Recent research highlights that physical activity rewires metabolism at the molecular level, with aspartate playing a crucial role in brain health by acting as a precursor for neurotransmitters involved in learning and memory, thereby linking physical activity, metabolic health, and cognitive resilience.

Tracking molecular changes in metabolism through blood biomarkers can provide insights into healthy aging and potentially help protect against cognitive decline and dementia by influencing amino-acid signaling pathways.

Machine learning models, especially boosting algorithms, have achieved over 91% accuracy in distinguishing active from less-active older adults based on blood metabolite profiles, with aspartate identified as the most prominent biomarker associated with active aging.

Network analysis using tools like COVRECON revealed that enzymes such as aspartate aminotransferase (AST) and alanine aminotransferase (ALT) serve as central hubs in metabolic networks, with their fluctuations indicating greater metabolic flexibility in active individuals.

Researchers developed a 'Body Activity Index' from fitness tests and a 'Metabolomics Index' from blood samples, which showed a high correlation, demonstrating that blood molecular signatures reflect physical fitness levels.

A collaborative study by the University of Vienna and Nankai University combined metabolomics, machine learning, and network modeling to identify molecular processes underlying active aging, emphasizing the importance of blood biomarkers.

Active participants exhibited greater fluctuations in enzymes like AST and ALT over six months, suggesting increased metabolic adaptability in liver and muscle functions associated with physical activity, which are vital for healthy aging.