The microRNA-29 family members miR-29a-3p, miR-29b-3p, and miR-29c-3p are ubiquitously expressed and consistently increased in various tissues and cell types in conditions of metabolic disease, obesity, insulin resistance, and type 2 diabetes. In pancreatic β cells, miR-29a is required for normal exocytosis, but increased levels are associated with impaired β-cell function. Similarly, in liver, miR-29 species are higher in models of insulin resistance and type 2 diabetes, and either knock-out or depletion using a microRNA inhibitor improves hepatic insulin resistance. In skeletal muscle, miR-29 family upregulation is associated with insulin resistance and altered substrate oxidation, and similarly, in adipocytes, overexpression of miR-29a leads to insulin resistance. Blocking miR-29a using nucleic acid antisense therapeutics show promising results in preclinical animal models of obesity and type 2 diabetes, although the widespread expression pattern of miR-29 family members complicates the exploration of single target tissues. However, in fibrotic diseases, such as in late complications of diabetes and metabolic disease (diabetic kidney disease, nonalcoholic steatohepatitis), miR-29 species expression is suppressed by TGF-β allowing increased extracellular matrix collagen to form. In the clinical setting, circulating levels of miR-29a and miR-29b are consistently increased in type 2 diabetes and in gestational diabetes and are also possible prognostic markers for deterioration of glucose tolerance. In conclusion, miR-29 family miRNAs play an essential role in various organs relevant to intermediary metabolism and its upregulation contributes to impaired glucose metabolism, whereas it suppresses fibrosis development. Thus, a correct balance of levels of miR-29 family miRNA seems important for cellular and organ homeostasis in metabolism.

The aim of this cross-sectional study was to compare plasma C-peptide presence and levels in people without diabetes (CON) and with Type 1 diabetes and relate C-peptide status to clinical factors. In a subset we evaluated 50 microRNAs (miRs) previously implicated in beta-cell death and associations with clinical status and C-peptide levels. Diabetes age of onset was stratified as adult (≥ 18 y.o) or childhood (< 18 y.o.), and diabetes duration was stratified as ≤ 10 years, 10–20 years and > 20 years. Plasma C-peptide was measured by ultrasensitive ELISA. Plasma miRs were quantified using TaqMan probe-primer mix on an OpenArray platform. C-peptide was detectable in 55.3% of (n = 349) people with diabetes, including 64.1% of adults and 34.0% of youth with diabetes, p < 0.0001 and in all (n = 253) participants without diabetes (CON). C-peptide levels, when detectable, were lower in the individuals with diabetes than in the CON group [median lower quartile (LQ)–upper quartile (UQ)] 5.0 (2.6–28.7) versus 650.9 (401.2–732.4) pmol/L respectively, p < 0.0001 and lower in childhood versus adult-onset diabetes [median (LQ–UQ) 4.2 (2.6–12.2) pmol/L vs. 8.0 (2.3–80.5) pmol/L, p = 0.02, respectively]. In the childhood-onset group more people with longer diabetes duration (> 20 years) had detectable C-peptide (60%) than in those with shorter diabetes duration (39%, p for trend < 0.05). Nine miRs significantly correlated with detectable C-peptide levels in people with diabetes and 16 miRs correlated with C-peptide levels in CON. Our cross-sectional study results are supportive of (a) greater beta-cell function loss in younger onset Type 1 diabetes; (b) persistent insulin secretion in adult-onset diabetes and possibly regenerative secretion in childhood-onset long diabetes duration; and (c) relationships of C-peptide levels with circulating miRs. Confirmatory clinical studies and related basic science studies are merited.

The loss of functional beta cell mass characterises all forms of diabetes. Beta cells are highly susceptible to stress, including cytokine, endoplasmic reticulum (ER) and oxidative stress. This study examined the role of pleckstrin homology-like, domain family A, member 3 (Phlda3) in beta cell survival under stress conditions and the regulatory basis. We found that the mRNA levels of Phlda3 were markedly upregulated in vivo in the islets of diabetic humans and mice. In vitro, exposure of MIN6 cells or islets to cytokines, palmitate, thapsigargin or ribose upregulated Phlda3 mRNA and protein levels, concurrent with the induction of ER stress (Ddit3 and Trb3) and antioxidant (Hmox1) genes. Furthermore, H₂O₂ treatment markedly increased PHLDA3 immunostaining in human islets. Phlda3 expression was differentially regulated by adaptive (Xbp1) and apoptotic (Ddit3) unfolded protein response (UPR) mediators. siRNA-mediated knockdown of Xbp1 inhibited the induction of Phlda3 by cytokines and palmitate, whereas knockdown of Ddit3 upregulated Phlda3. Moreover, knockdown of Phlda3 potentiated cytokine-induced apoptosis in association with upregulation of inflammatory genes (iNos, IL1β and IκBα) and NFκB phosphorylation and downregulation of antioxidant (Gpx1 and Srxn1) and adaptive UPR (Xbp1, Hspa5 and Fkbp11) genes. Knockdown of Phlda3 also potentiated apoptosis under oxidative stress conditions induced by ribose treatment. These findings suggest that Phlda3 is crucial for beta cell survival under stress conditions. Phlda3 regulates the cytokine, oxidative and ER stress responses in beta cells via the repression of inflammatory gene expression and the maintenance of antioxidant and adaptive UPR gene expression. Phlda3 may promote beta cell survival in diabetes.

Aims/hypothesis: Few large-scale prospective studies have investigated associations between relative leucocyte telomere length (rLTL) and kidney dysfunction in individuals with type 2 diabetes. We examined relationships between rLTL and incident end-stage kidney disease (ESKD) and the slope of eGFR decline in Chinese individuals with type 2 diabetes. Methods: We studied 4085 Chinese individuals with type 2 diabetes observed between 1995 and 2007 in the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data. rLTL was measured using quantitative PCR. ESKD was diagnosed based on the ICD-9 code and eGFR. Results: In this cohort (mean ± SD age 54.3 ± 12.6 years) followed up for 14.1 ± 5.3 years, 564 individuals developed incident ESKD and had shorter rLTL at baseline (4.2 ± 1.2 vs 4.7 ± 1.2, p < 0.001) than the non-progressors (n = 3521). On Cox regression analysis, each ∆∆C_t decrease in rLTL was associated with an increased risk of incident ESKD (HR 1.21 [95% CI 1.13, 1.30], p < 0.001); the association remained significant after adjusting for baseline age, sex, HbA_1c, lipids, renal function and other risk factors (HR 1.11 [95% CI 1.03, 1.19], p = 0.007). Shorter rLTL at baseline was associated with rapid decline in eGFR (>4% per year) during follow-up (unadjusted OR 1.22 [95% CI 1.15, 1.30], p < 0.001; adjusted OR 1.09 [95% CI 1.01, 1.17], p = 0.024). Conclusions/interpretation: rLTL is independently associated with incident ESKD and rapid eGFR loss in individuals with type 2 diabetes. Telomere length may be a useful biomarker for the progression of kidney function and ESKD in type 2 diabetes. Graphical

Identifying individuals at high risk of type 1 diabetes (T1D) is crucial as disease-delaying medications are available. Here we report a microRNA (miRNA)-based dynamic (responsive to the environment) risk score developed using multicenter, multiethnic and multicountry (‘multicontext’) cohorts for T1D risk stratification. Discovery (wet and dry lab) analysis identified 50 miRNAs associated with functional β cell loss, which is a hallmark of T1D. These miRNAs measured across n = 2,204 individuals from four contexts (4C: Australia, Denmark, Hong Kong SAR People’s Republic of China, India) led to a four-context, miRNA-based dynamic risk score (DRS) that effectively stratified individuals with and without T1D. Generative artificial intelligence was used to create an enhanced four-context, miRNA-based DRS, which offered good predictive power (area under the curve = 0.84) for T1D stratification in a separate multicontext validation dataset (n = 662), and accurately predicted future exogenous insulin requirement at 1 hour of islet transplantation. In a clinical trial assessing the imatinib drug therapy, baseline miRNA signature, rather than clinical characteristics, distinguished drug responders from nonresponders at 1 year. This study harnessed machine learning/generative artificial intelligence approaches, identifying and validating a miRNA-based DRS for T1D discrimination and treatment efficacy prediction.