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Gurdon B, Yates SC, Csucs G, Groeneboom NE, Hadad N, Telpoukhovskaia M, Ouellette A, Ouellette T, O'Connell KMS, Singh S, Murdy TJ, Merchant E, Bjerke I, Kleven H, Schlegel U, Leergaard TB, Puchades MA, Bjaalie JG, Kaczorowski CC. Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. Commun Biol 2024; 7:605. [PMID: 38769398 PMCID: PMC11106287 DOI: 10.1038/s42003-024-06242-1] [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: 08/16/2023] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.
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Affiliation(s)
- Brianna Gurdon
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Sharon C Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Gergely Csucs
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Nicolaas E Groeneboom
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Niran Hadad
- The Jackson Laboratory, Bar Harbor, ME, USA
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | - Andrew Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Tionna Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Kristen M S O'Connell
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Surjeet Singh
- The Jackson Laboratory, Bar Harbor, ME, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Ingvild Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
| | - Catherine C Kaczorowski
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA.
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA.
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
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Beigh S, Adnan R, Abdulaziz AJ, Abdullah S, Nasser N, Ghazzay R, Abdulaziz R, Mohammed E, Ahmad RM, Ali Alshehri M. Dementia and Multimorbidity Trends in Al-Baha, Saudi Arabia: An Analytical Retrospective Study Using Records-Based Data. Cureus 2024; 16:e52507. [PMID: 38371043 PMCID: PMC10874241 DOI: 10.7759/cureus.52507] [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] [Accepted: 01/18/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND The prevalence of dementia is escalating significantly, posing a substantial societal burden. Currently, there exists a dearth of comprehensive health data about dementia patients in Saudi Arabia, particularly within Al-Baha City. METHODS A retrospective case-series study was undertaken to ascertain the prevalence of dementia within the populace of the Al-Baha region, Kingdom of Saudi Arabia. This investigation utilized hospital-based records encompassing individuals exhibiting symptoms or diagnosed with dementia and its related forms across the Al-Baha region. Furthermore, the study aimed to evaluate the burden of comorbidities among dementia patients and document the pharmacological therapeutic interventions administered to manage dementia and its associated concurrent health conditions. RESULTS Our investigation explored the prevalence rates of various forms of dementia and the accompanying comorbidities among affected individuals. The study spanned from August 2020 to August 2023. Our study encompassed 407 patients diagnosed with Alzheimer's disease (AD), Parkinson's disease, vascular dementia (VaD), or other forms of dementia who were either admitted to or attended tertiary hospitals in Al-Baha. Assessment of the comorbidity burden was conducted using the Charlson Comorbidity Index (CCI). Our findings revealed that among these patients, 13.3% presented with AD, 23.6% with VaD, 33.4% with Parkinson's disease, 15.75% with amnesia, and 14.0% with other types of dementia. The spectrum of comorbidities observed among dementia patients encompassed various conditions, with diabetes mellitus emerging as the predominant comorbidity (19.1%), followed by hypertension (16.4%). Additionally, manifestations of depression were noted in 14% of patients, while 9.82% suffered from paralysis. Chronic conditions such as cancer, chronic obstructive pulmonary disorder (COPD), and cervical spondylosis were also observed among individuals afflicted with dementia and its varied forms. Statistically significant correlations were established between gender, age, nationality, comorbidities, and the prevalence of dementia. Therapeutic interventions in the form of pharmacological treatments were prescribed for dementia patients with comorbidities. Commonly administered medications included Amlod (6.3%), Amlodipine (6.6%), Amlor (5.8%), Aspirin (10.5%), chemotherapeutic drugs (4.4%), Glipizide (8.5%), Lantus (11.3%), Levodopa (23.5%), Metformin (7.8%), acetylcholinesterase inhibitors (6.8%), and Pulmicort (7.86%). These medications aimed to alleviate symptoms associated with dementia and its accompanying comorbidities. CONCLUSIONS Our investigation underscores the substantial burden of comorbidities experienced by dementia patients. These findings offer crucial insights into the overall health status of individuals grappling with dementia, serving as a catalyst for increased awareness among clinicians and policymakers. Such awareness can drive improvements in medical care and support frameworks tailored to the specific needs of dementia patients.
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Affiliation(s)
- Saba Beigh
- Public Health, Albaha University, Al-Baha, SAU
| | - Remas Adnan
- Public Health, Albaha University, Al-Baha, SAU
| | | | | | - Nada Nasser
- Public Health, Albaha University, Al-Baha, SAU
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Telpoukhovskaia MA, Murdy TJ, Marola OJ, Charland K, MacLean M, Luquez T, Lish AM, Neuner S, Dunn A, Onos KD, Wiley J, Archer D, Huentelman MJ, Arnold M, Menon V, Goate A, Van Eldik LJ, Territo PR, Howell GR, Carter GW, O'Connell KMS, Kaczorowski CC. New directions for Alzheimer's disease research from the Jackson Laboratory Center for Alzheimer's and Dementia Research 2022 workshop. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12458. [PMID: 38469553 PMCID: PMC10925728 DOI: 10.1002/trc2.12458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 03/13/2024]
Abstract
INTRODUCTION In September 2022, The Jackson Laboratory Center for Alzheimer's and Dementia Research (JAX CADR) hosted a workshop with leading researchers in the Alzheimer's disease and related dementias (ADRD) field. METHODS During the workshop, the participants brainstormed new directions to overcome current barriers to providing patients with effective ADRD therapeutics. The participants outlined specific areas of focus. Following the workshop, each group used standard literature search methods to provide background for each topic. RESULTS The team of invited experts identified four key areas that can be collectively addressed to make a significant impact in the field: (1) Prioritize the diversification of disease targets, (2) enhance factors promoting resilience, (3) de-risk clinical pipeline, and (4) centralize data management. DISCUSSION In this report, we review these four objectives and propose innovations to expedite ADRD therapeutic pipelines.
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Affiliation(s)
| | - Thomas J. Murdy
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Kevin Charland
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Michael MacLean
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Tain Luquez
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alexandra M. Lish
- Ann Romney Center for Neurologic DiseasesDepartment of NeurologyBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Sarah Neuner
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Amy Dunn
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Kristen D. Onos
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Derek Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Matthew J. Huentelman
- Neurogenomics DivisionTranslational Genomics Research Institute (TGen)PhoenixArizonaUSA
| | - Matthias Arnold
- Institute of Computational BiologyHelmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - Vilas Menon
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alison Goate
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | | | - Paul R. Territo
- Department of MedicineDivision of Clinical PharmacologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neuroscience Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gareth R. Howell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Gregory W. Carter
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Kristen M. S. O'Connell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Catherine C. Kaczorowski
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Department of NeurologyUniversity of MichiganAnn ArborMichiganUSA
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Carey H, Pegios M, Martin L, Saleeba C, Turner AJ, Everett NA, Bjerke IE, Puchades MA, Bjaalie JG, McMullan S. DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas. Nat Commun 2023; 14:5884. [PMID: 37735467 PMCID: PMC10514056 DOI: 10.1038/s41467-023-41645-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 09/12/2023] [Indexed: 09/23/2023] Open
Abstract
Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.
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Affiliation(s)
- Harry Carey
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Michael Pegios
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Chris Saleeba
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | - Anita J Turner
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Simon McMullan
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia.
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Palumbo G, Kunze LH, Oos R, Wind-Mark K, Lindner S, von Ungern-Sternberg B, Bartenstein P, Ziegler S, Brendel M. Longitudinal Studies on Alzheimer Disease Mouse Models with Multiple Tracer PET/CT: Application of Reduction and Refinement Principles in Daily Practice to Safeguard Animal Welfare during Progressive Aging. Animals (Basel) 2023; 13:1812. [PMID: 37531139 PMCID: PMC10251952 DOI: 10.3390/ani13111812] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/26/2023] [Accepted: 05/27/2023] [Indexed: 08/03/2023] Open
Abstract
Longitudinal studies on mouse models related to Alzheimer disease (AD) pathology play an important role in the investigation of therapeutic targets to help pharmaceutical research in the development of new drugs and in the attempt of an early diagnosis that can contribute to improving people's quality of life. There are several advantages to enriching longitudinal studies in AD models with Positron Emission Tomography (PET); among these advantages, the possibility of following the principle of the 3Rs of animal welfare is fundamental. In this manuscript, good daily experimental practice focusing on animal welfare is described and commented upon, based on the experience attained from studies conducted in our Nuclear Medicine department.
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Affiliation(s)
- Giovanna Palumbo
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
| | - Lea Helena Kunze
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Strasse 17, 81377 Munich, Germany
| | - Rosel Oos
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
| | - Karin Wind-Mark
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Strasse 17, 81377 Munich, Germany
| | - Simon Lindner
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
| | | | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
| | - Sibylle Ziegler
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital LMU Munich, Marchionini Strasse 15, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Strasse 17, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
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Gurdon B, Yates SC, Csucs G, Groeneboom NE, Hadad N, Telpoukhovskaia M, Ouellette A, Ouellette T, O'Connell K, Singh S, Murdy T, Merchant E, Bjerke I, Kleven H, Schlegel U, Leergaard TB, Puchades MA, Bjaalie JG, Kaczorowski CC. Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.27.530226. [PMID: 36909528 PMCID: PMC10002670 DOI: 10.1101/2023.02.27.530226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Alzheimer's disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA-sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models.
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Affiliation(s)
- Brianna Gurdon
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
| | - Sharon C Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Gergely Csucs
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Nicolaas E Groeneboom
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | | | - Andrew Ouellette
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
| | - Tionna Ouellette
- The Jackson Laboratory, Bar Harbor, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
| | - Kristen O'Connell
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
| | | | - Tom Murdy
- The Jackson Laboratory, Bar Harbor, ME
| | | | - Ingvild Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Catherine C Kaczorowski
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
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Fasano M, Alberio T. Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence. HANDBOOK OF CLINICAL NEUROLOGY 2023; 192:73-86. [PMID: 36796949 DOI: 10.1016/b978-0-323-85538-9.00007-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.
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Affiliation(s)
- Mauro Fasano
- Department of Science and High Technology, University of Insubria, Busto Arsizio and Como, Italy; Center of Neuroscience, University of Insubria, Busto Arsizio and Como, Italy.
| | - Tiziana Alberio
- Department of Science and High Technology, University of Insubria, Busto Arsizio and Como, Italy; Center of Neuroscience, University of Insubria, Busto Arsizio and Como, Italy
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Genetically modified mice for research on human diseases: A triumph for Biotechnology or a work in progress? THE EUROBIOTECH JOURNAL 2022. [DOI: 10.2478/ebtj-2022-0008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2022] Open
Abstract
Abstract
Genetically modified mice are engineered as models for human diseases. These mouse models include inbred strains, mutants, gene knockouts, gene knockins, and ‘humanized’ mice. Each mouse model is engineered to mimic a specific disease based on a theory of the genetic basis of that disease. For example, to test the amyloid theory of Alzheimer’s disease, mice with amyloid precursor protein genes are engineered, and to test the tau theory, mice with tau genes are engineered. This paper discusses the importance of mouse models in basic research, drug discovery, and translational research, and examines the question of how to define the “best” mouse model of a disease. The critiques of animal models and the caveats in translating the results from animal models to the treatment of human disease are discussed. Since many diseases are heritable, multigenic, age-related and experience-dependent, resulting from multiple gene-gene and gene-environment interactions, it will be essential to develop mouse models that reflect these genetic, epigenetic and environmental factors from a developmental perspective. Such models would provide further insight into disease emergence, progression and the ability to model two-hit and multi-hit theories of disease. The summary examines the biotechnology for creating genetically modified mice which reflect these factors and how they might be used to discover new treatments for complex human diseases such as cancers, neurodevelopmental and neurodegenerative diseases.
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9
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Executive Summary of the 2021 International Conference of Korean Dementia Association: A Report From the Academic Committee of the Korean Dementia Association. Dement Neurocogn Disord 2022; 21:45-58. [PMID: 35585909 PMCID: PMC9085535 DOI: 10.12779/dnd.2022.21.2.45] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/20/2022] [Indexed: 11/27/2022] Open
Abstract
Recently, aducanumab, a beta amyloid targeted immunotherapy, has been approved by the US Food and Drug Administration for the treatment of Alzheimer’s dementia (AD). Although many questions need to be answered, this approval provides a promising hope for the development of AD drugs that could be supported by new biomarkers such as blood-based ones and composite neuropsychological tests that can confirm pathologic changes in early stages of AD. It is important to elucidate the complexity of AD which is known to be associated with other factors such as vascular etiologies and neuro-inflammation. Through the second international conference of the Korean Dementia Association (KDA), researchers from all over the world have participated in the exchange of opinions with KDA members on the most up-to-date topics. The Academic Committee of the KDA summarizes lectures to provide the depth of the conference as well as discussions. This will be an important milestone to widen the latest knowledge in the research of AD’s diagnosis, therapeutics, pathogenesis that can lead to the establishment of future directions.
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