1
|
Momen YS, Mishra J, Kumar N. Brain-Gut and Microbiota-Gut-Brain Communication in Type-2 Diabetes Linked Alzheimer's Disease. Nutrients 2024; 16:2558. [PMID: 39125436 PMCID: PMC11313915 DOI: 10.3390/nu16152558] [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: 05/27/2024] [Revised: 06/20/2024] [Accepted: 06/25/2024] [Indexed: 08/12/2024] Open
Abstract
The gastrointestinal (GI) tract, home to the largest microbial population in the human body, plays a crucial role in overall health through various mechanisms. Recent advancements in research have revealed the potential implications of gut-brain and vice-versa communication mediated by gut-microbiota and their microbial products in various diseases including type-2 diabetes and Alzheimer's disease (AD). AD is the most common type of dementia where most of cases are sporadic with no clearly identified cause. However, multiple factors are implicated in the progression of sporadic AD which can be classified as non-modifiable (e.g., genetic) and modifiable (e.g. Type-2 diabetes, diet etc.). Present review focusses on key players particularly the modifiable factors such as Type-2 diabetes (T2D) and diet and their implications in microbiota-gut-brain (MGB) and brain-gut (BG) communication and cognitive functions of healthy brain and their dysfunction in Alzheimer's Disease. Special emphasis has been given on elucidation of the mechanistic aspects of the impact of diet on gut-microbiota and the implications of some of the gut-microbial products in T2D and AD pathology. For example, mechanistically, HFD induces gut dysbiosis with driven metabolites that in turn cause loss of integrity of intestinal barrier with concomitant colonic and systemic chronic low-grade inflammation, associated with obesity and T2D. HFD-induced obesity and T2D parallel neuroinflammation, deposition of Amyloid β (Aβ), and ultimately cognitive impairment. The review also provides a new perspective of the impact of diet on brain-gut and microbiota-gut-brain communication in terms of transcription factors as a commonly spoken language that may facilitates the interaction between gut and brain of obese diabetic patients who are at a higher risk of developing cognitive impairment and AD. Other commonality such as tyrosine kinase expression and functions maintaining intestinal integrity on one hand and the phagocytic clarence by migratory microglial functions in brain are also discussed. Lastly, the characterization of the key players future research that might shed lights on novel potential pharmacological target to impede AD progression are also discussed.
Collapse
Affiliation(s)
| | | | - Narendra Kumar
- Department of Pharmaceutical Sciences, ILR College of Pharmacy, Texas A&M Health Science Center, Kingsville, TX 78363, USA
| |
Collapse
|
2
|
Sathyasaikumar KV, Blanco-Ayala T, Zheng Y, Schwieler L, Erhardt S, Tufvesson-Alm M, Poeggeler B, Schwarcz R. The Tryptophan Metabolite Indole-3-Propionic Acid Raises Kynurenic Acid Levels in the Rat Brain In Vivo. Int J Tryptophan Res 2024; 17:11786469241262876. [PMID: 38911967 PMCID: PMC11191616 DOI: 10.1177/11786469241262876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 05/22/2024] [Indexed: 06/25/2024] Open
Abstract
Alterations in the composition of the gut microbiota may be causally associated with several brain diseases. Indole-3-propionic acid (IPrA) is a tryptophan-derived metabolite, which is produced by intestinal commensal microbes, rapidly enters the circulation, and crosses the blood-brain barrier. IPrA has neuroprotective properties, which have been attributed to its antioxidant and bioenergetic effects. Here, we evaluate an alternative and/or complementary mechanism, linking IPrA to kynurenic acid (KYNA), another neuroprotective tryptophan metabolite. Adult Sprague-Dawley rats received an oral dose of IPrA (200 mg/kg), and both IPrA and KYNA were measured in plasma and frontal cortex 90 minutes, 6 or 24 hours later. IPrA and KYNA levels increased after 90 minutes and 6 hours (brain IPrA: ~56- and ~7-fold; brain KYNA: ~4- and ~3-fold, respectively). In vivo microdialysis, performed in the medial prefrontal cortex and in the striatum, revealed increased KYNA levels (~2.5-fold) following the administration of IPrA (200 mg/kg, p.o), but IPrA failed to affect extracellular KYNA when applied locally. Finally, treatment with 100 or 350 mg IPrA, provided daily to the animals in the chow for a week, resulted in several-fold increases of IPrA and KYNA levels in both plasma and brain. These results suggest that exogenously supplied IPrA may provide a novel strategy to affect the function of KYNA in the mammalian brain.
Collapse
Affiliation(s)
- Korrapati V Sathyasaikumar
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, USA
| | - Tonali Blanco-Ayala
- Neurobiochemistry and Behavior Laboratory, National Institute of Neurology and Neurosurgery “Manuel Velasco Suárez,” Mexico City, Mexico
| | - Yiran Zheng
- Departments of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | - Lilly Schwieler
- Departments of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | - Sophie Erhardt
- Departments of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | | | - Burkhard Poeggeler
- Department of Physiology, Johann-Friedrich-Blumenbach-Institute for Zoology and Anthropology, Georg-August-Universität Göttingen, Germany
| | - Robert Schwarcz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, USA
| |
Collapse
|
3
|
Chen Y, Al-Nusaif M, Li S, Tan X, Yang H, Cai H, Le W. Progress on early diagnosing Alzheimer's disease. Front Med 2024; 18:446-464. [PMID: 38769282 DOI: 10.1007/s11684-023-1047-1] [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: 09/23/2023] [Accepted: 11/15/2023] [Indexed: 05/22/2024]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.
Collapse
Affiliation(s)
- Yixin Chen
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China
| | - Murad Al-Nusaif
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China
| | - Song Li
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China
| | - Xiang Tan
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China
| | - Huijia Yang
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China
| | - Huaibin Cai
- Transgenic Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Weidong Le
- Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China.
- Institute of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China.
| |
Collapse
|
4
|
Gómez-Pascual A, Naccache T, Xu J, Hooshmand K, Wretlind A, Gabrielli M, Lombardo MT, Shi L, Buckley NJ, Tijms BM, Vos SJB, Ten Kate M, Engelborghs S, Sleegers K, Frisoni GB, Wallin A, Lleó A, Popp J, Martinez-Lage P, Streffer J, Barkhof F, Zetterberg H, Visser PJ, Lovestone S, Bertram L, Nevado-Holgado AJ, Gualerzi A, Picciolini S, Proitsi P, Verderio C, Botía JA, Legido-Quigley C. Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease. Comput Biol Med 2024; 176:108588. [PMID: 38761503 DOI: 10.1016/j.compbiomed.2024.108588] [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: 01/04/2024] [Revised: 05/09/2024] [Accepted: 05/09/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.
Collapse
Affiliation(s)
- Alicia Gómez-Pascual
- Department of Information and Communications Engineering Faculty of Informatics, University of Murcia, Murcia, Spain; Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Talel Naccache
- Department of Data Science, City University of London, United Kingdom
| | - Jin Xu
- Institute of Pharmaceutical Science, King's College London, London, United Kingdom
| | | | | | | | - Marta Tiffany Lombardo
- CNR Institute of Neuroscience, 20854, Vedano al Lambro, Italy; School of Medicine and Surgery, University of Milano-Bicocca, 20126, Italy
| | - Liu Shi
- Novo Nordisk Research Centre Oxford (NNRCO), Oxford, United Kingdom
| | - Noel J Buckley
- Department of Psychiatry, University of Oxford, United Kingdom; Kavli Institute for Nanoscience Discovery, Denmark
| | - Betty M Tijms
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium; Department of Neurology and Bru-BRAIN, UZ Brussel and Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Kristel Sleegers
- Complex Genetics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium; Institute Born-Bunge, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Giovanni B Frisoni
- University of Geneva, Geneva, Switzerland; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Alberto Lleó
- Neurology Department, Hospital Sant Pau, Barcelona, Spain, Centro de Investigación en Red en enfermedades neurodegenerativas (CIBERNED)
| | - Julius Popp
- Old age psychiatry, University Hospital of Lausanne, University of Lausanne, Switzerland; Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, University of Zürich, Switzerland
| | | | - Johannes Streffer
- AC Immune SA, Lausanne, Switzerland, formerly Janssen R&D, LLC. Beerse, Belgium at the time of study conduct
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, United Kingdom
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden; UK Dementia Research Institute at UCL, London, United Kingdom; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
| | - Pieter Jelle Visser
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands; Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, United Kingdom; Janssen Medical (UK), High Wycombe, United Kingdom
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany; Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Alice Gualerzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS in Milan, Italy
| | | | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | | | - Juan A Botía
- Department of Information and Communications Engineering Faculty of Informatics, University of Murcia, Murcia, Spain
| | - Cristina Legido-Quigley
- Steno Diabetes Center Copenhagen, Herlev, Denmark; Institute of Pharmaceutical Science, King's College London, London, United Kingdom.
| |
Collapse
|
5
|
Yuan S, Dan L, Zhang Y, Wu J, Zhao J, Kivipelto M, Chen J, Ludvigsson JF, Li X, Larsson SC. Digestive System Diseases, Genetic Risk, and Incident Dementia: A Prospective Cohort Study. Am J Prev Med 2024; 66:516-525. [PMID: 37918457 DOI: 10.1016/j.amepre.2023.10.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 11/04/2023]
Abstract
INTRODUCTION Although digestive system disease affects gut microbiota and their metabolites associated with dementia risk, the association between digestive system diseases and incident dementia has not yet been established. METHODS This cohort analysis included 458,181 participants free of baseline dementia in the UK Biobank (2006-2021). The associations of 14 digestive system diseases with dementia incidence were examined in 2022 using Cox proportional hazards regression models. Analyses were performed to differentiate the associations for early-onset (age <65 years) and late-onset (age ≥65 years) dementia. Interaction and stratification analyses were performed for polygenic risk score and APOE. RESULTS During a median follow-up of 12.4 years, 6,415 incident dementia cases were diagnosed. Eleven digestive system diseases showed significant associations with an increased risk of dementia after controlling for covariates and multiple testing. Compared with hazard ratios for individuals without digestive system diseases, the hazard ratios of dementia increased from 1.15 (95% confidence interval=1.09, 1.23) for patients with intestinal diverticular disease to 2.31 (95% confidence interval=1.98, 2.70) for patients with cirrhosis. The associations were different between certain digestive system diseases and dementia by onset age. The associations appeared to be stronger for cirrhosis (Q=0.001), irritable bowel syndrome (Q<0.001), gastritis and duodenitis (Q=0.002), gastroesophageal reflux disease (Q<0.001), ulcerative colitis (Q=0.047), gallbladder disease (Q=0.012), and peptic ulcer (Q=0.030) with early-onset dementia. There were no interactions for polygenic risk score or APOE (p>0.05). CONCLUSIONS These findings suggest an increased need for dementia prevention among patients with digestive system diseases.
Collapse
Affiliation(s)
- Shuai Yuan
- Department of Big Data in Health Science, School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lintao Dan
- Department of Big Data in Health Science, School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Zhang
- Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jing Wu
- Aging Research Center (ARC), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Jianhui Zhao
- Department of Big Data in Health Science, School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland; Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Jie Chen
- Department of Big Data in Health Science, School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Jonas F Ludvigsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Pediatrics, Örebro University Hospital, Örebro, Sweden
| | - Xue Li
- Department of Big Data in Health Science, School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| |
Collapse
|
6
|
Mateo D, Marquès M, Domingo JL, Torrente M. Influence of gut microbiota on the development of most prevalent neurodegenerative dementias and the potential effect of probiotics in elderly: A scoping review. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32959. [PMID: 37850544 DOI: 10.1002/ajmg.b.32959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/29/2023] [Accepted: 09/19/2023] [Indexed: 10/19/2023]
Abstract
Dementia is one of today's greatest public health challenges. Its high socio-economic impact and difficulties in diagnosis and treatment are of increasing concern to an aging world population. In recent years, the study of the relationship between gut microbiota and different neurocognitive disorders has gained a considerable interest. Several studies have reported associations between gut microbiota dysbiosis and some types of dementia. Probiotics have been suggested to restore dysbiosis and to improve neurocognitive symptomatology in these dementias. Based on these previous findings, the available scientific evidence on the gut microbiota in humans affected by the most prevalent dementias, as well as the probiotic trials conducted in these patients in recent years, have been here reviewed. Decreased concentrations of short-chain fatty acids (SCFA) and other bacterial metabolites appear to play a major role in the onset of neurocognitive symptoms in Alzheimer disease (AD) and Parkinson disease dementia (PDD). Increased abundance of proinflammatory taxa could be closely related to the more severe clinical symptoms in both, as well as in Lewy Bodies dementia. Important lack of information was noted in Frontotemporal dementia behavioral variant. Moreover, geographical differences in the composition of the gut microbiota have been reported in AD. Some potential beneficial effects of probiotics in AD and PDD have been reported. However, due to the controversial results further investigations are clearly necessary.
Collapse
Affiliation(s)
- David Mateo
- Laboratory of Toxicology and Environmental Health - TecnATox, School of Medicine, Universitat Rovira i Virgili, Reus, Catalonia, Spain
| | - Montse Marquès
- Laboratory of Toxicology and Environmental Health - TecnATox, School of Medicine, Universitat Rovira i Virgili, Reus, Catalonia, Spain
| | - José L Domingo
- Laboratory of Toxicology and Environmental Health - TecnATox, School of Medicine, Universitat Rovira i Virgili, Reus, Catalonia, Spain
| | - Margarita Torrente
- Laboratory of Toxicology and Environmental Health - TecnATox, School of Medicine, Universitat Rovira i Virgili, Reus, Catalonia, Spain
- Department of Psychology, CRAMC (Research Center for Behaviour Assessment), Faculty of Education Sciences and Psychology, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
- Institute Lerin Neurocognitive, Alzheimer and other Neurocognitive Disorders Association, Reus, Catalonia, Spain
| |
Collapse
|
7
|
Han Y, Zeng X, Hua L, Quan X, Chen Y, Zhou M, Chuang Y, Li Y, Wang S, Shen X, Wei L, Yuan Z, Zhao Y. The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders. MICROBIOME 2024; 12:12. [PMID: 38243335 PMCID: PMC10797890 DOI: 10.1186/s40168-023-01717-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 11/07/2023] [Indexed: 01/21/2024]
Abstract
BACKGROUND The increasing prevalence of neurocognitive disorders (NCDs) in the aging population worldwide has become a significant concern due to subjectivity of evaluations and the lack of precise diagnostic methods and specific indicators. Developing personalized diagnostic strategies for NCDs has therefore become a priority. RESULTS Multimodal electroencephalography (EEG) data of a matched cohort of normal aging (NA) and NCDs seniors were recorded, and their faecal samples and urine exosomes were collected to identify multi-omics signatures and metabolic pathways in NCDs by integrating metagenomics, proteomics, and metabolomics analysis. Additionally, experimental verification of multi-omics signatures was carried out in aged mice using faecal microbiota transplantation (FMT). We found that NCDs seniors had low EEG power spectral density and identified specific microbiota, including Ruminococcus gnavus, Enterocloster bolteae, Lachnoclostridium sp. YL 32, and metabolites, including L-tryptophan, L-glutamic acid, gamma-aminobutyric acid (GABA), and fatty acid esters of hydroxy fatty acids (FAHFAs), as well as disturbed biosynthesis of aromatic amino acids and TCA cycle dysfunction, validated in aged mice. Finally, we employed a support vector machine (SVM) algorithm to construct a machine learning model to classify NA and NCDs groups based on the fusion of EEG data and multi-omics profiles and the model demonstrated 92.69% accuracy in classifying NA and NCDs groups. CONCLUSIONS Our study highlights the potential of multi-omics profiling and EEG data fusion in personalized diagnosis of NCDs, with the potential to improve diagnostic precision and provide insights into the underlying mechanisms of NCDs. Video Abstract.
Collapse
Affiliation(s)
- Yan Han
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | - Xinglin Zeng
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | - Lin Hua
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | - Xingping Quan
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | - Ying Chen
- School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China
| | - Manfei Zhou
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | | | - Yang Li
- Department of Gastrointestinal Surgery, Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, 518020, China
| | - Shengpeng Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China
| | - Xu Shen
- Jiangsu Key Laboratory of Drug Target and Drug for Degenerative Diseases, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lai Wei
- School of Pharmaceutical Science, Southern Medical University, Guangzhou, 510515, China
| | - Zhen Yuan
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China.
| | - Yonghua Zhao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, 999078, Macau SAR, China.
- Department of Pharmaceutical Sciences, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China.
| |
Collapse
|
8
|
Bhalala OG, Watson R, Yassi N. Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease. Int J Mol Sci 2024; 25:1231. [PMID: 38279230 PMCID: PMC10816901 DOI: 10.3390/ijms25021231] [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: 12/07/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 01/28/2024] Open
Abstract
Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.
Collapse
Affiliation(s)
- Oneil G. Bhalala
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
| | - Rosie Watson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
| | - Nawaf Yassi
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
| |
Collapse
|
9
|
Huang YH, Chen WY, Liu YH, Li TY, Lin CP, Cheong PL, Wang YM, Jeng JS, Sun CW, Wu CC. Mild cognitive impairment estimation based on functional near-infrared spectroscopy. JOURNAL OF BIOPHOTONICS 2024; 17:e202300251. [PMID: 37697821 DOI: 10.1002/jbio.202300251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/13/2023]
Abstract
Patients with mild cognitive impairment (MCI) are at a high risk of developing future dementia. However, early identification and active intervention could potentially reduce its morbidity and the incidence of dementia. Functional near-infrared spectroscopy (fNIRS) has been proposed as a noninvasive modality for detecting oxygenation changes in the time-varying hemodynamics of the prefrontal cortex. This study sought to provide an effective method for detecting patients with MCI using fNIRS and the Wisconsin card sorting test (WCST) to evaluate changes in blood oxygenation. The results revealed that all groups with a lower mini-mental state examination grade had a higher increase in HHb concentration during a modified WCST (MCST). The increase in the change in oxygenated hemoglobin concentration in the stroke group was smaller than that in the normal group due to weak cerebrovascular reactivity.
Collapse
Affiliation(s)
- Yi-Hua Huang
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Yu Chen
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yao-Hong Liu
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Ting-Ying Li
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Medical Device Innovation and Translation Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Pou-Leng Cheong
- Department of Pediatrics, National Taiwan University Hospital, Hsinchu, Taiwan
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yi-Min Wang
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Jiann-Shing Jeng
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chia-Wei Sun
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Medical Device Innovation and Translation Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Biomedical Engineering, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Chau-Chung Wu
- Department of Internal Medicine (Cardiology Section), National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Medical Education and Bioethics, College of Medicine, National Taiwan University, Taipei, Taiwan
| |
Collapse
|
10
|
Zhou Y, Chen Y, He H, Peng M, Zeng M, Sun H. The role of the indoles in microbiota-gut-brain axis and potential therapeutic targets: A focus on human neurological and neuropsychiatric diseases. Neuropharmacology 2023; 239:109690. [PMID: 37619773 DOI: 10.1016/j.neuropharm.2023.109690] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/17/2023] [Accepted: 08/19/2023] [Indexed: 08/26/2023]
Abstract
At present, a large number of relevant studies have suggested that the changes in gut microbiota are related to the course of nervous system diseases, and the microbiota-gut-brain axis is necessary for the proper functioning of the nervous system. Indole and its derivatives, as the products of the gut microbiota metabolism of tryptophan, can be used as ligands to regulate inflammation and autoimmune response in vivo. In recent years, some studies have found that the levels of indole and its derivatives differ significantly between patients with central nervous system diseases and healthy individuals, suggesting that they may be important mediators for the involvement of the microbiota-gut-brain axis in the disease course. Tryptophan metabolites produced by gut microbiota are involved in multiple physiological reactions, take indole for example, it participates in the process of inflammation and anti-inflammatory effects through various cellular physiological activities mediated by aromatic hydrocarbon receptors (AHR), which can influence a variety of neurological and neuropsychiatric diseases. This review mainly explores and summarizes the relationship between indoles and human neurological and neuropsychiatric disorders, including ischemic stroke, Alzheimer's disease, Parkinson's disease, multiple sclerosis, cognitive impairment, depression and anxiety, and puts forward that the level of indoles can be regulated through various direct or indirect ways to improve the prognosis of central nervous system diseases and reverse the dysfunction of the microbiota-gut-brain axis. This article is part of the Special Issue on "Microbiome & the Brain: Mechanisms & Maladies".
Collapse
Affiliation(s)
- Yi Zhou
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Yue Chen
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Hui He
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Meichang Peng
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Meiqin Zeng
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Haitao Sun
- Clinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital and the Second Clinical Medical College, Southern Medical University, Guangzhou, 510280, China; Neurosurgery Center, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China; Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, 510280, China.
| |
Collapse
|
11
|
Wang K, Theeke LA, Liao C, Wang N, Lu Y, Xiao D, Xu C. Deep learning analysis of UPLC-MS/MS-based metabolomics data to predict Alzheimer's disease. J Neurol Sci 2023; 453:120812. [PMID: 37776718 DOI: 10.1016/j.jns.2023.120812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/22/2023] [Accepted: 09/14/2023] [Indexed: 10/02/2023]
Abstract
OBJECTIVE Metabolic biomarkers can potentially inform disease progression in Alzheimer's disease (AD). The purpose of this study is to identify and describe a new set of diagnostic biomarkers for developing deep learning (DL) tools to predict AD using Ultra Performance Liquid Chromatography Mass Spectrometry (UPLC-MS/MS)-based metabolomics data. METHODS A total of 177 individuals, including 78 with AD and 99 with cognitive normal (CN), were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort along with 150 metabolomic biomarkers. We performed feature selection using the Least Absolute Shrinkage and Selection Operator (LASSO). The H2O DL function was used to build multilayer feedforward neural networks to predict AD. RESULTS The LASSO selected 21 metabolic biomarkers. To develop DL models, the 21 biomarkers identified by LASSO were imported into the H2O package. The data was split into 70% for training and 30% for validation. The best DL model with two layers and 18 neurons achieved an accuracy of 0.881, F1-score of 0.892, and AUC of 0.873. Several metabolomic biomarkers involved in glucose and lipid metabolism, in particular bile acid metabolites, were associated with APOE-ε4 allele and clinical biomarkers (Aβ42, tTau, pTau), cognitive assessments [the Alzheimer's Disease Assessment Scale-cognitive subscale 13 (ADAS13), the Mini-Mental State Examination (MMSE)], and hippocampus volume. CONCLUSIONS This study identified a new set of diagnostic metabolomic biomarkers for developing DL tools to predict AD. These biomarkers may help with early diagnosis, prognostic risk stratification, and/or early treatment interventions for patients at risk for AD.
Collapse
Affiliation(s)
- Kesheng Wang
- School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV 26506, USA.
| | - Laurie A Theeke
- School of Nursing, The George Washington University, Ashburn, VA 20147, USA
| | - Christopher Liao
- Department of Electrical and Computer Engineering, Boston University, MA 02215, USA
| | - Nianyang Wang
- Department of Health Policy and Management, School of Public Health, University of Maryland, College Park, MD 20742, USA
| | - Yongke Lu
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25755, USA
| | - Danqing Xiao
- Department of STEM, School of Arts and Sciences, Regis College, Weston, MA 02493, USA
| | - Chun Xu
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA.
| |
Collapse
|
12
|
Huang CH, Lee WJ, Huang YL, Tsai TF, Chen LK, Lin CH. Sebacic Acid as a Potential Age-Related Biomarker of Liver Aging: Evidence Linking Mice and Human. J Gerontol A Biol Sci Med Sci 2023; 78:1799-1808. [PMID: 37148322 DOI: 10.1093/gerona/glad121] [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: 11/18/2022] [Indexed: 05/08/2023] Open
Abstract
The aging process is complicated and involves diverse organ dysfunction; furthermore, the biomarkers that are able to reflect biological aging are eagerly sought after to monitor the system-wide decline associated with the aging process. To address this, we performed a metabolomics analysis using a longitudinal cohort study from Taiwan (N = 710) and established plasma metabolomic age using a machine learning algorithm. The resulting estimation of age acceleration among the older adults was found to be correlated with HOMA-insulin resistance. In addition, a sliding window analysis was used to investigate the undulating decrease in hexanoic and heptanoic acids that occurs among the older adults at different ages. A comparison of the metabolomic alterations associated with aging between humans and mice implied that ω-oxidation of medium-chain fatty acids was commonly dysregulated in older subjects. Among these fatty acids, sebacic acid, an ω-oxidation product produced by the liver, was significantly decreased in the plasma of both older humans and aged mice. Notably, an increase in the production and consumption of sebacic acid within the liver tissue of aged mice was observed, along with an elevation of pyruvate-to-lactate conversion. Taken together, our study reveals that sebacic acid and metabolites of ω-oxidation are the common aging biomarkers in both humans and mice. The further analysis suggests that sebacic acid may play an energetic role in supporting the production of acetyl-CoA during liver aging, and thus its alteration in plasma concentration potentially reflects the aging process.
Collapse
Affiliation(s)
- Chen-Hua Huang
- Department of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Wei-Ju Lee
- Department of Geriatric Medicine, School of Medicine, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, Yilan, Taiwan
| | - Yi-Long Huang
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Ting-Fen Tsai
- Department of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Miaoli, Taiwan
| | - Liang-Kung Chen
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chao-Hsiung Lin
- Department of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| |
Collapse
|
13
|
Does the Gut Microbial Metabolome Really Matter? The Connection between GUT Metabolome and Neurological Disorders. Nutrients 2022; 14:nu14193967. [PMID: 36235622 PMCID: PMC9571089 DOI: 10.3390/nu14193967] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 11/30/2022] Open
Abstract
Herein we gathered updated knowledge regarding the alterations of gut microbiota (dysbiosis) and its correlation with human neurodegenerative and brain-related diseases, e.g., Alzheimer’s and Parkinson’s. This review underlines the importance of gut-derived metabolites and gut metabolic status as the main players in gut-brain crosstalk and their implications on the severity of neural conditions. Scientific evidence indicates that the administration of probiotic bacteria exerts beneficial and protective effects as reduced systemic inflammation, neuroinflammation, and inhibited neurodegeneration. The experimental results performed on animals, but also human clinical trials, show the importance of designing a novel microbiota-based probiotic dietary supplementation with the aim to prevent or ease the symptoms of Alzheimer’s and Parkinson’s diseases or other forms of dementia or neurodegeneration.
Collapse
|
14
|
Gut Microbiota Dysbiosis after Traumatic Brain Injury Contributes to Persistent Microglial Activation Associated with Upregulated Lyz2 and Shifted Tryptophan Metabolic Phenotype. Nutrients 2022; 14:nu14173467. [PMID: 36079724 PMCID: PMC9459947 DOI: 10.3390/nu14173467] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 08/19/2022] [Accepted: 08/19/2022] [Indexed: 11/22/2022] Open
Abstract
Traumatic brain injury (TBI) is a common cause of disability and mortality, affecting millions of people every year. The neuroinflammation and immune response post-TBI initially have neuroprotective and reparative effects, but prolonged neuroinflammation leads to secondary injury and increases the risk of chronic neurodegenerative diseases. Persistent microglial activation plays a critical role in chronic neuroinflammation post-TBI. Given the bidirectional communication along the brain–gut axis, it is plausible to suppose that gut microbiota dysbiosis post-TBI influences microglial activation. In the present study, hippocampal microglial activation was observed at 7 days and 28 days post-TBI. However, in TBI mice with a depletion of gut microbiota, microglia were activated at 7 days post-TBI, but not at 28 days post-TBI, indicating that gut microbiota contributes to the long-term activation of microglia post-TBI. In addition, in conventional mice colonized by the gut microbiota of TBI mice using fecal microbiota transplant (FMT), microglial activation was observed at 28 days post-TBI, but not at 7 days post-TBI, supporting the role of gut microbiota dysbiosis in persistent microglial activation post-TBI. The RNA sequencing of the hippocampus identified a microglial activation gene, Lyz2, which kept upregulation post-TBI. This persistent upregulation was inhibited by oral antibiotics and partly induced by FMT. 16s rRNA gene sequencing showed that the composition and function of gut microbiota shifted over time post-TBI with progressive dysbiosis, and untargeted metabolomics profiling revealed that the tryptophan metabolic phenotype was differently reshaped at 7 days and 28 days post-TBI, which may play a role in the persistent upregulation of Lyz2 and the activation of microglia. This study implicates that gut microbiota and Lyz2 are potential targets for the development of novel strategies to address persistent microglial activation and chronic neuroinflammation post-TBI, and further investigations are warranted to elucidate the specific mechanism.
Collapse
|
15
|
Biological Effects of Indole-3-Propionic Acid, a Gut Microbiota-Derived Metabolite, and Its Precursor Tryptophan in Mammals' Health and Disease. Int J Mol Sci 2022; 23:ijms23031222. [PMID: 35163143 PMCID: PMC8835432 DOI: 10.3390/ijms23031222] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/19/2022] [Accepted: 01/19/2022] [Indexed: 02/06/2023] Open
Abstract
Actions of symbiotic gut microbiota are in dynamic balance with the host’s organism to maintain homeostasis. Many different factors have an impact on this relationship, including bacterial metabolites. Several substrates for their synthesis have been established, including tryptophan, an exogenous amino acid. Many biological processes are influenced by the action of tryptophan and its endogenous metabolites, serotonin, and melatonin. Recent research findings also provide evidence that gut bacteria-derived metabolites of tryptophan share the biological effects of their precursor. Thus, this review aims to investigate the biological actions of indole-3-propionic acid (IPA), a gut microbiota-derived metabolite of tryptophan. We searched PUBMED and Google Scholar databases to identify pre-clinical and clinical studies evaluating the impact of IPA on the health and pathophysiology of the immune, nervous, gastrointestinal and cardiovascular system in mammals. IPA exhibits a similar impact on the energetic balance and cardiovascular system to its precursor, tryptophan. Additionally, IPA has a positive impact on a cellular level, by preventing oxidative stress injury, lipoperoxidation and inhibiting synthesis of proinflammatory cytokines. Its synthesis can be diminished in the presence of different risk factors of atherosclerosis. On the other hand, protective factors, such as the introduction of a Mediterranean diet, tend to increase its plasma concentration. IPA seems to be a promising new target, linking gut health with the cardiovascular system.
Collapse
|