Understanding Parkinson's: The microbiome and machine learning approach
This study successfully identified microbiome signatures that can differentiate patients with Parkinson's disease from healthy controls across different datasets. These findings highlight the potential of integrating machine learning and microbiome analysis for the diagnosis of Parkinson's disease. However, further research is needed to validate these microbiome signatures and to explore their therapeutic implications in developing targeted treatments and diagnostics for Parkinson's disease.
Authors
- Johan Garssen (ORCID: https://orcid.org/0000-0002-8678-9182)
- Alberto Tonda (ORCID: https://orcid.org/0000-0001-5895-4809)
- Mounîm A. El‐Yacoubi (ORCID: https://orcid.org/0000-0002-7383-0588)
- Alejandro Lopez‐Rincon (ORCID: https://orcid.org/0000-0003-4491-5889)
- David Rojas-Velázquez (ORCID: https://orcid.org/0000-0003-4402-4736)
- Ting Liu (ORCID: https://orcid.org/0000-0003-0389-2553)
- Sarah Kidwai (ORCID: https://orcid.org/0000-0002-6457-2011)
Institutions
- Centre National de la Recherche Scientifique (FR)
- ParisTech (FR)
- Utrecht University (NL)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- University Medical Center Utrecht (NL)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Pharmo Institute (NL)
- Institut Polytechnique de Paris (FR)
- Nutricia Research (Netherlands) (NL)
Publication Details
- Journal
- Maturitas
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1016/j.maturitas.2024.108185
- Citations
- 5
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.85