| Literature DB >> 35897024 |
Szu-Ju Chen1,2,3, Chin-Hsien Lin4,5.
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disease attributed to the synergistic effects of genetic risk and environmental stimuli. Although PD is characterized by motor dysfunction resulting from intraneuronal alpha-synuclein accumulations, termed Lewy bodies, and dopaminergic neuronal degeneration in the substantia nigra, multiple systems are involved in the disease process, resulting in heterogenous clinical presentation and progression. Genetic predisposition to PD regarding aberrant immune responses, abnormal protein aggregation, autophagolysosomal impairment, and mitochondrial dysfunction leads to vulnerable neurons that are sensitive to environmental triggers and, together, result in neuronal degeneration. Neuropathology studies have shown that, at least in some patients, Lewy bodies start from the enteric nervous system and then spread to the central dopaminergic neurons through the gut-brain axis, suggesting the contribution of an altered gut microenvironment in the pathogenesis of PD. A plethora of evidence has revealed different gut microbiomes and gut metabolites in patients with PD compared to unaffected controls. Chronic gut inflammation and impaired intestinal barrier integrity have been observed in human PD patients and mouse models of PD. These observations led to the hypothesis that an altered gut microenvironment is a potential trigger of the PD process in a genetically susceptible host. In this review, we will discuss the complex interplay between genetic factors and gut microenvironmental changes contributing to PD pathogenesis.Entities:
Keywords: Gastrointestinal inflammation; Gut microbiota; Gut microenvironment; Gut–brain axis; Impaired intestinal barrier; Parkinson’s disease
Mesh:
Year: 2022 PMID: 35897024 PMCID: PMC9327249 DOI: 10.1186/s12929-022-00839-6
Source DB: PubMed Journal: J Biomed Sci ISSN: 1021-7770 Impact factor: 12.771
Fig. 1Schematic of gut microenvironmental changes in PD and their contribution to disease pathophysiology. Enteric α-synuclein deposition, gastrointestinal inflammation, and intestinal epithelial barrier dysfunction are observed in PD. Pathological α-synuclein is found in enteroendocrine cells (EECs) and enteric neurons, which propagates through the vagus nerve to the brainstem, resulting in Lewy pathology in the central nervous system. Enteric α-synuclein also induces inflammatory responses involving activation of the caspase-1-dependent inflammasome and production of pro-inflammatory cytokines, leading to intestinal barrier malfunction [87]. Meanwhile, alteration of the gut microbiota composition in PD may accelerate α-synuclein aggregation, partly through secretion of bacterial amyloid [101, 117, 197]. Gut dysbiosis may also trigger enteric inflammation and increased intestinal permeability with systemic infiltration of microbial toxins and metabolites that activate and modulate immune responses and promote PD pathogenesis [85, 103]. Intestinal and systemic inflammation involving increased expression of TLR-4, T cells, and associated pro-inflammatory cytokines (e.g., TNF, IL-1ß, IL-6) results in greater permeability of the blood–brain barrier, neuroinflammation, and dopaminergic neuronal degeneration [64, 74, 166, 198]. BA, bile acid; HA, hippuric acid; IL-1ß, interleukin-1ß; TNF, tumor necrosis factor; TLR, toll-like receptor; TMA, trimethylamine; TMAO, trimethylamine N-oxide; Trp, tryptophan; LPS, lipopolysaccharide; SCFAs, short chain fatty acids
Alteration of microbial metabolites in Parkinson’s disease
| Study | Participants | H-Y stagea | Sample | Metabolite changes in Parkinson’s disease |
|---|---|---|---|---|
| Short chain fatty acids | ||||
| Unger, Germany [ | 34 PD, 34 controls | 2.5 (1–4) | Stool | AA↓ PA↓ BA↓ VA5- |
| Tan, Malaysia [ | 104 PD, 96 controls | 2.2 ± 0.5 | Stool | BA↓ |
| Aho, Finland [ | 55 PD, 56 controls | Stool | AA- PA↓ BA↓ VA- | |
| Pablo-Fernandez, UK [ | 35 PD, 50 controls | Stool | AA↓ PA↓ BA↓ VA↓ | |
| Chen, Taiwan [ | 96 PD, 85 controls | 2.3 ± 1.2 | Stool | AA↓ PA↓ BA↓ VA- |
| Yang, China [ | 95 PD, 33 controls | 2.2 ± 0.7 | Stool | AA↓ PA↓ BA↓ VA- |
| Ahmed, India [ | 43 Drug-naïve PD, 37 controls | 2.0 (1–3) | Plasma | AA↓ |
| Toczylowska, Poland [ | 19 PD, 21 controls | 2.6 ± 0.4 | Plasma | AA↑ |
| Zhao, China [ | 28 PD, 18 controls | Plasma | VA↓ | |
| Shin, South Korea [ | 38 PD, 33 controls | 2.0 ± 0.6 | Plasma | AA↑ PA- BA- |
| Wu, China [ | 50 PD, 50 controls | 2.5 (0.5) | Plasma | AA- PA↓ BA↓ VA- |
| Chen, Taiwan [ | 96 PD, 85 controls | 2.3 ± 1.2 | Plasma | AA- PA↑ BA↑ VA↑ |
| Kim, South Korea [ | 10 PD, 10 controls | Plasma | AA↑ | |
| Yang, China [ | 95 PD, 33 controls | 2.2 ± 0.7 | Plasma | AA↑ PA3↑ BA- VA5- |
| Yilmaz, USA [ | 20 PD, 20 controls | CSF | AA- | |
| Kumari, India [ | 76 PD, 37 controls | Saliva | AA↑ PA3↑ BA - | |
| Kumari, India [ | 100 PD, 50 controls | Urine | AA- BA↑ | |
| Indole derivatives | ||||
| Hatano, Japan [ | 35 PD, 15 controls | 2.9 ± 1.1 | Plasma | IAA↓ |
| Wuolikainen, Sweden [ | 22 PD, 28 controls | Plasma | indole↑ | |
| Sankowski, Poland [ | 18 PD, 9 controls | 2.9 ± 0.6 | Plasma | IS- |
| Shao, China [ | 223 PD, 237 controls | Plasma | ILA↓ | |
| Rosario, German [ | 8 PD, 10 controls | Plasma | IPA↑, IS↓ | |
| Chen, Taiwan [ | 56 PD, 43 controls | 2.3 ± 1.1 | Plasma | Trp- IAA- IPA↑ ILA- |
| Sankowski, Poland [ | 18 PD, 9 controls | 2.9 ± 0.6 | CSF | IS- |
| Luan, China [ | 106 PD, 104 controls | Urine | ILA↑ | |
| Cassani, Italy [ | 68 PD, 43 drug naïve PD, 50 controls | Urine | IS↑ | |
| Bile acids | ||||
| Zhao, China [ | 28 PD, 18 controls | Plasma | GUDCA↓ | |
| Yakhine-Diop, Spain [ | 24 PD, 8 controls | Plasma | CA↑, DCA↑, GDCA↑ | |
| Shao, China [ | 223 PD, 237 controls | Plasma | CA↑, DCA↑, GDCA↑, TDCA↑, GDCS↑, TCAS↑, GLCAS↑ | |
| Chen, Taiwan [ | 56 PD, 43 controls | 2.3 ± 1.1 | Plasma | CA-, DCA↑, GDCA↑, CDCA-, GCA-, GCDCA-, UDCA-, GUDCA- |
| Yilmaz, USA [ | 20 PD, 20 controls | CSF | CA-, DCA-, GDCA-, CDCA-, GCA-, GCDCA↑, UDCA-, GUDCA- LCA-, TCA-, TCDCA-, TDCA-, TUDCA- | |
| Li, USA [ | 15 PD, 12 controls | Appendix | DCA↑, LCA↑ | |
| Li, USA [ | 15 PD, 12 controls | Ileum | LCA↑ | |
| Trimethylamine | ||||
| Tan, Malaysia [ | 104 PD, 96 controls | 2.2 ± 0.5 | Stool | Choline↓ TMA↓ TMAO↓ |
| Ahmed, India [ | 43 Drug-naïve PD, 37 controls | 2.0 (1–3) | Plasma | TMA↓ |
| Sankowski, Poland [ | 18 PD, 9 controls | 2.9 ± 0.6 | Plasma | TMAO↑ |
| Chen, Taiwan [ | 60 PD, 30 controls | 3.2 ± 1.8 | Plasma | TMAO↑ |
| Chung, South Korea [ | 85 drug-naïve PD, 20 controls | Plasma | TMAO↓ | |
| Kim, South Korea [ | 10 PD, 10 controls | Plasma | TMA↓ | |
| Sankowski, Poland [ | 18 PD, 9 controls | 2.9 ± 0.6 | CSF | TMAO- |
| Kumari, India [ | 76 PD, 37 controls | Saliva | TMA↑ TMAO↑ Choline- | |
| Luan, China [ | 106 PD, 104 controls | Urine | Choline↑, TMAO↑ | |
| Hippuric acid related metabolites | ||||
| Burte, UK [ | 41 PD, 40 controls | Plasma | Catechol sulfate↓ | |
| Okuzumi, Japan [ | 15 | 2.4 ± 0.7 | Plasma | HA↓ catechol sulfate↓ |
| Rosario, German [ | 8 PD, 10 controls | Plasma | HA↑ | |
| Chen, Taiwan [ | 56 PD, 43 controls | 2.3 ± 1.1 | Plasma | HA↑ |
| Trivedi, UK [ | 43 PD, 21 controls | Sebum | HA↑ | |
| Wuolikainen, Sweden [ | 22 PD, 28 controls | CSF | Benzoic acid↑ | |
AA, acetic acid; BA, butyric acid; CA, cholic acid; CDCA, chenodeoxycholic acid; CSF, cerebrospinal fluid; DCA: deoxycholic acid; GCA, glycocholic acid; GCDCA, glycochenodeoxycholic acid; GDCA, glycodeoxycholic acid; GDCS, glycodeoxycholic acid 3-sulfate; GLCAS: glycolithocholic acid 3-sulfate; GUDCA, glycoursodeoxycholic acid; HA, hippuric acid; 3-HK, 3-hydroxykynurenine; H-Y stage, Hoehn and Yahr stage; IAA, indole-3-acetic acid; ILA, indolelactic acid; IS, indoxyl sulfate; LCA, lithocholic acid; PA, propionic acid; TCA, taurocholic acid; TCAS, taurocholic acid 3-sulfate; TCDCA, taurochenodeoxycholic acid; TDCA, taurodeoxycholic acid; TMA, trimethylamine; TMAO, trimethylamine N-oxide; Trp, tryptophan; TUDCA, tauroursodeoxycholic acid; UDCA, ursodeoxycholic acid; VA, valeric acid.↑, means increased levels; ↓means reduced levels; - means the levels are not changed
aHoehn and Yahr stage was expressed in median (range), median (interquartile range) or mean ± standard deviation
Fig. 2Genetic predisposition and gut microenvironmental changes collaboratively contribute to PD pathogenesis. Genetic susceptibility to PD leads to vulnerable neurons related to aberrant immune responses, abnormal protein aggregation, autophagolysosomal impairment, and mitochondrial dysfunction that together with gut microenvironmental changes attributed to intestinal stimuli (e.g., bacterial infection, exposure to pesticide or herbicide, gut dysbiosis, and altered bacterial amyloid and metabolites) contribute to PD pathogenesis
Double-hit rodent models of Parkinson’s disease
| PD model | Environmental toxin | Intestinal pathological change | Brain pathological change | Clinical symptoms | Study | |||
|---|---|---|---|---|---|---|---|---|
| Enteric α-syna | Impaired epithelial barrier | Central α-syna | Neuropathologyb | GI | Motor | |||
| Oral paraquat | + | − | − | Naudet [ | ||||
| DSS | + | + | + | + | Kishimoto [ | |||
| IP LPS | + | − | Vitola [ | |||||
| IP LPS | + | Kozina [ | ||||||
| DSS | + | + | − | + | + | Lin [ | ||
| IP rotenone | + | Martella [ | ||||||
| Oral bacteria | + | + | Matheoud [ | |||||
| Thy1-αSyn | Oral SCFAs | + | + | + | Sampson [ | |||
| Thy1-αSyn | Oral bacteria | + | + | + | + | + | Sampson [ | |
DSS, dextran sulfate sodium; GI, gastrointestinal; IP, intraperitoneal; LPS, lipopolysaccharide; PD, Parkinson’s disease; SCFAs, short chain fatty acids; α-syn, α-synuclein. + and − indicates positive and negative results. Blank indicates items not shown
aPathologic α-synuclein deposition at tissue
bNeuroinflammation, neuronal loss, and/or synaptopathy at brain