Circulating miRNA-375 levels are increased in autoantibodies-positive first-degree relatives of type 1 diabetes patients

A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes

Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.

Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care

In the past decade, growing interest in micro-ribonucleic acids (miRNAs) has catapulted these small, non-coding nucleic acids to the forefront of biomarker research. Advances in scientific knowledge have made it clear that miRNAs play a vital role in regulating cellular physiology throughout the human body. Perturbations in miRNA signaling have also been described in a variety of pediatric conditions-from cancer, to renal failure, to traumatic brain injury. Likewise, the number of studies across pediatric disciplines that pair patient miRNA-omics with longitudinal clinical data are growing. Analyses of these voluminous, multivariate data sets require understanding of pediatric phenotypic data, data science, and genomics. Use of machine learning techniques to aid in biomarker detection have helped decipher background noise from biologically meaningful changes in the data. Further, emerging research suggests that miRNAs may have potential as therapeutic targets for pediatric precision care. Here, we review current miRNA biomarkers of pediatric diseases and studies that have combined machine learning techniques, miRNA-omics, and patient health data to identify novel biomarkers and potential therapeutics for pediatric diseases. IMPACT: In the following review article, we summarized how recent developments in microRNA research may be coupled with machine learning techniques to advance pediatric precision care.

Nanotechnology in Immunotherapy for Type 1 Diabetes: Promising Innovations and Future Advances

Diabetes is a chronic condition which affects the glucose metabolism in the body. In lieu of any clinical “cure,” the condition is managed through the administration of pharmacological aids, insulin supplements, diet restrictions, exercise, and the like. The conventional clinical prescriptions are limited by their life-long dependency and diminished potency, which in turn hinder the patient’s recovery. This necessitated an alteration in approach and has instigated several investigations into other strategies. As Type 1 diabetes (T1D) is known to be an autoimmune disorder, targeting the immune system in activation and/or suppression has shown promise in reducing beta cell loss and improving insulin levels in response to hyperglycemia. Another strategy currently being explored is the use of nanoparticles in the delivery of immunomodulators, insulin, or engineered vaccines to endogenous immune cells. Nanoparticle-assisted targeting of immune cells holds substantial potential for enhanced patient care within T1D clinical settings. Herein, we summarize the knowledge of etiology, clinical scenarios, and the current state of nanoparticle-based immunotherapeutic approaches for Type 1 diabetes. We also discuss the feasibility of translating this approach to clinical practice.

Continuous subcutaneous insulin infusion alters microRNA expression and glycaemic variability in children with type 1 diabetes

To determine whether continuous subcutaneous insulin infusion (CSII) vs. multiple daily injections (MDI) therapy from near-diagnosis of type 1 diabetes is associated with reduced glycaemic variability (GV) and altered microRNA (miRNAs) expression. Adolescents (74% male) within 3-months of diabetes diagnosis (n = 27) were randomized to CSII (n = 12) or MDI. HbA1c, 1-5-Anhydroglucitol (1,5-AG), high sensitivity C-peptide and a custom TaqMan qPCR panel of 52 miRNAs were measured at baseline and follow-up (median (LQ-UQ); 535 (519–563) days). There were no significant differences between groups in baseline or follow-up HbA1c or C-peptide, nor baseline miRNAs. Mean ± SD 1,5-AG improved with CSII vs. MDI (3.1 ± 4.1 vs. − 2.2 ± − 7.0 mg/ml respectively, P = 0.029). On follow-up 11 miRNAs associated with diabetes vascular complications had altered expression in CSII-users. Early CSII vs. MDI use is associated with lower GV and less adverse vascular-related miRNAs. Relationships with future complications are of interest.

Circulating serum and plasma levels of micro-RNA in type-1 diabetes in children and adolescents: A systematic review and meta-analysis

BACKGROUND

Type 1 diabetes mellitus (T1DM) is a complex metabolic disorder characterized by hyperglycaemia, with constantly increasing incidence in paediatric population. The discovery of new molecules, such as microRNAs, and their possible interactions with T1DM create novel aspects in the diagnosis of the disease.

METHODS

This systematic review and meta-analysis adhered to PRISMA guidelines. MEDLINE, SCOPUS, Cochrane CENTRAL and Clinicaltrials.gov. were searched up to 20 April 2020. Inclusion criteria for individual studies were quantification of microRNAs in serum/plasma samples and study groups consisting of children and adolescents with T1DM and healthy controls. Primary outcome of the study was the qualitative expression of microRNAs between the two groups. Statistical analysis was performed with Comprehensive Meta-Analysis Software v3.0. Methodological quality of included studies was assessed using Newcastle-Ottawa scale.

RESULTS

A total of 484 studies were retrieved from the initial search of the databases. These were subsequently limited to seven included studies. Seven microRNAs demonstrated contrasting expression between the two groups, with two of them showing significant overexpression in T1DM group (miR-181:95% CI: 0.429 to 1.341 P < .001, miR-210:95% CI: 0.381 to 0.852, P < .001) and one micro-RNA being significantly overexpressed in control group (miR-375:95% CI: 0.293 to 1.459, P = .003).

CONCLUSION

A total of three micro-RNA molecules appeared to have a significantly different expression in T1DM patients, serving as a possible diagnostic panel of biomarkers. These findings may contribute as reference for future research to further support the use of microRNAs as a novel diagnostic tool in T1DM.

Baseline Assessment of Circulating MicroRNAs Near Diagnosis of Type 1 Diabetes Predicts Future Stimulated Insulin Secretion

Type 1 diabetes is an autoimmune disease resulting in severely impaired insulin secretion. We investigated whether circulating microRNAs (miRNAs) are associated with residual insulin secretion at diagnosis and predict the severity of its future decline. We studied 53 newly diagnosed subjects enrolled in placebo groups of TrialNet clinical trials. We measured serum levels of 2,083 miRNAs, using RNA sequencing technology, in fasting samples from the baseline visit (<100 days from diagnosis), during which residual insulin secretion was measured with a mixed meal tolerance test (MMTT). Area under the curve (AUC) C-peptide and peak C-peptide were stratified by quartiles of expression of 31 miRNAs. After adjustment for baseline C-peptide, age, BMI, and sex, baseline levels of miR-3187-3p, miR-4302, and the miRNA combination of miR-3187-3p/miR-103a-3p predicted differences in MMTT C-peptide AUC/peak levels at the 12-month visit; the combination miR-3187-3p/miR-4723-5p predicted proportions of subjects above/below the 200 pmol/L clinical trial eligibility threshold at the 12-month visit. Thus, miRNA assessment at baseline identifies associations with C-peptide and stratifies subjects for future severity of C-peptide loss after 1 year. We suggest that miRNAs may be useful in predicting future C-peptide decline for improved subject stratification in clinical trials.

Identification of a Multi-Long Noncoding RNA Signature for the Diagnosis of Type 1 Diabetes Mellitus

Due to the increasing prevalence of type 1 diabetes mellitus (T1DM) and its complications, there is an urgent need to identify novel methods for predicting the occurrence and understanding the pathogenetic mechanisms of the disease. Accumulated data have demonstrated the potential of long noncoding RNAs (lncRNAs), as biomarkers in establishing diagnosis and predicting prognosis of numerous diseases. Yet, little is known about the expression patterns and regulatory roles of lncRNAs in the pathogenesis of T1DM and whether they can be used as diagnostic biomarkers for the disease. To further explore these questions, in the present study, we conducted a comparative analysis of the expression patterns of lncRNAs between 20 T1DM patients and 42 health controls by retrospectively analyzing a published microarray data set. Our results indicate that, compared with healthy controls, diabetic patients had altered levels of lncRNAs. Then, we used three time cross-validation strategy and support vector machine to propose a specific 26-lncRNA signature (termed 26LncSigT1DM). This 26LncSigT1DM signature can be used to effectively distinguish between healthy and diabetic individuals (area under the curve = 0.825) of a validation cohort. After the 26LncSigT1DM was prospectively validated, we used Pearson correlation to identify 915 mRNAs, whose expression levels were positively correlated with those of the 26 lncRNAs. According to their Gene Ontology annotations, these mRNAs participate in processes including cellular response to stimulus, cell communication, multicellular organismal process, and cell motility. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the genes encoding the 915 mRNAs may be associated with the NOD-like receptor signaling pathway, transforming growth factor β signaling pathway, and mineral absorption, suggesting that the deregulation of these lncRNAs may mediate inflammatory abnormalities and immune dysfunctions, which jointly promote the pathogenesis of T1DM. Thus, our study identifies a novel diagnostic tool and may shed more light on the molecular mechanisms underlying the pathogenesis of T1DM.