ArticleFrontiers in medicine2026
Cerebrospinal fluid metabolite alterations associated with human brain aging: an untargeted metabolomics study.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Metabolic modifications underlying human brain aging still remains poorly investigated. This study aims to reveal the differential metabolite profile of cerebrospinal fluid (CSF) in the aging group, and demonstrate the metabolic drift in the cerebroventricular environment of human aging brain. Methods: Ten patients aged from 25 to 35 years old as the control group, and an identical number of patients aged from 70 to 80 years old as the aging group, who go through surgery without diagnosed aging-related neurological diseases, are enrolled in this study. CSF is collected prior to spinal anesthesia. Then, we conduct an untargeted metabolomics analysis of CSF samples, 10 specimens for each group, through using the Agilent 1,290 Infinity LC system. The stability of the instrument, the repeatability of the experiment, and the reliability of data are evaluated. Raw data are normalized and subjected to the subsequent analysis by R package (ropls). Differentially accumulated metabolites with a variable importance in projection greater than 1.0 are validated by Student's Results: A total of 1,041 metabolic features are obtained, and 33 differentially accumulated metabolites are identified from the control and aging groups. The instrument analysis system is tested to show a good stability, and acquired data are verified to be stable and reliable. The top three enriched chemical classifications of metabolites are lipids and lipid-like molecules, organic acids and derivatives, and organoheterocyclic compounds. Next, differentially accumulated metabolites are analysed under both patterns. Nepodin, Fa 18:2 + 1o, and L-threonate are significantly downregulated, and chlorophene, resorcinol, and isethionate are upregulated in the aging group compared to controls under the negative ion pattern. Notably, creatine, sarcosine, and N-stearoylsphinganine are upregulated in the positive ion pattern. Regulation of differentially accumulated metabolites is revealed. These differential metabolites are potentially involved in some overlapping pathways, including ABC transporters, protein digestion and absorption, and glycine, serine, and threonine metabolism. Conclusions: This untargeted metabolomics study identified age-associated differences in CSF metabolites, with enrichment in potential pathways such as ABC transporters and glycine, serine, and threonine metabolism. These preliminary findings require confirmation in larger, independently validated cohorts.
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