1
|
Kumar D, Bishnoi M, Kondepudi KK, Sharma SS. Gut Microbiota-Based Interventions for Parkinson's Disease: Neuroprotective Mechanisms and Current Perspective. Probiotics Antimicrob Proteins 2025:10.1007/s12602-024-10433-x. [PMID: 39809955 DOI: 10.1007/s12602-024-10433-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/09/2024] [Indexed: 01/16/2025]
Abstract
Recent evidence links gut microbiota alterations to neurodegenerative disorders, including Parkinson's disease (PD). Replenishing the abnormal composition of gut microbiota through gut microbiota-based interventions "prebiotics, probiotics, synbiotics, postbiotics, and fecal microbiota transplantation (FMT)" has shown beneficial effects in PD. These interventions increase gut metabolites like short-chain fatty acids (SCFAs) and glucagon-like peptide-1 (GLP-1), which may protect dopaminergic neurons via the gut-brain axis. Neuroprotective effects of these interventions are mediated by several mechanisms, including the enhancement of neurotrophin and activation of the PI3K/AKT/mTOR signaling pathway, GLP-1-mediated gut-brain axis signaling, Nrf2/ARE pathway, and autophagy. Other pathways, such as free fatty acid receptor activation, synaptic plasticity improvement, and blood-brain and gut barrier integrity maintenance, also contribute to neuroprotection. Furthermore, the inhibition of the TLR4/NF-кB pathway, MAPK pathway, GSK-3β signaling pathway, miR-155-5p-mediated neuroinflammation, and ferroptosis could account for their protective effects. Clinical studies involving gut microbiota-based interventions have shown therapeutic benefits in PD patients, particularly in improving gastrointestinal dysfunction and some neurological symptoms. However, the effectiveness in alleviating motor symptoms remains mild. Large-scale clinical trials are still needed to confirm these findings. This review emphasizes the neuroprotective mechanisms of gut microbiota-based interventions in PD as supported by both preclinical and clinical studies.
Collapse
Affiliation(s)
- Deepak Kumar
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Mohali, Punjab, 160062, India
| | - Mahendra Bishnoi
- Centre for Excellence in Functional Foods, Division of Food and Nutritional Biotechnology, National Agri-Food Biomanufacturing Institute (NABI), Knowledge City-Sector 81, S.A.S. Nagar, Punjab, 140306, India
| | - Kanthi Kiran Kondepudi
- Centre for Excellence in Functional Foods, Division of Food and Nutritional Biotechnology, National Agri-Food Biomanufacturing Institute (NABI), Knowledge City-Sector 81, S.A.S. Nagar, Punjab, 140306, India
| | - Shyam Sunder Sharma
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Mohali, Punjab, 160062, India.
| |
Collapse
|
2
|
Xie F, Feng Z, Xu B. Metabolic Characteristics of Gut Microbiota and Insomnia: Evidence from a Mendelian Randomization Analysis. Nutrients 2024; 16:2943. [PMID: 39275260 PMCID: PMC11397146 DOI: 10.3390/nu16172943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2024] [Revised: 08/28/2024] [Accepted: 08/30/2024] [Indexed: 09/16/2024] Open
Abstract
Insomnia is a common sleep disorder that significantly impacts individuals' sleep quality and daily life. Recent studies have suggested that gut microbiota may influence sleep through various metabolic pathways. This study aims to explore the causal relationships between the abundance of gut microbiota metabolic pathways and insomnia using Mendelian randomization (MR) analysis. This two-sample MR study used genetic data from the OpenGWAS database (205 gut bacterial pathway abundance) and the FinnGen database (insomnia-related data). We identified single nucleotide polymorphisms (SNPs) associated with gut bacterial pathway abundance as instrumental variables (IVs) and ensured their validity through stringent selection criteria and quality control measures. The primary analysis employed the inverse variance-weighted (IVW) method, supplemented by other MR methods, to estimate causal effects. The MR analysis revealed significant positive causal effects of specific carbohydrate, amino acid, and nucleotide metabolism pathways on insomnia. Key pathways, such as gluconeogenesis pathway (GLUCONEO.PWY) and TCA cycle VII acetate producers (PWY.7254), showed positive associations with insomnia (B > 0, p < 0.05). Conversely, pathways like hexitol fermentation to lactate, formate, ethanol and acetate pathway (P461.PWY) exhibited negative causal effects (B < 0, p < 0.05). Multivariable MR analysis confirmed the independent causal effects of these pathways (p < 0.05). Sensitivity analyses indicated no significant pleiotropy or heterogeneity, ensuring the robustness of the results. This study identifies specific gut microbiota metabolic pathways that play critical roles in the development of insomnia. These findings provide new insights into the biological mechanisms underlying insomnia and suggest potential targets for therapeutic interventions. Future research should further validate these causal relationships and explore how modulating gut microbiota or its metabolic products can effectively improve insomnia symptoms, leading to more personalized and precise treatment strategies.
Collapse
Affiliation(s)
- Fuquan Xie
- Institute of Biomedical & Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhijun Feng
- Department of Radiation Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Beibei Xu
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| |
Collapse
|
3
|
Pan R, Guo M, Chen Y, Lin G, Tian P, Wang L, Zhao J, Chen W, Wang G. Dynamics of the Gut Microbiota and Faecal and Serum Metabolomes during Pregnancy-A Longitudinal Study. Nutrients 2024; 16:483. [PMID: 38398806 PMCID: PMC10892471 DOI: 10.3390/nu16040483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
Normal pregnancy involves numerous physiological changes, including changes in hormone levels, immune responses, and metabolism. Although several studies have shown that the gut microbiota may have an important role in the progression of pregnancy, these findings have been inconsistent, and the relationship between the gut microbiota and metabolites that change dynamically during and after pregnancy remains to be clarified. In this longitudinal study, we comprehensively profiled the temporal dynamics of the gut microbiota, Bifidobacterium communities, and serum and faecal metabolomes of 31 women during their pregnancies and postpartum periods. The microbial composition changed as gestation progressed, with the pregnancy and postpartum periods exhibiting distinct bacterial community characteristics, including significant alterations in the genera of the Lachnospiraceae or Ruminococcaceae families, especially the Lachnospiraceae FCS020 group and Ruminococcaceae UCG-003. Metabolic dynamics, characterised by changes in nutrients important for fetal growth (e.g., docosatrienoic acid), anti-inflammatory metabolites (e.g., trans-3-indoleacrylic acid), and steroid hormones (e.g., progesterone), were observed in both serum and faecal samples during pregnancy. Moreover, a complex correlation was identified between the pregnancy-related microbiota and metabolites, with Ruminococcus1 and Ruminococcaceae UCG-013 making important contributions to changes in faecal and serum metabolites, respectively. Overall, a highly coordinated microbiota-metabolite regulatory network may underlie the pregnancy process. These findings provide a foundation for enhancing our understanding of the molecular processes occurring during the progression of pregnancy, thereby contributing to nutrition and health management during this period.
Collapse
Affiliation(s)
- Ruili Pan
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Min Guo
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Ying Chen
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Guopeng Lin
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Peijun Tian
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
| | - Linlin Wang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
| | - Jianxin Zhao
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
- (Yangzhou) Institute of Food Biotechnology, Jiangnan University, Yangzhou 225004, China
| | - Wei Chen
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
| | - Gang Wang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (R.P.); (M.G.); (Y.C.); (G.L.); (P.T.); (J.Z.); (W.C.); (G.W.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
- (Yangzhou) Institute of Food Biotechnology, Jiangnan University, Yangzhou 225004, China
| |
Collapse
|