Evidence map›Paper›PMID 42447752›Full record

ArticleEBioMedicine2026

Metabolomic signatures for diagnosis and clinical severity in Parkinson's disease.

Yige Wang, Yaqin Xiang, Xiurong Huang, Lizhi Li, Taole Li, Xuxiang Zhang, Yuxuan Hu, Jiabin Liu, Zhenhua Liu, Qiying Sun and 12 more

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Article in EBioMedicine, 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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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

22 authors.

Yige WangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Neurology, Qilu Hospital, Shandong University, Jinan, Shandong, China.
Yaqin XiangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xiurong HuangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Lizhi LiDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Taole LiDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xuxiang ZhangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yuxuan HuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Jiabin LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Zhenhua LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China.
Qiying SunKey Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Qian XuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China.
Jieqiong TanCenter for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Chunyu WangDepartment of Neurology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Lifang LeiDepartment of Neurology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
Heng WuThe First Affiliated Hospital, Multi-Omics Research Center for Brain Disorders and Department of Neurology, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Jinchen LiNational Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China; Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Junling WangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China.
Hong JiangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China.
Lu ShenDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China.
Xinxiang YanDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Beisha TangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Jifeng GuoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China. Electronic address: guojifeng@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParkinson's disease (PD) remains challenging to diagnose at early stages owing to subtle and heterogeneous clinical manifestations and the lack of reliable biomarkers. Metabolomics offers a powerful approach to capture disease-related biochemical alterations that reflect underlying pathophysiology. This study aimed to identify robust plasma metabolic signatures for PD diagnosis and to elucidate metabolic alterations associated with clinical severity.

methodsWe performed untargeted plasma metabolomic profiling using ultra-high performance liquid chromatography-tandem mass spectrometry in a large Chinese population comprising two independent early-stage PD groups, one of which consisted of drug-naïve, de novo patients. Integrative statistical analyses, pathway enrichment, and machine learning-based diagnostic modelling were applied to identify discriminative metabolites and characterise disease- and treatment-related metabolic changes.

findingsIn the two case-control datasets, 111 metabolites were consistently altered in early-stage PD, among which 12-hydroxyeicosatetraenoic acid, spermine, and niacinamide emerged as key differential metabolites. Pathway enrichment analysis highlighted sphingolipid metabolism as a major dysregulated pathway in early-stage PD. Using machine learning-based models, a classification model based on six metabolites achieved strong performance (area under the receiver operating characteristic curve [AUC] = 0.976), while individual metabolites also demonstrated good discriminative ability, with the highest AUC reaching 0.916. We further observed that antiparkinsonian medication was significantly associated with metabolic alterations in tyrosine, tryptophan, and polyamine pathways. In addition, gut microbiota-derived metabolites, particularly phenylacetylglutamine and p-Cresol glucuronide, were markedly elevated in PD and associated with both motor and non-motor symptom severity, suggesting a potential contribution to clinical heterogeneity.

interpretationThese findings indicate reproducible plasma metabolic differences associated with early PD and suggest the potential diagnostic value of internally validated classifiers for disease diagnosis. Alterations in gut microbiota-derived metabolites correlate with clinical severity, highlighting the need for further mechanistic and translational research.

fundingThis study was supported by the National Natural Science Foundation of China (82271281 and 82471267), the Science and Technology Major Project of Hunan Provincial Science and Technology Department (2021SK1010), and the National Key Research and Development Program of China (2021YFC2501204).

Indexed as

MetabolomeMetabolomicsParkinson DiseaseAgedBiomarkersCase-Control StudiesFemaleHumansMachine LearningMaleMiddle AgedROC CurveSeverity of Illness IndexTandem Mass SpectrometryBiomarkersBiomarkersGut microbiota-derived metabolitesMetabolomicsParkinson's disease

Identifiers

PMID42447752
PMCPMC13375951

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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.