Novel Strategy for Identification of Gut Microbiome Biomarkers of Parkinson’s Disease Using Artificial Intelligence Algorithms
Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by loss of dopamine neurons in the brain, especially in the substantia nigra. While motor symptoms are best known, non-motor manifestations may precede the motor symptoms by years. Those are also a dominant albeit less dramatic feature of PD including gastrointestinal dysfunctions as well as fatigue, dysphagia and sleep disorders.
There is increasing evidence of an altered gut microbiome of PD subjects and hypothesis arose that those differences may play an important role in the pathogenesis and exacerbations of PD. Bidirectional communication mechanisms between the central nervous system (CNS) and the gut (known as gut-brain axis) include nerve transmission, hormone-mediated immune system, and other molecular signals.
In the presented work we report the application of bioinformatics and Artificial Intelligence methodology with a goal to identify potential biomarkers of PD early onset.
The work resulted in discovery of a number of microbial features that are correlated with PD. Moreover we were able to match those metagenome-derived signatures with biological processes that may be further investigated for the discovery of a predictive biomarker of PD.