIMT). Propensity score matching included all cardiovascular risk (CVR) factors and corresponding laboratory markers.

RESULTS

Data were available for 299 participants (199 pSS/100 controls), aged 59.4 years (50.6-65.0), 19.1% male. After matching, the pSS cohort had greater cIMT (p<0.001) and plaque extent (OR=1.82; 95% CI 1.14 to 2.95). Subgroup analyses of patients with pSS revealed that OI was associated with increased cIMT (p=0.025) and increased plaque occurrence compared with patients without OI (OR=1.74; 95% CI 1.02 to 3.01). OxLDL ab tended to be lower in patients with plaque (p=0.052). Correlations of higher Oxidized Low Density Lipoprotein (oxLDL) ab with EULAR Sjögren's Syndrome Disease Activity Index (p<0.001) and anti-Sjögren's-syndrome-related antigen A autoantibodies (SSA/Ro antibodies) (p=0.026) were observed.

CONCLUSIONS

Subclinical atherosclerosis occurs earlier and more severely in patients with pSS. The difference in cIMT between pSS and controls seems mainly driven by patients with OI, suggesting that this subgroup is particularly at risk. OxLDL ab might protect against atherosclerotic progression in patients with pSS. CVR stratification and preventive medications such as Hydroxymethylglutaryl-CoA (HMG-CoA) reductase inhibitors should be discussed and further longitudinal studies are needed.

CXCL9 may serve as a potential biomarker for primary Sjögren's syndrome with extra-glandular manifestations

BACKGROUND

Primary Sjögren's syndrome (pSS) is an autoimmune condition that causes harm to exocrine glands and also has extra-glandular manifestations (EGM). pSS patients with EGM have a worse prognosis than those with only sicca symptoms. Previous studies have shown that the minor salivary glands (MSG) of pSS patients exhibit a unique profile of cytokines and chemokines compared to healthy controls. However, there is a lack of research comparing pSS with EGM (pSS-EGM) and pSS without EGM (pSS-non-EGM). This study aims to explore potential biomarkers associated with pSS, particularly pSS with EGM.

METHODS

By utilizing RNA sequencing, we conducted an analysis on the gene expression profiles of MSG in 63 patients diagnosed with pSS, as well as 12 non-pSS individuals. Furthermore, we also investigated the MSG of pSS patients, both with and without EGM. Through bioinformatics analysis, we identified genes with differential expression (DEGs) and determined the core hub genes using PPI network. We then analyzed the top 20 DEGs and their correlation with the patients' clinical characteristics, and validated our findings using peripheral blood plasma.

RESULTS

A total of 725 differentially expressed genes (DEGs) were identified in the comparison between pSS and non-pSS groups, and 727 DEGs were observed between pSS-EGM and pSS-non-EGM. It is noteworthy that the expression levels of CXCL9 were higher in both pSS patients and pSS-EGM when compared to the control group. Taking into consideration the significance of the top 20 DEGs in relation to clinical parameters and the central hub genes, we ultimately chose CXCL9. In comparison to the non-pSS group, pSS patients exhibited notably greater expression of the CXCL9 gene in the MSG, as well as higher levels of CXCL9 protein in their plasma (p < 0.001). Furthermore, the expression of the CXCL9 gene and levels of CXCL9 protein were notably higher in pSS patients accompanied by EGM and those with SSA antibodies. Additionally, a correlation was found between the expression of the CXCL9 gene and the EULAR Sjogren's Syndrome Disease Activity Index (ESSDAI), as well as with immunoglobulin G (IgG) levels and erythrocyte sedimentation rate (ESR). Meanwhile, the protein levels of CXCL9 were found to be correlated with IgG levels and ESSDAI.

CONCLUSION

CXCL9 proves to be a valuable biomarker in pSS, specifically due to its strong ability to differentiate between pSS patients with EGM and those without EGM. There is a significant correlation between CXCL9 and various clinical parameters both at the gene and protein level. Therefore, CXCL9 could be a potential target for future treatment of pSS.

Combining bioinformatics and machine learning algorithms to identify and analyze shared biomarkers and pathways in COVID-19 convalescence and diabetes mellitus

Background

Most patients who had coronavirus disease 2019 (COVID-19) fully recovered, but many others experienced acute sequelae or persistent symptoms. It is possible that acute COVID-19 recovery is just the beginning of a chronic condition. Even after COVID-19 recovery, it may lead to the exacerbation of hyperglycemia process or a new onset of diabetes mellitus (DM). In this study, we used a combination of bioinformatics and machine learning algorithms to investigate shared pathways and biomarkers in DM and COVID-19 convalescence.

Methods

Gene transcriptome datasets of COVID-19 convalescence and diabetes mellitus from Gene Expression Omnibus (GEO) were integrated using bioinformatics methods and differentially expressed genes (DEGs) were found using the R programme. These genes were also subjected to Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to find potential pathways. The hub DEGs genes were then identified by combining protein-protein interaction (PPI) networks and machine learning algorithms. And transcription factors (TFs) and miRNAs were predicted for DM after COVID-19 convalescence. In addition, the inflammatory and immune status of diabetes after COVID-19 convalescence was assessed by single-sample gene set enrichment analysis (ssGSEA).

Results

In this study, we developed genetic diagnostic models for 6 core DEGs beteen type 1 DM (T1DM) and COVID-19 convalescence and 2 core DEGs between type 2 DM (T2DM) and COVID-19 convalescence and demonstrated statistically significant differences (p<0.05) and diagnostic validity in the validation set. Analysis of immune cell infiltration suggests that a variety of immune cells may be involved in the development of DM after COVID-19 convalescence.

Conclusion

We identified a genetic diagnostic model for COVID-19 convalescence and DM containing 8 core DEGs and constructed a nomogram for the diagnosis of COVID-19 convalescence DM.

Application of omics in Sjögren's syndrome

OBJECTIVE

The pathogenesis, diagnosis, and treatment of Sjögren's syndrome (SS) face many challenges, and there is an urgent need to develop new technologies to improve our understanding of SS.

METHODS

By searching the literature published domestically and internationally in the past 20 years, this artical reviewed the research of various omics techniques in SS.

RESULTS

Omics technology provided valuable insights into the pathogenesis, early diagnosis, condition and efficacy evaluation of SS. It is helpful to reveal the pathogenesis of the disease and explore new treatment schemes, which will open a new era for the study of SS.

CONCLUSION

At present, omics research has made some gratifying achievements, but there are still many uncertainties. Therefore, in the future, we should improve research techniques, standardize the collection of samples, and adopt a combination of multi-omics techniques to jointly study the pathogenesis of SS and provide new schemes for its treatment.

Exploring the mechanisms of action of Zengye decoction (ZYD) against Sjogren's syndrome (SS) using network pharmacology and animal experiment

CONTEXT

Zengye decoction (ZYD) has been considered to have a curative effect on Sjogren's syndrome (SS). However, its therapeutic mechanisms remain obscure.

OBJECTIVES

This research explores the mechanisms of ZYD against SS.

MATERIALS AND METHODS

The active compounds and targets of ZYD were searched in the TCMSP and BATMAN-TCM databases. SS-related targets were obtained from the GeneCards database. The GO and KEGG enrichment analyses elucidated the molecular mechanisms. Animal experiments were performed using 8 C57BL/6 mice that served as the control group (physiological saline treatment) and 16 NOD mice randomly divided into the model group (physiological saline treatment) and the ZYD group (ZYD treatment) for 8 weeks to verify the therapeutic effects of ZYD on SS.

RESULTS

Twenty-nine active compounds with 313 targets of ZYD and 1038 SS-related targets were screened. Thirty-two common targets were identified. β-Sitosterol and stigmasterol might be important components. GO analysis suggested that the action of ZYD against SS mainly involved oxidative stress, apoptotic processes, and tumor necrosis factor receptor superfamily binding, etc. KEGG analysis indicated the most significant signaling pathway was apoptosis-multiple species. Animal experiments showed that ZYD improved lymphocytic infiltration of the submandibular glands (SMGs), reduced the serum levels of TNF-α, IL-1β, IL-6, and IL-17, upregulated the expression of Bcl-2, and downregulated the expression of Bax and Caspase-3 in the model mice.

DISCUSSION AND CONCLUSION

ZYD has anti-inflammatory and anti-apoptotic effects on SS, which provides a theoretical basis for the treatment of SS with ZYD.

Mitochondrial Dysfunction in the Pathogenesis and Treatment of Oral Inflammatory Diseases

Oral inflammatory diseases (OIDs) include many common diseases such as periodontitis and pulpitis. The causes of OIDs consist microorganism, trauma, occlusal factors, autoimmune dis-eases and radiation therapy. When treated unproperly, such diseases not only affect oral health but also pose threat to people's overall health condition. Therefore, identifying OIDs at an early stage and exploring new therapeutic strategies are important tasks for oral-related research. Mitochondria are crucial organelles for many cellular activities and disruptions of mitochondrial function not only affect cellular metabolism but also indirectly influence people's health and life span. Mitochondrial dysfunction has been implicated in many common polygenic diseases, including cardiovascular and neurodegenerative diseases. Recently, increasing evidence suggests that mitochondrial dysfunction plays a critical role in the development and progression of OIDs and its associated systemic diseases. In this review, we elucidated the critical insights into mitochondrial dysfunction and its involvement in the inflammatory responses in OIDs. We also summarized recent research progresses on the treatment of OIDs targeting mitochondrial dysfunction and discussed the underlying mechanisms.

Uncovering potential new biomarkers and immune infiltration characteristics in primary Sjögren's syndrome by integrated bioinformatics analysis

Primary Sjögren's syndrome (pSS) is known as autoimmune disease characterized by damage to endocrine glands, such as the salivary and lacrimal glands. This study aimed to identify potential biomarkers for pSS using integrated bioinformatics analysis and explore the relationship between differentially expressed genes (DEGs) and immune infiltration. Three pSS datasets (GSE7451, GSE23117, and GSE40611) from the gene expression omnibus database were integrated. All the datasets were processed in R (version 4.0.3). A total of 16 immune cells and 13 immune functions were obtained. The top immune cell and immune function were "activated" dendritic cells and major histocompatibility complex class I. Correlation analysis showed the top correlation among 16 immune cells were B cells and tumor infiltrating lymphocytes, check-point and T cell co-stimulation, respectively. In comparisons of immune score, "activated" dendritic cells (.657 vs 594, P < .001), B cells (.492 vs 434, P = .004), macrophages (.631 vs 601, P = .010), inflammation-promoting (.545 vs 478, P < .001), Type I interferon Reponse (.728 vs 625, P < .001) and so on were higher in pSS than control group. In correlation analysis, the up-regulation of interferon induced protein with tetratricopeptide repeats 1 gene was strongly correlated with Type I interferon response with a correlation coefficient of .87. The receiver operating characteristic curve of 5 genes showed that the area under curve was.891. In the verification model, the area under curve was.881. In addition, disease ontology analysis supported the association between DEGs and pSS. In summary, pSS has a variety of DEGs in immune infiltration, which is worthy of the attention from clinicians.

Unraveling the transcriptome-based network of tfh cells in primary sjogren syndrome: insights from a systems biology approach

Background

Primary Sjogren Syndrome (pSS) is an autoimmune disease characterized by immune cell infiltration. While the presence of follicular T helper (Tfh) cells in the glandular microenvironment has been observed, their biological functions and clinical significance remain poorly understood.

Methods

We enrolled a total of 106 patients with pSS and 46 patients without pSS for this study. Clinical data and labial salivary gland (LSG) biopsies were collected from all participants. Histological staining was performed to assess the distribution of Tfh cells and B cells. Transcriptome analysis using RNA-sequencing (RNA-seq) was conducted on 56 patients with pSS and 26 patients without pSS to uncover the underlying molecular mechanisms of Tfh cells. To categorize patients, we employed the single-sample gene set enrichment analysis (ssGSEA) algorithm, dividing them into low- and high-Tfh groups. We then utilized gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and deconvolution tools to explore functional and immune infiltration differences between the low- and high-Tfh groups.

Results

Patients with pSS had a higher positive rate of the antinuclear antibody (ANA), anti-Ro52, anti-SSA, anti-SSB and hypergammaglobulinaemia and higher levels of serum IgG compared to the non-pSS. Histopathologic analyses revealed the presence of Tfh cells (CD4+CXCR5+ICOS+) in germinal centers (GC) within the labial glands of pSS patients. GSEA, WGCNA, and correlation analysis indicated that the high-Tfh group was associated with an immune response related to virus-mediated IFN response and metabolic processes, primarily characterized by hypoxia, elevated glycolysis, and oxidative phosphorylation levels. In pSS, most immune cell types exhibited significantly higher infiltration levels in the high-Tfh group compared to the low-Tfh group. Additionally, patients in the Tfh-high group demonstrated a higher positive rate of the ANA, rheumatoid factor (RF), and hypergammaglobulinaemia, as well as higher serum IgG levels.

Conclusion

Our study suggests that Tfh cells may play a crucial role in the pathogenesis of pSS and could serve as potential therapeutic targets in pSS patients.

Prediction of Prognosis, Immunotherapy and Chemotherapy with an Immune-Related Risk Score Model for Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic cancer. The overall survival remains unsatisfying due to the lack of effective treatment screening approaches. Immunotherapy as a promising therapy has been applied for EC treatment, but still fails in many cases. Therefore, there is a strong need to optimize the screening approach for clinical treatment. In this study, we employed co-expression network (GCN) analysis to mine immune-related GCN modules and key genes and further constructed an immune-related risk score model (IRSM). The IRSM was proved effective as an independent predictor of poor prognosis. The roles of IRSM-related genes in EC were confirmed by IHC. The molecular basis, tumor immune microenvironment and clinical characteristics of the IRSM were revealed. Moreover, the IRSM effectiveness was associated with immunotherapy and chemotherapy. Patients in the low-risk group were more sensitive to immunotherapy and chemotherapy than those in the high-risk group. Interestingly, the patients responding to immunotherapy were also more sensitive to chemotherapy. Overall, we developed an IRSM which could be used to predict the prognosis, immunotherapy response and chemotherapy sensitivity of EC patients. Our analysis not only improves the treatment of EC but also offers targets for personalized therapeutic interventions.

Mitochondria-related genes and metabolic profiles of innate and adaptive immune cells in primary Sjögren's syndrome

Background

Primary Sjogren's syndrome (pSS) is a prototypical systemic autoimmune disease characterised by lymphocyte infiltration and immune-complex deposition in multiple organs. The specific distribution of immune cell populations and their relationship with mitochondria remain unknown.

Methods

Histological analysis was performed to assess the specific distribution of innate and adaptive immune cell populations in labial salivary gland (LSG) samples from 30 patients with pSS and 13 patients with non-pSS. The ultrastructural morphometric features of mitochondria within immune cells were observed under the transmission electron microscope (TEM). RNA sequencing was performed on LSG samples from 40 patients with pSS and 7 non-pSS patients. The Single-sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE, and CIBERSORT algorithms and Pearson correlation coefficients were used to examine the relationship between mitochondria-related genes and immune infiltration. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify the mitochondria-specific genes and the related pathways based on the immune cell types.

Results

HE staining revealed a massive infiltration of plasma cells with abundant immunoglobulin protein distributed around phenotypically normal-appearing acinar and ductal tissues of patients with pSS. Immunohistochemical analyses revealed that innate immune cells (macrophages, eosinophils and NK cells) were distributed throughout the glandular tissue. Dominant adaptive immune cell infiltration composed of B cells, CD4⁺T cells and CD8⁺ T cells or ectopic lymphoid follicle-like structures were observed in the LSGs of patients with pSS. TEM validated the swelling of mitochondria with disorganised cristae in some lymphocytes that had invaded the glandular tissue. Subsequently, bioinformatic analysis revealed that innate and adaptive immune cells were associated with different mitochondrial metabolism pathways. Mitochondrial electron transport and respiratory chain complexes in the glandular microenvironment were positively correlated with innate immune cells, whereas amino acid and nucleic acid metabolism were negatively correlated with adaptive immune cells. In addition, mitochondrial biogenesis and mitochondrial apoptosis in the glandular microenvironment were closely associated with adaptive immune cells.

Conclusion

Innate and adaptive immune cells have distinct distribution profiles in the salivary gland tissues of patients with pSS and are associated with different mitochondrial metabolic pathways, which may contribute to disease progression.

Outline of Salivary Gland Pathogenesis of Sjögren's Syndrome and Current Therapeutic Approaches

Sjögren's syndrome (SS) is an autoimmune disease characterized by the involvement of exocrine glands such as the salivary and lacrimal glands. The minor salivary glands, from which tissue samples may be obtained, are important for the diagnosis, evaluation of therapeutic efficacy, and genetic analyses of SS. In the onset of SS, autoantigens derived from the salivary glands are recognized by antigen-presenting dendritic cells, leading to the activation of T and B cells, cytokine production, autoantibody production by plasma cells, the formation of ectopic germinal centers, and the destruction of salivary gland epithelial cells. A recent therapeutic approach with immune checkpoint inhibitors for malignant tumors enhances the anti-tumor activity of cytotoxic effector T cells, but also induces SS-like autoimmune disease as an adverse event. In the treatment of xerostomia, muscarinic agonists and salivary gland duct cleansing procedure, as well as sialendoscopy, are expected to ameliorate symptoms. Clinical trials on biological therapy to attenuate the hyperresponsiveness of B cells in SS patients with systemic organ involvement have progressed. The efficacy of treatment with mesenchymal stem cells and chimeric antigen receptor T cells for SS has also been investigated. In this review, we will provide an overview of the pathogenesis of salivary gland lesions and recent trends in therapeutic approaches for SS.

Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells

Background

Sjögren's syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis.

Methods

We downloaded three datasets of SS patients' and healthy pepole's whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers' diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied.

Results

We obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2.

Conclusion

In this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

Development and verification of a combined diagnostic model for primary Sjögren's syndrome by integrated bioinformatics analysis and machine learning

Primary Sjögren's syndrome (pSS) is a chronic, systemic autoimmune disease mostly affecting the exocrine glands. This debilitating condition is complex and specific treatments remain unavailable. There is a need for the development of novel diagnostic models for early screening. Four gene profiling datasets were downloaded from the Gene Expression Omnibus database. The 'limma' software package was used to identify differentially expressed genes (DEGs). A random forest-supervised classification algorithm was used to screen disease-specific genes, and three machine learning algorithms, including artificial neural networks (ANN), random forest (RF), and support vector machines (SVM), were used to build a pSS diagnostic model. The performance of the model was measured using its area under the receiver operating characteristic curve. Immune cell infiltration was investigated using the CIBERSORT algorithm. A total of 96 DEGs were identified. By utilizing a RF classifier, a set of 14 signature genes that are pivotal in transcription regulation and disease progression in pSS were identified. Through the utilization of training and testing datasets, diagnostic models for pSS were successfully designed using ANN, RF, and SVM, resulting in AUCs of 0.972, 1.00, and 0.9742, respectively. The validation set yielded AUCs of 0.766, 0.8321, and 0.8223. It was the RF model that produced the best prediction performance out of the three models tested. As a result, an early predictive model for pSS was successfully developed with high diagnostic performance, providing a valuable resource for the screening and early diagnosis of pSS.

B-Cell Receptor Signaling Is Thought to Be a Bridge between Primary Sjogren Syndrome and Diffuse Large B-Cell Lymphoma

Primary Sjogren syndrome (pSS) is the second most common autoimmune disorder worldwide, which, in the worst scenario, progresses to Non-Hodgkin Lymphoma (NHL). Despite extensive studies, there is still a lack of knowledge about developing pSS for NHL. This study focused on cells' signaling in pSS progression to the NHL type of diffuse large B-cell lymphoma (DLBCL). Using bulk RNA and single cell analysis, we found five novel pathologic-independent clusters in DLBCL based on cells' signaling. B-cell receptor (BCR) signaling was identified as the only enriched signal in DLBCL and pSS peripheral naive B-cells or salivary gland-infiltrated cells. The evaluation of the genes in association with BCR has revealed that targeting CD79A, CD79B, and LAMTOR4 as the shared genes can provide novel biomarkers for pSS progression into lymphoma.

Identification of novel biomarkers involved in doxorubicin-induced acute and chronic cardiotoxicity, respectively, by integrated bioinformatics

Background

The mechanisms of doxorubicin (DOX) cardiotoxicity were complex and controversial, with various contradictions between experimental and clinical data. Understanding the differences in the molecular mechanism between DOX-induced acute and chronic cardiotoxicity may be an ideal entry point to solve this dilemma.

Methods

Mice were injected intraperitoneally with DOX [(20 mg/kg, once) or (5 mg/kg/week, three times)] to construct acute and chronic cardiotoxicity models, respectively. Survival record and ultrasound monitored the cardiac function. The corresponding left ventricular (LV) myocardium tissues were analyzed by RNA-seq to identify differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG), and Gene Set Enrichment Analysis (GSEA) found the key biological processes and signaling pathways. DOX cardiotoxicity datasets from the Gene expression omnibus (GEO) database were combined with RNA-seq to identify the common genes. Cytoscape analyzed the hub genes, which were validated by quantitative real-time PCR. ImmuCo and ImmGen databases analyzed the correlations between hub genes and immunity-relative markers in immune cells. Cibersort analyzed the immune infiltration and correlations between the hub genes and the immune cells. Logistic regression, receiver operator characteristic curve, and artificial neural network analysis evaluated the diagnosis ability of hub genes for clinical data in the GEO dataset.

Results

The survival curves and ultrasound monitoring demonstrated that cardiotoxicity models were constructed successfully. In the acute model, 788 DEGs were enriched in the activated metabolism and the suppressed immunity-associated signaling pathways. Three hub genes (Alas1, Atp5g1, and Ptgds) were upregulated and were negatively correlated with a colony of immune-activating cells. However, in the chronic model, 281 DEGs showed that G protein-coupled receptor (GPCR)-related signaling pathways were the critical events. Three hub genes (Hsph1, Abcb1a, and Vegfa) were increased in the chronic model. Furthermore, Hsph1 combined with Vegfa was positively correlated with dilated cardiomyopathy (DCM)-induced heart failure (HF) and had high accuracy in the diagnosis of DCM-induced HF (AUC = 0.898, P = 0.000).

Conclusion

Alas1, Atp5g1, and Ptgds were ideal biomarkers in DOX acute cardiotoxicity. However, Hsph1 and Vegfa were potential biomarkers in the myocardium in the chronic model. Our research, first, provided bioinformatics and clinical evidence for the discovery of the differences in mechanism and potential biomarkers of DOX-induced acute and chronic cardiotoxicity to find a therapeutic strategy precisely.

PSMC6 induces immune cell infiltration and inflammatory response to aggravate primary Sjögren's syndrome

Increasing evidence suggests that immune cell infiltration is involved in primary Sjögren's syndrome (pSS), while the underlying molecular mechanisms remain elusive. Herein, this study aims to explore the key molecular mechanism in immune cell infiltration in pSS based on Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained, followed by weighted gene co-expression network analysis to acquire the pSS-related module genes. Moreover, pSS-related DEGs and module genes were intersected. Additionally, the correlation between key genes and immune cell infiltration was analyzed by CIBERSORT algorithm. Furthermore, pSS mouse models were established to explore the effects of PSMC6 on immune cell infiltration and inflammatory responses in pSS. A total of 51 DEGs and 334 key module genes were involved in the occurrence of pSS. The immune cell infiltration was correlated with pSS, and PSMC6, highly expressed in pSS samples, may be the key immune gene. In vivo animal experiments demonstrated that PSMC6 was upregulated in pSS, and PSMC6 knockdown could reduce lymphocytic infiltration in salivary glands and lacrimal glands and the levels of related inflammatory factors in the pSS and increase the proportion of Treg cells. Collectively, PSMC6 could induce immune cell infiltration and inflammatory responses to promote the occurrence of pSS, providing us with a potential therapeutic target for treating pSS.

IRF9 and XAF1 as Diagnostic Markers of Primary Sjogren Syndrome

Objective. Primary Sjogren syndrome (pSS) is characterized by lymphocytic infiltration of the salivary and lacrimal glands. It is a chronic systemic autoimmune disease. Genetic contributions and disturbed biological systems are the two major causes of pSS, but its etiology is unclear. This study is aimed at identifying potential pSS diagnostic markers and mechanisms at the transcriptome level. Methods. Whole blood datasets of patients with pSS were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the online tool, GEO2R. R software was used to perform enrichment analyses to understand the functions and enriched pathways of the DEGs. A protein–protein interaction network was constructed to identify hub genes and significant gene clusters. The least absolute shrinkage and selection operator logistic regression was used to screen pSS diagnostic markers. The expression level and diagnostic performance of the identified genes were tested using another GEO dataset. Results. A total of 221 DEGs were screened from the whole blood samples of 161 patients with pSS and 59 healthy controls. Functional enrichment analysis demonstrated that DEGs were mostly enriched in defense response to virus, response to virus, and type I interferon signaling pathway. Cytoscape identified 10 hub genes and two gene clusters. IRF9 ( $\text{AUC}=0.799$ ) and XAF1 ( $\text{AUC}=0.792$ ) were identified as pSS diagnostic markers. The expression levels of the two identified genes were validated by GSE51092. Conclusion. IRF9 and XAF1 were identified as diagnostic markers. The potential underlying molecular mechanism of pSS was explored.

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 infection and primary Sjogren’s syndrome

Background

Accumulating evidence has revealed that the prevalence of Coronavirus 2019 (COVID-19) was significantly higher in patients with primary Sjogren’s syndrome (pSS) compared to the general population. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication.

Methods

The gene expression profiles of COVID-19 (GSE157103) and pSS (GSE40611) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for pSS and COVID-19, functional annotation, protein-protein interaction (PPI) network, module construction and hub gene identification were performed. Finally, we constructed transcription factor (TF)-gene regulatory network and TF-miRNA regulatory network for hub genes.

Results

A total of 40 common DEGs were selected for subsequent analyses. Functional analyses showed that cellular components and metabolic pathways collectively participated in the development and progression of pSS and COVID-19. Finally, 12 significant hub genes were identified using the cytoHubba plugin, including CMPK2, TYMS, RRM2, HERC5, IFI44L, IFI44, IFIT2, IFIT1, IFIT3, MX1, CDCA2 and TOP2A, which had preferable values as diagnostic markers for COVID-19 and pSS.

Conclusions

Our study reveals common pathogenesis of pSS and COVID-19. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

A Link Between Mitochondrial Dysfunction and the Immune Microenvironment of Salivary Glands in Primary Sjogren’s Syndrome

Background

Primary Sjogren’s syndrome (pSS) is a slowly progressive, inflammatory autoimmune disease characterized by lymphocytic infiltration into salivary and lacrimal glands. It becomes more recognized that morphology alterations of epithelial mitochondria are involved in altered cellular bioenergetics in pSS patients. The integrated analysis of the mitochondrial role in the pathogenesis and aberrant immune microenvironment in pSS remains unknown.

Methods

The mitochondria-related genes and gene expression data were downloaded from the MitoMiner, MitoCarta, and NCBI GEO databases. We performed novel transcriptomic analysis and constructed a network between the mitochondrial function and immune microenvironment in pSS-salivary glands by computer-aided algorithms. Subsequently, real-time PCR was performed in clinical samples in order to validate the bioinformatics results. Histological staining and transmission electron microscopy (TEM) were further studied on labial salivary gland samples of non-pSS and pSS patients characterized for mitochondria-related phenotypic observation in the different stages of the disease.

Results

The bioinformatic analysis revealed that the expression of several mitochondria-related genes was altered in pSS. Quantitative real-time PCR showed that four hub genes, CD38, CMPK2, TBC1D9, and PYCR1, were differentially expressed in the pSS clinical samples. These hub genes were associated with the degree of immune cell infiltration in salivary glands, the mitochondrial respiratory chain complexes, mitochondrial metabolic pathway in gluconeogenesis, TCA cycle, and pyruvate/ketone/lipid/amino acid metabolism in pSS. Clinical data revealed that the gene expression of fission (Fis1, DRP1, and MFF) and fusion (MFN1, MFN2, and OPA1) was downregulated in pSS samples, consistent with the results from the public validation database. As the disease progressed, cytochrome c and Bcl-2 proteins were regionally distributed in salivary glands from pSS patients. TEM revealed cytoplasmic lipid droplets and progressively swollen mitochondria in salivary epithelial cells.

Conclusion

Our study revealed cross talk between mitochondrial dysfunction and the immune microenvironment in salivary glands of pSS patients, which may provide important insights into SS clinical management based on modulation of mitochondrial function.