Biological age as estimated by baseline circulating metabolites is associated with incident diabetes and mortality.

OBJECTIVES: It is unclear how metabolomic assessment of biological aging performs in non-White populations and whether such an approach can predict future mortality. We aimed to evaluate the application of serum metabolomics combined with machine learning methodologies to predict incident diabetes and mortality in a Thai population. DESIGN, SETTING AND PARTICIPANTS: We analyzed serum samples and mortality data over 11 years from among 454 participants with no previous history of diabetes and with a fasting plasma glucose ≥85th percentile (5.4 mmol/L) but <7 mmol/L. MEASUREMENTS: Untargeted serum metabolomics were assessed using liquid chromatography/mass spectrometry. A deep artificial neural network was used to predict biological age based on serum metabolite profiles and chronological age. RESULTS: The mean age of participants was 40.5 ± 6.4 years, and 70.8% were men. We found a significant positive correlation between metabolomic age and chronological age (r = 0.71, P < 0.001). After 5 years, 61 of 404 participants with available glycated hemoglobin status (15.1%) progressed to diabetes. Chronological age was associated with incident diabetes but was not significant (P = 0.08), after adjusting for BMI and sex. Metabolomic age was significantly related to incident diabetes after controlling for BMI and sex (P < 0.05). Over the 11-year follow-up, 10 participants died owing to non-accidental causes. When metabolomic age and chronological age were included together in the model, metabolomic age (but not chronological age) was associated with mortality, independent of age, sex, and BMI. Among all identifiable metabolites, beta-D-mannosylphosphodecaprenyl and phosphatidylserines were the five leading metabolites associated with mortality. CONCLUSION: We concluded that serum metabolomic profile was associated with incident diabetes as well as mortality over our 11-year study period, which may render it potentially useful in assessing biological aging in humans.

An Increase in Vascular Stiffness Is Positively Associated With Mitochondrial Bioenergetics Impairment of Peripheral Blood Mononuclear Cells in the Older Adults.

The cardio-ankle vascular index (CAVI) is a noninvasive parameter reflecting vascular stiffness. CAVI correlates with the burden of atherosclerosis and future cardiovascular events. Mitochondria of peripheral blood mononuclear cells (PBMCs) have been identified as a noninvasive source for assessing systemic mitochondrial bioenergetics. This study aimed to investigate the relationship between CAVI values and mitochondrial bioenergetics of PBMCs in the older adults.. This cross-sectional study enrolled participants from the Electricity Generating Authority of Thailand between 2017 and 2018. A total of 1 640 participants with an ankle-brachial index greater than 0.9 were included in this study. All participants were stratified into 3 groups based on their CAVI values as high (CAVI ≥ 9), moderate (9 > CAVI ≥ 8), and low (CAVI < 8), in which each group comprised 702, 507, and 431 participants, respectively. The extracellular flux analyzer was used to measure mitochondrial respiration of isolated PBMCs. The mean age of the participants was 67.9 years, and 69.6% of them were male. After adjusted with potential confounders including age, sex, smoking status, body mass index, diabetes, dyslipidemia, hypertension, and creatinine clearance, participants with high CAVI values were independently associated with impaired mitochondrial bioenergetics, including decreased basal respiration, maximal respiration, and spare respiratory capacity, as well as increased mitochondrial reactive oxygen species. This study demonstrated that CAVI measurement reflects the underlying impairment of cellular mitochondrial bioenergetics in PBMCs. Further longitudinal studies are necessary to establish both a causal relationship between CAVI measurement and underlying cellular dysfunction.