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Probiotics Alleviate the Progressive Deterioration of Motor Functions in a Mouse Model of Parkinson’s Disease
Open AccessArticle

Can Gut Microbiota Be a Good Predictor for Parkinson’s Disease? A Machine Learning Approach

1
Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
2
UOSD Parkinson’s Center, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
3
Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
These authors have contributed equally to this work.
Brain Sci. 2020, 10(4), 242; https://doi.org/10.3390/brainsci10040242
Received: 16 March 2020 / Revised: 9 April 2020 / Accepted: 16 April 2020 / Published: 19 April 2020
(This article belongs to the Special Issue Brain–Microbiome Interactions)
The involvement of the gut microbiota in Parkinson’s disease (PD), investigated in several studies, identified some common alterations of the microbial community, such as a decrease in Lachnospiraceae and an increase in Verrucomicrobiaceae families in PD patients. However, the results of other bacterial families are often contradictory. Machine learning is a promising tool for building predictive models for the classification of biological data, such as those produced in metagenomic studies. We tested three different machine learning algorithms (random forest, neural networks and support vector machines), analyzing 846 metagenomic samples (472 from PD patients and 374 from healthy controls), including our published data and those downloaded from public databases. Prediction performance was evaluated by the area under curve, accuracy, precision, recall and F-score metrics. The random forest algorithm provided the best results. Bacterial families were sorted according to their importance in the classification, and a subset of 22 families has been identified for the prediction of patient status. Although the results are promising, it is necessary to train the algorithm with a larger number of samples in order to increase the accuracy of the procedure. View Full-Text
Keywords: Parkinson’s disease; gut microbiota; machine learning; predictor; gut–brain axis Parkinson’s disease; gut microbiota; machine learning; predictor; gut–brain axis
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MDPI and ACS Style

Pietrucci, D.; Teofani, A.; Unida, V.; Cerroni, R.; Biocca, S.; Stefani, A.; Desideri, A. Can Gut Microbiota Be a Good Predictor for Parkinson’s Disease? A Machine Learning Approach. Brain Sci. 2020, 10, 242.

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