Cytotoxicity-Related Gene Expression and Chromatin Accessibility Define a Subset of CD4+ T Cells That Mark Progression to Type 1 Diabetes

Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling

Abnormalities in glucose metabolism that precede the onset of type 2 diabetes (T2D) activate immune cells, leading to elevated inflammatory factors and chronic inflammation. However, no single-cell RNA sequencing (scRNA-seq) studies have characterized the properties and networks of individual immune cells in T2D. Here, we analyzed peripheral blood mononuclear cells (PBMCs) from non-diabetes and T2D patients by scRNA-seq. We found that CD14 monocytes in T2D patients were in a pro-inflammatory state and intermediate monocytes expressed more MHC class II genes. In T2D patients, cytotoxic CD4 T cells, effector memory CD8 T cells, and γδ T cells have increased cytotoxicity and clonal expansion. B cells were characterized by increased differentiation into intermediate B cells, plasma cells, and isotype class switching with increased expression of soluble antibody genes. These results suggest that monocytes, T cells, and B cells could interact to induce chronic inflammation in T2D patients with pro-inflammatory characteristics.

First-in-human, double-blind, randomized phase 1b study of peptide immunotherapy IMCY-0098 in new-onset type 1 diabetes: an exploratory analysis of immune biomarkers

BACKGROUND

IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile for the treatment of type 1 diabetes (T1D) in a recent phase 1b trial. This exploratory analysis of data from that trial aimed to identify the patient biomarkers at baseline associated with a positive response to treatment and examined the associations between immune response parameters and clinical efficacy endpoints (as surrogates for mechanism of action endpoints) using an artificial intelligence-based approach of unsupervised explainable machine learning.

METHODS

We conducted an exploratory analysis of data from a phase 1b, dose-escalation, randomized, placebo-controlled study of IMCY-0098 in patients with recent-onset T1D. Here, a panel of markers of T cell activation, memory T cells, and effector T cell response were analyzed via descriptive statistics. Artificial intelligence-based analyses of associations between all variables, including immune responses and clinical responses, were performed using the Knowledge Extraction and Management (KEM®) v 3.6.2 analytical platform.

RESULTS

The relationship between all available patient data was investigated using unsupervised machine learning implemented in the KEM® environment. Of 15 associations found for the dose C group (450 μg subcutaneously followed by 3 × 225 μg subcutaneously), seven involved human leukocyte antigen (HLA) type, all of which identified improvement/absence of worsening of disease parameters in DR4+ patients and worsening/absence of improvement in DR4- patients. This association with DR4+ and non-DR3 was confirmed using the endpoints normalized area under the curve C-peptide from mixed meal tolerance tests where presence of DR4 HLA haplotype was associated with an improvement in both endpoints. Exploratory immune analysis showed that IMCY-0098 dose B (150 μg subcutaneously followed by 3 × 75 μg subcutaneously) and dose C led to an increase in presumed/potentially protective antigen-specific cytolytic CD4+ T cells and a decrease in pathogenic CD8+ T cells, consistent with the expected mechanism of action of IMCY-0098. The analysis identified significant associations between immune and clinical responses to IMCY-0098.

CONCLUSIONS

Promising preliminary efficacy results support the design of a phase 2 study of IMCY-0098 in patients with recent-onset T1D.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03272269; EudraCT: 2016-003514-27.

Viruses as a potential environmental trigger of type 1 diabetes mellitus (Review)

The etiopathogenesis of type 1 diabetes mellitus (T1DM) is a complex multifactorial process that involves an intricate network of genetic, epigenetic, immunological, and environmental factors. Despite the advances in recent years, some aspects of the mechanisms involved in triggering the disease are still unclear. Infections with certain viruses have been suggested as possible environmental triggers for the autoimmune process that leads to selective and progressive destruction of pancreatic β-cells and insufficiency of insulin production, which is its hallmark. In this review, advances in knowledge and evidence that suggest the participation of certain viruses in the mechanisms of disease initiation and progression are described. It has been accepted that environmental factors, including viruses, can initiate and possibly sustain, accelerate, or slow down the autoimmune process and consequently damage insulin-producing pancreatic β-cells. Although the role of these agents, especially human enteroviruses, has been exhaustively studied as the most likely triggers of the activation of autoimmunity that destroys pancreatic islets and leads to T1DM, certain doubts remain. Clinical epidemiological and experimental studies in humans and animals provide consistent and increasing evidence that persistent viral infections, especially with human enteroviruses and rotavirus infections, are associated with an increased risk of the disease in individuals genetically predisposed to autoimmunity.

1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein-RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

Astilbin Activates the Reactive Oxidative Species/PPARγ Pathway to Suppress Effector CD4+ T Cell Activities via Direct Binding With Cytochrome P450 1B1

Astilbin, as a compound of flavonoids, exerts anti-inflammation, antioxidation, and immune-suppression activities. Decreased activation of NF-κB and p38 MAPK and increased activation of SOCS3 and AMPK have been found in astilbin-treated cells. However, what molecules are docked by astilbin to initiate signaling cascades and result in functional changes remains unknown. In the study, we found that astilbin efficiently suppressed TNF-α production and increased CCR9 and CD36 expression of CD4⁺ T cells. In vivo administration of astilbin repressed the occurrence of type 1 diabetes mellitus in non-obese diabetic mice. The PPARγ/SOCS3, PPARγ/PTEN, and PPARγ/AMPK signaling pathways were substantially activated and played key roles in astilbin-induced downregulation of CD4⁺ T cell functions. Transcriptome sequencing results confirmed the changes of signaling molecules involved in the immune system, inflammatory responses, and indicated variations of multiple enzymes with oxidant or antioxidant activities. Astilbin directly induced cytoplasmic ROS production of CD4⁺ T cells ex vivo, but had no effects on mitochondrial ROS and mitochondrial weight. When cellular ROS was depleted, astilbin-treated CD4⁺ T cells remarkably reversed the expression of TNF-α, IFN-γ, CCR9, CD36, and signaling molecules (PPARγ, PTEN, p-AMPK, and SOCS3). Based on bioinformatics, two P450 enzymes (CYP1B1 and CYP19A1) were selected as candidate receptors for astilbin. CYP1B1 was identified as a real docking protein of astilbin in ROS production by AutoDock Vina software analysis and surface plasmon resonance assay. Collectively, astilbin downregulates effector CD4⁺ T cell activities via the CYP1B1/ROS/PPARγ pathway, which firmly supports its potential use in the treatment of inflammation.