ArticleInternational journal of molecular sciences2026
Metabolomic Cerebrospinal Fluid Biomarkers for the Diagnosis of Atypical Parkinsonian Syndromes.
Article in International journal of molecular sciences, 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
Diagnosis of atypical parkinsonian syndromes (APS), including progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), rely on clinical criteria that often result in misclassification or delayed confirmation. Cerebrospinal fluid (CSF) metabolomics offers the potential to identify disease-specific biochemical "fingerprints". The aim of the study is to identify CSF metabolomic biomarkers that distinguish PSP and MSA from each other and from non-neurodegenerative controls. Targeted mass spectrometry-based metabolomics was performed on CSF samples from 30 patients with MSA, 41 with PSP, and 30 age- and sex-matched non-neurodegenerative controls. Global metabolomic profiles showed no clear group separation. Both PSP and MSA showed elevated gut-derived metabolites p-cresyl sulfate and deoxycholic acid versus controls. In PSP, decreased cortisone and increased hexosylceramide d18:1/24:1 were observed, whereas in MSA, dihydroxyphenylalanine was elevated alongside homoarginine and creatinine. In the direct comparison of APS, levels of α-aminoadipic acid were increased in PSP compared to MSA. Pathway analysis highlighted disrupted glycerophospholipid metabolism in both APS disorders. Distinct metabolite panels mainly combining membrane-associated lipids, gut-derived and neurotransmitter-related metabolites demonstrated high diagnostic accuracy for distinguishing PSP and MSA from control groups (AUC = 0.95 for PSP and AUC = 0.98 for MSA), while a separate panel showed moderate performance in differentiating PSP from MSA (AUC = 0.85). Distinct but partially overlapping CSF metabolomic profiles characterize PSP and MSA. These metabolomic fingerprints highlight gut-brain axis involvement, alterations in cell membrane-related lipid metabolism, and disease-specific changes in neurotransmitter-related metabolites. Further, a panel of these metabolites showed strong potential as diagnostic biomarkers.
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