AREAS COVERED: Mitochondrial deficits impact insulin-resistant skeletal muscles, adipose tissue, liver, and pancreatic β-cells, affecting glucose and lipid balance. Exercise emerges as a key factor in enhancing mitochondrial function, thereby reducing insulin resistance. Additionally, the therapeutic potential of mitochondrial uncoupling, which generates heat instead of ATP, is discussed. We explore the intricate link between mitochondrial function and diabetes, investigating genetic interventions to mitigate diabetes-related complications. We also cover the impact of insulin deficiency on mitochondrial function, the role of exercise in addressing mitochondrial defects in insulin resistance, and the potential of mitochondrial uncoupling. Furthermore, a comprehensive analysis of Mitochondrial Replacement Therapies (MRT) techniques is presented.
EXPERT OPINION: MRTs hold promise in preventing the transmission of mitochondrial disease. However, addressing ethical, regulatory, and technical considerations is crucial. Integrating mitochondrial-based treatments requires a careful balance between innovation and safety. Ethical dimensions and regulatory aspects of MRT are examined, emphasizing collaborative efforts for the responsible advancement of human health.
AIM OF THE STUDY: In the present study, we investigated the effects of TCS against insulin resistance in muscle cells through integrating in vitro experiment and identifying its active biomarker using metabolomics and in molecular docking validation.
MATERIALS AND METHODS: We used centrifugal partition chromatography (CPC) to isolate 33 fractions from methanolic extract of TCS, and then used UHPLC-Orbitrap-HRMS to identify the detectable metabolites in each fraction. We assessed the insulin sensitization activity of each fraction using enzyme-linked immunosorbent assay (ELISA), and then used confocal immunocytochemistry microscopy to measure the translocation of glucose transporter 4 (GLUT4) to the cell membrane. The identified active metabolites were further simulated for its molecular docking interaction using Autodock Tools.
RESULTS: The polar fractions of TCS significantly increased insulin sensitivity, as measured by the inhibition of phosphorylated insulin receptor substrate-1 (pIRS1) at serine-312 residue (ser312) also the increasing number of translocated GLUT4 and glycogen content. We identified 58 metabolites of TCS, including glycosides, flavonoids, alkaloids, coumarins, and nucleotides groups. The metabolomics and molecular docking simulations showed the presence of minor metabolites consisting of tinoscorside D, higenamine, and tinoscorside A as the active compounds.
CONCLUSIONS: Our findings suggest that TCS is a promising new treatment for insulin resistance and the identification of the active metabolites in TCS could lead to the development of new drugs therapies for diabetes that target these pathways.
METHODS: A systematic search was carried out among online databases to determine eligible RCTs published up to November 2022. A random-effects model was performed for the meta-analysis.
RESULTS: A total of 36 RCTs with 1851 participants were included in the pooled analysis. It was displayed that supplementation with MP effectively reduced levels of fasting blood glucose (FBG) (weighted mean difference (WMD): -1.83 mg/dL, 95% CI: -3.28, -0.38; P = 0.013), fasting insulin (WMD: -1.06 uU/mL, 95% CI: -1.76, -0.36; P = 0.003), and homeostasis model assessment of insulin resistance (HOMA-IR) (WMD: -0.27, 95% CI: -0.40, -0.14; P 8 weeks) with high or moderate doses (≥ 60 or 30-60 g/d) of MP or whey protein (WP). Serum FBG levels were considerably reduced upon short-term administration of a low daily dose of WP (
METHODS: This was a multi-centre, open-label randomised crossover study. Twenty-four overweight/obese T1DM patients aged ⩾18 years old with HbA1c ⩾ 7.0% (53 mmol/mol) were recruited and randomised into two study arms. For first 6-week, one arm remained on standard of care (SOC), the other arm received metformin, adjunctive to SOC. After 2-week washout, patients crossed over and continued for another 6 weeks. Glycaemic variability, other glycaemic parameters and metabolic profile were monitored.
RESULTS: There were significant reduction in metformin group for GV: mean (0.18 ± 1.73 vs -0.95 ± 1.24, p = 0.014), %CV (-15.84 (18.92) vs -19.08 (24.53), p = 0.044), glycemic risk assessment of diabetes equation (-0.69 (3.83) vs -1.61 (3.61), p = 0.047), continuous overlapping net glycaemic action (0.25 ± 1.62 vs -0.85 ± 1.22, p = 0.013), J-index (-0.75 (21.91) vs -7.11 (13.86), p = 0.034), time in range (1.13 ± 14.12% vs 10.83 ± 15.47%, p = 0.032); changes of systolic blood pressure (2.78 ± 11.19 mmHg vs -4.30 ± 9.81 mmHg, p = 0.027) and total daily dose (TDD) insulin (0.0 (3.33) units vs -2.17 (11.45) units, p = 0.012). Hypoglycaemic episodes were not significant in between groups.
CONCLUSION: Metformin showed favourable effect on GV in overweight/obese T1DM patients and reduction in systolic blood pressure, TDD insulin, fasting venous glucose and fructosamine.
METHODS: We used the TyG index as a surrogate measure for insulin resistance. Fasting triglycerides and fasting plasma glucose were measured at the baseline visit in 141 243 individuals aged 35-70 years from 22 countries in the Prospective Urban Rural Epidemiology (PURE) study. The TyG index was calculated as Ln (fasting triglycerides [mg/dL] x fasting plasma glucose [mg/dL]/2). We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random effects to test the associations between the TyG index and risk of cardiovascular diseases and mortality. The primary outcome of this analysis was the composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, and non-fatal myocardial infarction, or stroke). Secondary outcomes were non-cardiovascular mortality, cardiovascular mortality, all myocardial infarctions, stroke, and incident diabetes. We also did subgroup analyses to examine the magnitude of associations between insulin resistance (ie, the TyG index) and outcome events according to the income level of the countries.
FINDINGS: During a median follow-up of 13·2 years (IQR 11·9-14·6), we recorded 6345 composite cardiovascular diseases events, 2030 cardiovascular deaths, 3038 cases of myocardial infarction, 3291 cases of stroke, and 5191 incident cases of type 2 diabetes. After adjusting for all other variables, the risk of developing cardiovascular diseases increased across tertiles of the baseline TyG index. Compared with the lowest tertile of the TyG index, the highest tertile (tertile 3) was associated with a greater incidence of the composite outcome (HR 1·21; 95% CI 1·13-1·30), myocardial infarction (1·24; 1·12-1·38), stroke (1·16; 1·05-1·28), and incident type 2 diabetes (1·99; 1·82-2·16). No significant association of the TyG index was seen with non-cardiovascular mortality. In low-income countries (LICs) and middle-income countries (MICs), the highest tertile of the TyG index was associated with increased hazards for the composite outcome (LICs: HR 1·31; 95% CI 1·12-1·54; MICs: 1·20; 1·11-1·31; pinteraction=0·01), cardiovascular mortality (LICs: 1·44; 1·15-1·80; pinteraction=0·01), myocardial infarction (LICs: 1·29; 1·06-1·56; MICs: 1·26; 1·10-1·45; pinteraction=0·08), stroke (LICs: 1·35; 1·02-1·78; MICs: 1·17; 1·05-1·30; pinteraction=0·19), and incident diabetes (LICs: 1·64; 1·38-1·94; MICs: 2·68; 2·40-2·99; pinteraction <0·0001). In contrast, in high-income countries, higher TyG index tertiles were only associated with an increased hazard of incident diabetes (2·95; 2·25-3·87; pinteraction <0·0001), but not of cardiovascular diseases or mortality.
INTERPRETATION: The TyG index is significantly associated with future cardiovascular mortality, myocardial infarction, stroke, and type 2 diabetes, suggesting that insulin resistance plays a promoting role in the pathogenesis of cardiovascular and metabolic diseases. Potentially, the association between the TyG index and the higher risk of cardiovascular diseases and type 2 diabetes in LICs and MICs might be explained by an increased vulnerability of these populations to the presence of insulin resistance.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).