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Shade LMP, Katsumata Y, Abner EL, Aung KZ, Claas SA, Qiao Q, Heberle BA, Brandon JA, Page ML, Hohman TJ, Mukherjee S, Mayeux RP, Farrer LA, Schellenberg GD, Haines JL, Kukull WA, Nho K, Saykin AJ, Bennett DA, Schneider JA, Ebbert MTW, Nelson PT, Fardo DW. GWAS of multiple neuropathology endophenotypes identifies new risk loci and provides insights into the genetic risk of dementia. Nat Genet 2024; 56:2407-2421. [PMID: 39379761 PMCID: PMC11549054 DOI: 10.1038/s41588-024-01939-9] [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: 05/05/2023] [Accepted: 08/30/2024] [Indexed: 10/10/2024]
Abstract
Genome-wide association studies (GWAS) have identified >80 Alzheimer's disease and related dementias (ADRD)-associated genetic loci. However, the clinical outcomes used in most previous studies belie the complex nature of underlying neuropathologies. Here we performed GWAS on 11 ADRD-related neuropathology endophenotypes with participants drawn from the following three sources: the National Alzheimer's Coordinating Center, the Religious Orders Study and Rush Memory and Aging Project, and the Adult Changes in Thought study (n = 7,804 total autopsied participants). We identified eight independent significantly associated loci, of which four were new (COL4A1, PIK3R5, LZTS1 and APOC2). Separately testing known ADRD loci, 19 loci were significantly associated with at least one neuropathology after false-discovery rate adjustment. Genetic colocalization analyses identified pleiotropic effects and quantitative trait loci. Methylation in the cerebral cortex at two sites near APOC2 was associated with cerebral amyloid angiopathy. Studies that include neuropathology endophenotypes are an important step in understanding the mechanisms underlying genetic ADRD risk.
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Affiliation(s)
- Lincoln M P Shade
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Yuriko Katsumata
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Erin L Abner
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Epidemiology and Environmental Health, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Khine Zin Aung
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Steven A Claas
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Qi Qiao
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Bernardo Aguzzoli Heberle
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - J Anthony Brandon
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Madeline L Page
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Richard P Mayeux
- Department of Neurology, Columbia University, New York City, NY, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Ophthalmology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Walter A Kukull
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David A Bennett
- Department of Neurological Sciences, Rush Medical College, Chicago, IL, USA
- Rush Alzheimer's Disease Center, Rush Medical College, Chicago, IL, USA
| | - Julie A Schneider
- Department of Neurological Sciences, Rush Medical College, Chicago, IL, USA
- Rush Alzheimer's Disease Center, Rush Medical College, Chicago, IL, USA
- Department of Pathology, Rush Medical College, Chicago, IL, USA
| | - Mark T W Ebbert
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
- Division of Biomedical Informatics, Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Pathology and Laboratory Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - David W Fardo
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA.
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA.
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2
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Sandoval KE, Witt KA. Somatostatin: Linking Cognition and Alzheimer Disease to Therapeutic Targeting. Pharmacol Rev 2024; 76:1291-1325. [PMID: 39013601 PMCID: PMC11549939 DOI: 10.1124/pharmrev.124.001117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 07/01/2024] [Accepted: 07/08/2024] [Indexed: 07/18/2024] Open
Abstract
Over 4 decades of research support the link between Alzheimer disease (AD) and somatostatin [somatotropin-releasing inhibitory factor (SRIF)]. SRIF and SRIF-expressing neurons play an essential role in brain function, modulating hippocampal activity and memory formation. Loss of SRIF and SRIF-expressing neurons in the brain rests at the center of a series of interdependent pathological events driven by amyloid-β peptide (Aβ), culminating in cognitive decline and dementia. The connection between the SRIF and AD further extends to the neuropsychiatric symptoms, seizure activity, and inflammation, whereas preclinical AD investigations show SRIF or SRIF receptor agonist administration capable of enhancing cognition. SRIF receptor subtype-4 activation in particular presents unique attributes, with the potential to mitigate learning and memory decline, reduce comorbid symptoms, and enhance enzymatic degradation of Aβ in the brain. Here, we review the links between SRIF and AD along with the therapeutic implications. SIGNIFICANCE STATEMENT: Somatostatin and somatostatin-expressing neurons in the brain are extensively involved in cognition. Loss of somatostatin and somatostatin-expressing neurons in Alzheimer disease rests at the center of a series of interdependent pathological events contributing to cognitive decline and dementia. Targeting somatostatin-mediated processes has significant therapeutic potential for the treatment of Alzheimer disease.
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Affiliation(s)
- Karin E Sandoval
- Pharmaceutical Sciences, School of Pharmacy, Southern Illinois University Edwardsville, Edwardsville, Illinois
| | - Ken A Witt
- Pharmaceutical Sciences, School of Pharmacy, Southern Illinois University Edwardsville, Edwardsville, Illinois
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3
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Maksour S, Finol-Urdaneta RK, Hulme AJ, Cabral-da-Silva MEC, Targa Dias Anastacio H, Balez R, Berg T, Turner C, Sanz Muñoz S, Engel M, Kalajdzic P, Lisowski L, Sidhu K, Sachdev PS, Dottori M, Ooi L. Alzheimer's disease induced neurons bearing PSEN1 mutations exhibit reduced excitability. Front Cell Neurosci 2024; 18:1406970. [PMID: 39444394 PMCID: PMC11497635 DOI: 10.3389/fncel.2024.1406970] [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: 03/25/2024] [Accepted: 09/23/2024] [Indexed: 10/25/2024] Open
Abstract
Alzheimer's disease (AD) is a devastating neurodegenerative condition that affects memory and cognition, characterized by neuronal loss and currently lacking a cure. Mutations in PSEN1 (Presenilin 1) are among the most common causes of early-onset familial AD (fAD). While changes in neuronal excitability are believed to be early indicators of AD progression, the link between PSEN1 mutations and neuronal excitability remains to be fully elucidated. This study examined iPSC-derived neurons (iNs) from fAD patients with PSEN1 mutations S290C or A246E, alongside CRISPR-corrected isogenic cell lines, to investigate early changes in excitability. Electrophysiological profiling revealed reduced excitability in both PSEN1 mutant iNs compared to their isogenic controls. Neurons bearing S290C and A246E mutations exhibited divergent passive membrane properties compared to isogenic controls, suggesting distinct effects of PSEN1 mutations on neuronal excitability. Additionally, both PSEN1 backgrounds exhibited higher current density of voltage-gated potassium (Kv) channels relative to their isogenic iNs, while displaying comparable voltage-gated sodium (Nav) channel current density. This suggests that the Nav/Kv imbalance contributes to impaired neuronal firing in fAD iNs. Deciphering these early cellular and molecular changes in AD is crucial for understanding disease pathogenesis.
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Affiliation(s)
- Simon Maksour
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Rocio K. Finol-Urdaneta
- School of Medical and Indigenous Health Science and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Amy J. Hulme
- School of Medical and Indigenous Health Science and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | | | - Helena Targa Dias Anastacio
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Rachelle Balez
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Tracey Berg
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Calista Turner
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Sonia Sanz Muñoz
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Martin Engel
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Predrag Kalajdzic
- Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Leszek Lisowski
- Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
- Australian Genome Therapeutics Centre, Children’s Medical Research Institute and Sydney Children’s Hospitals Network, Westmead, NSW, Australia
- Laboratory of Molecular Oncology and Innovative Therapies, Military Institute of Medicine – National Research Institute, Warsaw, Poland
| | - Kuldip Sidhu
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Mirella Dottori
- School of Medical and Indigenous Health Science and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Lezanne Ooi
- School of Chemistry and Molecular Bioscience and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
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4
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Masurkar AV, Marsh K, Morgan B, Leitner D, Wisniewski T. Factors Affecting Resilience and Prevention of Alzheimer's Disease and Related Dementias. Ann Neurol 2024; 96:633-649. [PMID: 39152774 PMCID: PMC11534551 DOI: 10.1002/ana.27055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 07/27/2024] [Accepted: 07/31/2024] [Indexed: 08/19/2024]
Abstract
Alzheimer's disease (AD) is a devastating, age-associated neurodegenerative disorder and the most common cause of dementia. The clinical continuum of AD spans from preclinical disease to subjective cognitive decline, mild cognitive impairment, and dementia stages (mild, moderate, and severe). Neuropathologically, AD is defined by the accumulation of amyloid β (Aβ) into extracellular plaques in the brain parenchyma and in the cerebral vasculature, and by abnormally phosphorylated tau that accumulates intraneuronally forming neurofibrillary tangles (NFTs). Development of treatment approaches that prevent or even reduce the cognitive decline because of AD has been slow compared to other major causes of death. Recently, the United States Food and Drug Administration gave full approval to 2 different Aβ-targeting monoclonal antibodies. However, this breakthrough disease modifying approach only applies to a limited subset of patients in the AD continuum and there are stringent eligibility criteria. Furthermore, these approaches do not prevent progression of disease, because other AD-related pathologies, such as NFTs, are not directly targeted. A non-mutually exclusive alternative is to address lifestyle interventions that can help reduce the risk of AD and AD-related dementias (ADRD). It is estimated that addressing such modifiable risk factors could potentially delay up to 40% of AD/ADRD cases. In this review, we discuss some of the many modifiable risk factors that may be associated with prevention of AD/ADRD and/or increasing brain resilience, as well as other factors that may interact with these modifiable risk factors to influence AD/ADRD progression. [Color figure can be viewed at www.annalsofneurology.org] ANN NEUROL 2024;96:633-649.
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Affiliation(s)
- Arjun V. Masurkar
- Department of Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Center for Cognitive Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
| | - Karyn Marsh
- Department of Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Center for Cognitive Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
| | - Brianna Morgan
- Department of Medicine, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
| | - Dominique Leitner
- Department of Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Center for Cognitive Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
| | - Thomas Wisniewski
- Department of Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Center for Cognitive Neurology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Department of Pathology, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
- Department of Psychiatry, New York University Grossman School of Medicine, 560 First Avenue, New York, NY 10016
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5
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Guvenek A, Parikshak N, Zamolodchikov D, Gelfman S, Moscati A, Dobbyn L, Stahl E, Shuldiner A, Coppola G. Transcriptional profiling in microglia across physiological and pathological states identifies a transcriptional module associated with neurodegeneration. Commun Biol 2024; 7:1168. [PMID: 39294270 PMCID: PMC11411103 DOI: 10.1038/s42003-024-06684-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 08/06/2024] [Indexed: 09/20/2024] Open
Abstract
Microglia are the resident immune cells of the central nervous system and are involved in brain development, homeostasis, and disease. New imaging and genomics technologies are revealing microglial complexity across developmental and functional states, brain regions, and diseases. We curated a set of publicly available gene expression datasets from human microglia spanning disease and health to identify sets of genes reflecting physiological and pathological microglial states. We also integrated multiple human microglial single-cell RNA-seq datasets in Alzheimer's disease (AD), multiple sclerosis (MS), and Parkinson's disease, and identified a distinct microglial transcriptional signature shared across diseases. Analysis of germ-line DNA identified genes with variants associated with AD and MS that are overrepresented in microglial gene sets, including the disease-associated transcriptional signature. This work points to genes that are dysregulated in disease states and provides a resource for the analysis of diseases in which microglia are implicated by genetic evidence.
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Affiliation(s)
- Aysegul Guvenek
- Regeneron Genetics Center, Tarrytown, NY, USA
- Regeneron Pharmaceuticals Inc., Tarrytown, NY, USA
| | | | | | | | | | - Lee Dobbyn
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Eli Stahl
- Regeneron Genetics Center, Tarrytown, NY, USA
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6
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Lüleci HB, Jones A, Çakır T. Multi-omics analyses highlight molecular differences between clinical and neuropathological diagnoses in Alzheimer's disease. Eur J Neurosci 2024; 60:4922-4936. [PMID: 39072881 DOI: 10.1111/ejn.16482] [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: 02/11/2024] [Revised: 05/14/2024] [Accepted: 07/13/2024] [Indexed: 07/30/2024]
Abstract
Both clinical diagnosis and neuropathological diagnosis are commonly used in literature to categorize individuals as Alzheimer's disease (AD) or non-AD in omics analyses. Whether these diagnostic strategies result in distinct profiles of molecular abnormalities is poorly understood. Here, we analysed one of the most commonly used AD omics datasets in the literature from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort and compared the two diagnosis strategies using brain transcriptome and metabolome by grouping individuals as non-AD and AD according to clinical or neuropathological diagnosis separately. Differentially expressed genes, associated pathways related with AD hallmarks and AD-related genes showed that the categorization based on neuropathological diagnosis more accurately reflects the disease state at the molecular level than the categorization based on clinical diagnosis. We further identified consensus biomarker candidates between the two diagnosis strategies such as 5-hydroxylysine, sphingomyelin and 1-myristoyl-2-palmitoyl-GPC as metabolite biomarkers and sphingolipid metabolism as a pathway biomarker, which could be robust AD biomarkers since they are independent of diagnosis strategies. We also used consensus AD and consensus non-AD individuals between the two diagnostic strategies to train a machine-learning based model, which we used to classify the individuals who were cognitively normal but diagnosed as AD based on neuropathological diagnosis (asymptomatic AD individuals). The majority of these individuals were classified as consensus AD patients for both omics data types. Our study provides a detailed characterization of both diagnostic strategies in terms of the association of the corresponding multi-omics profiles with AD.
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Affiliation(s)
| | - Attila Jones
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Tunahan Çakır
- Department of Bioengineering, Gebze Technical University, Kocaeli, Turkey
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7
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Bobkova NV, Chuvakova LN, Kovalev VI, Zhdanova DY, Chaplygina AV, Rezvykh AP, Evgen'ev MB. A Mouse Model of Sporadic Alzheimer's Disease with Elements of Major Depression. Mol Neurobiol 2024:10.1007/s12035-024-04346-7. [PMID: 38980563 DOI: 10.1007/s12035-024-04346-7] [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: 12/20/2023] [Accepted: 07/02/2024] [Indexed: 07/10/2024]
Abstract
After olfactory bulbectomy, animals are often used as a model of major depression or sporadic Alzheimer's disease and, hence, the status of this model is still disputable. To elucidate the nature of alterations in the expression of the genome after the operation, we analyzed transcriptomes of the cortex, hippocampus, and cerebellum of the olfactory bulbectomized (OBX) mice. Analysis of the functional significance of genes in the brain of OBX mice indicates that the balance of the GABA/glutamatergic systems is disturbed with hyperactivation of the latter in the hippocampus, leading to the development of excitotoxicity and induction of apoptosis in the background of severe mitochondrial dysfunction and astrogliosis. On top of this, the synthesis of neurotrophic factors decreases leading to the disruption of the cytoskeleton of neurons, an increase in the level of intracellular calcium, and the activation of tau protein hyperphosphorylation. Moreover, the acetylcholinergic system is deficient in the background of the hyperactivation of acetylcholinesterase. Importantly, the activity of the dopaminergic, endorphin, and opiate systems in OBX mice decreases, leading to hormonal dysfunction. On the other hand, genes responsible for the regulation of circadian rhythms, cell migration, and innate immunity are activated in OBX animals. All this takes place in the background of a drastic downregulation of ribosomal protein genes in the brain. The obtained results indicate that OBX mice represent a model of Alzheimer's disease with elements of major depression.
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Affiliation(s)
- N V Bobkova
- Institute of Cell Biophysics of the Russian Academy of Sciences-Federal Research Center, Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, 142290, Pushchino, Moscow Region, Russia
| | - L N Chuvakova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, Moscow, Russia
| | - V I Kovalev
- Institute of Cell Biophysics of the Russian Academy of Sciences-Federal Research Center, Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, 142290, Pushchino, Moscow Region, Russia
| | - D Y Zhdanova
- Institute of Cell Biophysics of the Russian Academy of Sciences-Federal Research Center, Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, 142290, Pushchino, Moscow Region, Russia
| | - A V Chaplygina
- Institute of Cell Biophysics of the Russian Academy of Sciences-Federal Research Center, Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, 142290, Pushchino, Moscow Region, Russia
| | - A P Rezvykh
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, Moscow, Russia
| | - M B Evgen'ev
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, Moscow, Russia.
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8
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Collins HM, Greenfield S. Rodent Models of Alzheimer's Disease: Past Misconceptions and Future Prospects. Int J Mol Sci 2024; 25:6222. [PMID: 38892408 PMCID: PMC11172947 DOI: 10.3390/ijms25116222] [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: 04/03/2024] [Revised: 05/28/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease with no effective treatments, not least due to the lack of authentic animal models. Typically, rodent models recapitulate the effects but not causes of AD, such as cholinergic neuron loss: lesioning of cholinergic neurons mimics the cognitive decline reminiscent of AD but not its neuropathology. Alternative models rely on the overexpression of genes associated with familial AD, such as amyloid precursor protein, or have genetically amplified expression of mutant tau. Yet transgenic rodent models poorly replicate the neuropathogenesis and protein overexpression patterns of sporadic AD. Seeding rodents with amyloid or tau facilitates the formation of these pathologies but cannot account for their initial accumulation. Intracerebral infusion of proinflammatory agents offer an alternative model, but these fail to replicate the cause of AD. A novel model is therefore needed, perhaps similar to those used for Parkinson's disease, namely adult wildtype rodents with neuron-specific (dopaminergic) lesions within the same vulnerable brainstem nuclei, 'the isodendritic core', which are the first to degenerate in AD. Site-selective targeting of these nuclei in adult rodents may recapitulate the initial neurodegenerative processes in AD to faithfully mimic its pathogenesis and progression, ultimately leading to presymptomatic biomarkers and preventative therapies.
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Affiliation(s)
- Helen M. Collins
- Neuro-Bio Ltd., Building F5 The Culham Campus, Abingdon OX14 3DB, UK;
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9
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Rush A, Weil C, Siminoff L, Griffin C, Paul CL, Mahadevan A, Sutherland G. The Experts Speak: Challenges in Banking Brain Tissue for Research. Biopreserv Biobank 2024; 22:179-184. [PMID: 38621226 PMCID: PMC11265615 DOI: 10.1089/bio.2024.29135.ajr] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024] Open
Affiliation(s)
- A Rush
- Menzies Centre for Health Policy and Economics, The University of Sydney, Sydney, Australia
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - C Weil
- Independent Consultant, Human Research Protections and Bioethics, Bethesda, USA
| | - L Siminoff
- College of Public Health, Department of Social and Behavioral Sciences, Temple University, Pennsylvania, USA
| | - C Griffin
- College of Health, Medicine and Wellbeing University of Newcastle, Newcastle, Australia
- Hunter Medical Research Institute, Newcastle, Australia
- Mark Hughes Foundation Centre for Brain Cancer Research, The University of Newcastle, Newcastle, Australia
| | - C L Paul
- College of Health, Medicine and Wellbeing University of Newcastle, Newcastle, Australia
- Hunter Medical Research Institute, Newcastle, Australia
- Mark Hughes Foundation Centre for Brain Cancer Research, The University of Newcastle, Newcastle, Australia
| | - A Mahadevan
- Department of Neuropathology, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | - G Sutherland
- Charles Perkins Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
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10
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Fedorov A, Geenjaar E, Wu L, Sylvain T, DeRamus TP, Luck M, Misiura M, Mittapalle G, Hjelm RD, Plis SM, Calhoun VD. Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. Neuroimage 2024; 285:120485. [PMID: 38110045 PMCID: PMC10872501 DOI: 10.1016/j.neuroimage.2023.120485] [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: 08/24/2023] [Revised: 11/15/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023] Open
Abstract
In recent years, deep learning approaches have gained significant attention in predicting brain disorders using neuroimaging data. However, conventional methods often rely on single-modality data and supervised models, which provide only a limited perspective of the intricacies of the highly complex brain. Moreover, the scarcity of accurate diagnostic labels in clinical settings hinders the applicability of the supervised models. To address these limitations, we propose a novel self-supervised framework for extracting multiple representations from multimodal neuroimaging data to enhance group inferences and enable analysis without resorting to labeled data during pre-training. Our approach leverages Deep InfoMax (DIM), a self-supervised methodology renowned for its efficacy in learning representations by estimating mutual information without the need for explicit labels. While DIM has shown promise in predicting brain disorders from single-modality MRI data, its potential for multimodal data remains untapped. This work extends DIM to multimodal neuroimaging data, allowing us to identify disorder-relevant brain regions and explore multimodal links. We present compelling evidence of the efficacy of our multimodal DIM analysis in uncovering disorder-relevant brain regions, including the hippocampus, caudate, insula, - and multimodal links with the thalamus, precuneus, and subthalamus hypothalamus. Our self-supervised representations demonstrate promising capabilities in predicting the presence of brain disorders across a spectrum of Alzheimer's phenotypes. Comparative evaluations against state-of-the-art unsupervised methods based on autoencoders, canonical correlation analysis, and supervised models highlight the superiority of our proposed method in achieving improved classification performance, capturing joint information, and interpretability capabilities. The computational efficiency of the decoder-free strategy enhances its practical utility, as it saves compute resources without compromising performance. This work offers a significant step forward in addressing the challenge of understanding multimodal links in complex brain disorders, with potential applications in neuroimaging research and clinical diagnosis.
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Affiliation(s)
- Alex Fedorov
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA.
| | - Eloy Geenjaar
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Lei Wu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | | | - Thomas P DeRamus
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Margaux Luck
- Mila - Quebec AI Institute, Montréal, QC, Canada
| | - Maria Misiura
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Girish Mittapalle
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - R Devon Hjelm
- Mila - Quebec AI Institute, Montréal, QC, Canada; Apple Machine Learning Research, Seattle, WA, USA
| | - Sergey M Plis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
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Cao THM, Le APH, Tran TT, Huynh VK, Pham BH, Le TM, Nguyen QL, Tran TC, Tong TM, Than THN, Nguyen TTT, Ha HTT. Plasma cell-free RNA profiling of Vietnamese Alzheimer's patients reveals a linkage with chronic inflammation and apoptosis: a pilot study. Front Mol Neurosci 2023; 16:1308610. [PMID: 38178908 PMCID: PMC10764507 DOI: 10.3389/fnmol.2023.1308610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/04/2023] [Indexed: 01/06/2024] Open
Abstract
Introduction Circulating cell-free RNA (cfRNA) is a potential hallmark for early diagnosis of Alzheimer's Disease (AD) as it construes the genetic expression level, giving insights into the pathological progress from the outset. Profiles of cfRNA in Caucasian AD patients have been investigated thoroughly, yet there was no report exploring cfRNAs in the ASEAN groups. This study examined the gap, expecting to support the development of point-of-care AD diagnosis. Methods cfRNA profiles were characterized from 20 Vietnamese plasma samples (10 probable AD and 10 age-matched controls). RNA reads were subjected to differential expression (DE) analysis. Weighted gene correlation network analysis (WGCNA) was performed to identify gene modules that were significantly co-expressed. These modules' expression profiles were then correlated with AD status to identify relevant modules. Genes with the highest intramodular connectivity (module membership) were selected as hub genes. Transcript counts of differentially expressed genes were correlated with key AD measures-MMSE and MTA scores-to identify potential biomarkers. Results 136 genes were identified as significant AD hallmarks (p < 0.05), with 52 downregulated and 84 upregulated in the AD cohort. 45.6% of these genes are highly expressed in the hippocampus, cerebellum, and cerebral cortex. Notably, all markers related to chronic inflammation were upregulated, and there was a significant shift in all apoptotic markers. Three co-expressed modules were found to be significantly correlated with Alzheimer's status (p < 0.05; R2> 0.5). Functional enrichment analysis on these modules reveals an association with focal adhesion, nucleocytoplasmic transport, and metal ion response leading to apoptosis, suggesting the potential participation of these pathways in AD pathology. 47 significant hub genes were found to be differentially expressed genes with the highest connectivity. Six significant hub genes (CREB1, YTHDC1, IL1RL1, PHACTR2, ANKRD36B, RNF213) were found to be significantly correlated with MTA and MMSE scores. Other significant transcripts (XRN1, UBB, CHP1, THBS1, S100A9) were found to be involved in inflammation and neuronal death. Overall, we have identified candidate transcripts in plasma cf-RNA that are differentially expressed and are implicated in inflammation and apoptosis, which can jumpstart further investigations into applying cf-RNA as an AD biomarker in Vietnam and ASEAN countries.
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Affiliation(s)
- Thien Hoang Minh Cao
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Anh Phuc Hoang Le
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Tai Tien Tran
- Department of Physiology, Pathophysiology and Immunology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam
| | - Vy Kim Huynh
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Bao Hoai Pham
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Thao Mai Le
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Quang Lam Nguyen
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
| | - Thang Cong Tran
- Department of Neurology, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Trang Mai Tong
- Department of Neurology, University Medical Center, Ho Chi Minh City, Vietnam
| | - The Ha Ngoc Than
- Department of Geriatrics, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
- Department of Geriatrics and Palliative Care, University Medical Center, Ho Chi Minh City, Vietnam
| | - Tran Tran To Nguyen
- Department of Geriatrics, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Huong Thi Thanh Ha
- School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam
- Vietnam National University, Ho Chi Minh City, Vietnam
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12
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Tamburini B, Badami GD, La Manna MP, Shekarkar Azgomi M, Caccamo N, Dieli F. Emerging Roles of Cells and Molecules of Innate Immunity in Alzheimer's Disease. Int J Mol Sci 2023; 24:11922. [PMID: 37569296 PMCID: PMC10418700 DOI: 10.3390/ijms241511922] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/24/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
The inflammatory response that marks Alzheimer's disease (neuroinflammation) is considered a double-edged sword. Microglia have been shown to play a protective role at the beginning of the disease. Still, persistent harmful stimuli further activate microglia, inducing an exacerbating inflammatory process which impairs β-amyloid peptide clearance capability and leads to neurotoxicity and neurodegeneration. Moreover, microglia also appear to be closely involved in the spread of tau pathology. Soluble TREM2 also represents a crucial player in the neuroinflammatory processes. Elevated levels of TREM2 in cerebrospinal fluid have been associated with increased amyloid plaque burden, neurodegeneration, and cognitive decline in individuals with Alzheimer's disease. Understanding the intricate relationship between innate immunity and Alzheimer's disease will be a promising strategy for future advancements in diagnosis and new therapeutic interventions targeting innate immunity, by modulating its activity. Still, additional and more robust studies are needed to translate these findings into effective treatments. In this review, we focus on the role of cells (microglia, astrocytes, and oligodendrocytes) and molecules (TREM2, tau, and β-amyloid) of the innate immune system in the pathogenesis of Alzheimer's disease and their possible exploitation as disease biomarkers and targets of therapeutical approaches.
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Affiliation(s)
- Bartolo Tamburini
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
| | - Giusto Davide Badami
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
| | - Marco Pio La Manna
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), AOUP Paolo Giaccone, 90127 Palermo, Italy
| | - Mojtaba Shekarkar Azgomi
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
| | - Nadia Caccamo
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), AOUP Paolo Giaccone, 90127 Palermo, Italy
| | - Francesco Dieli
- Department of Biomedicine, Neuroscience and Advanced Diagnosis (BIND), University of Palermo, 90127 Palermo, Italy; (B.T.); (G.D.B.); (M.P.L.M.); (M.S.A.); (F.D.)
- Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), AOUP Paolo Giaccone, 90127 Palermo, Italy
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13
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Sobue A, Komine O, Yamanaka K. Neuroinflammation in Alzheimer's disease: microglial signature and their relevance to disease. Inflamm Regen 2023; 43:26. [PMID: 37165437 PMCID: PMC10170691 DOI: 10.1186/s41232-023-00277-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 04/26/2023] [Indexed: 05/12/2023] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia, pathologically characterized by senile plaques and neurofibrillary tangles (NFTs), resulting in neurodegeneration. Neuroinflammation, defined as the activation of glial cells such as microglia and astrocytes, is observed surrounding senile plaques and affected neurons in AD. Recently conducted genome-wide association studies (GWAS) indicate that a large section of identified AD risk genes are involved in immune responses and are enriched in microglia. Microglia are innate immune cells in the central nervous system (CNS), which are involved in immune surveillance and maintenance of homeostasis in the CNS. Recently, a novel subpopulation of activated microglia named as disease-associated microglia (DAM), also known as activated response microglia (ARM) or microglial neurodegenerative phenotype (MGnD), was identified in AD model mice. These microglia closely associate with β-amyloid (Aβ) plaques and exhibit characteristic gene expression profiles accompanied with reduced expressions of homeostatic microglial genes. However, it remains unclear whether decreased homeostatic microglia functions or increased DAM/ARM/MGnD functions correlate with the degree of neuronal loss in AD. To translate the results of rodent studies to human AD, precuneus, the brain region vulnerable to β-amyloid accumulation in preclinical AD, is of high interest, as it can provide novel insights into the mechanisms of microglia response to Aβ in early AD. In this study, we performed comparative analyses of gene expression profiles of microglia among three representative neurodegenerative mouse models and the human precunei with early AD pathology. We proceeded to evaluate the identified genes as potential therapeutic targets for AD. We believe that our findings will provide important resources to better understand the role of glial dysfunction in AD.
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Affiliation(s)
- Akira Sobue
- Department of Neuroscience and Pathobiology, Research Institute of Environmental Medicine, Nagoya University, Aichi, 464-8601, Japan.
- Department of Neuroscience and Pathobiology, Nagoya University Graduate School of Medicine, Aichi, 466-8550, Japan.
- Medical Interactive Research and Academia Industry Collaboration Center, Research Institute of Environmental Medicine, Nagoya University, Aichi, 464-8601, Japan.
| | - Okiru Komine
- Department of Neuroscience and Pathobiology, Research Institute of Environmental Medicine, Nagoya University, Aichi, 464-8601, Japan.
- Department of Neuroscience and Pathobiology, Nagoya University Graduate School of Medicine, Aichi, 466-8550, Japan.
| | - Koji Yamanaka
- Department of Neuroscience and Pathobiology, Research Institute of Environmental Medicine, Nagoya University, Aichi, 464-8601, Japan.
- Department of Neuroscience and Pathobiology, Nagoya University Graduate School of Medicine, Aichi, 466-8550, Japan.
- Institute for Glyco-core Research (iGCORE), Nagoya University, Aichi, Japan.
- Center for One Medicine Innovative Translational Research (COMIT), Nagoya University, Aichi, Japan.
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14
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. Alzheimers Res Ther 2023; 15:78. [PMID: 37038196 PMCID: PMC10088180 DOI: 10.1186/s13195-023-01216-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. METHODS We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. RESULTS We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. CONCLUSIONS Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Juan I Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Eden R Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA.
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
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15
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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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16
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. RESEARCH SQUARE 2023:rs.3.rs-2391364. [PMID: 36865230 PMCID: PMC9980279 DOI: 10.21203/rs.3.rs-2391364/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- University of Miami, Miller School of Medicine
| | - Juan I Young
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | - Michael A Schmidt
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | | | | | - Eden R Martin
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | - Lily Wang
- University of Miami, Miller School of Medicine
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17
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Hadiyoso S, Ong PA, Zakaria H, Rajab TLE. EEG-Based Spectral Dynamic in Characterization of Poststroke Patients with Cognitive Impairment for Early Detection of Vascular Dementia. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:5666229. [PMID: 36444210 PMCID: PMC9701122 DOI: 10.1155/2022/5666229] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 09/08/2022] [Accepted: 11/03/2022] [Indexed: 10/17/2023]
Abstract
One common type of vascular dementia (VaD) is poststroke dementia (PSD). Vascular dementia can occur in one-third of stroke patients. The worsening of cognitive function can occur quickly if not detected and treated early. One of the potential medical modalities for observing this disorder by considering costs and safety factors is electroencephalogram (EEG). It is thought that there are differences in the spectral dynamics of the EEG signal between the normal group and stroke patients with cognitive impairment so that it can be used in detection. Therefore, this study proposes an EEG signal characterization method using EEG spectral power complexity measurements to obtain features of poststroke patients with cognitive impairment and normal subjects. Working memory EEGs were collected and analyzed from forty-two participants, consisting of sixteen normal subjects, fifteen poststroke patients with mild cognitive impairment, and eleven poststroke patients with dementia. From the analysis results, it was found that there were differences in the dynamics of the power spectral in each group, where the spectral power of the cognitively impaired group was more regular than the normal group. Notably, (1) significant differences in spectral entropy (SpecEn) with a p value <0.05 were found for all electrodes, (2) there was a relationship between SpecEn values and the severity of dementia (SpecEnDem < SpecEnMCI < SpecEnNormal), and (3) a post hoc multiple comparison test showed significant differences between groups at the F7 electrode. This study shows that spectral complexity analysis can discriminate between normal and poststroke patients with cognitive impairment. For further studies, it is necessary to simulate performance validation so that the proposed approach can be used in the early detection of poststroke dementia and monitoring the development of dementia.
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Affiliation(s)
- Sugondo Hadiyoso
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
- School of Applied Science, Telkom University, Bandung, Indonesia
| | - Paulus Anam Ong
- Departement of Neurology, Faculty of Medicine, Padjadjaran University, Dr. Hasan Sadikin General Hospital, Bandung, Indonesia
| | - Hasballah Zakaria
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
| | - Tati Latifah E. Rajab
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
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18
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Lin J, Wang S, Audano PA, Meng D, Flores JI, Kosters W, Yang X, Jia P, Marschall T, Beck CR, Ye K. SVision: a deep learning approach to resolve complex structural variants. Nat Methods 2022; 19:1230-1233. [PMID: 36109679 PMCID: PMC9985066 DOI: 10.1038/s41592-022-01609-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 08/11/2022] [Indexed: 01/23/2023]
Abstract
Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequencing data. SVision outperforms current callers at identifying the internal structure of complex events and has revealed 80 high-quality CSVs with 25 distinct structures from an individual genome. SVision directly detects CSVs without matching known structures, allowing sensitive detection of both common and previously uncharacterized complex rearrangements.
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Affiliation(s)
- Jiadong Lin
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, the Netherlands
| | - Songbo Wang
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Peter A Audano
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Deyu Meng
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China
- Macau Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau
| | - Jacob I Flores
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Walter Kosters
- Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, the Netherlands
| | - Xiaofei Yang
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Peng Jia
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Dusseldorf, Germany
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, USA
| | - Kai Ye
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- The School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
- Faculty of Science, Leiden University, Leident, the Netherlands.
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19
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Das D, Podder S. Deregulation of ceRNA Networks in Frontal Cortex and Choroid Plexus of Brain during SARS-CoV-2 Infection Aggravates Neurological Manifestations: An Insight from Bulk and Single-Cell Transcriptomic Analyses. Adv Biol (Weinh) 2022; 6:e2101310. [PMID: 35661455 PMCID: PMC9348399 DOI: 10.1002/adbi.202101310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 05/20/2022] [Indexed: 01/28/2023]
Abstract
Although transcriptomic studies of SARS-CoV-2-infected brains have depicted variability in gene expression, the landscape of deregulated cell-specific regulatory circuits has not been elucidated yet. Hence, bulk and single-cell RNA-seq data are analyzed to gain detailed insights. Initially, two ceRNA networks with 19 and 3 differentially expressed (DE) hub lncRNAs are reconstructed in SARS-CoV-2 infected Frontal Cortex (FC) and Choroid Plexus (CP), respectively. Functional and pathway enrichment analyses of downstream mRNAs of deregulated ceRNA axes demonstrate impairment of neurological processes. Mapping of hub lncRNA-mRNA pairs from bulk RNA-seq with snRNA-seq data has indicated that NORAD, NEAT1, and STXBP5-AS1 are downregulated across 4, 4, and 2 FC cell types, respectively. At the same time, MIRLET7BHG and MALAT1 are upregulated in excitatory neurons of FC and neurons of CP, respectively. Here, it is hypothesized that downregulation of NORAD, NEAT1, and STXBP5-AS1, and upregulation of MIRLET7BHG and MALAT1 might deregulate respectively 51, 6, and 37, and 31 and 19 mRNAs in cell types of FC and CP. Afterward, 13 therapeutic miRNAs are traced that might safeguard against deregulated lncRNA-mRNA pairs of NORAD, NEAT1, and MIRLET7BHG in FC. This study helps to explain the plausible mechanism of post-COVID neurological manifestation and also to devise therapeutics against it.
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Affiliation(s)
- Deepyaman Das
- Department of MicrobiologyRaiganj UniversityRaiganjUttar DinajpurWest Bengal733134India
| | - Soumita Podder
- Department of MicrobiologyRaiganj UniversityRaiganjUttar DinajpurWest Bengal733134India
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20
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Needham H, Torpey G, Flores CC, Davis CJ, Vanderheyden WM, Gerstner JR. A Dichotomous Role for FABP7 in Sleep and Alzheimer's Disease Pathogenesis: A Hypothesis. Front Neurosci 2022; 16:798994. [PMID: 35844236 PMCID: PMC9280343 DOI: 10.3389/fnins.2022.798994] [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: 10/20/2021] [Accepted: 05/10/2022] [Indexed: 11/15/2022] Open
Abstract
Fatty acid binding proteins (FABPs) are a family of intracellular lipid chaperone proteins known to play critical roles in the regulation of fatty acid uptake and transport as well as gene expression. Brain-type fatty acid binding protein (FABP7) is enriched in astrocytes and has been implicated in sleep/wake regulation and neurodegenerative diseases; however, the precise mechanisms underlying the role of FABP7 in these biological processes remain unclear. FABP7 binds to both arachidonic acid (AA) and docosahexaenoic acid (DHA), resulting in discrete physiological responses. Here, we propose a dichotomous role for FABP7 in which ligand type determines the subcellular translocation of fatty acids, either promoting wakefulness aligned with Alzheimer's pathogenesis or promoting sleep with concomitant activation of anti-inflammatory pathways and neuroprotection. We hypothesize that FABP7-mediated translocation of AA to the endoplasmic reticulum of astrocytes increases astrogliosis, impedes glutamatergic uptake, and enhances wakefulness and inflammatory pathways via COX-2 dependent generation of pro-inflammatory prostaglandins. Conversely, we propose that FABP7-mediated translocation of DHA to the nucleus stabilizes astrocyte-neuron lactate shuttle dynamics, preserves glutamatergic uptake, and promotes sleep by activating anti-inflammatory pathways through the peroxisome proliferator-activated receptor-γ transcriptional cascade. Importantly, this model generates several testable hypotheses applicable to other neurodegenerative diseases, including amyotrophic lateral sclerosis and Parkinson's disease.
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Affiliation(s)
- Hope Needham
- Department of Biology, Gonzaga University, Spokane, WA, United States
| | - Grace Torpey
- Department of Biology, Gonzaga University, Spokane, WA, United States
| | - Carlos C. Flores
- Department of Translational Medicine and Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - Christopher J. Davis
- Department of Translational Medicine and Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
- Sleep and Performance Research Center, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - William M. Vanderheyden
- Department of Translational Medicine and Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
- Sleep and Performance Research Center, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - Jason R. Gerstner
- Department of Translational Medicine and Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
- Sleep and Performance Research Center, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
- Steve Gleason Institute for Neuroscience, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
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21
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The cytokines interleukin-6 and interferon-α induce distinct microglia phenotypes. J Neuroinflammation 2022; 19:96. [PMID: 35429976 PMCID: PMC9013466 DOI: 10.1186/s12974-022-02441-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 03/24/2022] [Indexed: 12/12/2022] Open
Abstract
Background Elevated production of the cytokines interleukin (IL)-6 or interferon (IFN)-α in the central nervous system (CNS) is implicated in the pathogenesis of neurological diseases such as neuromyelitis optica spectrum disorders or cerebral interferonopathies, respectively. Transgenic mice with CNS-targeted chronic production of IL-6 (GFAP-IL6) or IFN-α (GFAP-IFN) recapitulate important clinical and pathological features of these human diseases. The activation of microglia is a prominent manifestation found both in the human diseases and in the transgenic mice, yet little is known about how this contributes to disease pathology. Methods Here, we used a combination of ex vivo and in situ techniques to characterize the molecular, cellular and transcriptomic phenotypes of microglia in GFAP-IL6 versus GFAP-IFN mice. In addition, a transcriptomic meta-analysis was performed to compare the microglia response from GFAP-IL6 and GFAP-IFN mice to the response of microglia in a range of neurodegenerative and neuroinflammatory disorders. Results We demonstrated that microglia show stimulus-specific responses to IL-6 versus IFN-α in the brain resulting in unique and extensive molecular and cellular adaptations. In GFAP-IL6 mice, microglia proliferated, had shortened, less branched processes and elicited transcriptomic and molecular changes associated with phagocytosis and lipid processing. In comparison, microglia in the brain of GFAP-IFN mice exhibited increased proliferation and apoptosis, had larger, hyper-ramified processes and showed transcriptomic and surface marker changes associated with antigen presentation and antiviral response. Further, a transcriptomic meta-analysis revealed that IL-6 and IFN-α both contribute to the formation of a core microglia response in animal models of neurodegenerative and neuroinflammatory disorders, such as Alzheimer’s disease, tauopathy, multiple sclerosis and lipopolysaccharide-induced endotoxemia. Conclusions Our findings demonstrate that microglia responses to IL-6 and IFN-α are highly stimulus-specific, wide-ranging and give rise to divergent phenotypes that modulate microglia responses in neuroinflammatory and neurodegenerative diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02441-x.
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22
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Kocurova G, Ricny J, Ovsepian SV. Autoantibodies targeting neuronal proteins as biomarkers for neurodegenerative diseases. Theranostics 2022; 12:3045-3056. [PMID: 35547759 PMCID: PMC9065204 DOI: 10.7150/thno.72126] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 03/09/2022] [Indexed: 01/08/2023] Open
Abstract
Neurodegenerative diseases (NDDs) are associated with the accumulation of a range of misfolded proteins across the central nervous system and related autoimmune responses, including the generation of antibodies and the activation of immune cells. Both innate and adaptive immunity become mobilized, leading to cellular and humoral effects. The role of humoral immunity in disease onset and progression remains to be elucidated with rising evidence suggestive of positive (protection, repair) and negative (injury, toxicity) outcomes. In this study, we review advances in research of neuron-targeting autoantibodies in the most prevalent NDDs. We discuss their biological origin, molecular diversity and changes in the course of diseases, consider their relevance to the initiation and progression of pathology as well as diagnostic and prognostic significance. It is suggested that the emerging autoimmune aspects of NDDs not only could facilitate the early detection but also might help to elucidate previously unknown facets of pathobiology with relevance to the development of precision medicine.
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Affiliation(s)
- Gabriela Kocurova
- Experimental Neurobiology Program, National Institute of Mental Health, Klecany, Czech Republic
| | - Jan Ricny
- Experimental Neurobiology Program, National Institute of Mental Health, Klecany, Czech Republic
| | - Saak V. Ovsepian
- Faculty of Science and Engineering, University of Greenwich London, Chatham Maritime, Kent, ME4 4TB, United Kingdom
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23
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Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease. Cells 2022; 11:cells11060987. [PMID: 35326437 PMCID: PMC8946735 DOI: 10.3390/cells11060987] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/02/2022] [Accepted: 03/10/2022] [Indexed: 12/27/2022] Open
Abstract
Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.
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24
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Shadfar S, Brocardo M, Atkin JD. The Complex Mechanisms by Which Neurons Die Following DNA Damage in Neurodegenerative Diseases. Int J Mol Sci 2022; 23:ijms23052484. [PMID: 35269632 PMCID: PMC8910227 DOI: 10.3390/ijms23052484] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 02/12/2022] [Accepted: 02/17/2022] [Indexed: 01/18/2023] Open
Abstract
Human cells are exposed to numerous exogenous and endogenous insults every day. Unlike other molecules, DNA cannot be replaced by resynthesis, hence damage to DNA can have major consequences for the cell. The DNA damage response contains overlapping signalling networks that repair DNA and hence maintain genomic integrity, and aberrant DNA damage responses are increasingly described in neurodegenerative diseases. Furthermore, DNA repair declines during aging, which is the biggest risk factor for these conditions. If unrepaired, the accumulation of DNA damage results in death to eliminate cells with defective genomes. This is particularly important for postmitotic neurons because they have a limited capacity to proliferate, thus they must be maintained for life. Neuronal death is thus an important process in neurodegenerative disorders. In addition, the inability of neurons to divide renders them susceptible to senescence or re-entry to the cell cycle. The field of cell death has expanded significantly in recent years, and many new mechanisms have been described in various cell types, including neurons. Several of these mechanisms are linked to DNA damage. In this review, we provide an overview of the cell death pathways induced by DNA damage that are relevant to neurons and discuss the possible involvement of these mechanisms in neurodegenerative conditions.
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Affiliation(s)
- Sina Shadfar
- Centre for Motor Neuron Disease Research, Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia; (S.S.); (M.B.)
| | - Mariana Brocardo
- Centre for Motor Neuron Disease Research, Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia; (S.S.); (M.B.)
| | - Julie D. Atkin
- Centre for Motor Neuron Disease Research, Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia; (S.S.); (M.B.)
- Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Bundoora, Melbourne, VIC 3086, Australia
- Correspondence:
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25
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Paasila PJ, Aramideh JA, Sutherland GT, Graeber MB. Synapses, Microglia, and Lipids in Alzheimer's Disease. Front Neurosci 2022; 15:778822. [PMID: 35095394 PMCID: PMC8789683 DOI: 10.3389/fnins.2021.778822] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/06/2021] [Indexed: 12/17/2022] Open
Abstract
Alzheimer's disease (AD) is characterised by synaptic dysfunction accompanied by the microscopically visible accumulation of pathological protein deposits and cellular dystrophy involving both neurons and glia. Late-stage AD shows pronounced loss of synapses and neurons across several differentially affected brain regions. Recent studies of advanced AD using post-mortem brain samples have demonstrated the direct involvement of microglia in synaptic changes. Variants of the Apolipoprotein E and Triggering Receptors Expressed on Myeloid Cells gene represent important determinants of microglial activity but also of lipid metabolism in cells of the central nervous system. Here we review evidence that may help to explain how abnormal lipid metabolism, microglial activation, and synaptic pathophysiology are inter-related in AD.
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Affiliation(s)
- Patrick J. Paasila
- Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
| | - Jason A. Aramideh
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Greg T. Sutherland
- Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Manuel B. Graeber
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
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26
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Highet B, Parker R, Faull RLM, Curtis MA, Ryan B. RNA Quality in Post-mortem Human Brain Tissue Is Affected by Alzheimer's Disease. Front Mol Neurosci 2022; 14:780352. [PMID: 34992523 PMCID: PMC8724529 DOI: 10.3389/fnmol.2021.780352] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 11/25/2021] [Indexed: 11/13/2022] Open
Abstract
Gene expression studies of human post-mortem brain tissue are useful for understanding the pathogenesis of neurodegenerative disease. These studies rely on the assumption that RNA quality is consistent between disease and neurologically normal cases; however, previous studies have suggested that RNA quality may be affected by neurodegenerative disease. Here, we compared RNA quality in human post-mortem brain tissue between neurologically normal cases (n = 14) and neurodegenerative disease cases (Alzheimer’s disease n = 10; Parkinson’s disease n = 11; and Huntington’s disease n = 9) in regions affected by pathology and regions that are relatively devoid of pathology. We identified a statistically significant decrease in RNA integrity number (RIN) in Alzheimer’s disease tissue relative to neurologically normal tissue (mixed effects model, p = 0.04). There were no statistically significant differences between neurologically normal cases and Parkinson’s disease or Huntington’s disease cases. Next, we investigated whether total RNA quality affected mRNA quantification, by correlating RIN with qPCR threshold cycle (CT). CT values for all six genes investigated were strongly correlated with RIN (p < 0.05, Pearson correlation); this effect was only partially mitigated by normalization to RPL30. Our results indicate that RNA quality is decreased in Alzheimer’s disease tissue. We recommend that RIN should be considered when this tissue is used in gene expression analyses.
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Affiliation(s)
- Blake Highet
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Remai Parker
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Richard L M Faull
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Maurice A Curtis
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Brigid Ryan
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
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27
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Primary Cilia Structure Is Prolonged in Enteric Neurons of 5xFAD Alzheimer's Disease Model Mice. Int J Mol Sci 2021; 22:ijms222413564. [PMID: 34948356 PMCID: PMC8707868 DOI: 10.3390/ijms222413564] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/09/2021] [Accepted: 12/15/2021] [Indexed: 02/06/2023] Open
Abstract
Neurodegenerative diseases such as Alzheimer’s disease (AD) have long been acknowledged as mere disorders of the central nervous system (CNS). However, in recent years the gut with its autonomous nervous system and the multitude of microbial commensals has come into focus. Changes in gut properties have been described in patients and animal disease models such as altered enzyme secretion or architecture of the enteric nervous system. The underlying cellular mechanisms have so far only been poorly investigated. An important organelle for integrating potentially toxic signals such as the AD characteristic A-beta peptide is the primary cilium. This microtubule-based signaling organelle regulates numerous cellular processes. Even though the role of primary cilia in a variety of developmental and disease processes has recently been recognized, the contribution of defective ciliary signaling to neurodegenerative diseases such as AD, however, has not been investigated in detail so far. The AD mouse model 5xFAD was used to analyze possible changes in gut functionality by organ bath measurement of peristalsis movement. Subsequently, we cultured primary enteric neurons from mutant mice and wild type littermate controls and assessed for cellular pathomechanisms. Neurite mass was quantified within transwell culturing experiments. Using a combination of different markers for the primary cilium, cilia number and length were determined using fluorescence microscopy. 5xFAD mice showed altered gut anatomy, motility, and neurite mass of enteric neurons. Moreover, primary cilia could be demonstrated on the surface of enteric neurons and exhibited an elongated phenotype in 5xFAD mice. In parallel, we observed reduced β-Catenin expression, a key signaling molecule that regulates Wnt signaling, which is regulated in part via ciliary associated mechanisms. Both results could be recapitulated via in vitro treatments of enteric neurons from wild type mice with A-beta. So far, only a few reports on the probable role of primary cilia in AD can be found. Here, we reveal for the first time an architectural altered phenotype of primary cilia in the enteric nervous system of AD model mice, elicited potentially by neurotoxic A-beta. Potential changes on the sub-organelle level—also in CNS-derived neurons—require further investigations.
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