Metabolomics-Driven Integration of Traditional Chinese Medicine for Neurological Disorders: From Precision Diagnosis...

Neurological disorders are leading causes of disability and death worldwide, yet many patients still face delayed diagnosis, limited disease-modifying options and substantial treatment-related adverse effects. Traditional Chinese medicine (TCM) provides holistic, multi-target interventions through acupuncture, herbal formulas and adjunctive therapies, but its mechanisms remain insufficiently defined. Metabolomics, which enables system-wide profiling of small-molecule metabolites, offers an objective way to characterise disease-related metabolic networks and quantify the global effects of TCM. We systematically searched PubMed, Web of Science and China National Knowledge Infrastructure for studies published between January 2005 and June 2025 that evaluated TCM-related interventions for neurological disorders and reported metabolomic outcomes. Peer-reviewed animal and clinical studies were included, whereas reviews, conference abstracts, methodological-only papers and non-neurological studies were excluded. Across Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), ischaemic stroke (IS), epilepsy and high-altitude cerebral oedema (HACE), consistent alterations were identified in amino acid, lipid and energy-related pathways, such as nicotinamide and lysophosphatidylcholine species in AD, branched-chain amino acids in PD and phenylalanine and asymmetric dimethylarginine in MS. Metabolomics studies indicate that acupuncture and herbal formulas can jointly modulate neurotransmitter balance, cerebral energy metabolism, oxidative stress, neuroinflammation and blood-brain barrier integrity. Emerging spatial metabolomics based on mass spectrometry imaging links individual TCM components, including ginsenosides and Astragalus membranaceus-Carthamus tinctorius decoctions, to region-specific metabolic reprogramming in the cortex, hippocampus and thalamus. However, most metabolite-disease associations are correlative and are constrained by small sample sizes, heterogeneous designs and lack of technical standardisation. Metabolomics therefore provides a quantitative framework to dissect the multi-target mechanisms of TCM in neurology and to connect molecular changes with functional outcomes. Standardised workflows, larger multicentre clinical studies and integration of spatial metabolomics, multi-omics and artificial-intelligence-based analysis are required to translate these findings into TCM-informed precision diagnosis and personalised treatment for neurological disorders.