ArticleCNS neuroscience & therapeutics2025
Metabolic Characterization of Cerebrospinal Fluid for Patients With Autoimmune Encephalitis: A Preliminary Study.
Article in CNS neuroscience & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Metabolic Signatures and Diagnostic Strategies for Different Types of Encephalitis.CNS neuroscience & therapeutics · 2026Article
- Cerebrospinal fluid metabolites and their association with female reproductive disorders: insights from mendelian randomization.Journal of ovarian research · 2026Article
- Multi-omics-driven biomarker discovery in autoimmune diseases: a comprehensive review.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundMetabolomics offers promise in uncovering potential biomarkers and understanding the pathophysiology of autoimmune encephalitis (AE), which is a cluster of disorders with the host immune system targeting self-antigens expressed in the central nervous system (CNS). In this research, our objective was to explore metabolic characterization in cerebrospinal fluid (CSF) from individuals with AE, aiming to shed light on the pathophysiology of AE.
methodsA targeted approach was applied using an ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) system to study CSF metabolites in patients with AE (n = 18), and control subjects without neurological diseases (n = 17).
resultsA total of 21 potential biomarkers were acquired by getting the intersection of the differential metabolites from univariate statistics and multidimensional statistics between the AE (cell-based assay panel, CBA-panel) group and the control group. Specifically, the levels of pyruvic acid and oxoglutaric acid were notably elevated in the AE(CBA-panel) group compared to those in the control group, indicating that the dysregulated TCA cycle may play a pivotal role in the progression of AE(CBA-panel). Interestingly, 27 potential biomarkers were acquired by getting the intersection of the differential metabolites from univariate statistics and multidimensional statistics between the anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) group and the control group, suggesting that the disparities between patients with greater homogeneity and the controls are amplified. In addition, seven differential metabolites were identified by the univariate statistics between the AE (tissue-based assay, TBA) group and the control group, including alpha-linolenic acid and gamma-linolenic acid, suggesting that dysregulated biosynthesis of unsaturated fatty acids and alpha-linolenic acid metabolism might be crucial in the AE(TBA) disease course.
conclusionCollectively, distinct metabolic profiles were evident in the CSF of the AE group compared to the control group, notably involving metabolites associated with mitochondrial dysfunction, which helped to elucidate the pathophysiology of AE.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.