In a recent Npj Biofilms and Microbiomes journal study, researchers conducted an integrative metaproteogenomic analysis to characterize saliva samples collected from patients with Parkinson’s disease (PD) experiencing cognitive impairments.
Study: Metaproteogenomic analysis of saliva samples from Parkinson’s disease patients with cognitive impairment. Image Credit: Ground Picture / Shutterstock.com
PD is a neurodegenerative disorder that is globally prevalent. In the future, the incidence of PD is expected to substantially increase due to the aging population.
Mechanistically, alpha-synuclein (α-syn) aggregates accumulate in the neurons of PD patients, causing significant disruption in both motor and non-motor functions. Cognitive impairment (CI) is one of the most common non-motor symptoms of PD.
PD symptoms progressively worsen with time, with a shift from mild cognitive impairment (MCI) to full-scale dementia (PDD). Several studies have indicated that PD patients are at a greater risk of dementia, as almost half of PD patients develop dementia within 10 years of diagnosis, and almost all patients develop dementia within 20 years from diagnosis.
It is extremely difficult for PD patients to live independent lives, thus necessitating the need for care from families and nursing homes. The families of PD patients suffer a significant economic burden; therefore, it would be highly beneficial to identify PD patients at an increased risk of developing cognitive decline to implement preventive or delaying measures.
Saliva contains host cells, biomolecules, and microbiota, thus reflecting its potential source of biomarkers for many chronic diseases. Previous studies have revealed that α-syn can be detected in cerebrospinal fluid (CSF) and saliva. In PD patients, α-syn leads to poor secretion of dysphagia and saliva.
Drooling is a common oral motor disorder of PD that has been linked to CI in these patients. Oral microbiota dysbiosis has also been observed in PD patients and is associated with drooling, oral pH, and dysphagia.
About the study
The current study hypothesized that dynamic shifts in salivary biomolecules and microbiota occur with CI progression in PD. Furthermore, saliva samples could be used to predict CI stages in PD.
Metaproteogenomic analysis was used to test this hypothesis. Here, 16 S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing was integrated with metaproteomics data developed from saliva samples.
A total of 115 candidates were recruited in this study to determine whether shifts in saliva composition can help identify different CI stages in PD patients. All study participants were between 50 and 75 years of age. All control group participants underwent neuropsychological testing, and their cognitive capacity was assessed.
The composition of the saliva of PD patients was determined based on 16 S rRNA gene amplicon sequencing and metaproteomics profiling and was compared with controls. Integrative metaproteogenomics enabled the determination of distinct saliva composition signatures associated with CI stages of PD.
An integrative analysis of saliva metaproteomics and metagenomics highlighted dynamic shifts in the salivary microbiome and changes in protein translation machinery and defense mechanisms associated with the CI progression in PD.
In line with previous studies, the metaproteomic and metagenomic profiles indicated the abundance of Prevotella, Streptococcus, Fusobacterium, Veillonella, and Neisseria in the PD cohort as compared to controls. Compared to metaproteomics profiling, many more bacterial genera, phyla, and families were identified through the amplicon sequencing approach. This could be attributed to only a subset of bacterial genera that have been used to develop a custom-based standard protein database to identify proteins.
The study groups had no significant difference in alpha diversity in amplicon-based microbiota. In contrast, considerable changes in the beta diversity of saliva samples were observed between groups that significantly distinguished CI stages.
Thus, the salivary bacterial community changes and re-rearranges with the progression of CI. In line with a previous study, the current study reports a decrease in the Neisseria genus with the progression of CI in PD patients.
Metaproteome profiles indicated a differential composition that contributed to functional changes linked with CI. Moreover, functions associated with biogenesis, ribosomal structure, cytoskeleton and translation, energy production and conversion, and defense mechanisms were amongst the most significantly modified functions between the PD and control cohorts.
The decrease in Neisseria has attracted significant attention because this taxon is associated with the prevention of oral diseases through the conversion of low-pH products into weak acids. In addition, the presence of a high level of Lactobacillaceae members in the oral cavity of PD patients has been linked to many adverse effects due to a reduced secretion of neuroprotective hormones like ghrelin.
The study findings indicate a continual shift in saliva microbiota composition across the CI spectrum in PD. A significant lowering of pyruvate phosphate dikinase (PPDK) enzyme, which plays an important role in gluconeogenesis and lactic acid production, also emerged as a potential biomarker for CI during PD.
Bactericidal permeability-increasing (BPI) proteins, which are associated with host defenses against bacterial pathogens, were also identified as microbial translocation markers. A decrease in salivary BPI abundance indicates a potential BPI imbalance in PD patients that deteriorates with CI progression.
The current study determined that changes in salivary microbiota and biomolecules can be used to detect the CI stages in PD patients. Although the microbial taxa identified in this study are robust, more studies are needed to confirm the saliva proteins linked to CI in PD.
- Arıkan, M., Demir, T. K., Yildiz, Z., et al. (2023) Metaproteogenomic analysis of saliva samples from Parkinson’s disease patients with cognitive impairment. Npj Biofilms and Microbiomes 9(1); 1-10. doi:10.1038/s41522-023-00452-x