Genome-wide gene expression profiling reveals that CD274 is up-regulated new-onset type 1 diabetes mellitus

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Immune cells and their inflammatory mediators modify β cells and cause checkpoint inhibitor-induced diabetes

Checkpoint inhibitors (CPIs) targeting programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) have revolutionized cancer treatment but can trigger autoimmune complications, including CPI-induced diabetes mellitus (CPI-DM), which occurs preferentially with PD-1 blockade. We found evidence of pancreatic inflammation in patients with CPI-DM with shrinkage of pancreases, increased pancreatic enzymes, and in a case from a patient who died with CPI-DM, peri-islet lymphocytic infiltration. In the NOD mouse model, anti-PD-L1 but not anti-CTLA-4 induced diabetes rapidly. RNA sequencing revealed that cytolytic IFN-γ+CD8+ T cells infiltrated islets with anti-PD-L1. Changes in β cells were predominantly driven by IFN-γ and TNF-α and included induction of a potentially novel β cell population with transcriptional changes suggesting dedifferentiation. IFN-γ increased checkpoint ligand expression and activated apoptosis pathways in human β cells in vitro. Treatment with anti-IFN-γ and anti-TNF-α prevented CPI-DM in anti-PD-L1-treated NOD mice. CPIs targeting the PD-1/PD-L1 pathway resulted in transcriptional changes in β cells and immune infiltrates that may lead to the development of diabetes. Inhibition of inflammatory cytokines can prevent CPI-DM, suggesting a strategy for clinical application to prevent this complication.

Advances in CD247

CD247, which is also known as CD3ζ, CD3H, CD3Q, CD3Z, IMD25, T3Z, and TCRZ, encodes CD3ζ protein, which is expressed primarily in natural killer (NK) and T cells. Since the discovery of the ζ peptide in 1986, it has been continuously investigated. In this paper, we review the composition, molecular mechanisms and regulatory factors of CD247 expression in T cells; and review the autoimmune diseases, tumors and inflammatory diseases associated with CD247, providing a detailed and comprehensive reference for further research on the mechanism of CD247 and related diseases.

Syngeneically transplanted insulin producing cells differentiated from adipose derived stem cells undergo delayed damage by autoimmune responses in NOD mice

Insulin-producing cells (IPCs) generated by our established protocol have reached the non-clinical ‘proof of concept’ stage. Our strategy for their clinical application is the autotransplantation of IPCs into patients with type 1 diabetes mellitus (T1DM). In this context, the autoimmunity that characterized T1DM is important, rather than allorejection. We aimed to determine how these IPCs respond to T1DM autoimmunity. IPCs were generated from the subcutaneous fat tissue of non-obese diabetic (NOD) mice using our protocol. IPCs derived from NOD mice were transplanted under the kidney capsules of NOD mice at the onset of diabetes and the subsequent changes in blood glucose concentration were characterized. Blood glucose decreased within 30 days of transplantation, but increased again after 40–60 days in three of four recipient NOD mice. In tissue samples, the numbers of CD4⁺ and CD8⁺ T cells were significantly higher 60 days after transplantation than 30 days after transplantation. In conclusion, IPCs significantly ameliorate the diabetes of mice in the short term, but are damaged by autoimmunity in the longer term, as evidenced by local T cells accumulation. This study provides new insights into potential stem cell therapies for T1DM.

Integrative Analyses of Genes Associated with Fulminant Type 1 Diabetes

Objective

Fulminant type 1 diabetes (FT1D) is a type of type 1 diabetes, which is characterized by rapid onset of disease and severe metabolic disorders. We intend to screen for crucial genes and potential molecular mechanisms in FT1D in this study.

Method

We downloaded GSE44314, which includes six healthy controls and five patients with FT1D, from the GEO database. Identification of differentially expressed genes (DEGs) was performed by NetworkAnalyst. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were screened by an online tool-Database for Annotation, Visualization, and Integration Discovery (DAVID). Protein-protein interaction (PPI) network and hub genes among DEGs were analyzed by NetworkAnalyst. And we also use NetworkAnalyst to find out the microRNAs (miRNAs) and transcription factors (TFs) which regulate the expression of DEGs.

Result

We identified 130 DEGs (60 upregulated and 70 downregulated DEGs) between healthy controls and FT1D patients. GO analysis results revealed that DEGs were mostly enriched in generation of precursor metabolites and energy, neurohypophyseal hormone activity, and mitochondrial inner membrane. KEGG pathway analysis demonstrated that DEGs were mostly involved in nonalcoholic fatty liver disease. Results indicated that NCOA1, SRF, ERBB3, EST1, TOP1, UBE2S, INO80, COX7C, ITGAV, and COX6C were the top hub genes in the PPI network. Furthermore, we recognized that LDLR, POTEM, IFNAR2, BAZ2A, and SRF were the top hub genes in the miRNA-target gene network, and SRF, TSPAN4, CD59, ETS1, and SLC25A25 were the top hub genes in the TF-target gene network.

Conclusion

Our study pinpoints key genes and pathways associated with FT1D by a sequence of bioinformatics analysis on DEGs. These identified genes and pathways provide more detailed molecular mechanisms of FT1D and may provide novel therapeutic targets.

Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows

Ketosis is a metabolic disorder of increasing importance in high-yielding dairy cows, but accurate population-wide binary health trait recording is difficult to implement. Against this background, proper Gaussian indicator traits, which can be routinely measured in milk, are needed. Consequently, we focused on the ketone bodies acetone and β-hydroxybutyrate (BHB), measured via Fourier-transform infrared spectroscopy (FTIR) in milk. In the present study, 62,568 Holstein cows from large-scale German co-operator herds were phenotyped for clinical ketosis (KET) according to a veterinarian diagnosis key. A sub-sample of 16,861 cows additionally had first test-day observations for FTIR acetone and BHB. Associations between FTIR acetone and BHB with KET and with test-day traits were studied phenotypically and quantitative genetically. Furthermore, we estimated SNP marker effects for acetone and BHB (application of genome-wide association studies) based on 40,828 SNP markers from 4,384 genotyped cows, and studied potential candidate genes influencing body fat mobilization. Generalized linear mixed models were applied to infer the influence of binary KET on Gaussian-distributed acetone and BHB (definition of an identity link function), and vice versa, such as the influence of acetone and BHB on KET (definition of a logit link function). Additionally, linear models were applied to study associations between BHB, acetone and test-day traits (milk yield, fat percentage, protein percentage, fat-to-protein ratio and somatic cell score) from the first test-day after calving. An increasing KET incidence was statistically significant associated with increasing FTIR acetone and BHB milk concentrations. Acetone and BHB concentrations were positively associated with fat percentage, fat-to-protein ratio and somatic cell score. Bivariate linear animal models were applied to estimate genetic (co)variance components for KET, acetone, BHB and test-day traits within parities 1 to 3, and considering all parities simultaneously in repeatability models. Pedigree-based heritabilities were quite small (i.e., in the range from 0.01 in parity 3 to 0.07 in parity 1 for acetone, and from 0.03-0.04 for BHB). Heritabilites from repeatability models were 0.05 for acetone, and 0.03 for BHB. Genetic correlations between acetone and BHB were moderate to large within parities and considering all parities simultaneously (0.69-0.98). Genetic correlations between acetone and BHB with KET from different parities ranged from 0.71 to 0.99. Genetic correlations between acetone across parities, and between BHB across parities, ranged from 0.55 to 0.66. Genetic correlations between KET, acetone, and BHB with fat-to-protein ratio and with fat percentage were large and positive, but negative with milk yield. In genome-wide association studies, we identified SNP on BTA 4, 10, 11, and 29 significantly influencing acetone, and on BTA 1 and 16 significantly influencing BHB. The identified potential candidate genes NRXN3, ACOXL, BCL2L11, HIBADH, KCNJ1, and PRG4 are involved in lipid and glucose metabolism pathways.

PD-1 and PD-L1 Expression in Peripheral CD4/CD8+ T Cells Is Restored in the Partial Remission Phase in Type 1 Diabetes

CONTEXT

Partial remission (PR) in type 1 diabetes (T1D) is accompanied by downregulation of the immune response. Programmed cell death-1 (PD-1) and its ligand (PD-L1) are important immunosuppressive molecules, but their changes in the PR phase are unclear.

OBJECTIVE

We investigated the dynamic changes of PD-1/PD-L1 expression on T cells around the PR phase in T1D.

METHODS

Ninety-eight T1D patients were recruited cross-sectionally and grouped according to PR status into nonremitters (individuals who did not undergo PR during the disease course; n = 39), pre-PR (n = 15), mid-PR (n = 30), and post-PR (n = 14) subgroups. PR was defined according to C-peptide level ≥300 pmol/L or index of insulin-adjusted hemoglobin A1c ≤9 as recommended. Among all the 98 patients, 29 newly diagnosed individuals were prospectively followed up for 1 year. The dynamic changes of PD-1/PD-L1 expression, frequency of regulatory T cells (Tregs) and IL-35+ Tregs among peripheral CD4/CD8+ T cells were determined.

RESULTS

PD-1/PD-L1 on CD4+/CD8+ T cells showed a dynamic change around the PR phase: lowest in pre-PR phase, restored in mid-PR phase, and declined again in post-PR phase. Conversely, this pattern did not occur for nonremitters. Notably, PD-1 expression on CD8+ T cells in mid-PR was positively correlated with the length of the PR phase. The percentages of circulating Tregs and IL-35+ Tregs showed no relation to PR.

CONCLUSIONS

The PR phase is associated with restoration of PD-1/PD-L1 on CD4+ and CD8+ T cells, suggesting that PD-1/PD-L1 may be a potential target for prolonging this phase in T1D.

Identification of hub genes and small-molecule compounds in medulloblastoma by integrated bioinformatic analyses

Background

Medulloblastoma (MB) is the most common intracranial malignant tumor in children. The genes and pathways involved in the pathogenesis of MB are relatively unknown. We aimed to identify potential biomarkers and small-molecule drugs for MB.

Methods

Gene expression profile data sets were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the Limma package in R. Functional annotation, and cell signaling pathway analysis of DEGs was carried out using DAVID and Kobas. A protein-protein interaction network was generated using STRING. Potential small-molecule drugs were identified using CMap.

Result

We identified 104 DEGs (29 upregulated; 75 downregulated). Gene ontology analysis showed enrichment in the mitotic cell cycle, cell cycle, spindle, and DNA binding. Cell signaling pathway analysis identified cell cycle, HIF-1 signaling pathway, and phospholipase D signaling pathway as key pathways. SYN1, CNTN2, FAIM2, MT3, and SH3GL2 were the prominent hub genes and their expression level were verified by RT-qPCR. Vorinostat, resveratrol, trichostatin A, pyrvinium, and prochlorperazine were identified as potential drugs for MB. The five hub genes may be targets for diagnosis and treatment of MB, and the small-molecule compounds are promising drugs for effective treatment of MB.

Conclusion

In this study we obtained five hub genes of MB, SYN1, CNTN2, FAIM2, MT3, and SH3GL2 were confirmed as hub genes. Meanwhile, Vorinostat, resveratrol, trichostatin A, pyrvinium, and prochlorperazine were identified as potential drugs for MB.

Targeting Type 1 Diabetes: Selective Approaches for New Therapies

The clinical onset of type 1 diabetes is characterized by the destruction of the insulin-producing β cells of the pancreas and is caused by autoantigen-induced inflammation (insulitis) of the islets of Langerhans. The current standard of care for type 1 diabetes mellitus patients allows for management of the disease with exogenous insulin, but patients eventually succumb to many chronic complications such as limb amputation, blindness, and kidney failure. New therapeutic approaches now on the horizon are looking beyond glycemic management and are evaluating new strategies from protecting and regenerating endogenous islets to treating the underlying autoimmunity through selective modulation of key immune cell populations. Currently, there are no effective treatments for the autoimmunity that causes the disease, and strategies that aim to delay or prevent the onset of the disease will play an important role in the future of diabetes research. In this review, we summarize many of the key efforts underway that utilize molecular approaches to selectively modulate this disease and look at new therapeutic paradigms that can transform clinical treatment.

Bioinformatics approach reveals the key role of C‑X‑C motif chemokine receptor 2 in endometriosis development

Endometriosis is a common gynecological disease, affecting 6‑10% of women of reproductive age. The precise mechanisms underlying the development of endometriosis remain unclear. In the present study, a bioinformatics approach was applied to systematically identify the pathways and genes involved in the development of endometriosis and to discover potential biomarkers. The gene expression profiles of GSE6364, a microarray dataset of endometrial biopsies obtained from women with or without endometriosis, was downloaded from the Gene Expression Omnibus DataSets database that stores original submitter‑supplied records (series, samples and platforms), as well as curated datasets. Differentially expressed gene (DEG) analysis was performed with GEO2R. DAVID was used to analyze the gene ontology enrichment of the DEGs. Gene Set Enrichment Analysis (GSEA) was conducted using the GSEA v3.0 software. Protein‑protein interactions (PPI) were evaluated with the Search Tool for the Retrieval of Interacting Genes, and PPI network visualization was performed with Cytoscape. In addition, Cell Counting kit‑8 and Transwell assays were performed on human endometrial stromal cells (HESCs). A total of 172 DEGs were extracted. Inflammatory response genes were significantly upregulated in the endometriosis tissues and C‑X‑C motif chemokine receptor 2 (CXCR2), was one of the most up‑regulated genes according to DEG analysis. Cell‑based experiments confirmed that CXCR2 promoted the proliferation, migration and invasion of HESCs. In conclusion, a bioinformatics approach combined with in vitro experiments in the present study revealed that CXCR2 may be associated with the development of endometriosis and has potential as a biomarker for the diagnosis of endometriosis.

Interferon-gamma drives programmed death-ligand 1 expression on islet β cells to limit T cell function during autoimmune diabetes

Type 1 diabetes is caused by autoreactive T cell-mediated β cell destruction. Even though co-inhibitory receptor programmed death-1 (PD-1) restrains autoimmunity, the expression and regulation of its cognate ligands on β cell remains unknown. Here, we interrogated β cell-intrinsic programmed death ligand-1 (PD-L1) expression in mouse and human islets. We measured a significant increase in the level of PD-L1 surface expression and the frequency of PD-L1+ β cells as non-obese diabetic (NOD) mice aged and developed diabetes. Increased β cell PD-L1 expression was dependent on T cell infiltration, as β cells from Rag1-deficient mice lacked PD-L1. Using Rag1-deficient NOD mouse islets, we determined that IFN-γ promotes β cell PD-L1 expression. We performed analogous experiments using human samples, and found a significant increase in β cell PD-L1 expression in type 1 diabetic samples compared to type 2 diabetic, autoantibody positive, and non-diabetic samples. Among type 1 diabetic samples, β cell PD-L1 expression correlated with insulitis. In vitro experiments with human islets from non-diabetic individuals showed that IFN-γ promoted β cell PD-L1 expression. These results suggest that insulin-producing β cells respond to pancreatic inflammation and IFN-γ production by upregulating PD-L1 expression to limit self-reactive T cells.