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Barzegar Behrooz A, Latifi‐Navid H, Lotfi J, Khodagholi F, Shojaei S, Ghavami S, Fahanik Babaei J. CSF amino acid profiles in ICV-streptozotocin-induced sporadic Alzheimer's disease in male Wistar rat: a metabolomics and systems biology perspective. FEBS Open Bio 2024; 14:1116-1132. [PMID: 38769074 PMCID: PMC11216934 DOI: 10.1002/2211-5463.13814] [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: 03/05/2024] [Revised: 03/19/2024] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Alzheimer's disease (AD) is an increasingly important public health concern due to the increasing proportion of older individuals within the general population. The impairment of processes responsible for adequate brain energy supply primarily determines the early features of the aging process. Restricting brain energy supply results in brain hypometabolism prior to clinical symptoms and is anatomically and functionally associated with cognitive impairment. The present study investigated changes in metabolic profiles induced by intracerebroventricular-streptozotocin (ICV-STZ) in an AD-like animal model. To this end, male Wistar rats received a single injection of STZ (3 mg·kg-1) by ICV (2.5 μL into each ventricle for 5 min on each side). In the second week after receiving ICV-STZ, rats were tested for cognitive performance using the Morris Water Maze test and subsequently prepared for positron emission tomography (PET) to confirm AD-like symptoms. Tandem Mass Spectrometry (MS/MS) analysis was used to detect amino acid changes in cerebrospinal fluid (CFS) samples. Our metabolomics study revealed a reduction in the concentrations of various amino acids (alanine, arginine, aspartic acid, glutamic acid, glycine, isoleucine, methionine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine, and valine) in CSF of ICV-STZ-treated animals as compared to controls rats. The results of the current study indicate amino acid levels could potentially be considered targets of nutritional and/or pharmacological interventions to interfere with AD progression.
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Affiliation(s)
- Amir Barzegar Behrooz
- Electrophysiology Research Center, Neuroscience InstituteTehran University of Medical SciencesIran
- Department of Human Anatomy and Cell Science, College of MedicineUniversity of ManitobaWinnipegCanada
| | - Hamid Latifi‐Navid
- Electrophysiology Research Center, Neuroscience InstituteTehran University of Medical SciencesIran
- Department of Molecular MedicineNational Institute of Genetic Engineering and BiotechnologyTehranIran
- School of Biological SciencesInstitute for Research in Fundamental Sciences (IPM)TehranIran
| | - Jabar Lotfi
- Growth and Development Research CenterTehran University of Medical SciencesIran
| | - Fariba Khodagholi
- Neuroscience Research CenterShahid Beheshti University of Medical SciencesTehranIran
| | - Shahla Shojaei
- Department of Human Anatomy and Cell Science, College of MedicineUniversity of ManitobaWinnipegCanada
| | - Saeid Ghavami
- Department of Human Anatomy and Cell Science, College of MedicineUniversity of ManitobaWinnipegCanada
- Faculty of Medicine in ZabrzeUniversity of Technology in KatowiceZabrzePoland
- Research Institute of Oncology and HematologyCancer Care Manitoba‐University of ManitobaWinnipegCanada
- Children Hospital Research Institute of ManitobaUniversity of ManitobaWinnipegCanada
| | - Javad Fahanik Babaei
- Electrophysiology Research Center, Neuroscience InstituteTehran University of Medical SciencesIran
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Carraro C, Montgomery JV, Klimmt J, Paquet D, Schultze JL, Beyer MD. Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs. Front Mol Neurosci 2024; 17:1414886. [PMID: 38952421 PMCID: PMC11215216 DOI: 10.3389/fnmol.2024.1414886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/04/2024] [Indexed: 07/03/2024] Open
Abstract
Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.
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Affiliation(s)
- Caterina Carraro
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Jessica V. Montgomery
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Bonn, Germany
| | - Julien Klimmt
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Dominik Paquet
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Joachim L. Schultze
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
- PRECISE, Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn and West German Genome Center, Bonn, Germany
| | - Marc D. Beyer
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Bonn, Germany
- PRECISE, Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn and West German Genome Center, Bonn, Germany
- Immunogenomics & Neurodegeneration, Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Bonn, Germany
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Zhuang H, Cao X, Tang X, Zou Y, Yang H, Liang Z, Yan X, Chen X, Feng X, Shen L. Investigating metabolic dysregulation in serum of triple transgenic Alzheimer's disease male mice: implications for pathogenesis and potential biomarkers. Amino Acids 2024; 56:10. [PMID: 38315232 PMCID: PMC10844422 DOI: 10.1007/s00726-023-03375-1] [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: 05/15/2023] [Accepted: 11/11/2023] [Indexed: 02/07/2024]
Abstract
Alzheimer's disease (AD) is a multifactorial neurodegenerative disease that lacks convenient and accessible peripheral blood diagnostic markers and effective drugs. Metabolic dysfunction is one of AD risk factors, which leaded to alterations of various metabolites in the body. Pathological changes of the brain can be reflected in blood metabolites that are expected to explain the disease mechanisms or be candidate biomarkers. The aim of this study was to investigate the changes of targeted metabolites within peripheral blood of AD mouse model, with the purpose of exploring the disease mechanism and potential biomarkers. Targeted metabolomics was used to quantify 256 metabolites in serum of triple transgenic AD (3 × Tg-AD) male mice. Compared with controls, 49 differential metabolites represented dysregulation in purine, pyrimidine, tryptophan, cysteine and methionine and glycerophospholipid metabolism. Among them, adenosine, serotonin, N-acetyl-5-hydroxytryptamine, and acetylcholine play a key role in regulating neural transmitter network. The alteration of S-adenosine-L-homocysteine, S-adenosine-L-methionine, and trimethylamine-N-oxide in AD mice serum can served as indicator of AD risk. The results revealed the changes of metabolites in serum, suggesting that metabolic dysregulation in periphery in AD mice may be related to the disturbances in neuroinhibition, the serotonergic system, sleep function, the cholinergic system, and the gut microbiota. This study provides novel insights into the dysregulation of several key metabolites and metabolic pathways in AD, presenting potential avenues for future research and the development of peripheral biomarkers.
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Affiliation(s)
- Hongbin Zhuang
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Xueshan Cao
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Xiaoxiao Tang
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Yongdong Zou
- Center for Instrumental Analysis, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Hongbo Yang
- Center for Instrumental Analysis, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Zhiyuan Liang
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Xi Yan
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, 550025, People's Republic of China
| | - Xiaolu Chen
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, 550025, People's Republic of China
| | - Xingui Feng
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China
| | - Liming Shen
- College of Life Science and Oceanography, Shenzhen University, Shenzhen, 518071, People's Republic of China.
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, People's Republic of China.
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4
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Krishnamoorthy N, Kalyan M, Hediyal TA, Anand N, Kendaganna PH, Pendyala G, Yelamanchili SV, Yang J, Chidambaram SB, Sakharkar MK, Mahalakshmi AM. Role of the Gut Bacteria-Derived Metabolite Phenylacetylglutamine in Health and Diseases. ACS OMEGA 2024; 9:3164-3172. [PMID: 38284070 PMCID: PMC10809373 DOI: 10.1021/acsomega.3c08184] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/30/2024]
Abstract
Over the past few decades, it has been well established that gut microbiota-derived metabolites can disrupt gut function, thus resulting in an array of diseases. Notably, phenylacetylglutamine (PAGln), a bacterial derived metabolite, has recently gained attention due to its role in the initiation and progression of cardiovascular and cerebrovascular diseases. This meta-organismal metabolite PAGln is a byproduct of amino acid acetylation of its precursor phenylacetic acid (PAA) from a range of dietary sources like egg, meat, dairy products, etc. The microbiota-dependent metabolism of phenylalanine produces PAA, which is a crucial intermediate that is catalyzed by diverse microbial catalytic pathways. PAA conjugates with glutamine and glycine in the liver and kidney to predominantly form phenylacetylglutamine in humans and phenylacetylglycine in rodents. PAGln is associated with thrombosis as it enhances platelet activation mediated through the GPCRs receptors α2A, α2B, and β2 ADRs, thereby aggravating the pathological conditions. Clinical evidence suggests that elevated levels of PAGln are associated with pathology of cardiovascular, cerebrovascular, and neurological diseases. This Review further consolidates the microbial/biochemical synthesis of PAGln and discusses its role in the above pathophysiologies.
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Affiliation(s)
- Naveen
Kumar Krishnamoorthy
- Department
of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru 570015, India
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
| | - Manjunath Kalyan
- Department
of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru 570015, India
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
| | - Tousif Ahmed Hediyal
- Department
of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru 570015, India
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
| | - Nikhilesh Anand
- Department
of Pharmacology, College of Medicine, American
University of Antigua, P. O. Box W-1451, Saint John’s, Antigua and Barbuda
| | - Pavan Heggadadevanakote Kendaganna
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
| | - Gurudutt Pendyala
- Department
of Anesthesiology, University of Nebraska
Medical Center (UNMC), Omaha, Nebraska 68198, United States
- Department
of Genetics, Cell Biology, and Anatomy, UNMC, Omaha, Nebraska 68198, United States
- Child Health
Research Institute, UNMC, Omaha, Nebraska 68198, United States
- National
Strategic Research Institute, UNMC, Omaha, Nebraska 68198, United States
| | - Sowmya V. Yelamanchili
- Department
of Anesthesiology, University of Nebraska
Medical Center (UNMC), Omaha, Nebraska 68198, United States
- Department
of Genetics, Cell Biology, and Anatomy, UNMC, Omaha, Nebraska 68198, United States
- National
Strategic Research Institute, UNMC, Omaha, Nebraska 68198, United States
| | - Jian Yang
- Drug
Discovery and Development Research Group, College of Pharmacy and
Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5E5, Canada
| | - Saravana Babu Chidambaram
- Department
of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru 570015, India
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
| | - Meena Kishore Sakharkar
- Drug
Discovery and Development Research Group, College of Pharmacy and
Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5E5, Canada
| | - Arehally M. Mahalakshmi
- Department
of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru 570015, India
- Centre
for Experimental Pharmacology and Toxicology, Central Animal Facility, JSS Academy of Higher Education and Research, Mysuru 570015, India
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5
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Snytnikova O, Telegina D, Savina E, Tsentalovich Y, Kolosova N. Quantitative Metabolomic Analysis of the Rat Hippocampus: Effects of Age and of the Development of Alzheimer's Disease-Like Pathology. J Alzheimers Dis 2024; 99:S327-S344. [PMID: 37980669 DOI: 10.3233/jad-230706] [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] [Indexed: 11/21/2023]
Abstract
Background Alzheimer's disease (AD) is the most common type of dementia in the elderly. Incomplete knowledge about the pathogenesis of this disease determines the absence of medications for the treatment of AD today. Animal models can provide the necessary knowledge to understand the mechanisms of biochemical processes occurring in the body in health and disease. Objective To identify the most promising metabolomic predictors and biomarkers reflecting metabolic disorders in the development of AD signs. Methods High resolution 1H NMR spectroscopy was used for quantitative metabolomic profiling of the hippocampus of OXYS rats, an animal model of sporadic AD, which demonstrates key characteristics of this disease. Animals were examined during several key periods: 20 days group corresponds to the "preclinical" period preceding the development of AD signs, during their manifestation (3 months), and active progression (18 months). Wistar rats of the same age were used as control. Results Ranges of variation and mean concentrations were established for 59 brain metabolites. The main metabolic patterns during aging, which are involved in energy metabolism pathways and metabolic shifts of neurotransmitters, have been established. Of particular note is the significant increase of scyllo-inositol and decrease of hypotaurine in the hippocampus of OXYS rats as compared to Wistars for all studied age groups. Conclusions We suggest that the accumulation of scyllo-inositol and the reduction of hypotaurine in the brain, even at an early age, can be considered as predictors and potential biomarkers of the development of AD signs in OXYS rats and, probably, in humans.
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Affiliation(s)
- Olga Snytnikova
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Darya Telegina
- The Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Ekaterina Savina
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yuri Tsentalovich
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Nataliya Kolosova
- The Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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6
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Milos T, Rojo D, Nedic Erjavec G, Konjevod M, Tudor L, Vuic B, Svob Strac D, Uzun S, Mimica N, Kozumplik O, Barbas C, Zarkovic N, Pivac N, Nikolac Perkovic M. Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110830. [PMID: 37454721 DOI: 10.1016/j.pnpbp.2023.110830] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 06/07/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.
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Affiliation(s)
- Tina Milos
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.
| | - David Rojo
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo CEU, CEU Universities Madrid, Spain.
| | | | - Marcela Konjevod
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.
| | - Lucija Tudor
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.
| | - Barbara Vuic
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.
| | | | - Suzana Uzun
- School of Medicine, University of Zagreb, Zagreb, Croatia; Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapče, Zagreb, Croatia.
| | - Ninoslav Mimica
- Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapče, Zagreb, Croatia.
| | - Oliver Kozumplik
- Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapče, Zagreb, Croatia.
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo CEU, CEU Universities Madrid, Spain.
| | - Neven Zarkovic
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.
| | - Nela Pivac
- Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia; University of Applied Sciences Hrvatsko Zagorje Krapina, Krapina, Croatia.
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7
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Winchester LM, Harshfield EL, Shi L, Badhwar A, Khleifat AA, Clarke N, Dehsarvi A, Lengyel I, Lourida I, Madan CR, Marzi SJ, Proitsi P, Rajkumar AP, Rittman T, Silajdžić E, Tamburin S, Ranson JM, Llewellyn DJ. Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia. Alzheimers Dement 2023; 19:5860-5871. [PMID: 37654029 PMCID: PMC10840606 DOI: 10.1002/alz.13390] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/13/2023] [Accepted: 06/19/2023] [Indexed: 09/02/2023]
Abstract
With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.
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Affiliation(s)
| | - Eric L Harshfield
- Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, Cambridge, UK
| | - Liu Shi
- Novo Nordisk Research Centre Oxford (NNRCO), Headington, UK
| | - AmanPreet Badhwar
- Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Faculté de Médecine, Université de Montréal, Montreal, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Ahmad Al Khleifat
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Natasha Clarke
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Amir Dehsarvi
- School of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Imre Lengyel
- Wellcome-Wolfson Institute of Experimental Medicine, Queen's University, Belfast, UK
| | - Ilianna Lourida
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | | | - Sarah J Marzi
- UK Dementia Research Institute at Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Petroula Proitsi
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anto P Rajkumar
- Institute of Mental Health, Mental Health and Clinical Neurosciences academic unit, University of Nottingham, Nottingham, UK, Mental health services of older people, Nottinghamshire healthcare NHS foundation trust, Nottingham, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Edina Silajdžić
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Janice M Ranson
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | - David J Llewellyn
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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8
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Lohinai ZM, Ruksakiet K, Földes A, Dinya E, Levine M. Genetic Control of GCF Exudation: Innate Immunity Genes and Periodontitis Susceptibility. Int J Mol Sci 2023; 24:14249. [PMID: 37762554 PMCID: PMC10532312 DOI: 10.3390/ijms241814249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/07/2023] [Accepted: 08/13/2023] [Indexed: 09/29/2023] Open
Abstract
Chronic periodontitis is a bacterial infection associated with dentally adherent biofilm (plaque) accumulation and age-related comorbidities. The disease begins as an inflammatory exudate from gingival margins, gingival crevicular fluid (GCF) in response to biofilm lysine. After a week of experimental gingivitis (no oral hygiene), biofilm lysine concentration was linearly related to biofilm accumulation (plaque index) but to GCF as an arch-shaped double curve which separated 9 strong from 6 weak GCF responders (hosts). Host DNA was examined for single nucleotide polymorphisms (SNPs) of alleles reported in 7 periodontitis-associated genes. Across all 15 hosts, an adenine SNP (A) at IL1B-511 (rs16944), was significant for strong GCF (Fisher's exact test, p < 0.05), and a thymidine SNP (T) at IL1B+3954 (rs1143634) for weak GCF provided 2 hosts possessing IL6-1363(T), rs2069827, were included. The phenotype of IL1B+3954(T) was converted from weak to strong in one host, and of the non-T allele from strong to weak in the other (specific epistasis, Fisher's exact test, p < 0.01). Together with homozygous alternate or reference SNPs at IL10-1082 or CD14-260 in 4 hosts, all hosts were identified as strong or weak GCF responders. The GCF response is therefore a strong or weak genetic trait that indicates strong or weak innate immunity in EG and controllable or uncontrollable periodontal disease, dental implant survival and late-life comorbidities.
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Affiliation(s)
- Zsolt M. Lohinai
- Department of Restorative Dentistry and Endodontics, Semmelweis University, H-1088 Budapest, Hungary;
| | - Kasidid Ruksakiet
- Department of Oral Biology, Semmelweis University, H-1089 Budapest, Hungary; (K.R.); (A.F.)
- Department of Restorative Dentistry, Faculty of Dentistry, Naresuan University, Phitsanulok 65000, Thailand
| | - Anna Földes
- Department of Oral Biology, Semmelweis University, H-1089 Budapest, Hungary; (K.R.); (A.F.)
| | - Elek Dinya
- Digital Health Department, Semmelweis University, H-1094 Budapest, Hungary;
| | - Martin Levine
- Department of Periodontology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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