Non-immune-mediated versus immune-mediated type 1 diabetes: diagnosis and long-term differences-retrospective analysis

mNFE: microbiome network flow entropy for detecting pre-disease states of type 1 diabetes

In the development of Type 1 diabetes (T1D), there are critical states just before drastic changes, and identifying these pre-disease states may predict T1D or provide crucial early-warning signals. Unlike gene expression data, gut microbiome data can be collected noninvasively from stool samples. Gut microbiome sequencing data contain different levels of phylogenetic information that can be utilized to detect the tipping point or critical state in a reliable manner, thereby providing accurate and effective early-warning signals. However, it is still difficult to detect the critical state of T1D based on gut microbiome data due to generally non-significant differences between healthy and critical states. To address this problem, we proposed a new method - microbiome network flow entropy (mNFE) based on a single sample from each individual - for detecting the critical state before seroconversion and abrupt transitions of T1D at various taxonomic levels. The numerical simulation validated the robustness of mNFE under different noise levels. Furthermore, based on real datasets, mNFE successfully identified the critical states and their dynamic network biomarkers (DNBs) at different taxonomic levels. In addition, we found some high-frequency species, which are closely related to the unique clinical characteristics of autoantibodies at the four levels, and identified some non-differential 'dark species' play important roles during the T1D progression. mNFE can robustly and effectively detect the pre-disease states at various taxonomic levels and identify the corresponding DNBs with only a single sample for each individual. Therefore, our mNFE method provides a new approach not only for T1D pre-disease diagnosis or preventative treatment but also for preventative medicine of other diseases by gut microbiome.

The Epidemiology and Genetic Analysis of Children With Idiopathic Type 1 Diabetes in the State of Qatar

Context

Idiopathic type 1 diabetes is characterized by the absence of autoantibodies and the underlying mechanisms are not clear.

Objective

We aimed to study the epidemiology, describe the clinical characteristics, and report results of genetic studies in pediatric patients with idiopathic type 1 diabetes.

Methods

This was a prospective study of type 1 diabetes patients attending Sidra Medicine from 2018 to 2020. Autoantibodies (GAD65, IAA, IA-2A, and ZnT8) were measured and genetic testing was undertaken in patients negative for autoantibodies to rule out monogenic diabetes. Demographic and clinical data of patients with idiopathic type 1 diabetes were compared with patients with autoimmune type 1 diabetes.

Results

Of 1157 patients with type 1 diabetes, 63 were antibody-negative. Upon genome sequencing, 4 had maturity onset diabetes of the young (MODY), 2 had Wolfram syndrome, 1 had H syndrome, and 3 had variants of uncertain significance in MODY genes; 53 patients had idiopathic type 1 diabetes. The most common age of diagnosis was 10 to 14 years. C-peptide level was low but detectable in 30 patients (56.6%) and normal in 23 patients (43.4%) The average body mass index was in the normal range and 33% of the patients had a history of diabetic ketoacidosis (DKA).

Conclusion

Four percent of the children had idiopathic type 1 diabetes. There were statistically significant differences in the C-peptide level and insulin requirement between the 2 groups. DKA was less common in the idiopathic group. Mutations in MODY genes suggest the importance of autoantibody testing and genetic screening for known causes of monogenic diabetes in idiopathic type 1 diabetes. The mechanism of idiopathic type 1 diabetes is unknown but could be due to defects in antibody production or due to autoantibodies that are not yet detectable or discovered.

Beta Cell Therapies for Preventing Type 1 Diabetes: From Bench to Bedside

Type 1 diabetes (T1D) is a chronic metabolic disease characterized by insulin deficiency, generally resulting from progressive autoimmune-mediated destruction of pancreatic beta cells. While the phenomenon of beta cell autoimmunity continues to be an active area of investigation, recent evidence suggests that beta cell stress responses are also important contributors to disease onset. Here we review the pathways driving different kinds of beta cell dysfunction and their respective therapeutic targets in the prevention of T1D. We discuss opportunities and important open questions around the effectiveness of beta cell therapies and challenges for clinical utility. We further evaluate ways in which beta cell drug therapy could be combined with immunotherapy for preventing T1D in light of our growing appreciation of disease heterogeneity and patient endotypes. Ultimately, the emergence of pharmacologic beta cell therapies for T1D have armed us with new tools and closing the knowledge gaps in T1D etiology will be essential for maximizing the potential of these approaches.