Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study.

INTRODUCTION: It has been suggested that type 1 diabetes was associated with increased COVID-19 morbidity and mortality. However, their causal relationship is still unclear. Herein, we performed a two-sample Mendelian randomization (MR) to investigate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. RESEARCH DESIGN AND METHODS: The summary statistics of type 1 diabetes were obtained from two published genome-wide association studies of European population, one as a discovery sample including 15 573 cases and 158 408 controls, and the other data as a replication sample consisting of 5913 cases and 8828 controls. We first performed a two-sample MR analysis to evaluate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. Then, reverse MR analysis was conducted to determine whether reverse causality exists. RESULTS: MR analysis results showed that the genetically predicted type 1 diabetes was associated with higher risk of severe COVID-19 (OR=1.073, 95% CI: 1.034 to 1.114, pFDR=1.15×10-3) and COVID-19 death (OR=1.075, 95% CI: 1.033 to 1.119, pFDR=1.15×10-3). Analysis of replication dataset showed similar results, namely a positive association between type 1 diabetes and severe COVID-19 (OR=1.055, 95% CI: 1.029 to 1.081, pFDR=1.59×10-4), and a positively correlated association with COVID-19 death (OR=1.053, 95% CI: 1.026 to 1.081, pFDR=3.50×10-4). No causal association was observed between type 1 diabetes and COVID-19 positive, hospitalized COVID-19, the time to the end of COVID-19 symptoms in the colchicine treatment group and placebo treatment group. Reverse MR analysis showed no reverse causality. CONCLUSIONS: Type 1 diabetes had a causal effect on severe COVID-19 and death after COVID-19 infection. Further mechanistic studies are needed to explore the relationship between type 1 diabetes and COVID-19 infection and prognosis.

Contribution of Retrotransposons to the Pathogenesis of Type 1 Diabetes and Challenges in Analysis Methods.

Type 1 diabetes (T1D) is one of the most common chronic diseases of the endocrine system, associated with several life-threatening comorbidities. While the etiopathogenesis of T1D remains elusive, a combination of genetic susceptibility and environmental factors, such as microbial infections, are thought to be involved in the development of the disease. The prime model for studying the genetic component of T1D predisposition encompasses polymorphisms within the HLA (human leukocyte antigen) region responsible for the specificity of antigen presentation to lymphocytes. Apart from polymorphisms, genomic reorganization caused by repeat elements and endogenous viral elements (EVEs) might be involved in T1D predisposition. Such elements are human endogenous retroviruses (HERVs) and non-long terminal repeat (non-LTR) retrotransposons, including long and short interspersed nuclear elements (LINEs and SINEs). In line with their parasitic origin and selfish behaviour, retrotransposon-imposed gene regulation is a major source of genetic variation and instability in the human genome, and may represent the missing link between genetic susceptibility and environmental factors long thought to contribute to T1D onset. Autoreactive immune cell subtypes with differentially expressed retrotransposons can be identified with single-cell transcriptomics, and personalized assembled genomes can be constructed, which can then serve as a reference for predicting retrotransposon integration/restriction sites. Here we review what is known to date about retrotransposons, we discuss the involvement of viruses and retrotransposons in T1D predisposition, and finally we consider challenges in retrotransposons analysis methods.

PDE12 in type 1 diabetes.

Type 1 diabetes (T1D) incidence is increased after COVID-19 infection in children under 18 years of age. Interferon-α-activated oligoadenylate synthetase and downstream RNAseL activation degrade pathogen RNA, but can also damage host RNA when RNAseL activity is poorly regulated. One such regulator is PDE12 which degrades 2'-5' oligoadenylate units, thereby decreasing RNAseL activity. We analyzed PDE12 expression in islets from non-diabetic donors, individuals with newly (median disease duration 35 days) and recently (5 years) diagnosed T1D, and individuals with type 2 diabetes (T2D). We also analyzed PDE12 single-nucleotide polymorphisms (SNPs) relative to T1D incidence. PDE12 expression was decreased in individuals with recently diagnosed T1D, in three of five individuals with newly diagnosed T1D, but not in individuals with T2D. Two rare PDE12 SNPs were found to have odds ratios of 1.80 and 1.74 for T1D development. We discuss whether decreased PDE12 expression after COVID-19 infection might be part of the up to 2.5-fold increase in T1D incidence.

General population screening for childhood type 1 diabetes: is it time for a UK strategy?

Type 1 diabetes (T1D) is a chronic autoimmune disease of childhood affecting 1:500 children aged under 15 years, with around 25% presenting with life-threatening diabetic ketoacidosis (DKA). While first-degree relatives have the highest risk of T1D, more than 85% of children who develop T1D do not have a family history. Despite public health awareness campaigns, DKA rates have not fallen over the last decade. T1D has a long prodrome, and it is now possible to identify children who go on to develop T1D with a high degree of certainty. The reasons for identifying children presymptomatically include prevention of DKA and related morbidities and mortality, reducing the need for hospitalisation, time to provide emotional support and education to ensure a smooth transition to insulin treatment, and opportunities for new treatments to prevent or delay progression. Research studies of population-based screening strategies include using islet autoantibodies alone or in combination with genetic risk factors, both of which can be measured from a capillary sample. If found during screening, the presence of two or more islet autoantibodies has a high positive predictive value for future T1D in childhood (under 18 years), offering an opportunity for DKA prevention. However, a single time-point test will not identify all children who go on to develop T1D, and so combining with genetic risk factors for T1D may be an alternative approach. Here we discuss the pros and cons of T1D screening in the UK, the different strategies available, the knowledge gaps and why a T1D screening strategy is needed.

New-onset Type 1 Diabetes after COVID-19 mRNA Vaccination.

During the ongoing coronavirus disease 2019 (COVID-19) pandemic, it is critical to ensure the safety of COVID-19 vaccines. We herein report a 51-year-old Japanese woman who developed acute-onset type 1 diabetes with diabetic ketoacidosis six weeks after receiving the first dose of a COVID-19 messenger ribonucleic acid (mRNA) vaccine. Laboratory tests indicated exhaustion of endogenous insulin secretion, a positive result for insulin autoantibody, and latent thyroid autoimmunity. Human leukocyte antigen typing was homozygous for DRB1*09:01-DQB1*03:03 haplotypes. This case suggests that COVID-19 vaccination can induce type 1 diabetes in some individuals with a genetic predisposition.

Genetic Indices Relationship to Hyperglycemia-associated Biomarkers: Consistency with miRNA Expression in Egyptian Children with T1DM

Objective: Micro RNAs (miRNAs) are gaining acceptance as novel biomarkers for the autoimmune disorders. However, miRNA profiles have not been investigated in individuals at risk of or diagnosed with type 1 diabetes mellitus (T1DM). To study the expression pattern of miRNAs in plasma obtained from patients with T1DM and compare with matched healthy controls. Methods: Equal numbers of patients with T1DM (90) and healthy-matched control children (90) were assessed for the expression profile of plasma miRNAs including miRNA-101-5p, miRNA-146-5p, miRNA-21-5p, miRNA-375, miRNA-126, and Let7a-5p using reverse transcriptase polymerase chain reaction methodology and quantitative real-time testing. Results: Analysis showed that miRNA-101, miRNA-21 and miRNA-375 were highly expressed, whereas, miRNA-146-5p, miRNA-126, and miRNA-Let7a-5p showed significantly low levels of expression in T1DM patients compared to controls (p<0.05). In addition, miRNA-101 and miRNA-146 correlated with age at diagnosis of T1DM and disease duration, respectively. Furthermore, multivariate analysis showed that miRNA-126 and Let7a-5p had a significant negative correlation with mean hemoglobin A1c (HbA1c) values. Conclusion: Dysregulation of the six miRNAs analyzed suggested a possible role as biomarkers in T1DM. miRNA-101 was correlated with age at diagnosis while miRNA-146 correlated with disease duration. Two further miRNAs correlated with the existing biomarker, HbA1c.

Diabetic fibrosis.

Diabetes-associated morbidity and mortality is predominantly due to complications of the disease that may cause debilitating conditions, such as heart and renal failure, hepatic insufficiency, retinopathy or peripheral neuropathy. Fibrosis, the excessive and inappropriate deposition of extracellular matrix in various tissues, is commonly found in patients with advanced type 1 or type 2 diabetes, and may contribute to organ dysfunction. Hyperglycemia, lipotoxic injury and insulin resistance activate a fibrotic response, not only through direct stimulation of matrix synthesis by fibroblasts, but also by promoting a fibrogenic phenotype in immune and vascular cells, and possibly also by triggering epithelial and endothelial cell conversion to a fibroblast-like phenotype. High glucose stimulates several fibrogenic pathways, triggering reactive oxygen species generation, stimulating neurohumoral responses, activating growth factor cascades (such as TGF-ß/Smad3 and PDGFs), inducing pro-inflammatory cytokines and chemokines, generating advanced glycation end-products (AGEs) and stimulating the AGE-RAGE axis, and upregulating fibrogenic matricellular proteins. Although diabetes-activated fibrogenic signaling has common characteristics in various tissues, some organs, such as the heart, kidney and liver develop more pronounced and clinically significant fibrosis. This review manuscript summarizes current knowledge on the cellular and molecular pathways involved in diabetic fibrosis, discussing the fundamental links between metabolic perturbations and fibrogenic activation, the basis for organ-specific differences, and the promises and challenges of anti-fibrotic therapies for diabetic patients.

Autoantibody-negative insulin-dependent diabetes mellitus after SARS-CoV-2 infection: a case report.

Here we report a case where the manifestations of insulin-dependent diabetes occurred following SARS-CoV-2 infection in a young individual in the absence of autoantibodies typical for type 1 diabetes mellitus. Specifically, a 19-year-old white male presented at our emergency department with diabetic ketoacidosis, C-peptide level of 0.62 µg l-1, blood glucose concentration of 30.6 mmol l-1 (552 mg dl-1) and haemoglobin A1c of 16.8%. The patient´s case history revealed probable COVID-19 infection 5-7 weeks before admission, based on a positive test for antibodies against SARS-CoV-2 proteins as determined by enzyme-linked immunosorbent assay. Interestingly, the patient carried a human leukocyte antigen genotype (HLA DR1-DR3-DQ2) considered to provide only a slightly elevated risk of developing autoimmune type 1 diabetes mellitus. However, as noted, no serum autoantibodies were observed against islet cells, glutamic acid decarboxylase, tyrosine phosphatase, insulin and zinc-transporter 8. Although our report cannot fully establish causality between COVID-19 and the development of diabetes in this patient, considering that SARS-CoV-2 entry receptors, including angiotensin-converting enzyme 2, are expressed on pancreatic ß-cells and, given the circumstances of this case, we suggest that SARS-CoV-2 infection, or COVID-19, might negatively affect pancreatic function, perhaps through direct cytolytic effects of the virus on ß-cells.