Journal of Advanced Research

Endometrial cancer is a common malignant tumor in women, with rising incidence rates and an unoptimistic prognosis. DSN1 is a kinetochore protein-coding gene that affects centromere assembly and progression in cell cycles, which is associated with adverse predictions for many cancers. However, the role of DSN1 in UCEC has not yet been reported. We identified the UCEC-related gene module and obtained the differential genes. Then we constructed a diagnostic model and identified the subtype of the molecule and its association with predictions. Subsequently, we identified DSN1 as the core gene and predicted its predictive value. Furthermore, using bioinformatics methods, we found DSN1 was associated with certain clinical characteristics and experimentally validated the expression in cancer tissues of DSN1. Pathway enrichment analysis identified DSN1 as a cell cycle-associated protein, which was validated by WB. The protein interaction network also revealed DSN1 was significantly associated with NDC80. Then we explored the correlation of DSN1 and immune cells and immune cell infiltration and found that DSN1 may affect Th2 enrichment by affecting CCL7 and CCL8. Drug susceptibility analysis showed DSN1 was sensitive to cisplatin and resistant to sunitinib. In conclusion, DSN1 was a novel biomarker that contributes to prognosis and treatment.

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease. We performed a comprehensive analysis to construct the correlation of m6A and immune in HCM. Two HCM datasets (GSE141910 and GSE160997) and m6A-related regulators were obtained from GEO and published articles, respectively. Differentially expressed m6A-related regulators were obtained. Random forest model and nomogram were conducted to assess the risk of HCM, and finally, the m6A subtype was constructed. Functional enrichment analysis was conducted. Protein-protein interaction network of differentially expressed genes between m6A subtypes was performed. Furthermore, we constructed the Hubgene-chemical network, Hubgene-microRNA network, and Hubgene-transcription factor network of the top 10 hubgenes. Additionally, the immune subtype and hubgene subtype were constructed. PCR was performed to validate the m6A-related regulators. We obtained 20 m6A-related regulators in HCM. Among them, 8 m6A-related regulators differentially expressed (YTHDC1, HNRNPC, and FMR1 were up-regulated while YTHDC2, FTO, WTAP, IGF2BP2, and IGF2BP3 were down-regulated). FTO, FMR1, IGF2BP3, YTHDC1, and IGF2BP2 were the top 5 important m6A-related regulators and were used to conduct the nomogram. We obtained 329 differentially expressed genes in m6A subtype and these genes enriched HCM-related processes and pathways. Furthermore, we constructed the Hubgene-chemical network, Hubgene-microRNA network, and Hubgene-transcription factor network of the top 10 hubgenes (NFKBIA, NFKB1, PSMA3, PSMC4, PSMA2, PSMA4, PSMD7, PSMD10, PSMD8, and PSMA6). And then we constructed an immune subtype based on the immune cell infiltration levels and hubgene subtype based on the expression of the top 10 hubgenes. Finally, we verified the main results through experiments. In conclusion, we built a nomogram and identified 8 m6A-related regulators and 10 hubgenes, which were prominently associated with HCM. We found that m6A and the immune system may play a crucial role in the HCM. Accordingly, those genes and pathways might become therapeutic targets with clinical usefulness in the future.

BackgroundGlycosylation plays a crucial role in various pathologic conditions, including inflammation. This study conducted a comprehensive glycan analysis of serum to determine how glycan biomarkers are associated with the pathophysiology of chronic inflammatory demyelinating polyneuropathy (CIDP) and the effects of its treatment. MethodsWe comparatively analyzed N- and O-glycans in the pretreatment serum of 27 treatment-naive patients with typical CIDP and age- and sex-matched 20 healthy controls (HC) using mass spectrometry. We determined the association between clinical parameters and glycans. Treatment response was defined according to the degree of improvement in the modified Rankin Scale 2 weeks after the first dose of intravenous immunoglobulin (IVIg), and the serum glycan and neurofilament light chain (NfL) levels were assessed at the baseline. ResultsCompared with the HC, the CIDP group demonstrated significantly lower levels of serum total N-glycans (CIDP, median 973.3 [IQR 836.2-1131.3] pmol/{micro}L; HC, 1125.0 [1005.0-1236.2] pmol/{micro}L; p < 0.05), especially sialylated N-glycans (CIDP, 898.0 [752.2-1037.2] pmol/{micro}L; HC, 1064.4 [942.7-1189.8] pmol/{micro}L; p < 0.01). In contrast, the O-glycan levels did not differ significantly between the two groups. Treatment response was associated with low N-glycan levels but not with the serum NfL levels. For individual glycans, low levels of Hex2HexNAc2NeuAc2 [2,6/2,6] + Man3GlcNAc2, 2,6-linked sialylated N-glycans, showed the treatment response group to have an area under the curve of 0.802 (p < 0.05). ConclusionsLow levels of sialylated N-glycans may serve as a novel biomarker reflecting pathophysiology and therapeutic resistance in typical CIDP. KEY MESSAGEO_LIWhat is already known on this topic C_LI Abnormal conformational changes in glycans of serum proteins are associated with the pathogenesis of inflammatory diseases. In a demyelinating mouse model, N-glycans suppress the activity of inflammatory helper T- and B-cells. A decrease in sialylated N-glycans of serum IgG-Fc in the serum of patients with CIDP correlates with disease severity, suggesting the potential of serum glycans as biomarkers for CIDP. O_LIWhat this study adds C_LI In the patients with typical CIDP, serum total N-glycans, especially sialylated types, were significantly decreased, indicating a reduction in sialylated N-glycans derived from glycoproteins in CIDP. Moreover, lower levels of total N-glycans, particularly 2,6-sialylated N-glycans, were associated with reduced responsiveness to initial IVIg treatment. O_LIHow this study might affect research, practice or policy C_LI The studys findings provide a new approach to exploring the immunological and therapeutic aspects of the role of glycans in CIDP. The decrease in serum total N-glycans, specifically sialylated types, may reflect an inflammatory pathophysiology in CIDP. Furthermore, it is suggested that these changes may serve as novel biomarkers to predict response to initial IVIg treatment.

ObjectiveAutoimmune encephalitis (AE) is a large category disorder urging antibody characterization. The aim was to identify a novel AE related autoantibody targeting an intracellular synaptic protein. MethodsSuspected AE patients had negative conventional antibodies screening but strong immunolabel signals on rat brain sections with the serum and cerebrospinal fluid (CSF) samples were considered burdening unkown antibody. Immunoprecipitation from the rat brain protein lysate followed by mass spectrometry analysis was used to identify the targeting antigen. Western blotting and/or cell-based assay (CBA) with antigen-overexpressing HEK293T cells were used for antibody specificity, epitope and IgG subtype determination. Patients with similar immunostaining pattern on rat brain sections were retrospectively screened for the antibody. ResultsThe antibody against collapsin response mediator protein 2 (CRMP2), a synaptic protein involved in axon guidance, was identified in a patient with suspected AE. The patient samples reactivated with HEK293T cell overexpressed CRMP2, rather than CRMP1, 3, 4, and 5. The patient samples mainly stained neuronal cytoplasm of the cortex, hippocampus and cerebellum Purkinje cells. This reactivity was eliminated by pre-immunoabsorption with CRMP2-overexpressing HEK293T cells. CRMP2 truncation experiments indicated that 536 amino acids at C-terminus was necessary for the epitope. Subtype analysis showed that anti-CRMP2 antibody was IgG4. Moreover, screening from 19 suspected AE patients led to identification of anti-CRMP2 antibody in another patient with a diagnosis of encephalomyelitis. The two patients responded to immunotherapy. ConclusionsThis study discovered a novel anti-CRMP2 antibody associated with AE. Testing of the antibody might be promising for AE diagnosis and treatment.

The clinical diagnosis of major depressive disorder (MDD), a heterogeneous disorder, still depends on subjective information in terms of various symptoms regarding mood. Detecting extracellular vesicles (EVs) in blood may result in finding a diagnostic biomarker that reflects the depressive stage of patients with MDD. Here, we report the results on the glycosylation pattern of enriched plasma EVs from patients with MDD and age-matched healthy subjects. In this cohort, the levels of Triticum vulgaris (wheat germ) agglutinin (WGA), N-acetyl glucosamine (GlcNAc) and N-acetylneuraminic acid (Neu5Ac, sialic acid) - binding lectin, were significantly decreased in patients with MDD in depressive state compared to healthy subjects (area under the curve (AUC): 0.87 (95% confidence interval (CI) 0.76 - 0.97)) and in remission state (AUC: 0.88 (95% CI 0.72 - 1.00)). Furthermore, proteome analysis revealed that the von Willebrand factor (vWF) was a significant factor recognized by WGA. WGA-binding vWF antigen differentiated patients with MDD versus healthy subjects (AUC: 0.92 (95% CI 0.82 - 1.00)) and the same patients with MDD in depressive versus remission state (AUC: 0.98 (95% CI 0.93 - 1.00)). In this study, the change patterns in the glycoproteins contained in plasma EVs support the usability of testing to identify patients who are at increased risk of depression during antidepressant treatment.

Background and ObjectiveFOLR3 serves as an important member of the folate metabolic pathway and plays a crucial role in various malignant tumors. However, the expression pattern, diagnostic value, and regulatory mechanism of FOLR3 in endometrial cancer (EC) remain unclear. This study aimed to explore the expression characteristics, clinical significance, and related molecular regulatory networks of FOLR3 in EC through bioinformatics analysis. MethodsTCGA datasets served as training sets, while GSE17025 from GEO served as validation sets. FOLR3 differential expression was analyzed using Wilcoxon rank-sum test, diagnostic efficacy evaluated by ROC curves, and prognostic value assessed via Kaplan-Meier survival analysis. Candidate genes were identified through WGCNA, univariate Cox regression, and differential expression analysis. Key genes were screened using machine learning algorithms (RF, LASSO, SVM-RFE) and PPI network analysis. ceRNA regulatory networks were constructed, and immune infiltration was analyzed using CIBERSORT. ResultsFOLR3 was significantly overexpressed in EC (P < 0.01) with diagnostic AUC values > 0.6 in both datasets. High FOLR3 expression indicated poor prognosis (HR=2.5, P < 0.05). Among 5,539 differentially expressed genes, 3 key genes (AURKA, POLQ, CDKN2A) were identified via multi-algorithm screening. Enrichment analysis showed involvement in cell division, p53 signaling, and cellular senescence. The ceRNA network comprised 72 nodes and 169 relationships, with KCNQ1OT1 and XIST as key lncRNA regulators. FOLR3 positively correlated with memory B cells and M0 macrophages, negatively with naive B cells and resting mast cells, with significant immune score differences (P < 0.05). ConclusionFOLR3 was significantly upregulated in EC, serving as an effective diagnostic biomarker and independent prognostic predictor. FOLR3 participated in tumorigenesis via complex ceRNA networks and regulated the tumor immune microenvironment. This study provides novel molecular targets and theoretical foundation for precision diagnosis and therapy of EC.

Immunotherapy has changed the standard of treatment for many cancers. However, the same treatments showed disappointing outcomes in cervical cancer so far. Thus, understanding the mechanisms that support the immune tolerance of cervical cancer will provide a way to design new strategies to enhance immunotherapies. Here, we characterized cellular compositions of the immune infiltrates in cervical cancer and investigated if the tumor immune landscape is a predictor for patient prognosis. The fraction of ten immune infiltrates of cervical and other cancers were analyzed by using QuanTIseq software base on the bulk mRNA sequencing data from The Cancer Genome Atlas Program (TCGA). Cervical cancer is one of the cancers that had the lowest percentage of total immune infiltrates, but it had the highest ratio for CD8 T cells to all immune infiltrates among all solid cancers. Both the principal components (PCA) analysis and heatmap with dendrogram analysis showed that cervical cancer had a similar immune infiltrated microenvironment with other squamous cell carcinomas, such as head and neck cancer and lung squamous cell cancer. The PCA and heatmap with dendrogram analysis showed that cervical cancer and HPV positive head and neck cancers were clustered more closer and partially separated with HPV negative head and neck cancer. Further analysis showed that HPV-positive cervical and head and neck cancers had a significantly higher level of CD8 T cells and M1-liked macrophages, but a lower level of M2 macrophages. The survival analysis showed that a higher level of CD8 T cells was associated with a better patient prognosis. However, immuno-suppressive immune infiltrates including M2 macrophages and Treg cells that are known to suppress anti-tumor immunity also demonstrated positive patient overall survival. Our study provided a conceptual framework to understand the tumor immune microenvironment of cervical cancer. Our results also demonstrated that the immune infiltrates can be a prognosis marker for cervical cancer. Simple SummaryCervical cancer is the most common gynecologic cancer and the fourth leading cause of cancer-related death in women worldwide. There are relatively limited treatment options for late-stage cervical cancer. Immunotherapy is a new therapeutic treatment developed with great success in treating many cancers, but the same treatment has not been producing satisfactory results in many cases of cervical cancer. In the present study, we provided a comprehensive immune characterization specifically for cervical cancer. We determined the prognostic value of a specific subtype of tumor-infiltrating immune cells for clinical outcomes and demonstrated that HPV infection affected the immune cell infiltration and induce pro-inflammatory phenotypes. Our study provides a systematic insight into the tumor immune microenvironment of cervical cancers and offers a conceptual framework for the future design of rational combination treatment strategies to improve immunotherapy outcomes.

To perform a bibliometric visualization in lipidomics-related research with two decades. The primary data was retrieved from the Web of Science, three sotwares (VOSviewer, CiteSpace, and R) provided an overview of this field. The countries, institutions, authors, key terms, and keywords were tracked and corresponding mapping was generated. From January 1st in 2001 to March 21th in 2022, 45,325 authors from 234 organizations in 101 countries published 7,338 publications in 382 journals were found. Journal of Lipid Research was the most productive (284 publications) and highly cited journal (18,293 citations). We clustered four keywords themes. The niche theme were shotgun lipidomics, tandem mass-spectrometry, and electrospray-ionization. The motor theme were expression, diseases, and inflammation. The emerging or decling theme were identification, mass-spectrometry, and fatty acids.The basic theme were metabolism, cell, and plasma. Though eight categories the lipid were classified, the keywords showed two of which were got more attention for research, fatty acyls and glycerophospholipids. The top 3 lipidomics-favoured diseases were insulin resistance, obesity, and Alzheimers disease. The top 3 lipidomics-favoured tissue was plasma, brain, and adipose tissue. Burst citations show "women" and "pregnancy" with the strength of 8.91 and 7.1, both topics may be a potential hotspot in the future.

BackgroundMajor depressive disorder (MDD) and its most severe phenotype, major dysmood disorder (MDMD), are distinguished by the activation of the immune-inflammatory response system, T cell activation, and a relative T regulatory cell suppression. Nevertheless, these immune data were not used to characterize the features of the immune protein-protein interaction (PPI) network of MDMD. ObjectivesTo identify the networks nodes and bottlenecks as well as the biological processes that are overrepresented in the PPI network, we conducted PPI network, annotation, and enrichment analyses. ResultsThe PPI network analysis has identified the following backbone genes: tumor necrosis factor- (TNF), interleukin (IL)6, CXCL12, CXCL10, CCL5, cluster of differentiation (CD)4, CD8A, human leukocyte antigen (HLA)-DR, and FOXP3. A "cellular and defense response", an "immune response system response", and "a viral process that involves viral protein interaction with cytokines and cytokine receptors" were all highly associated with the network. The chemokine network and TNF and nuclear factor-{kappa}B (NFKB) pathways are additional biological pathways that are enriched in the PPI network. Molecular complex detection extracted one component from the data, including viral protein interaction with cytokine and cytokine receptors and "regulated by RELA" (an NFKB subunit). ConclusionsViral processes may underlie the activation of T cells and the cytokine and chemokine networks that are associated with MDMD. Future research on the pathogenesis of MDMD and MDD should examine whether and which viral infections are associated with the onset of these conditions, or whether viral reactivation is associated with the recurrence of illness.

BackgroundAutoimmune autonomic ganglionopathy (AAG) is a rare disorder characterized by autonomic failure associated with the presence of anti-ganglionic acetylcholine receptor (gAChR) antibodies; however, several studies have reported that individuals with anti-gAChR antibodies present with central nervous system (CNS) symptoms such as impaired consciousness and seizures. In the present study, we investigated whether the presence of serum anti-gAChR antibodies correlated with autonomic symptoms in patients with functional neurological symptom disorder/conversion disorder (FNSD/CD). MethodsClinical data were collected for 59 patients presenting with neurologically unexplained motor and sensory symptoms at the Department of Neurology and Geriatrics between January 2013 and October 2017 and who were ultimately diagnosed with FNSD/CD according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. Correlations between serum anti-gAChR antibodies and clinical symptoms and laboratory data were analyzed. Data analysis was conducted in 2021. ResultsOf the 59 patients with FNSD/CD, 52 (88.1%) exhibited autonomic disturbances and 16 (27.1%) were positive for serum anti-gAChR antibodies. Cardiovascular autonomic dysfunction, including orthostatic hypotension, was significantly more prevalent (75.0% vs 34.9%, p = 0.008), whereas involuntary movements were significantly less prevalent (31.3% vs 69.8%, p = 0.007), among anti-gAChR antibody-positive compared with - negative patients. Anti-gAChR antibody serostatus did not correlate significantly with the frequency of other autonomic, sensory, or motor symptoms analyzed. ConclusionsAn autoimmune mechanism mediated by anti-gAChR antibodies may be involved in the etiology of FNSD/CD in a subgroup of patients.

BackgroundGardners syndrome was once considered a subtype of familial adenomatous polyposis (FAP), and their molecular pathological features remain to be clarified. Familiar Gardners syndrome complicated by a rare giant left atrial appendage aneurysm (LAAA) is an unreported novel type of FAP syndrome, and exploring its causative cellular subtypes and molecular pathological features will provide new insights into the precise treatment of the syndrome. MethodsWhole-exome sequencing was performed in the familial Gardners syndrome patients, and single cell sequencing of left atrial dilatation tumor, intestinal polyp and scalp cyst in the proband was performed to explore the cellular and molecular pathological mechanisms. ResultsExon sequencing indicated the presence of a rare germline variant (c. 4666 dup A, p. Thr1556fs, rs587783031) in APC (the adenomatous polyposis coli gene), which caused changes in the APC related Wnt pathway. Sc-RNA seq in LAAA revealed an increased proportion of fibroblasts and immune cells. We re-clustered fibroblasts and identified five distinct sub-populations in LAAA: cancer associcated fibroblasts (CAF), cardiomyocyte like fibroblasts (CLF), endothelial like fibroblasts (ELF), T_cells like fibroblasts (TLF), and nomal like fibroblasts (NLF). Notably, nomal fibroblasts should constitute the main component of normal cardiac fibroblasts in LA tissues, while CAF mainly dominated in LAAA tissues. The trajectory and RNA velocity analysis revealed LAAA fibroblasts made a preferential transition from the immature phase (CLF, ELF, TLF, and NLF) at the apex of the trajectory to mature phase of tumor-like properties (CAF), indicating normal fibroblast was reprogrammed into CAF in LAAA. These results suggested diseased LA tissue with GS patient appears to display tumor-prone properties. Moreover, Sc-RNA seq in intestinal polyp revealed an increased proportion of T_NK cells, and epithelial cells, while plasma cells, mesenchymal cells, and fibroblasts showed a significantly decreased in this patient. GO terms of intestinal polyp-derived fibroblasts suggested that APC/c-MYC signaling modulates fibrotic subpopulation remodeling in intestinal polyp of GS patient. In addition, Sc-RNA seq in scalp cyst revealed an increased proportion in epithelial cells and T cells in this patient. Furthermore, the expression of APC was lowly expressed in endothelial cell, fibroblasts, melanocytes, luminal epithelial, and T cells and the expression of c-MYC was highly expressed in melanocytes, luminal epithelial, and endothelial cell in scalp cyst. Fibroblasts of three tissues was integrated and re-clustered to evaluate the commone menchanisms of fibroblasts remodeling. We identified three fibroblast subpopulations (FC0, FC1 and FC2), the ratio of FC2 was shown a significantly increased in GS patient, and APC-C-MYC signaling might modulates FC2 subpopulation to proliferate fibroblasts in the occurrence of three GS tissues. ConclusionsUsing large-scale single cell RNA sequencing, cellular landscape and aetiology-specific alterations were identified in the left atrial dilatation tumor, intestinal polyp and scalp cyst of the proband. APC-C-MYC signaling modulates fibrotic subpopulation remodeling in LAAA and intestinal polyp while epithelial subpopulation remodeling in scalp cyst, indicating that syndrome subtypes caused by the same gene mutation in the same individual may still lead to different cellular and gene expression signatures and heterogeneity. This new approach provides a wealth of novel insights into the molecular changes that underlie the cellular processes relevant for cardiac biology and pathophysiology and also shed light on strategies for cell type- and stage-specific intervention in cardiac diseases.

Depressive and anxiety symptoms occur more frequently in chronic encephalomyelitis. Inflammatory diseases are highly associated with psychiatric comorbidities, which has been well established in Multiple Sclerosis. However, no biomarkers have been found with the capacity to discern between MS and depression. Thirty-six individuals with a diagnosis of MS according to the revised McDonald criteria, were recruited from an outpatient Neurology and Psychiatry from the medical unit of high specialty in Mexico. We measured the association between BDNF, IL-1{beta}, and TNF in serum with the presence of depression and anxiety using the semi-structured psychiatric interview, the Beck Depression Inventory (IDB), and Hospital Anxiety and Depression Scale (HADS). This was a cross-sectional study. The Logistic Regression was used for the multivariate analysis adjusted by the Multiple Sclerosis Severity Score (MSSS). With a power of 0.75 in the final model, patients with multiple sclerosis, depression, and anxiety obtained the highest values of IL-1 {beta} in our study.

ObjectiveThe prognostic effect of tumor-infiltrating immune cells (TIICs) on endometrial cancer (EMC) has not been extensively investigated. In the present study, we systematically analyzed the role of TIICs in EMC development. MethodsPatient data were downloaded from The Cancer Genome Atlas (TCGA). We comprehensively analyzed TIIC population in EMC tissue and their role in EMC progression and prognosis by using a deconvolution algorithm (CIBERSORT) and clinically annotated expression profiles. ResultsThe proportions of gamma delta T cells, resting NK cells, M1 macrophages, and resting mast cells were significantly different in normal endometrium and EMC tissue. The proportion of CD8+ T cells, resting memory CD4 T cells, and M0 macrophages was reversed middle correlated. The proportion of resting dendritic cells, resting memory CD4 T cells, and T regulatory cells (Tregs) decreased in accordance with the cancer cell differentiation grade (G); the lower proportion of activated dendritic cells and gamma delta T cells and higher proportion of Tregs predicted longer EMC survival time and vice versa. The low proportion of gamma delta T cells indicated better response to therapy. ConclusionCollectively, our data suggested subtle differences in the cellular composition of TIICs in EMC, and these differences were likely to be important determinants of both prognosis and therapy of EMC.

Targeted therapy was a promising therapy for aggressive B-cell lymphoma. However, drug resistance was still an unavoidable problem. Here, we explored the effect of EFNB1 on drug response. Analysis of IC50 data showed that high level of EFNB1 was associated with resistance to most targeted drugs targeting BCR in human DLBCL cell lines. Drug response assay showed that Efnb1 could enhance SRC phosphorylation and increased the sensitivity of cells to SRC inhibitors. Meanwhile, Efnb1 could sensitize cells to most cytotoxic drugs, especially DOX and VCR. Efnb1 could confer cells sensitivity to VCR by enhancing the phosphorylation of Stmn1 at serine 28. Survival analysis revealed that the expression level of genes phosphorylated in Efnb1 cells were associated with poor prognosis of human DLBC. Together, this study revealed that EFNB1 level, as a non-genetic mechanism, greatly affected drug response of targeted drugs and cytotoxic drugs through the phosphorylation network. Our findings would provide important insights into EFNB1-SRC activated B-cell lymphoma and efficacy evaluation.

BackgroundInflammation and autoimmune responses contribute to the pathophysiology of Long COVID, and its affective and chronic fatigue syndrome (CFS) symptoms, labeled "the physio-affective phenome." ObjectivesTo investigate whether Long COVID and its physio-affective phenome are linked to autoimmunity to the tight junction proteins, zonulin and occludin (ZOOC), and immune reactivity to lipopolysaccharides (LPS), and whether the latter are associated with signs of human herpes virus-6 reactivation (HHV-6), autoimmunity directed against oligodendrocyte and neuronal proteins, including myelin basic protein (MBP). MethodsIgA/IgM/IgG responses to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), HHV-6, ZOOC, and neuronal proteins, C-reactive protein (CRP) and advanced oxidation protein products (AOPP), were measured in 90 Long COVID patients and 90 healthy controls. The physio-affective phenome was conceptualized as a factor extracted from physical and affective symptom domains. ResultsNeural network identified IgA directed to LPS (IgA-LPS), IgG-ZOOC, IgG-LPS, and IgA-ZOOC as the most important variables associated with Long COVID diagnosis with an area under the ROC curve of 0.755. Partial Least Squares analysis showed that 40.9% of the variance in the physio-affective phenome was explained by CRP, IgA-MPB and IgG-MBP. A large part of the variances in both autoimmune responses to MBP (36.3-39.7%) was explained by autoimmunity (IgA and IgG) directed to ZOOC. The latter was strongly associated with indicants of HHV-6 reactivation, which in turn was associated with increased IgM-SARS-CoV-2. ConclusionsAutoimmunity against components of the tight junctions and increased bacterial translocation may be involved in the pathophysiology of Long COVIDs physio-affective phenome.

Keshan disease (KD), an endemic heart disease with multifocal necrosis and replacement fibrosis of the myocardium,is still a nightmare situation for human health. However, molecular mechanism in the pathogenesis of KD remains unclear. Herein, blood samples were collected from 68 KD patients and 100 controls, and we systematically analyzed mutation profiles using whole-exome sequencing (WES). Causative genes of dilated cardiomyopathy (DCM), gene-based burden analysis, disease and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. Of the 98 DCM-causative genes, 106 rare variants in 28 genes were detected in KD patients with minor allele frequency (MAF) < 0.001. Gene-based burden analysis, PPI network analysis, and automated Phenolyzer analysis were performed to prioritize 199 candidate genes, which combined with 98 DCM-causative genes, and reference genes from gene microarray or proteomics in KD. Then, 19 candidate pathogenic genes were selected, and 9 candidate genes were identified using PPI analysis, including HIF1A, GART, ALAD, VCL, DTNA, NEXN, INPPL1, NOS3, and JAK2. The 199 candidate genes were further analyzed using disease enrichment with CTD database and PPI analysis, and 21 candidate genes were identified. By combining with disease enrichment and PPI analysis, 7 Selenium (Se)-related genes were further identified, including ALAD, RBM10, GSN, GGT1, ADD1, PARP1, and NOS3. Based on the gene function and data validation, NEXN, TAF1C, FUT4, ALAD, ZNF608, and STX2 were the most likely pathogenic genes in KD. Notably, ALAD is the only candidate pathogenic gene identified by four different analyses, and its homozygous mutant mice could affect heart development and cause death.

Circulating miRNAs in small vesicles known as exosomes within blood have been emerging as a new research hotspot in the field of psychiatric disorders. The aim of this work was to characterize the changes in exosomal microRNA profiles, both short-term and long-term, during substance withdrawal using a cross-sectional study design. Using weighted gene co-expression network analysis, a series of known, conserved, and novel exosomal microRNAs were identified as being associated with withdrawal stage and key neurotransmitters GABA, choline, and serotonin. Bioinformatics analyses established that the differences in the miRNA profile target signaling pathways are associated with developmental and intellectual abnormalities. Notably, a set of dysregulated microRNA signatures including hsa-mia-451a and hsa-mir-21a resulted in an AUC of 0.966 and 0.861, respectively, for predicting patients with substance use disorders. Furthermore, hsa-miR-744a-5p was positively correlated with serotonin, and its important role in maintaining neuronal development and function was revealed using an in vitro human induced pluripotent stem cells derived neuronal model. Taken together, these data suggest that the microRNA content of circulating exosomes represent a biomolecular "fingerprint" of the progression of substance withdrawal and may uncover the putative mechanism of how these exosomal microRNAs contribute to central nervous system development and function.

BackgroundThe risk of intracranial aneurysm (IAs) development and rupture is significantly higher in patients with periodontitis (PD), suggesting an association between the two. However, the specific mechanisms of association between these two diseases have not been fully investigated. The aim of this study was to investigate potential crosstalk genes, pathways between IAs and PD. MethodsWe downloaded IAs and PD data from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed on these overlapping DEGs. The protein-protein interaction (PPI) network was constructed and the cytoHubba plugin was used to identify PPI key genes. Next, weighted gene co-expression network analysis (WGCNA) was performed. Subsequently, we validated the key crosstalk genes in 2 independent external datasets. In addition, the immune cell landscape was assessed and the correlation of key crosstalk genes with each immune cell was calculated. Finally, transcription factors (TFs) regulating key crosstalk genes were explored and their expression levels were further validated in the full dataset. Results127 overlapping DEGs were identified and functional enrichment analysis highlighted the important role of immune reflection in the pathogenesis. We identified ITGAX and COL4A2 as key crosstalk genes and the expression levels of them were significantly elevated in the test dataset and external validation dataset. In addition, the expression of multiple immune cells was significantly elevated in PDs and IAs compared to controls, and both key crosstalk genes were significantly negatively associated with Macrophages M2. Finally, GATA2 was identified as a potential key transcription factor (TF), which regulates two key crosstalk genes and was upregulated in expression in the full dataset. ConclusionThe present study identifies key crosstalk genes and TF in IAs and PD, providing new insights for further study of the co-pathogenesis of IAs and PD from an immune and inflammatory perspective.

Atopic dermatitis is a common inflammatory skin disorder characterised by recurrent eczematous lesions and intense itch. Quercetin is a naturally occurring flavonoid, exhibits antioxidant and anti-inflammatory properties. Previous studies have indicated its beneficial role in managing atopic dermatitis (AD); however, the precise underlying mechanism remains unclear. This study aimed to investigate the protective effects of quercetin against AD and to elucidate its potential mechanisms. We demonstrated that quercetin effectively suppressed the overexpression of pro-inflammatory effector factors--including interleukin (IL)-1{beta}, thymic stromal lymphopoietin (TSLP) and chemokine (C-X-C motif) ligand 1/10/11 (CXCL1/10/11)--in immortalized human keratinocytes (HaCaT) stimulated by TNF-/IFN-{gamma}. Proteomic analysis revealed 88 differentially expressed proteins, suggesting that quercetins therapeutic action involves multiple pathways. Notably, the NOD-like receptor signaling pathway was identified as a key factor. The key proteins related to this pathway including inhibitor of nuclear factor kappa B kinase epsilon (IKBKE), indoleamine 2,3-dioxygenase 1 (IDO1) and chemokine (C-X-C motif) ligand 9 (CXCL9) showed a significant decrease in expression levels after quercetin treatment. Collectively, these results demonstrate that quercetin alleviates AD symptoms by attenuating inflammatory responses, likely through inhibition of the NOD-like receptor signaling pathway.

Sequencing-based studies have recognized hundreds of genetic variants that increase the risk of schizophrenia (SCZ), but only a few percents of heritability can be attributed to these loci. It is challenging to discover the full spectrum of schizophrenia genes and reveal the dysregulated functions underlying the disease. Here, we proposed a holistic model for predicting disease genes (HMPDG), a novel machine learning prediction strategy integrated by Protein-Protein Interaction Network (PPIN), pathogenicity score, and RNA expression data. Applying HMPDG, 1946 potential risk genes (PRGs) as a complement of the genetic basis of SCZ were predicted. Among these, the first decile genes were highlighted as high confidence genes (HCGs). PRGs were validated by multiple independent studies of schizophrenia, including genome-wide association studies (GWASs), gene expression studies, and epigenetic studies. Remarkably, the strategy revealed causal genes of schizophrenia in GWAS loci and regions of copy number variant (CNV), providing a new insight to identify key genes in disease-related loci with multi genes. Leveraging our predictions, we depict the spatiotemporal expression pattern and functional groups of schizophrenia risk genes, which can help us figure out the pathophysiology of schizophrenia and facilitate the discovery of biomarkers. Taken together, our strategy will advance the understanding of schizophrenia genetic basis and the development of diagnosis and therapeutics.