Abstract
Gut ecosystem dysfunction is implicated in Parkinson’s disease (PD), but integrative faecal metabolome-metagenome links are undefined. We explored these interactions in Chinese PD patients to develop diagnostic panels. Targeted faecal metabolomics (LC‒MS/MS) was performed on 132 PD and 113 healthy controls (HCs) and shotgun metagenomics was integrated for 39 PD/HC pairs. We identified 33 significantly altered faecal metabolites in PD (FDR-P < 0.05). A novel 12-metabolite panel could distinguish PD from HCs. Multi-omic integration revealed gut ecosystem dysfunction manifests via co-disruptions in microbial genes (e.g., amino acid metabolism genes) and metabolites. Critically, a combinatorial diagnostic panel integrating faecal metabolites and microbial gene markers achieved exceptional PD detection (AUC = 0.961, 95% CI = 0.923-0.998). This study deciphers metabolome-metagenome links driving gut dysfunction in PD, identifying amino acid metabolism as a core perturbed pathway. The novel diagnostic panels provide mechanistic insights and clinical tools for PD precision diagnosis.
Similar content being viewed by others
Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files.
References
Zhang, Z.-X. et al. Parkinson’s disease in China: prevalence in Beijing, Xian, and Shanghai. Lancet 365, 595–597 (2005).
Armstrong, M. J. & Okun, M. S. Diagnosis and treatment of Parkinson disease. JAMA 323, 548 (2020).
Sampson, T. R. et al. Gut microbiota regulate motor deficits and neuroinflammation in a model of Parkinson’s disease. Cell 167, 1469–1480 e1412 (2016).
Bedarf, J. R. et al. Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naive Parkinson’s disease patients. Genome Med. 9, 39 (2017).
Nishiwaki, H. et al. Meta-analysis of gut dysbiosis in Parkinson’s disease. Mov. Disord. 35, 1626–1635 (2020).
Zierer, J. et al. The fecal metabolome as a functional readout of the gut microbiome. Nat. Genet. 50, 790–795 (2018).
Tang, J. Microbial metabolomics. Curr. Genomics 12, 391–403 (2011).
Chen, M. X., Wang, S. Y., Kuo, C. H. & Tsai, I. L. Metabolome analysis for investigating host-gut microbiota interactions. J. Formos. Med. Assoc. 118, S10–S22 (2019).
Yang, X. et al. Parkinson’s disease is associated with impaired gut-blood barrier for short-chain fatty acids. Mov. Disord. 37, 1634–1643 (2022).
Chen, S. J. et al. Association of fecal and plasma levels of short-chain fatty acids with gut microbiota and clinical severity in patients with parkinson disease. Neurology 98, e848–e858 (2022).
Unger, M. M. et al. Short chain fatty acids and gut microbiota differ between patients with Parkinson’s disease and age-matched controls. Parkinsonism Relat. Disord. 32, 66–72 (2016).
Lin, A. et al. Gut microbiota in patients with Parkinson’s disease in southern China. Parkinsonism Relat. Disord. 53, 82–88 (2018).
Qian, Y. et al. Alteration of the fecal microbiota in Chinese patients with Parkinson’s disease. Brain, Behav., Immun. 70, 194–202 (2018).
Tan, A. H. et al. Gut Microbial Ecosystem in Parkinson Disease: new Clinicobiological Insights from Multi-Omics. Ann. Neurol. 89, 546–559 (2021).
Vascellari, S. et al. Gut microbiota and metabolome alterations associated with Parkinson’s disease. mSystems 5, (2020).
Jeffery, I. B. et al. Differences in fecal microbiomes and metabolomes of people with vs without irritable bowel syndrome and bile acid malabsorption. Gastroenterology 158, 1016–1028 e1018 (2020).
Oh, T. G. et al. A universal gut-microbiome-derived signature predicts cirrhosis. Cell Metab. 32, 878–888 e876 (2020).
Yu, M. et al. Variations in gut microbiota and fecal metabolic phenotype associated with depression by 16S rRNA gene sequencing and LC/MS-based metabolomics. J. Pharm. Biomed. Anal. 138, 231–239 (2017).
Li, P. et al. Gut microbiota dysbiosis is associated with elevated bile acids in Parkinson’s disease. Metabolites 11, (2021).
Qian, Y. et al. Gut metagenomics-derived genes as potential biomarkers of Parkinson’s disease. Brain 143, 2474–2489 (2020).
Dalile, B., Van Oudenhove, L., Vervliet, B. & Verbeke, K. The role of short-chain fatty acids in microbiota-gut-brain communication. Nat Rev Gastroenterol Hepatol. 16, 461–478 (2019).
Van Treuren, W. & Dodd, D. Microbial contribution to the human metabolome: implications for health and disease. Annu. Rev. Pathol.: Mech. Dis. 15, 345–369 (2020).
Cirstea, M. S. et al. Microbiota composition and metabolism are associated with gut function in Parkinson’s disease. Mov. Disord. 35, 1208–1217 (2020).
Keshavarzian, A. et al. Colonic bacterial composition in Parkinson’s disease. Mov. Disord. : Off. J. Mov. Disord. Soc. 30, 1351–1360 (2015).
Yan, Z. et al. Alterations of gut microbiota and metabolome with Parkinson’s disease. Micro. Pathog. 160, 105187 (2021).
Zhang, Y. et al. Plasma branched-chain and aromatic amino acids correlate with the gut microbiota and severity of Parkinson’s disease. NPJ Parkinsons Dis. 8, 48 (2022).
DiFrancisco-Donoghue, J., Rabin, E., Lamberg, E. M. & Werner, W. G. Effects of tyrosine on parkinson’s disease: a randomized, double-blind, placebo-controlled trial. Mov. Disord. Clin. Pr. 1, 348–353 (2014).
Zhang, Y. et al. Association between microbial tyrosine decarboxylase gene and levodopa responsiveness in patients with Parkinson disease. Neurology 99, e2443–e2453 (2022).
Maini Rekdal, V., Bess, E. N., Bisanz, J. E., Turnbaugh, P. J. & Balskus, E. P. Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism. Science 364, (2019).
Jimenez-Jimenez, F. J., Alonso-Navarro, H., Garcia-Martin, E. & Agundez, J. A. G. Cerebrospinal and blood levels of amino acids as potential biomarkers for Parkinson’s disease: review and meta-analysis. Eur. J. Neurol. 27, 2336–2347 (2020).
Tong, Q. et al. Reduced plasma serotonin and 5-hydroxyindoleacetic acid levels in Parkinson’s disease are associated with nonmotor symptoms. Parkinsonism Relat. Disord. 21, 882–887 (2015).
Olivola, E. et al. Serotonin impairment in CSF of PD patients, without an apparent clinical counterpart. PLoS ONE 9, e101763 (2014).
Shannak, K. et al. Noradrenaline, dopamine and serotonin levels and metabolism in the human hypothalamus: observations in Parkinson's disease and normal subjects. Brain Res. 639, 33–41 (1994).
Augustin, A. et al. Faecal metabolite deficit, gut inflammation and diet in Parkinson’s disease: Integrative analysis indicates inflammatory response syndrome. Clin. Transl. Med. 13, e1152 (2023).
Shao, Y. & Le, W. Recent advances and perspectives of metabolomics-based investigations in Parkinson’s disease. Mol. Neurodegener. 14, 3 (2019).
Graham, S. F. et al. Biochemical profiling of the brain and blood metabolome in a mouse model of prodromal Parkinson’s disease reveals distinct metabolic profiles. J. Proteome Res. 17, 2460–2469 (2018).
Stoessel, D. et al. Promising metabolite profiles in the plasma and CSF of early clinical Parkinson’s disease. Front Aging Neurosci. 10, 51 (2018).
Luan, H. et al. Elevated excretion of biopyrrin as a new marker for idiopathic Parkinson’s disease. Parkinsonism Relat. Disord. 21, 1371–1372 (2015).
Burte, F. et al. Metabolic profiling of Parkinson’s disease and mild cognitive impairment. Mov. Disord. 32, 927–932 (2017).
Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov. Disord. 30, 1591–1601 (2015).
Tomlinson, C. L. et al. Systematic review of levodopa dose equivalency reporting in Parkinson’s disease. Mov. Disord. 25, 2649–2653 (2010).
Xie, G. et al. A Metabolite array technology for precision medicine. Anal. Chem. 93, 5709–5717 (2021).
Ho, T. K. (1995) Random Decision Forest. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, Montreal, 14–16 August 1995 278–282 (1995).
Cortes, C. & Vapnik, V. Support-vector networks. Mach. Learn. 20, 273–297 (1995).
Kursa, M., Jankowski, A. & Rudnicki, W. Boruta—a system for feature selection. Fundam. Inform. 101, 271–285 (2010).
Acknowledgements
This study was funded by the National Natural Science Foundation of China (Grant Nos. 82171246, 81870998, 81901283, 82571430 and 81801254), the Key Field Research and Development Program of Guangdong Province (Grant No. 2018B030337001), the Clinical Research Plan of SHDC (Grant No. SHDC2020CR3012A), the Shanghai Rising-Star Program (Grant No. 22QA1405700), the Shanghai Sailing Program (Grant No. 22YF1440200) and the National Key Research and Development Program of China (Grant No. 2022YFE0210100). The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.
Author information
Authors and Affiliations
Contributions
Y.Q. and S.X. performed the experiments, clinical analysis, and manuscript writing; X.H. and Y.L. collected the samples; Y.Z., C.M. and P.A. helped to recruit the PD patients and controls; and X.Y. performed the study design, manuscript revision and provided financial support. Q.X. designed the study, recruited the P.D. patients and controls, managed the project, provided financial support and revised the manuscript. All the authors meet the qualifications for authorship and have reviewed and approved the final version of the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Consent to publication
All the authors have approved the manuscript.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Qian, Y., Xu, S., He, X. et al. Gut ecosystem dysfunction in parkinson’s disease: deciphering faecal metabolome-metagenome links for novel diagnostic panels. npj Parkinsons Dis. (2026). https://doi.org/10.1038/s41531-026-01299-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41531-026-01299-7


