Targeting biological age with bioactive, microbiota-accessible nutritional complexes: a pilot study on healthspan extension in medically healthy adults.

backgroundMicrobiota-accessible nutritional complexes (MAC), a formulation comprising prebiotics, postbiotics, autophagy stimulators, senolytic activators, and natural probiotics, may influence systemic biomarkers and biological aging in healthy individuals. This pilot interventional study aimed to evaluate the effects of a 60-day MAC supplementation on serum biomarkers and biological age (BioAge) in medically healthy adults. Methods: Of 13 screened, 12 enrolled; 3 were excluded from the final analysis. Nine participants (five females, four males; mean age 61 ± 9.29 years) completed 60 days of daily MAC supplementation and were included in the analyses. Serum biomarkers were measured at baseline and post-intervention. BioAge was estimated using three machine-learning regressors: Support Vector Regression (SVR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). Feature importance analysis was conducted to identify key predictors of BioAge. Results: No adverse events occurred. A significant reduction in high-sensitivity C-reactive protein (hs-CRP) levels was observed from 2.66 ± 4.65 to 0.84 ± 0.54 mg/L (-69%; p = 0.009; Cohen’s d ≈ 0.55; post-mean 95% CI: 1.44 to 5.10), indicating decreased systemic inflammation. Lactate dehydrogenase (LDH) also declined significantly from 171.11 ± 21.32 to 159.44 ± 26.86 U/L (-6.8%; p = 0.038; Cohen’s d ≈ 0.22; post-mean 95% CI: 0.97 to 22.37). Other biomarkers, including gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and glucose, showed trends toward improvement without reaching statistical significance. Stratified analysis revealed that females experienced a significant reduction in hs-CRP (p = 0.043) and a mild increase in creatinine (p = 0.042), whereas males exhibited non-significant trends toward improved inflammatory and metabolic markers. AI modeling indicated a reduction in BioAge for several participants. The XGBoost model consistently captured moderate improvements (e.g., Participant 7: 3.3 years), while the RF model showed more variability. SVR did not detect significant changes. An independent empirical model confirmed a statistically significant reduction in BioAge post-intervention (p < 0.0001). Top predictors were low-density lipoprotein cholesterol (LDL-C), glucose, and total cholesterol (TC) as key predictors in the RF and SVR models, while ferritin and hs-CRP ranked highest in the XGBoost model. Conclusions: Sixty days of MAC was safe and associated with clinically relevant hs-CRP reductions and small LDH decreases, alongside AI-inferred BioAge improvements most stably detected by XGBoost. Limitations include small sample size (n = 9), single-arm design, 60-day duration, non-fasting sampling, and a multicomponent intervention that precludes mechanistic attribution, with no microbiome/postbiotic readouts. Larger randomized trials with microbiome/metabolomic profiling and pre-registered, externally validated AI pipelines are required to confirm causality. Trial registration: ISRCTN, ISRCTN85957759. Registered 04 February 2025, https://www.isrctn.com/ISRCTN85957759 .