A blood test might soon tell you more than your cholesterol levels. Scientists have identified molecular signatures in blood plasma that mirror physical fitness in elderly adults, with one amino acid standing out as a dominant marker of healthy aging.
Researchers led by Wolfram Weckwerth from the University of Vienna combined metabolomics analysis with machine learning to study 263 blood samples from adults averaging 83 years old. The team wanted to know whether the benefits of an active lifestyle show up directly in the blood, and which molecules matter most.
They found their answer in aspartate, an amino acid that emerged as the strongest predictor of physical performance. Machine learning models distinguished “active” from “less-active” participants with over 91% accuracy, and aspartate consistently topped the list across five different algorithms.
From Fitness Tests to Blood Fingerprints
The researchers first created a “Body Activity Index” by combining scores from walking tests, chair-rise exercises, handgrip strength, and balance assessments into a single measure. Separately, they derived a “Metabolomics Index” from blood concentrations of 35 small molecules. The correlation between these two indices reached 0.85, demonstrating that molecular patterns in blood closely track physical fitness.
To capture complex patterns, the team trained five machine learning models ranging from basic statistical methods to advanced deep learning networks. Both gradient boosting methods achieved accuracy rates exceeding 91%. Eight metabolites consistently emerged as predictors: aspartate, proline, fructose, malic acid, pyruvate, valine, citrate, and ornithine. Among these, aspartate dominated by a factor of two to three.
Physical activity does more than building up muscle mass. It rewires our metabolism at the molecular level. By decoding those changes, we can track, and even guide, how well someone is aging.
But correlation does not explain causation. To uncover the underlying mechanisms, the team applied COVRECON, a data-driven modeling tool that reconstructs networks of biochemical interactions. The analysis identified two well-known liver enzymes, aspartate aminotransferase (AST) and alanine aminotransferase (ALT), as central hubs in the metabolic network.
Dynamic Enzymes Signal Metabolic Flexibility
Standard blood tests confirmed the predictions. Over six months, AST and ALT levels fluctuated more strongly in physically active participants than in their less-active peers. Active individuals showed larger decreases in these enzymes during the first three months, followed by larger increases in the next three months. This suggests greater metabolic flexibility in liver and muscle function, rather than disease pathology.
The finding aligns with long-term studies of athletes, where AST and ALT show significantly larger variations compared to the general population. Physical exercise can transiently elevate these enzymes within healthy ranges, and the levels return to baseline after exertion. The pattern indicates that active aging involves dynamic metabolic adjustments, not static states.
Aspartate plays multiple roles in the body. It participates in the malate-aspartate shuttle, which transfers energy between cellular compartments and supports ATP production in tissues with high energy demands like muscle, liver, and heart. The amino acid also helps remove ammonia through the urea cycle, a process that becomes important during exercise when ammonia accumulates as a metabolic byproduct.
The brain connection adds another dimension. Aspartate serves as a precursor for neurotransmitters and activates NMDA receptors essential for learning and memory. Independent studies have linked low midlife AST and ALT levels, or an elevated AST/ALT ratio, with increased risk of Alzheimer’s disease and cognitive decline. The present study suggests physical activity may protect cognitive function through measurable shifts in amino acid metabolism.
Aspartate is more than a simple metabolic intermediate: in the brain it also serves as a precursor of neurotransmitters, activating NMDA receptors that are essential for learning and memory.
The researchers emphasize that endurance exercise, particularly walking distance, showed the strongest effects on the metabolic signature. This observation matches previous findings that endurance training, not resistance training, correlates most strongly with anti-aging effects in cellular markers. Among 100 older women studied elsewhere, strength endurance training significantly reduced age-related immune cell senescence, while intensive training showed no such benefit.
The study analyzed participants from five Viennese retirement homes who underwent either resistance training, resistance training with protein-vitamin supplements, or cognitive training as a control. Blood samples were collected at baseline, three months, and six months. While resistance training improved certain strength measures, the metabolic signature captured by the Body Activity Index related more strongly to endurance capacity than to resistance metrics.
The COVRECON analysis revealed that enzyme transaminases, which facilitate amino acid production, appear central to the metabolic rewiring. Beyond AST and ALT, the enzyme asparagine synthetase emerged in multiple highlighted interactions, though its role in elderly health remains less studied. Recent work has identified asparagine synthetase deficiency as a metabolic disorder of non-essential amino acids, suggesting this pathway deserves further investigation.
The findings point toward practical applications. If aspartate and related enzymes reliably indicate physical fitness and metabolic flexibility, routine blood tests could track aging trajectories. Some researchers have explored aspartate supplementation to reduce exercise-induced ammonia accumulation and increase endurance, though the present study focused on natural variations rather than interventions.
The convergence of physical fitness, blood biomarkers, and brain health suggests a tightly linked system. Regular physical activity elevates neurogenesis and brain-derived neurotrophic factor while protecting against neurodegeneration. Meta-analyses show higher activity levels reduce dementia incidence by approximately 28%, with even minimal exercise like walking over 6,000 steps daily showing protective effects. The molecular bridge may run through aspartate metabolism and the plasticity of liver enzymes.
The researchers acknowledge limitations. The study population consisted largely of women in Viennese nursing homes, and the findings require validation in more diverse cohorts. The connection to dementia remains hypothetical without direct investigation in patient populations. Future work will explore whether weighting enzyme-level regulation or reaction kinetics can add precision to the inferred network structure.
Still, the integration of machine learning with metabolic network modeling offers a powerful approach for understanding aging. By identifying aspartate as a robust biomarker and mapping the dynamic interactions that support active aging, the study provides a framework for monitoring, and potentially improving, how people age at the molecular level.
npj Systems Biology and Applications: 10.1038/s41540-025-00580-4
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