B cells in type 1 diabetes mellitus and diabetic kidney disease

Systemic Inflammation and Disruption of the Local Microenvironment Compromise Muscle Regeneration: Critical Pathogenesis of Autoimmune-Associated Sarcopenia

Unlabelled

Sarcopenia is defined by age-related reductions in muscle mass, strength, and physiological function, and it is especially prevalent among individuals with autoimmune diseases. Autoimmune disorders, characterized by immune dysregulation, cause systemic inflammation and damage to multiple tissues through unregulated immune activity. Research indicates that autoimmune diseases negatively impact skeletal muscle functions and may worsen the progression of sarcopenia. This viewpoint comprehensively discusses the pathogenesis and potential mechanism of sarcopenia in 3 autoimmune diseases: inflammatory bowel disease, rheumatoid arthritis, and type 1 diabetes mellitus. Mechanistically, chronic immune microenvironment alterations induce compartment-specific redistribution of leukocyte subsets and cytokine networks. These perturbations disrupt critical signaling pathways governing muscle protein synthesis, satellite cell activation, and mitochondrial bioenergetics, leading to impaired regeneration and accelerated sarcopenia progression. By delineating shared and distinct pathomechanisms across these models, this analysis reframes our understanding of immune-mediated muscle wasting. Beyond mechanistic insights, it establishes a translational framework for targeted therapies and highlights emerging research directions bridging immunology and age-related musculoskeletal decline.

Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset

Autoimmune destruction of pancreatic β cells results in type 1 diabetes (T1D), with pancreatic immune infiltrate representing a key feature in this process. However, characterization of the immunological processes occurring in human pancreatic lymphatic tissues is lacking. Here, we conduct a comprehensive study of immune cells from pancreatic, mesenteric, and splenic lymphatic tissues of non-diabetic control (ND), β cell autoantibody-positive non-diabetic (AAb+), and T1D donors using flow cytometry and CITEseq. Compared to ND pancreas-draining lymph nodes (pLN), AAb+ and T1D donor pLNs display decreased CD4+ Treg and increased stem-like CD8+ T cell signatures, while only T1D donor pLNs exhibit naive T cell and NK cell differentiation. Mesenteric LNs have modulations only in CD4+ Tregs and naive cells, while splenocytes lack these perturbations. Further, T cell expression of activation markers and IL7 receptor correlate with T1D genetic risk. These results demonstrate tissue-restricted immune changes occur before and after T1D onset.

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy

Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive understanding of the mechanism is lacking. This work aimed to pinpoint distinctive anoikis-related genes (ARGs) in DN and delve into their impact on the immune landscape. Three datasets (GSE30528, GSE47184, and GSE96804) were downloaded from the gene expression omnibus (GEO) dataset. Differentially expressed genes (DEGs) were identified using the "limma" package, while ARGs were obtained from GSEA, GeneCard, and Harmonizome datasets. The intersection of DEGs and ARGs was analyzed for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The CIBERSORT algorithm was employed to estimate the infiltration percentage of 22 immune cell types in DN renal tissue. Subsequently, the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) algorithms were adopted to screen key ARGs related to DN. After that, receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of each gene and the real-time quantitative polymerase chain reaction (RT-qPCR) was adopted to quantitatively detect the expression of biomarkers in DN cell models. Finally, correlations between key genes and immune cell infiltration were analyzed, and a competitive endogenous ribonucleic acid (RNA) (ceRNA) network based on key genes was constructed. A total of 59 DEARGs were identified. GO functional annotation enrichment analysis revealed their involvement in kidney development, extracellular matrix (ECM), cytoplasmic vesicle cavity, immunoinflammatory response, and cytokine effect. KEGG pathway analysis indicated that MAPK, PI3K -Akt, IL -17, TNF, and HIF- 1 signaling pathways are critical for DN. In addition, seven key genes, including PDK4, S100A8, HTRA1, CHI3L1, WT1, CDKN1B, and EGF, were screened by machine learning algorithm. Most of these genes exhibited low expression in renal tissue of DN patients and positive correlation with neutrophils, and their expressions were verified in an external dataset cell model. The ceRNA analysis suggested potential regulatory pathways (H19/miR-15b-5p/PDK4 and KCNQ1T1/miR-1207-3p/WT1) influencing early DN progression. This work provided a comprehensive analysis of the role of DEARGs in DN for the first time, offering valuable insights for further understanding the disease mechanism and guiding clinical diagnosis, treatment, and research of DN.

The role of fatty acid metabolism on B cells and B cell-related autoimmune diseases

Fatty acid metabolism plays a critical role in regulating immune cell function, including B cells, which are central to humoral immunity and the pathogenesis of autoimmune diseases. Emerging evidence suggests that fatty acid metabolism influences B cell development, activation, differentiation, and antibody production, thereby impacting B cell-related autoimmune diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and multiple sclerosis (MS). In this review, we discuss the mechanisms by which fatty acid metabolism modulates B cell biology, including energy provision, membrane composition, and signaling pathways. We highlight how alterations in fatty acid synthesis, oxidation, and uptake affect B cell function and contribute to autoimmune pathogenesis. Additionally, we explore the therapeutic potential of targeting fatty acid metabolism in B cells to treat autoimmune diseases. Understanding the interplay between fatty acid metabolism and B cell immunity may provide novel insights into the development of precision therapies for B cell-mediated autoimmune disorders.

T-bet-expressing B cells promote atherosclerosis in apolipoprotein E-deficient mice

The humoral immune system influences the development of atherosclerosis, but the contributions of specific memory B cell subsets and IgG isotypes are poorly understood. We assessed the relationship between atherosclerosis and age-associated B cells (ABCs), a T-bet-expressing memory B cell subset that is enriched for IgG2c production and implicated in humoral autoimmunity. We found increased numbers of splenic CD11c+ ABCs in 6-mo-old, chow-fed Apoe-/- mice versus C57BL/6 control mice, which were exacerbated by high-fat diet. Deletion of T-bet in the B lineage in high-fat diet-fed Apoe-/- mice reduced aortic lesion area, and this correlated with decreased splenic CD11c+ B cells and reduced serum oxidized low-density lipoprotein-specific IgG2c. Our findings suggest that T-bet-expressing B cells are atherogenic agents in the Apoe-/- model and indicate that interventions to inhibit a T-bet-driven humoral response may improve atherosclerotic disease.

Insulin autoantibodies, D-dimer and microalbuminuria: A cross-sectional, case-control study of type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) often leads to vascular complications, such as albuminuria. The role of insulin autoantibodies (IAA) and their interaction with D-dimer in this context remains unclear.

AIM

To investigate the characteristics of IAA and its effect on albuminuria in T2DM patients.

METHODS

We retrospectively analyzed clinical data from 115 T2DM patients with positive IAA induced by exogenous insulin, and 115 age- and sex-matched IAA-negative T2DM patients as controls. Propensity scores were calculated using multivariate logistic regression. Key variables were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. We constructed a prediction model and analyzed the association between IAA and albuminuria based on demographic and laboratory parameters.

RESULTS

The IAA-positive group had significantly higher D-dimer levels [0.30 (0.19-0.55) mg/L vs 0.21 (0.19-0.33) mg/L, P = 0.008] and plasma insulin levels [39.1 (12.0-102.7) μU/mL vs 9.8 (5.5-17.6) μU/mL, P < 0.001] compared to the IAA-negative group. Increases in the insulin dose per weight ratio, diabetes duration, and urinary albumin-to-creatinine ratio (UACR) were observed but did not reach statistical significance. The LASSO model identified plasma insulin and D-dimer as key factors with larger coefficients. D-dimer was significantly associated with UACR in the total and IAA-positive groups but not in the IAA-negative group. The odds ratio for D-dimer elevation (> 0.5 g/L) was 2.88 (95% confidence interval: 1.17-7.07) in the IAA-positive group (P interaction < 0.05).

CONCLUSION

D-dimer elevation is an independent risk factor for abnormal albuminuria and interacts with IAA in the development of abnormal albuminuria in T2DM patients.

Disease-specific signatures of circulating extracellular vesicles detected by the surface plasmon resonance imaging: a pilot study

Aim: Cells in the human body release extracellular vesicles (EVs) into fluids, such as plasma, urine, and cerebrospinal fluid. EVs express tetraspanin family proteins (e.g., CD63, CD9, and CD81) and cell-specific antigens on their surface as common and specific markers, respectively. In this study, we hypothesized that the profile of blood cell-derived circulating EVs could reveal both common and specific pathophysiology in atherogenic diseases. Methods: Using surface plasmon resonance imaging (SPRi), we analyzed EVs surface molecules and identified circulating EVs in healthy controls (n = 18), patients with type 2 diabetes mellitus (T2DM; n = 71), and those with hypertension (HT; n = 47). Results: Patients with T2DM and HT exhibited distinct EV profiles: (i) CD9, CD110, CD20, activin receptor type-2A (AcvRIIA), Duffy antigen receptor for chemokine, and CD44 positive EVs were upregulated in T2DM; (ii) CD9, Maackia amurensis agglutinin lectin binding molecules (MBM), CD20, AcvRIIA, and CD44 positive EVs were upregulated in HT. By analyzing an appropriate set of three antigens or using dimensional reduction clustering, we were able to clearly differentiate between T2DM, HT, and control groups. In some patients, disease severity correlated with CD44 and CD20 in T2DM and MBM and AcvRIIA in HT. Conclusion: Our findings demonstrate that profiling of circulating EVs via the SPRi method offers a novel approach for diagnosing and monitoring human diseases.

Machine learning-based identification and validation of amino acid metabolism related genes as novel biomarkers in chronic kidney disease

Objectives

Chronic kidney disease (CKD) is a progressive illness with a high rate of morbidity and mortality with no proven therapy. Alterations of amino acid(AA) metabolism are associated with the incidence and progression of CKD. To characterize the potential value of AA metabolism related genes in the diagnosis and progression of CKD.

Methods

We filtered the key genes associated with AA metabolism based on the least absolute shrinkage and selection operator (LASSO) and SVM algorithm. Then, we constructed logistic regression models and evaluated the accuracy and specificity by nomogram analysis and DCA. Also, we mapped the ROC curves.Meanwhile, in order to determine the underlying mechanism and relevant biological features of CKD, we conducted differential analysis between high and low risk subgroups in CKD. Moreover,we employed ssGSEA algorithm to evaluate the infiltration abundance of immune cells and calculated the correlation among the immune cells with the key genes. Finally,we validated the expression and clinical relevance of amino acid metabolism key genes via cultured cells and clinical data. A total of six key genes related to amino acid metabolism were identified, including ALDH18A1, CENPF, CSAD, CTH, CYP27B1, HBB.

Results

All six genes exhibited promising diagnostic capabilities (AUC:0.7 to 0.9). Immune cells such as Activated CD4+ T cells, Regulatory T cells, Immature B cells and MDSC,etc.infiltrated differentially in the high and low risk groups of CKD. There were correlations between immune cells abundance and the expression of key genes. All key genes correlated significantly with markers of kidney injury, such as eGFR and serum creatinine. The expression of ALDH18A1, CENPF were increased while CSAD, CTH and CYP27B1 were decreased in HK-2 cells cultured with indole sulfate.

Conclusions

Our study identified key genes involved in amino acid metabolism associated with immune cells infiltration and renal function in CKD, which may be potential biomarkers for the diagnosis and prognosis of CKD.

POU2F2 activates the Akt/mTOR signalling pathway and enhances B lymphocyte function during diabetic kidney disease by promoting PIK3CD transcription

BACKGROUND

Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD) is the predominant isoform of the catalytic subunit of PI3K in lymphocytes. Based on comprehensive bioinformatics, this study explores the functions of PIK3CD in diabetic kidney disease (DKD) progression in mice and B lymphocyte activity.

METHODS

Non-obese diabetic (NOD) mice that spontaneously develop DKD were applied as animal models. Lentiviral vector-mediated PIK3CD silencing was introduced in mice, followed by histological staining and biomarker assessments to evaluate DKD-associated symptoms. The activity of the Akt/mTOR signalling pathway was determined by western blot analysis. Following bioinformatics analyses, the interaction between POU class 2 homeobox 2 (POU2F2) and PIK3CD in B lymphocytes was determined by chromatin immunoprecipitation and luciferase reporter assays. Their functions in B cell function were identified by MTT, flow cytometry and IgG deposition assessment.

RESULTS

PIK3CD was found to be highly expressed in the kidney of DKD mice. Knockdown of PIK3CD inactivated the Akt/mTOR signalling, thus ameliorating tissue injury and fibrosis, enhancing the expression of AQP1 and decreasing urinary NGAL contents, UACR, BUN and β-NAG/creatinine ratio. These effects were negated by the Akt-specific activator SC79. POU2F2 was found to promote PIK3CD transcription by binding to its promoter, thus activating the Akt/mTOR pathway. Knockdown of POU2F2 suppressed B cell proliferation in vitro and decreased B cell population and IgG deposition in the mouse kidney. However, these trends were reversed upon additional PIK3CD overexpression.

CONCLUSION

This study demonstrates that POU2F2 mediates PIK3CD-dependent Akt/mTOR signalling activation, thus enhancing B lymphocyte function and promoting DKD progression.

Mechanism and therapeutic targets of circulating immune cells in diabetic retinopathy

Diabetic retinopathy (DR) continues to be the leading cause of preventable vision loss among working-aged adults, marked by immune dysregulation within the retinal microenvironment. Typically, the retina is considered as an immune-privileged organ, where circulating immune cells are restricted from entry under normal conditions. However, during the progression of DR, this immune privilege is compromised as circulating immune cells breach the barrier and infiltrate the retina. Increasing evidence suggests that vascular and neuronal degeneration in DR is largely driven by the infiltration of immune cells, particularly neutrophils, monocyte-derived macrophages, and lymphocytes. This review delves into the mechanisms and therapeutic targets associated with these immune cell populations in DR, offering a promising and innovative approach to managing the disease.

Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy

AIM

To identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation.

METHODS

Microarray and RNA-sequencing datasets (GSE47184, GSE96804, GSE104948, GSE104954, GSE142025 and GSE175759) were obtained from the Gene Expression Omnibus database. Differential expression analysis identified the differentially expressed genes (DEGs) between patients with DN and controls. Diverse machine learning algorithms, including least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest, were used to enhance gene selection accuracy and predictive power. We integrated summary-level data from genome-wide association studies on DN with expression quantitative trait loci data to identify genes with potential causal relationships to DN. The predictive performance of the biomarker gene was validated using receiver operating characteristic (ROC) curves. Gene set enrichment and correlation analyses were conducted to investigate potential mechanisms. Finally, the biomarker gene was validated using quantitative real-time polymerase chain reaction in clinical samples from patients with DN and controls.

RESULTS

Based on identified 314 DEGs, seven characteristic genes with high predictive performance were identified using three integrated machine learning algorithms. MR analysis revealed 219 genes with significant causal effects on DN, ultimately identifying one co-expressed gene, carbonic anhydrase II (CA2), as a key biomarker for DN. The ROC curves demonstrated the excellent predictive performance of CA2, with area under the curve values consistently above 0.878 across all datasets. Additionally, our analysis indicated a significant association between CA2 and infiltrating immune cells in DN, providing potential mechanistic insights. This biomarker was validated using clinical samples, confirming the reliability of our findings in clinical practice.

CONCLUSION

By integrating machine learning, MR and experimental validation, we successfully identified and validated CA2 as a promising biomarker for DN with excellent predictive performance. The biomarker may play a role in the pathogenesis and progression of DN via immune-related pathways. These findings provide important insights into the molecular mechanisms underlying DN and may inform the development of personalized treatment strategies for this disease.

Causal relationship between 731 immune cells and the risk of diabetic nephropathy: a two‑sample bidirectional Mendelian randomization study

OBJECTIVE

Previous observational studies have indicated associations between various immune cells and diabetic nephropathy (DN). However, the causality remains unclear. We aimed to further evaluate the causal association between immune cells and DN using bidirectional two-sample Mendelian randomization (MR) analysis.

METHOD

The DN data were retrieved from the IEU OpenGWAS Project database, while the data for 731 immune cells were sourced from GWAS summary statistics by Orru ̀ et al. The investigation into the causal relationship between immune cells and DN employed the inverse variance weighted (IVW), weighted median (WME), and MR-Egger methods. The stability and reliability of the findings underwent evaluation through Cochran's Q test, MR-Egger intercept's P-value, MR-PRESSO, and Leave-One-Out (LOO) method.

RESULT

The IVW estimates suggested a positive causal effect of CD25 on IgD-CD38dim B cell, CD25 on naive-mature B cell, CD127 on granulocyte, SSC-A on HLA DR + Natural Killer, HLA DR on plasmacytoid Dendritic Cell, and HLA DR on Dendritic Cell on DN. Conversely, the abundance of Myeloid Dendritic Cell, CD62L- Dendritic Cell %Dendritic Cell, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD14- CD16-, CX3CR1 on CD14- CD16-, and SSC-A on CD4+ T cell had negative causal effects on DN. However, after correcting the P value for significant causality results using the FDR method, it was concluded that only Myeloid Dendritic Cells had a causal relationship with DN (FDR-p = 0.041), while the other immune cells showed no significant association with DN, so their relationship was suggestive. The results were stable with no observed horizontal pleiotropy and heterogeneity. Reverse MR analysis indicated no causal relationship between DN and the increased risk of positively identified immune cells.

CONCLUSION

This study provides an initial insight into the genetic perspective of the causal relationship between immune cells and DN. It establishes a crucial theoretical foundation for future endeavors in precision medicine and individualized treatment.

The advance of single cell transcriptome to study kidney immune cells in diabetic kidney disease

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and a primary cause of end-stage renal disease (ESRD). Increasing studies suggest that immune cells are involved in regulating renal inflammation, which contributes to the progression of DKD. Compared with conventional methods, single-cell sequencing technology is more developed technique that has advantages in resolving cellular heterogeneity, parallel multi-omics studies, and discovering new cell types. ScRNA-seq helps researchers to analyze specifically gene expressions, signaling pathways, intercellular communication as well as their regulations in various immune cells of kidney biopsy and urine samples. It is still challenging to investigate the function of each cell type in the pathophysiology of kidney due to its complex and heterogeneous structure and function. Here, we discuss the application of single-cell transcriptomics in the field of DKD and highlight several recent studies that explore the important role of immune cells including macrophage, T cells, B cells etc. in DKD through scRNA-seq analyses. Through combing the researches of scRNA-seq on immune cells in DKD, this review provides novel perspectives on the pathogenesis and immune therapeutic strategy for DKD.

Integrated bioinformatics analysis and in vivo validation of potential immune-related genes linked to diabetic nephropathy

Background

Diabetic nephropathy (DN) is a common microvascular complication of diabetes mellitus and the main cause of chronic renal failure. This study explored the potential immunomodulation-related genes (IRGs) in DN using bioinformatics.

Methods

IRGs were identified using GeneCards, and differentially expressed genes were identified using the GSE99339, GSE96804, and GSE30122 datasets. We conducted enrichment analyses using Gene Ontology, gene set enrichment analysis (GSEA), and Kyoto Encyclopedia of Genes and Genomes to identify the associated signaling pathways. Prognostic models were constructed using Least Absolute Shrinkage and Selection Operator regression. The predictive power of IRGs was evaluated using receiver operating characteristic (ROC) curves. Furthermore, we utilized ssGSEA to determine the relative abundance of immune cell infiltration. The expression of five significant IRGs was further validated using immunohistochemistry (IHC) in individuals with DN and real-time PCR (RT-PCR) in animal experiments.

Results

In total, 17 immunomodulation-related differentially expressed genes were identified, which were enriched in immune-associated pathways and inflammation. GSEA unveiled substantial enrichments in metabolic irregularities and the structural composition of the extracellular matrix. ROC analysis results revealed that the diagnostic efficacy of IFNAR2 and CASP3 was comparatively high. Notably, we identified potential IRGs for DN, including CASP3, LGALS9, and SST, using IHC and RT-PCR.

Conclusions

CASP3, LGALS9, and SST are potential IRGs in patients with DN. Our findings may offer a theoretical basis for developing more focused and innovative immunotherapy approaches for patients with DN.

Exploring the mechanism of comorbidity in patients with T1DM and COVID-19: Integrating bioinformatics and Mendelian randomization methods

During the coronavirus disease 2019 (COVID-19) pandemic, the incidence of type 1 diabetes mellitus (T1DM) has increased. Additionally, evidence suggests that individuals with diabetes mellitus may have increased susceptibility to severe acute respiratory syndrome coronavirus 2 infection. However, the specific causal relationships and interaction mechanisms between T1DM and COVID-19 remain unclear. This study aims to investigate the causal relationship between T1DM and COVID-19, utilizing differential gene expression and Mendelian randomization analyses. Differentially expressed gene sets from datasets GSE156035 and GSE171110 were intersected to identify shared genes, analyzed for functional enrichment. Mendelian randomization models were employed to assess causal effects, revealing no direct causal link between T1DM and COVID-19 in the European population (P > .05). Notably, DNA replication and sister chromatid cohesion 1 (DSCC1) showed negative causal associations with both diseases (T1DM: OR = 0.943, 95% CI: 0.898-0.991, P = .020; COVID-19: OR = 0.919, 95% CI: 0.882-0.958, P < .001), suggesting a protective effect against their comorbidity. This genetic evidence highlights DSCC1 as a potential target for monitoring and managing the co-occurrence of T1DM and COVID-19.

Occurrence and role of Tph cells in various renal diseases

A new population of peripheral helper T (Tph) cells has been identified and contributed to various autoimmune diseases. Tph cells can secrete interleukin-21 (IL-21), interferon (IFN) and C-X-C motif chemokine ligand 13 (CXCL13) to moderate renal disease. Moreover, Tph cells can congregate in huge numbers and immerse within inflamed tissue. Compared to Tfh cells, Tph cells express high programmed cell death protein 1 (PD-1), major histocompatibility complex II (MHC-II), C-C chemokine receptor 2 (CCR2) and C-C chemokine receptor 5 (CCR5) but often lack expression of the chemokine receptor C-X-C chemokine receptor 5 (CXCR5). They display features distinct from other T cells, which are uniquely poised to promote responses and antibody production of B cells within pathologically inflamed non-lymphoid tissues and a key feature of Tph cells. In this review, we summarize recent findings on the role of Tph cells in chronic kidney disease, acute kidney injury, kidney transplantation and various renal diseases.

Type 1 diabetes: immune pathology and novel therapeutic approaches

Type 1 diabetes (T1D) is characterized by the progressive destruction of insulin-producing beta cells in the pancreas. Despite improvements in insulin monitoring techniques, there remains no cure for T1D. Individuals with T1D require lifelong insulin therapy and some develop life-threatening complications. T1D is a complex, multifactorial, autoimmune condition. Understanding why people get T1D and how it progresses has advanced our knowledge of the disease and led to the discovery of specific targets that can be therapeutically manipulated to halt or reverse the course of T1D. Scientists investigating the potential of immunotherapy treatment for the treatment have recently had some encouraging results. Teplizumab, an anti-CD3 monoclonal antibody that has been approved by the FDA, delays the onset of clinical T1D in patients ≥ 8 years of age with preclinical T1D and improves beta cell function. Therapies targeting beta cell health, vitality, and function are now thought to be an essential component of successful combination therapy for T1D. The idea that the beta cells themselves may influence their own destruction during the development of T1D is a notion that has recently been gaining acceptance in the field. Researchers have recently made remarkable strides in beta cell replacement therapy and beta cell regeneration techniques. This review offers a detailed exploration of the pathophysiological mechanisms of T1D. It discusses the intricate interplay of factors leading to T1D development and the innovative approaches being explored to discover new treatments and a cure for the millions of people living with T1D worldwide.

Integrative Analysis by Mendelian Randomization and Large-Scale Single-Cell Transcriptomics Reveals Causal Links between B Cell Subtypes and Diabetic Kidney Disease

Introduction

The increasing incidence of diabetic kidney disease (DKD) and the challenges in its management highlight the necessity for a deeper understanding of its pathogenesis. While recent studies have underscored the substantial impact of circulating immunity on the development of diabetic microvascular complications such as retinopathy and neuropathy, research on circulating immunity in DKD remains limited.

Methods

This study utilized Mendelian randomization analysis to explore the potential independent causal relationships between circulating immune cells and DKD pathogenesis. Additionally, a combination of single-cell disease relevance score (scDRS) and immune cell infiltration analysis was employed to map the circulating immunity landscape in DKD patients.

Results

Ten immune traits, including 5 of B cells, 2 of T cells, 2 of granulocytes, and one of monocytes, were defined to be associated with the pathogenesis of DKD. Notably, IgD - CD27 - B cell Absolute Count (IVW: OR, 1.102 [1.023-1.189], p = 0.011) and IgD - CD24 - B cell Absolute Count (IVW: OR, 1.106 [1.030-1.188], p = 0.005) were associated with promoting DKD pathogenesis, while CD24 + CD27 + B cell %B cell (IVW: OR, 0.943 [0.898-0.989], p = 0.016) demonstrated a protective effect against DKD onset. The presence of B cell-activating factor receptor (BAFF-R) on CD20 - CD38 - B cell (IVW: OR, 0.946 [0.904-0.989], p = 0.015) and BAFF-R on IgD - CD38 + B cell (IVW: OR, 0.902 [0.834-0.975], p = 0.009) also indicated a potential role in preventing DKD. scDRS analysis revealed that two main subsets of B cells, naïve B and memory B cells, had a higher proportion of DKD-related cells or a higher scDRS score of DKD phenotype, indicating their strong association with DKD. Furthermore, immune infiltrate deconvolution analysis showed a notable decrease in the circulating memory B cells and class-switched memory B cells in DKD patients compared to those of DM patients without DKD.

Conclusion

Our study revealed the causal relations between circulating immunity and DKD susceptibility, particularly highlighted the potential roles of B cell subtypes in DKD development. Further studies addressing the related mechanisms would broaden the current understanding of DKD pathogenesis.

Relationship between immune cells and diabetic nephropathy: a Mendelian randomization study

OBJECTIVE

Although previous studies have suggested potential correlations between immunocytes and diabetic nephropathy (DN), the causal correlations between them remain unclarified. In this study, we employed Mendelian randomization (MR) to analyze the potential causative correlations between immune 731 cells and DN.

METHODS

We used the Genome-Wide Association Studies (GWAS) database to aggregate signatures of immune cells and DN from European and East Asian populations. Single-nucleotide polymorphisms (SNPs) were used as instrumental variables. MR analysis was conducted using Mendelian randomization-Egger (MR-Egger) regression and the random-effects inverse-variance weighted (IVW) method.

RESULTS

A total of 3,571 SNPs were included as instrumental variables. The MR-Egger regression model indicated no genetic pleiotropy (P = 0.6284). The results of the IVW method indicated a statistically significant causal relationship between immune cell HLA-DR on CD14-CD16- (P = 0.029), CD45RA-CD28-CD8 + T cell% T cells (P = 0.0278), CD11c on myeloid dendritic cells (P = 0.0352), HLA-DR on CD14+ monocytes (P < 0.001), CD27 on CD24 + CD27 + B cells (P = 0.0334), CD27 on IgD + CD24 + B cells (P = 0.0137), CD4 on CD39 + CD4 + T cells (P = 0.0347), CD28 on CD39 + CD4 + T cells (P = 0.0414), CD39 on CD39 + CD4 + T cells (P = 0.0426), and DN. Additionally, there was no heterogeneity in SNPs related HLA-DR on CD14-CD16-cells and DN(I2 = 32%, Cochran's Q = 2.9476, P = 0.2291). Moreover, leave-one-out analysis showed a causal correlation between HLA-DR on CD14-CD16- cells and DN.

CONCLUSION

Higher expression of immune cell HLA-DR on CD14-CD16- cells may indicate a lower risk of DN.

Role of hypoxia-inducible factor 1 in type 1 diabetes

Type 1 diabetes (T1D) is a common autoimmune disease in which dysregulated glucose metabolism is a key feature. T1D is both poorly understood and in need of improved therapeutics. Hypoxia is frequently encountered in multiple tissues in T1D patients including the pancreas and sites of diabetic complications. Hypoxia-inducible factor (HIF)-1, a ubiquitous master regulator of the adaptive response to hypoxia, promotes glucose metabolism through transcriptional and non-transcriptional mechanisms and alters disease progression in multiple preclinical T1D models. However, how HIF-1 activation in β-cells of the pancreas and immune cells (two key cell types in T1D) ultimately affects disease progression remains controversial. We discuss recent advances in our understanding of the role of hypoxia/HIF-1-induced glycolysis in T1D and explore the possible use of drugs targeting this pathway as potential new therapeutics.

Predicting autoimmune diseases: A comprehensive review of classic biomarkers and advances in artificial intelligence

Autoimmune diseases comprise a spectrum of disorders characterized by the dysregulation of immune tolerance, resulting in tissue or organ damage and inflammation. Their prevalence has been on the rise, significantly impacting patients' quality of life and escalating healthcare costs. Consequently, the prediction of autoimmune diseases has recently garnered substantial interest among researchers. Despite their wide heterogeneity, many autoimmune diseases exhibit a consistent pattern of paraclinical findings that hold predictive value. From serum biomarkers to various machine learning approaches, the array of available methods has been continuously expanding. The emergence of artificial intelligence (AI) presents an exciting new range of possibilities, with notable advancements already underway. The ultimate objective should revolve around disease prevention across all levels. This review provides a comprehensive summary of the most recent data pertaining to the prediction of diverse autoimmune diseases and encompasses both traditional biomarkers and the latest innovations in AI.

Evaluation of teplizumab's efficacy and safety in treatment of type 1 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

Islets of Langerhans beta cells diminish in autoimmune type 1 diabetes mellitus (T1DM). Teplizumab, a humanized anti-CD3 monoclonal antibody, may help T1DM. Its long-term implications on clinical T1DM development, safety, and efficacy are unknown.

AIM

To assess the effectiveness and safety of teplizumab as a therapeutic intervention for individuals with T1DM.

METHODS

A systematic search was conducted using four electronic databases (PubMed, Embase, Scopus, and Cochrane Library) to select publications published in peer-reviewed journals written in English. The odds ratio (OR) and risk ratio (RR) were calculated, along with their 95%CI. We assessed heterogeneity using Cochrane Q and I 2 statistics and the appropriate P value.

RESULTS

There were 8 randomized controlled trials (RCTs) in the current meta-analysis with a total of 1908 T1DM patients from diverse age cohorts, with 1361 patients receiving Teplizumab and 547 patients receiving a placebo. Teplizumab was found to have a substantial link with a decrease in insulin consumption, with an OR of 4.13 (95%CI: 1.72 to 9.90). Teplizumab is associated with an improved C-peptide response (OR 2.49; 95%CI: 1.62 to 3.81) and a significant change in Glycated haemoglobin A1c (HbA1c) levels in people with type 1 diabetes [OR 1.75 (95%CI: 1.03 to 2.98)], and it has a RR of 0.71 (95%CI: 0.53 to 0.95).

CONCLUSION

In type 1 diabetics, teplizumab decreased insulin consumption, improved C-peptide response, and significantly changed HbA1c levels with negligible side effects. Teplizumab appears to improve glycaemic control and diabetes management with good safety and efficacy.

Pathological mechanism of immune disorders in diabetic kidney disease and intervention strategies

Diabetic kidney disease is one of the most severe chronic microvascular complications of diabetes and a primary cause of end-stage renal disease. Clinical studies have shown that renal inflammation is a key factor determining kidney damage during diabetes. With the development of immunological technology, many studies have shown that diabetic nephropathy is an immune complex disease, and that most patients have immune dysfunction. However, the immune response associated with diabetic nephropathy and autoimmune kidney disease, or caused by ischemia or infection with acute renal injury, is different, and has a com-plicated pathological mechanism. In this review, we discuss the pathogenesis of diabetic nephropathy in immune disorders and the intervention mechanism, to provide guidance and advice for early intervention and treatment of diabetic nephropathy.

The Role of Immune Cells in DKD: Mechanisms and Targeted Therapies

Diabetic kidney disease (DKD), is a common microvascular complication and a major cause of death in patients with diabetes. Disorders of immune cells and immune cytokines can accelerate DKD development of in a number of ways. As the kidney is composed of complex and highly differentiated cells, the interactions among different cell types and immune cells play important regulatory roles in disease development. Here, we summarize the latest research into the molecular mechanisms underlying the interactions among various immune and renal cells in DKD. In addition, we discuss the most recent studies related to single cell technology and bioinformatics analysis in the field of DKD. The aims of our review were to explore immune cells as potential therapeutic targets in DKD and provide some guidance for future clinical treatments.

An insight into the mechanistic role of (-)-Ampelopsin F from Vatica chinensis L. in inducing insulin secretion in pancreatic beta cells

Resveratrol oligomers, ranging from dimers to octamers, are formed through regioselective synthesis involving the phenoxy radical coupling of resveratrol building blocks, exhibiting remarkable therapeutic potential, including antidiabetic properties. In this study, we elucidate the mechanistic insights into the insulin secretion potential of a resveratrol dimer, (-)-Ampelopsin F (AmF), isolated from the acetone extract of Vatica chinensis L. stem bark in Pancreatic Beta-TC-6 cell lines. The AmF (50 µM) treated cells exhibited a 3.5-fold increase in insulin secretion potential as compared to unstimulated cells, which was achieved through the enhancement of mitochondrial membrane hyperpolarization, elevation of intracellular calcium concentration, and upregulation of GLUT2 and glucokinase expression in pancreatic Beta-TC-6 cell lines. Furthermore, AmF effectively inhibited the activity of DPP4, showcasing a 2.5-fold decrease compared to the control and a significant 6.5-fold reduction compared to the positive control. These findings emphasize AmF as a potential lead for the management of diabetes mellitus and point to its possible application in the next therapeutic initiatives.

An antigen-specific immunotherapeutic, AKS-107, deletes insulin-specific B cells and prevents murine autoimmune diabetes

Introduction

The antigen-presenting cell function of insulin-reactive B cells promotes type 1 diabetes (T1D) in non-obese diabetic (NOD) mice by stimulating pathogenic T cells leading to destruction of insulin-producing β-cells of pancreatic islets.

Methods/Results

To target insulin-reactive B cells, AKS-107, a human IgG1 Fc molecule fused with human insulin A and B chains, was engineered to retain conformational insulin epitopes that bound mouse and human B cell receptors but prevented binding to the insulin metabolic receptor. AKS-107 Fc-mediated deletion of insulin-reactive B cells was demonstrated via ex vivo and in vivo experiments with insulin-reactive B cell receptor transgenic mouse strains, VH125Tg/NOD and Tg125(H+L)/NOD. As an additional immune tolerance feature, the Y16A mutation of the insulin B(9-23) dominant T cell epitope was engineered into AKS-107 to suppress activation of insulin-specific T cells. In mice and non-human primates, AKS-107 was well-tolerated, non-immunogenic, did not cause hypoglycemia even at high doses, and showed an expectedly protracted pharmacokinetic profile. AKS-107 reproducibly prevented spontaneous diabetes from developing in NOD and VH125Tg/NOD mice that persisted for months after cessation of treatment, demonstrating durable immune tolerance.

Discussion

These preclinical outcomes position AKS-107 for clinical development in T1D prevention settings.

New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era

Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.

Suppression of B-Cell Activation by Human Cord Blood-Derived Stem Cells (CB-SCs) through the Galectin-9-Dependent Mechanism

We developed the Stem Cell Educator therapy among multiple clinical trials based on the immune modulations of multipotent cord blood-derived stem cells (CB-SCs) on different compartments of immune cells, such as T cells and monocytes/macrophages, in type 1 diabetes and other autoimmune diseases. However, the effects of CB-SCs on the B cells remained unclear. To better understand the molecular mechanisms underlying the immune education of CB-SCs, we explored the modulations of CB-SCs on human B cells. CB-SCs were isolated from human cord blood units and confirmed by flow cytometry with different markers for their purity. B cells were purified by using anti-CD19 immunomagnetic beads from human peripheral blood mononuclear cells (PBMCs). Next, the activated B cells were treated in the presence or absence of coculture with CB-SCs for 7 days before undergoing flow cytometry analysis of phenotypic changes with different markers. Reverse transcription-polymerase chain reaction (RT-PCR) was utilized to evaluate the levels of galectin expressions on CB-SCs with or without treatment of activated B cells in order to find the key galectin that was contributing to the B-cell modulation. Flow cytometry demonstrated that the proliferation of activated B cells was markedly suppressed in the presence of CB-SCs, leading to the downregulation of immunoglobulin production from the activated B cells. Phenotypic analysis revealed that treatment with CB-SCs increased the percentage of IgD+CD27- naïve B cells, but decreased the percentage of IgD-CD27+ switched B cells. The transwell assay showed that the immune suppression of CB-SCs on B cells was dependent on the galectin-9 molecule, as confirmed by the blocking experiment with the anti-galectin-9 monoclonal antibody. Mechanistic studies demonstrated that both calcium levels of cytoplasm and mitochondria were downregulated after the treatment with CB-SCs, causing the decline in mitochondrial membrane potential in the activated B cells. Western blot exhibited that the levels of phosphorylated Akt and Erk1/2 signaling proteins in the activated B cells were also markedly reduced in the presence of CB-SCs. CB-SCs displayed multiple immune modulations on B cells through the galectin-9-mediated mechanism and calcium flux/Akt/Erk1/2 signaling pathways. The data advance our current understanding of the molecular mechanisms underlying the Stem Cell Educator therapy to treat autoimmune diseases in clinics.

Therapeutic tactics for targeting B lymphocytes in autoimmunity and cancer

B lymphocytes have become a very popular therapeutic target in a number of autoimmune indications due to their newly appreciated roles, and approachability, in these diseases. Many of the therapies now applied in autoimmunity were initially developed to deplete malignant B cells. These strategies have also been found to benefit patients suffering from such autoimmune diseases as multiple sclerosis, type I diabetes, systemic lupus erythematosus, and rheumatoid arthritis, to name a few. These observations have supported the expansion of research addressing the mechanistic contributions of B cells in these diseases, as well as blossoming of therapeutics that target them. This review seeks to summarize cutting-edge modalities for targeting B cells, including monoclonal antibodies, bispecific antibodies, antibody-drug conjugates, chimeric antigen receptor-T cells, and small molecule inhibitors. Efforts to refine B-cell targeted therapy to eliminate only pathogenic autoreactive cells will be addressed as well as the potential for future B-cell-based cellular therapeutics. Finally, we also address approaches that seek to silence B-cell function without depletion.

Association between type 1 diabetes mellitus and ankylosing spondylitis: a two-sample Mendelian randomization study

Objective

The development of ankylosing spondylitis (AS) is closely related to autoimmune system dysfunction. Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is a risk factor for many diseases. This study aimed to investigate the causal relationship between T1DM mellitus and AS genetically.

Methods

A genome-wide association study (GWAS) of causal relationships between exposure (T1DM) and outcome (AS) was performed using summary data from the GWAS database. We conducted a two-sample Mendelian randomization (MR) study of these two diseases. Inverse variance weighting (IVW) was used as the primary analysis method, with MR Egger, weighted median, and weighted mode used as supplementary methods. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-Pleiotropy RESidual Sum and outlier methods, leave-one-out analysis, and funnel plots.

Results

A total of 11 single nucleotide polymorphisms (SNPs)were identified for instrumental variables(IVs) for MR analysis.IVW found that T1DM was causally associated with AS ((IVW: OR = 1.0006 (95% CI 1.0001, 1.0011), p = 0.0057; MR-Egger: OR = 1.0003 (95% CI 0.9995, 1.0012), p = 0.4147; weighted median: OR = 1.0006 (95% CI 1.0003, 1.0008), p = 0.0001; weighted mode: OR = 1.0007 (95% CI 1.0005, 1.0009), p = 0.0001). No horizontal pleiotropy was found for the MR-Egger intercept, and leave -one-out analysis found that the results remained stable after the removal of individual SNPs.

Conclusion

The results of the two-sample MR analysis supported a causal relationship between T1DM and AS risk.

Update on the ZNT8 epitope and its role in the pathogenesis of type 1 diabetes

Type 1 diabetes (T1D) is an organ-specific chronic autoimmune disease mediated by autoreactive T cells. ZnT8 is a pancreatic islet-specific zinc transporter that is mainly located in β cells. It not only participates in the synthesis, storage and secretion of insulin but also maintains the structural integrity of insulin. ZnT8 is the main autoantigen recognized by autoreactive CD8+ T cells in children and adults with T1D. This article summarizes the latest research results on the T lymphocyte epitope and B lymphocyte epitope of ZnT8 in the current literature. The structure and expression of ZnT8, the role of ZnT8 in insulin synthesis and its role in autoimmunity are reviewed. ZnT8 is the primary autoantigen of T1D and is specifically expressed in pancreatic islets. Thus, it is one of biomarkers for the diagnosis of T1D. It has broad prospects for further research on immunomodulators for the treatment of T1D.

Common mechanisms underlying diabetic vascular complications: focus on the interaction of metabolic disorders, immuno-inflammation, and endothelial dysfunction

Diabetic vascular complications (DVCs), including macro- and micro- angiopathy, account for a high percentage of mortality in patients with diabetes mellitus (DM). Endothelial dysfunction is the initial and role step for the pathogenesis of DVCs. Hyperglycemia and lipid metabolism disorders contribute to endothelial dysfunction via direct injury of metabolism products, crosstalk between immunity and inflammation, as well as related interaction network. Although physiological and phenotypic differences support their specified changes in different targeted organs, there are still several common mechanisms underlying DVCs. Also, inhibitors of these common mechanisms may decrease the incidence of DVCs effectively. Thus, this review may provide new insights into the possible measures for the secondary prevention of DM. And we discussed the current limitations of those present preventive measures in DVCs research. Video Abstract.

Elevated glucose metabolism driving pro-inflammatory response in B cells contributes to the progression of type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease characterized by the immune system's failure to maintain self-tolerance, resulting in the autoimmune destruction of pancreatic beta cells. Although T1D has conventionally been viewed as a T-cell-dominant disease, recent research has emphasized the contribution of B cells in the onset of the disease. However, the mechanism underlying aberrant B cell responses remains unknown. B cell metabolism is a crucial prerequisite for B cell function and the development of adaptive immune responses. Here, we investigated the metabolic features of B cells, first in a cross-sectional cohort and subsequently in non-obese diabetic (NOD) mice, and revealed that there is an increased frequency of high-glucose-avidity (2-NBDGhigh) B cell population that may contribute to T1D progression. Further characterization of the metabolic, transcriptional and functional phenotype of B cells in NOD mice found that elevated glucose avidity is associated with a greater capacity for co-stimulation, proliferation and inflammatory cytokine production. Mechanistically, elevated Myc signaling orchestrated the glucose metabolism and the pro-inflammatory response of B cells in T1D. In vitro experiments demonstrated that pharmacological inhibition of glucose metabolism using metformin and 2-DG reduced pro-inflammatory cytokine production and B cell proliferation. Moreover, the combination of these inhibitors successfully delayed insulitis development, onset of diabetes, and improved high blood glucose levels in streptozotocin (STZ)-induced diabetic mice model. Taken together, our work has uncovered these high-glucose-avidity B cells as novel adjuvant diagnostic and therapeutic targets for T1D.

Immunomodulation by subcutaneously injected methacrylic acid-based hydrogels and tolerogenic dendritic cells in a mouse model of autoimmune diabetes

Type 1 diabetes is an autoimmune disease associated with the destruction of insulin-producing β cells. Immunotherapies are being developed to mitigate autoimmune diabetes. One promising option is the delivery of tolerogenic dendritic cells (DCs) primed with specific β-cell-associated autoantigens. These DCs can combat autoreactive cells and promote expansion of β-cell-specific regulatory immune cells, including Tregs. Tolerogenic DCs are typically injected systemically (or near target lymph nodes) in suspension, precluding control over the microenvironment surrounding tolerogenic DC interactions with the host. In this study we show that degradable, synthetic methacrylic acid (MAA)-based hydrogels are an inherently immunomodulating delivery vehicle that enhances tolerogenic DC therapy in the context of autoimmune diabetes. MAA hydrogels were found to affect the local recruitment and activation state of macrophages, DCs, T cells and other cells. Delivering tolerogenic DCs in the MAA hydrogel improved the local host response (e.g., fewer cytotoxic T cells) and enhanced peripheral Treg expansion. Non obese diabetic (NOD) mice treated with tolerogenic DCs subcutaneously injected in MAA hydrogels showed a delay in onset of autoimmune diabetes compared to control vehicles. Our findings further demonstrate the usefulness of MAA-based hydrogels as platforms for regenerative medicine in the context of type 1 diabetes.

Mitochondrial quality control and its emerging role in the pathogenesis of diabetic kidney disease

Most eukaryotic cells have mitochondrial networks that can change in shape, distribution, and size depending on cellular metabolic demands and environments. Mitochondrial quality control is critical for various mitochondrial functions including energy production, redox homeostasis, intracellular calcium handling, cell differentiation, proliferation, and cell death. Quality control mechanisms within mitochondria consist of antioxidant defenses, protein quality control, DNA damage repair systems, mitochondrial fusion and fission, mitophagy, and mitochondrial biogenesis. Defects in mitochondrial quality control and disruption of mitochondrial homeostasis are common characteristics of various kidney cell types under hyperglycemic conditions. Such defects contribute to diabetes-induced pathologies in renal tubular cells, podocytes, endothelial cells, and immune cells. In this review, we focus on the roles of mitochondrial quality control in diabetic kidney disease pathogenesis and discuss current research evidence and future directions.

B cell metabolism in autoimmune diseases: signaling pathways and interventions

Autoimmune diseases are heterogeneous disorders believed to stem from the immune system's inability to distinguish between auto- and foreign- antigens. B lymphocytes serve a crucial role in humoral immunity as they generate antibodies and present antigens. Dysregulation of B cell function induce the onset of autoimmune disorders by generating autoantibodies and pro-inflammatory cytokines, resulting in an imbalance in immune regulation. New research in immunometabolism shows that cellular metabolism plays an essential role in controlling B lymphocytes immune reactions by providing the energy and substrates for B lymphocytes activation, differentiation, and function. However, dysregulated immunometabolism lead to autoimmune diseases by disrupting self-tolerance mechanisms. This review summarizes the latest research on metabolic reprogramming of B lymphocytes in autoimmune diseases, identifying crucial pathways and regulatory factors. Moreover, we consider the potential of metabolic interventions as a promising therapeutic strategy. Understanding the metabolic mechanisms of B cells brings us closer to developing novel therapies for autoimmune disorders.

Identification of an anergic BND cell-derived activated B cell population (BND2) in young-onset type 1 diabetes patients

Recent evidence suggests a role for B cells in the pathogenesis of young-onset type 1 diabetes (T1D), wherein rapid progression occurs. However, little is known regarding the specificity, phenotype, and function of B cells in young-onset T1D. We performed a cross-sectional analysis comparing insulin-reactive to tetanus-reactive B cells in the blood of T1D and controls using mass cytometry. Unsupervised clustering revealed the existence of a highly activated B cell subset we term BND2 that falls within the previously defined anergic BND subset. We found a specific increase in the frequency of insulin-reactive BND2 cells in the blood of young-onset T1D donors, which was further enriched in the pancreatic lymph nodes of T1D donors. The frequency of insulin-binding BND2 cells correlated with anti-insulin autoantibody levels. We demonstrate BND2 cells are pre-plasma cells and can likely act as APCs to T cells. These findings identify an antigen-specific B cell subset that may play a role in the rapid progression of young-onset T1D.

Measuring anti-islet autoimmunity in mouse and human by profiling peripheral blood antigen-specific CD4 T cells

The endocrine pancreas is one of the most inaccessible organs of the human body. Its autoimmune attack leads to type 1 diabetes (T1D) in a genetically susceptible population and a lifelong need for exogenous insulin replacement. Monitoring disease progression by sampling peripheral blood would provide key insights into T1D immune-mediated mechanisms and potentially change preclinical diagnosis and the evaluation of therapeutic interventions. This effort has been limited to the measurement of circulating anti-islet antibodies, which despite a recognized diagnostic value, remain poorly predictive at the individual level for a fundamentally CD4 T cell-dependent disease. Here, peptide-major histocompatibility complex tetramers were used to profile blood anti-insulin CD4 T cells in mice and humans. While percentages of these were not directly informative, the state of activation of anti-insulin T cells measured by RNA and protein profiling was able to distinguish the absence of autoimmunity versus disease progression. Activated anti-insulin CD4 T cell were detected not only at time of diagnosis but also in patients with established disease and in some at-risk individuals. These results support the concept that antigen-specific CD4 T cells might be used to monitor autoimmunity in real time. This advance can inform our approach to T1D diagnosis and therapeutic interventions in the preclinical phase of anti-islet autoimmunity.

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases

Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.

Epigenetic modification in diabetic kidney disease

Diabetic kidney disease (DKD) is a common microangiopathy in diabetic patients and the main cause of death in diabetic patients. The main manifestations of DKD are proteinuria and decreased renal filtration capacity. The glomerular filtration rate and urinary albumin level are two of the most important hallmarks of the progression of DKD. The classical treatment of DKD is controlling blood glucose and blood pressure. However, the commonly used clinical therapeutic strategies and the existing biomarkers only partially slow the progression of DKD and roughly predict disease progression. Therefore, novel therapeutic methods, targets and biomarkers are urgently needed to meet clinical requirements. In recent years, increasing attention has been given to the role of epigenetic modification in the pathogenesis of DKD. Epigenetic variation mainly includes DNA methylation, histone modification and changes in the noncoding RNA expression profile, which are deeply involved in DKD-related inflammation, oxidative stress, hemodynamics, and the activation of abnormal signaling pathways. Since DKD is reversible at certain disease stages, it is valuable to identify abnormal epigenetic modifications as early diagnosis and treatment targets to prevent the progression of end-stage renal disease (ESRD). Because the current understanding of the epigenetic mechanism of DKD is not comprehensive, the purpose of this review is to summarize the role of epigenetic modification in the occurrence and development of DKD and evaluate the value of epigenetic therapies in DKD.

Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy

Background

Aging and immune infiltration have essential role in the physiopathological mechanisms of diabetic nephropathy (DN), but their relationship has not been systematically elucidated. We identified aging-related characteristic genes in DN and explored their immune landscape.

Methods

Four datasets from the Gene Expression Omnibus (GEO) database were screened for exploration and validation. Functional and pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Characteristic genes were obtained using a combination of Random Forest (RF) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm. We evaluated and validated the diagnostic performance of the characteristic genes using receiver operating characteristic (ROC) curve, and the expression pattern of the characteristic genes was evaluated and validated. Single-Sample Gene Set Enrichment Analysis (ssGSEA) was adopted to assess immune cell infiltration in samples. Based on the TarBase database and the JASPAR repository, potential microRNAs and transcription factors were predicted to further elucidate the molecular regulatory mechanisms of the characteristic genes.

Results

A total of 14 differentially expressed genes related to aging were obtained, of which 10 were up-regulated and 4 were down-regulated. Models were constructed by the RF and SVM-RFE algorithms, contracted to three signature genes: EGF-containing fibulin-like extracellular matrix (EFEMP1), Growth hormone receptor (GHR), and Vascular endothelial growth factor A (VEGFA). The three genes showed good efficacy in three tested cohorts and consistent expression patterns in the glomerular test cohorts. Most immune cells were more infiltrated in the DN samples compared to the controls, and there was a negative correlation between the characteristic genes and most immune cell infiltration. 24 microRNAs were involved in the transcriptional regulation of multiple genes simultaneously, and Endothelial transcription factor GATA-2 (GATA2) had a potential regulatory effect on both GHR and VEGFA.

Conclusion

We identified a novel aging-related signature allowing assessment of diagnosis for DN patients, and further can be used to predict immune infiltration sensitivity.

The Interplay between Immune and Metabolic Pathways in Kidney Disease

Kidney disease is a significant health problem worldwide, affecting an estimated 10% of the global population. Kidney disease encompasses a diverse group of disorders that vary in their underlying pathophysiology, clinical presentation, and outcomes. These disorders include acute kidney injury (AKI), chronic kidney disease (CKD), glomerulonephritis, nephrotic syndrome, polycystic kidney disease, diabetic kidney disease, and many others. Despite their distinct etiologies, these disorders share a common feature of immune system dysregulation and metabolic disturbances. The immune system and metabolic pathways are intimately connected and interact to modulate the pathogenesis of kidney diseases. The dysregulation of immune responses in kidney diseases includes a complex interplay between various immune cell types, including resident and infiltrating immune cells, cytokines, chemokines, and complement factors. These immune factors can trigger and perpetuate kidney inflammation, causing renal tissue injury and progressive fibrosis. In addition, metabolic pathways play critical roles in the pathogenesis of kidney diseases, including glucose and lipid metabolism, oxidative stress, mitochondrial dysfunction, and altered nutrient sensing. Dysregulation of these metabolic pathways contributes to the progression of kidney disease by inducing renal tubular injury, apoptosis, and fibrosis. Recent studies have provided insights into the intricate interplay between immune and metabolic pathways in kidney diseases, revealing novel therapeutic targets for the prevention and treatment of kidney diseases. Potential therapeutic strategies include modulating immune responses through targeting key immune factors or inhibiting pro-inflammatory signaling pathways, improving mitochondrial function, and targeting nutrient-sensing pathways, such as mTOR, AMPK, and SIRT1. This review highlights the importance of the interplay between immune and metabolic pathways in kidney diseases and the potential therapeutic implications of targeting these pathways.

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Combined with Multiple Machine Learning Identified a Novel Immune Signature in Diabetic Nephropathy

Background

Increasing evidence suggests that immune modulation contributes to the pathogenesis and progression of diabetic nephropathy (DN). However, the role of immune modulation in DN has not been elucidated. The purpose of this study was to search for potential immune-related therapeutic targets and molecular mechanisms of DN.

Methods

Gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. A total of 1793 immune-related genes were acquired from the Immunology Database and Analysis Portal (ImmPort). Weighted gene co-expression network analysis (WGCNA) was performed for GSE142025, and the red and turquoise co-expression modules were found to be key for DN progression. We utilized four machine learning algorithms, namely, random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), and k-nearest neighbor (KNN), to evaluate the diagnostic value of hub genes. Immune infiltration patterns were analyzed using the CIBERSORT algorithm, and the correlation between immune cell type abundance and hub gene expression was also investigated.

Results

A total of 77 immune-related genes of advanced DN were selected for subsequent analyzes. Functional enrichment analysis showed that the regulation of cytokine-cytokine receptor interactions and immune cell function play a corresponding role in the progression of DN. The final 10 hub genes were identified through multiple datasets. In addition, the expression levels of the identified hub genes were corroborated through a rat model. The RF model exhibited the highest AUC. CIBERSORT analysis and single-cell sequencing analysis revealed changes in immune infiltration patterns between control subjects and DN patients. Several potential drugs to reverse the altered hub genes were identified through the Drug-Gene Interaction database (DGIdb).

Conclusion

This pioneering work provided a novel immunological perspective on the progression of DN, identifying key immune-related genes and potential drug targets, thus stimulating future mechanistic research and therapeutic target identification for DN.

Characteristic gene prognostic model of type 1 diabetes mellitus via machine learning strategy

The present study was designed to detect possible biomarkers associated with Type 1 diabetes mellitus (T1DM) incidence in an effort to develop novel treatments for this condition. Three mRNA expression datasets of peripheral blood mononuclear cells (PBMCs) were obtained from the GEO database. Differentially expressed genes (DEGs) between T1DM patients and healthy controls were identified by Limma package in R, and using the DEGs to conduct GO and DO pathway enrichment. The LASSO-SVM were used to screen the hub genes. We performed immune correlation analysis of hub genes and established a T1DM prognosis model. CIBERSORT algorithm was used to identify the different immune cells in distribution between T1DM and normal samples. The correlation of the hub genes and immune cells was analyzed by Spearman. ROC curves were used to assess the diagnostic value of genes in T1DM. A total of 60 immune related DEGs were obtained from the T1DM and normal samples. Then, DEGs were further screened to obtain 3 hub genes, ANP32A-IT1, ESCO2 and NBPF1. CIBERSORT analysis revealed the percentage of immune cells in each sample, indicating that there was significant difference in monocytes, T cells CD8+, gamma delta T cells, naive CD4+ T cells and activated memory CD4+ T cells between T1DM and normal samples. The area under curve (AUC) of ESCO2, ANP32A-IT1 and NBPF1 were all greater than 0.8, indicating that these three genes have high diagnostic value for T1DM. Together, the findings of these bioinformatics analyses thus identified key hub genes associated with T1DM development.

Maternal provisions in type 1 diabetes: Evidence for both protective & pathogenic potential

Maternal influences on the immune health and development of an infant begin in utero and continue well into the postnatal period, shaping and educating the child's maturing immune system. Two maternal provisions include early microbial colonizers to initiate microbiota establishment and the transfer of antibodies from mother to baby. Maternal antibodies are a result of a lifetime of antigenic experience, reflecting the infection history, health and environmental exposure of the mother. These same factors are strong influencers of the microbiota, inexorably linking the two. Together, these provisions help to educate the developing neonatal immune system and shape lymphocyte repertoires, establishing a role for external environmental influences even before birth. In the context of autoimmunity, the transfer of maternal autoantibodies has the potential to be harmful for the child, sometimes targeting tissues and cells with devastating consequences. Curiously, this does not seem to apply to maternal autoantibody transfer in type 1 diabetes (T1D). Moreover, despite the rising prevalence of the disease, little research has been conducted on the effects of maternal dysbiosis or antibody transfer from an affected mother to her offspring and thus their relevance to disease development in the offspring remains unclear. This review seeks to provide a thorough evaluation of the role of maternal microorganisms and antibodies within the context of T1D, exploring both their pathogenic and protective potential. Although a definitive understanding of their significance in infant T1D development remains elusive at present, we endeavor to present what has been learned with the goal of spurring further interest in this important and intriguing question.

Modulatory role of prolactin in type 1 diabetes

OBJECTIVES

Patients with type 1 diabetes mellitus have been reported to have elevated prolactin levels and a possible relationship between prolactin levels and the development of the disease has been proposed. However, some studies show that prolactin mediates beneficial functions in beta cells. Therefore, we review information on the roles of prolactin in type 1 diabetes mellitus.

CONTENT

Here we summarize the functions of prolactin in the immune system and in pancreatic beta cells, in addition, we describe studies related to PRL levels, its regulation and alterations of secretion in patients with type 1 diabetes mellitus.

SUMMARY

Studies in murine models have shown that prolactin protects beta cells from apoptosis, stimulates their proliferation and promotes pancreatic islet revascularization. In addition, some studies in patients with type 1 diabetes mellitus have shown that elevated prolactin levels correlate with better disease control.

OUTLOOK

Prolactin treatment appears to be a promising strategy to improve beta-cell vascularization and proliferation in transplantation and immunotherapies.

Integrated analysis of RNA methylation regulators crosstalk and immune infiltration for predictive and personalized therapy of diabetic nephropathy

BACKGROUND

RNA methylation is a widely known post-transcriptional regulation which exists in many cancer and immune system diseases. However, the potential role and crosstalk of five types RNA methylation regulators in diabetic nephropathy (DN) and immune microenvironment remain unclear.

METHODS

The mRNA expression of 37 RNA modification regulators and RNA modification regulators related genes were identified in 112 samples from 5 Gene Expression Omnibus datasets. Nonnegative Matrix Factorization clustering method was performed to determine RNA modification patterns. The ssGSEA algorithms and the expression of human leukocyte antigen were employed to assess the immune microenvironment characteristics. Risk model based on differentially expression genes responsible for the modification regulators was constructed to evaluate its predictive capability in DN patients. Furthermore, the results were validated by using immunofluorescence co-localizations and protein experiments in vitro.

RESULTS

We found 24 RNA methylation regulators were significant differently expressed in glomeruli in DN group compared with control group. Four methylation-related genes and six RNA regulators were introduced into riskScore model using univariate Logistic regression and integrated LASSO regression, which could precisely distinguish the DN and healthy individuals. Group with high-risk score was associated with high immune infiltration. Three distinct RNA modification patterns were identified, which has significant differences in immune microenvironment, biological pathway and eGFR. Validation analyses showed the METTL3, ADAR1, DNMT1 were upregulated whereas YTHDC1 was downregulated in DN podocyte cell lines comparing with cells cultured by the normal glucose.

CONCLUSION

Our study reveals that RNA methylation regulators and immune infiltration regulation play critical roles in the pathogenesis of DN. The bioinformatic analyses combine with verification in vitro could provide robust evidence for identification of predictive RNA methylation regulators in DN.

Cell-Surface Autoantibody Targets Zinc Transporter-8 (ZnT8) for In Vivo β-Cell Imaging and Islet-Specific Therapies

Type 1 diabetes (T1D) is a disease in which autoimmune attacks are directed at the insulin-producing β-cell in the pancreatic islet. Autoantigens on the β-cell surface membrane are specific markers for molecular recognition and targets for engagement by autoreactive B lymphocytes, which produce islet cell surface autoantibody (ICSA) upon activation. We report the cloning of an ICSA (mAb43) that recognizes a major T1D autoantigen, ZnT8, with a subnanomolar binding affinity and conformation specificity. We demonstrate that cell-surface binding of mAb43 protects the extracellular epitope of ZnT8 against immunolabeling by serum ICSA from a patient with T1D. Furthermore, mAb43 exhibits in vitro and ex vivo specificity for islet cells, mirroring the exquisite specificity of islet autoimmunity in T1D. Systemic administration of mAb43 yields a pancreas-specific biodistribution in mice and islet homing of an mAb43-linked imaging payload through the pancreatic vasculature, thereby validating the in vivo specificity of mAb43. Identifying ZnT8 as a major antigenic target of ICSA allows for research into the molecular recognition and engagement of autoreactive B cells in the chronic phase of T1D progression. The in vivo islet specificity of mAb43 could be further exploited to develop in vivo imaging and islet-specific immunotherapies.

Maintenance of Enteral ACE2 Prevents Diabetic Retinopathy in Type 1 Diabetes

BACKGROUND

We examined components of systemic and intestinal renin-angiotensin system on gut barrier permeability, glucose homeostasis, systemic inflammation, and progression of diabetic retinopathy (DR) in human subjects and mice with type 1 diabetes (T1D).

METHODS

T1D individual with (n=18) and without (n=20) DR and controls (n=34) were examined for changes in gut-regulated components of the immune system, gut leakage markers (FABP2 [fatty acid binding protein 2] and peptidoglycan), and Ang II (angiotensin II); Akita mice were orally administered a Lactobacillus paracasei (LP) probiotic expressing humanized ACE2 (angiotensin-converting enzyme 2) protein (LP-ACE2) as either a prevention or an intervention. Akita mice with genetic overexpression of humanAce2 by small intestine epithelial cells (Vil-Cre.hAce2KI-Akita) were similarly examined. After 9 months of T1D, circulatory, enteral, and ocular end points were assessed.

RESULTS

T1D subjects exhibit elevations in gut-derived circulating immune cells (ILC1 cells) and higher gut leakage markers, which were positively correlated with plasma Ang II and DR severity. The LP-ACE2 prevention cohort and genetic overexpression of intestinal ACE2 preserved barrier integrity, reduced inflammatory response, improved hyperglycemia, and delayed development of DR. Improvements in glucose homeostasis were due to intestinal MasR activation, resulting in a GSK-3β (glycogen synthase kinase-3 beta)/c-Myc (cellular myelocytomatosis oncogene)-mediated decrease in intestinal glucose transporter expression. In the LP-ACE2 intervention cohort, gut barrier integrity was improved and DR reversed, but no improvement in hyperglycemia was observed. These data support that the beneficial effects of LP-ACE2 on DR are due to the action of ACE2, not improved glucose homeostasis.

CONCLUSIONS

Dysregulated systemic and intestinal renin-angiotensin system was associated with worsening gut barrier permeability, gut-derived immune cell activation, systemic inflammation, and progression of DR in human subjects. In Akita mice, maintaining intestinal ACE2 expression prevented and reversed DR, emphasizing the multifaceted role of the intestinal renin-angiotensin system in diabetes and DR.