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Gaynor-Gillett SC, Cheng L, Shi M, Liu J, Wang G, Spector M, Flaherty M, Wall M, Hwang A, Gu M, Chen Z, Chen Y, Consortium P, Moran JR, Zhang J, Lee D, Gerstein M, Geschwind D, White KP. Validation of Enhancer Regions in Primary Human Neural Progenitor Cells using Capture STARR-seq. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.585066. [PMID: 38562832 PMCID: PMC10983874 DOI: 10.1101/2024.03.14.585066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genome-wide association studies (GWAS) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. We performed capture STARR-sequencing of over 78,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We selected candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWAS. Over 8,000 regions demonstrated enhancer activity in the phNPCs, and we linked these regions to over 2,200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including dopaminergic synapse, axon guidance, and schizophrenia. We functionally validated a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identified thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.
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Affiliation(s)
- Sophia C. Gaynor-Gillett
- Tempus Labs, Inc.; Chicago, IL, 60654, USA
- Department of Biology, Cornell College; Mount Vernon, IA, 52314, USA
| | | | - Manman Shi
- Tempus Labs, Inc.; Chicago, IL, 60654, USA
| | - Jason Liu
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Gaoyuan Wang
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | | | | | | | - Ahyeon Hwang
- Department of Computer Science, University of California Irvine; Irvine, CA, 92697, USA
| | - Mengting Gu
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Zhanlin Chen
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Yuhang Chen
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | | | | | - Jing Zhang
- Department of Computer Science, University of California Irvine; Irvine, CA, 92697, USA
| | - Donghoon Lee
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai; New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai; New York, NY, 10029, USA
| | - Mark Gerstein
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
- Department of Statistics and Data Science, Yale University; New Haven, CT, 06511, USA
- Department of Molecular Biophysics and Biochemistry, Yale University; New Haven, CT, 06511, USA
- Department of Computer Science, Yale University; New Haven, CT, 06511, USA
| | - Daniel Geschwind
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles; Los Angeles, CA, 90095, USA
- Department of Psychiatry and Semel Institute, David Geffen School of Medicine, University of California Los Angeles; Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles; Los Angeles, CA, 90095, USA
| | - Kevin P. White
- Yong Loo Lin School of Medicine, National University of Singapore; Singapore, 117597
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases. Am J Hum Genet 2024; 111:150-164. [PMID: 38181731 PMCID: PMC10806756 DOI: 10.1016/j.ajhg.2023.12.006] [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: 07/19/2023] [Revised: 12/04/2023] [Accepted: 12/04/2023] [Indexed: 01/07/2024] Open
Abstract
Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.
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Affiliation(s)
- Chelsea X Alvarado
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Cory A Weller
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mathew J Koretsky
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Kristin Levine
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
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3
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Kucikova L, Zeng J, Muñoz-Neira C, Muniz-Terrera G, Huang W, Gregory S, Ritchie C, O'Brien J, Su L. Genetic risk factors of Alzheimer's Disease disrupt resting-state functional connectivity in cognitively intact young individuals. J Neurol 2023; 270:4949-4958. [PMID: 37358635 PMCID: PMC10511575 DOI: 10.1007/s00415-023-11809-9] [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: 04/28/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/27/2023]
Abstract
BACKGROUND Past evidence shows that changes in functional brain connectivity in multiple resting-state networks occur in cognitively healthy individuals who have non-modifiable risk factors for Alzheimer's Disease. Here, we aimed to investigate how those changes differ in early adulthood and how they might relate to cognition. METHODS We investigated the effects of genetic risk factors of AD, namely APOEe4 and MAPTA alleles, on resting-state functional connectivity in a cohort of 129 cognitively intact young adults (aged 17-22 years). We used Independent Component Analysis to identify networks of interest, and Gaussian Random Field Theory to compare connectivity between groups. Seed-based analysis was used to quantify inter-regional connectivity strength from the clusters that exhibited significant between-group differences. To investigate the relationship with cognition, we correlated the connectivity and the performance on the Stroop task. RESULTS The analysis revealed a decrease in functional connectivity in the Default Mode Network (DMN) in both APOEe4 carriers and MAPTA carriers in comparison with non-carriers. APOEe4 carriers showed decreased connectivity in the right angular gyrus (size = 246, p-FDR = 0.0079), which was correlated with poorer performance on the Stroop task. MAPTA carriers showed decreased connectivity in the left middle temporal gyrus (size = 546, p-FDR = 0.0001). In addition, we found that only MAPTA carriers had a decreased connectivity between the DMN and multiple other brain regions. CONCLUSIONS Our findings indicate that APOEe4 and MAPTA alleles modulate brain functional connectivity in the brain regions within the DMN in cognitively intact young adults. APOEe4 carriers also showed a link between connectivity and cognition.
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Affiliation(s)
- Ludmila Kucikova
- Department of Neuroscience, Faculty of Medicine, Dentistry and Heath, Sheffield Institute for Translational Neuroscience, University of Sheffield, 385a Glossop Road, Sheffield, S10 2HQ, SY, UK
- Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, UK
| | - Jianmin Zeng
- Sino-Britain Centre for Cognition and Ageing Research, Faculty of Psychology, Southwest University, Chongqing, China.
| | - Carlos Muñoz-Neira
- Department of Neuroscience, Faculty of Medicine, Dentistry and Heath, Sheffield Institute for Translational Neuroscience, University of Sheffield, 385a Glossop Road, Sheffield, S10 2HQ, SY, UK
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Ohio University Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, USA
| | - Weijie Huang
- Department of Neuroscience, Faculty of Medicine, Dentistry and Heath, Sheffield Institute for Translational Neuroscience, University of Sheffield, 385a Glossop Road, Sheffield, S10 2HQ, SY, UK
- Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, UK
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Craig Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Brain Sciences, Edinburgh, UK
| | - John O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Li Su
- Department of Neuroscience, Faculty of Medicine, Dentistry and Heath, Sheffield Institute for Translational Neuroscience, University of Sheffield, 385a Glossop Road, Sheffield, S10 2HQ, SY, UK.
- Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
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4
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: an Open Multi-omic Community Resource for Identifying Druggable Targets across Neurodegenerative Diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.06.23288266. [PMID: 37090611 PMCID: PMC10120805 DOI: 10.1101/2023.04.06.23288266] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Treatments for neurodegenerative disorders remain rare, although recent FDA approvals, such as Lecanemab and Aducanumab for Alzheimer's Disease, highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use Summary-data-based Mendelian Randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer's disease, 3 amyotrophic lateral sclerosis, 5 Lewy body dementia, 46 Parkinson's disease, and 9 Progressive supranuclear palsy target genes passing multiple test corrections (pSMR_multi < 2.95×10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics - classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these 69.8% are expressed in the disease relevant cell type from single nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as Riluzole in AD. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community [https://nih-card-ndd-smr-home-syboky.streamlit.app/].
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Affiliation(s)
- Chelsea X. Alvarado
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK, WC1N 3BG
- UCL Movement Disorders Centre, University College London, London, UK, WC1N 3BG
| | - Cory A. Weller
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Dan Vitale
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mathew J. Koretsky
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hirotaka Iwaki
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Kristin Levine
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Andrew Singleton
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Faraz Faghri
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Mike A. Nalls
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hampton L. Leonard
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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5
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Zhang Q, Yang P, Pang X, Guo W, Sun Y, Wei Y, Pang C. Preliminary exploration of the co-regulation of Alzheimer's disease pathogenic genes by microRNAs and transcription factors. Front Aging Neurosci 2022; 14:1069606. [PMID: 36561136 PMCID: PMC9764863 DOI: 10.3389/fnagi.2022.1069606] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022] Open
Abstract
Background Alzheimer's disease (AD) is the most common form of age-related neurodegenerative disease. Unfortunately, due to the complexity of pathological types and clinical heterogeneity of AD, there is a lack of satisfactory treatment for AD. Previous studies have shown that microRNAs and transcription factors can modulate genes associated with AD, but the underlying pathophysiology remains unclear. Methods The datasets GSE1297 and GSE5281 were downloaded from the gene expression omnibus (GEO) database and analyzed to obtain the differentially expressed genes (DEGs) through the "R" language "limma" package. The GSE1297 dataset was analyzed by weighted correlation network analysis (WGCNA), and the key gene modules were selected. Next, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis for the key gene modules were performed. Then, the protein-protein interaction (PPI) network was constructed and the hub genes were identified using the STRING database and Cytoscape software. Finally, for the GSE150693 dataset, the "R" package "survivation" was used to integrate the data of survival time, AD transformation status and 35 characteristics, and the key microRNAs (miRNAs) were selected by Cox method. We also performed regression analysis using least absolute shrinkage and selection operator (Lasso)-Cox to construct and validate prognostic features associated with the four key genes using different databases. We also tried to find drugs targeting key genes through DrugBank database. Results GO and KEGG enrichment analysis showed that DEGs were mainly enriched in pathways regulating chemical synaptic transmission, glutamatergic synapses and Huntington's disease. In addition, 10 hub genes were selected from the PPI network by using the algorithm Between Centrality. Then, four core genes (TBP, CDK7, GRM5, and GRIA1) were selected by correlation with clinical information, and the established model had very good prognosis in different databases. Finally, hsa-miR-425-5p and hsa-miR-186-5p were determined by COX regression, AD transformation status and aberrant miRNAs. Conclusion In conclusion, we tried to construct a network in which miRNAs and transcription factors jointly regulate pathogenic genes, and described the process that abnormal miRNAs and abnormal transcription factors TBP and CDK7 jointly regulate the transcription of AD central genes GRM5 and GRIA1. The insights gained from this study offer the potential AD biomarkers, which may be of assistance to the diagnose and therapy of AD.
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Affiliation(s)
- Qi Zhang
- School of Computer Science, Sichuan Normal University, Chengdu, China
| | - Ping Yang
- School of Computer Science, Sichuan Normal University, Chengdu, China
| | - Xinping Pang
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Wenbo Guo
- School of Computer Science, Sichuan Normal University, Chengdu, China
| | - Yue Sun
- School of Computer Science, Sichuan Normal University, Chengdu, China
| | - Yanyu Wei
- National Key Laboratory of Science and Technology on Vacuum Electronics, School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China,*Correspondence: Yanyu Wei,
| | - Chaoyang Pang
- School of Computer Science, Sichuan Normal University, Chengdu, China,*Correspondence: Yanyu Wei,
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6
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Martínez-Iglesias O, Naidoo V, Carrera I, Corzo L, Cacabelos R. Nosustrophine: An Epinutraceutical Bioproduct with Effects on DNA Methylation, Histone Acetylation and Sirtuin Expression in Alzheimer's Disease. Pharmaceutics 2022; 14:pharmaceutics14112447. [PMID: 36432638 PMCID: PMC9698419 DOI: 10.3390/pharmaceutics14112447] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
Alzheimer's disease (AD), the most common cause of dementia, causes irreversible memory loss and cognitive deficits. Current AD drugs do not significantly improve cognitive function or cure the disease. Novel bioproducts are promising options for treating a variety of diseases, including neurodegenerative disorders. Targeting the epigenetic apparatus with bioactive compounds (epidrugs) may aid AD prevention treatment. The aims of this study were to determine the composition of a porcine brain-derived extract Nosustrophine, and whether treating young and older trigenic AD mice produced targeted epigenetic and neuroprotective effects against neurodegeneration. Nosustrophine regulated AD-related APOE and PSEN2 gene expression in young and older APP/BIN1/COPS5 mice, inflammation-related (NOS3 and COX-2) gene expression in 3-4-month-old mice only, global (5mC)- and de novo DNA methylation (DNMT3a), HDAC3 expression and HDAC activity in 3-4-month-old mice; and SIRT1 expression and acetylated histone H3 protein levels in 8-9-month-old mice. Mass spectrometric analysis of Nosustrophine extracts revealed the presence of adenosylhomocysteinase, an enzyme implicated in DNA methylation, and nicotinamide phosphoribosyltransferase, which produces the NAD+ precursor, enhancing SIRT1 activity. Our findings show that Nosustrophine exerts substantial epigenetic effects against AD-related neurodegeneration and establishes Nosustrophine as a novel nutraceutical bioproduct with epigenetic properties (epinutraceutical) that may be therapeutically effective for prevention and early treatment for AD-related neurodegeneration.
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7
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Kramer P. Mitochondria-Microbiota Interaction in Neurodegeneration. Front Aging Neurosci 2022; 13:776936. [PMID: 35002678 PMCID: PMC8733591 DOI: 10.3389/fnagi.2021.776936] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
Alzheimer’s and Parkinson’s are the two best-known neurodegenerative diseases. Each is associated with the excessive aggregation in the brain and elsewhere of its own characteristic amyloid proteins. Yet the two afflictions have much in common and often the same amyloids play a role in both. These amyloids need not be toxic and can help regulate bile secretion, synaptic plasticity, and immune defense. Moreover, when they do form toxic aggregates, amyloids typically harm not just patients but their pathogens too. A major port of entry for pathogens is the gut. Keeping the gut’s microbe community (microbiota) healthy and under control requires that our cells’ main energy producers (mitochondria) support the gut-blood barrier and immune system. As we age, these mitochondria eventually succumb to the corrosive byproducts they themselves release, our defenses break down, pathogens or their toxins break through, and the side effects of inflammation and amyloid aggregation become problematic. Although it gets most of the attention, local amyloid aggregation in the brain merely points to a bigger problem: the systemic breakdown of the entire human superorganism, exemplified by an interaction turning bad between mitochondria and microbiota.
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Affiliation(s)
- Peter Kramer
- Department of General Psychology, University of Padua, Padua, Italy
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8
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Zaman Q, Zhang D, Reddy OS, Wong WT, Lai WF. Roles and Mechanisms of Astragaloside IV in Combating Neuronal Aging. Aging Dis 2022; 13:1845-1861. [DOI: 10.14336/ad.2022.0126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 01/26/2022] [Indexed: 11/18/2022] Open
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9
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Leveille E, Ross OA, Gan-Or Z. Tau and MAPT genetics in tauopathies and synucleinopathies. Parkinsonism Relat Disord 2021; 90:142-154. [PMID: 34593302 DOI: 10.1016/j.parkreldis.2021.09.008] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/25/2021] [Accepted: 09/09/2021] [Indexed: 10/20/2022]
Abstract
MAPT encodes the microtubule-associated protein tau, which is the main component of neurofibrillary tangles (NFTs) and found in other protein aggregates. These aggregates are among the pathological hallmarks of primary tauopathies such as frontotemporal dementia (FTD). Abnormal tau can also be observed in secondary tauopathies such as Alzheimer's disease (AD) and synucleinopathies such as Parkinson's disease (PD). On top of pathological findings, genetic data also links MAPT to these disorders. MAPT variations are a cause or risk factors for many tauopathies and synucleinopathies and are associated with certain clinical and pathological features in affected individuals. In addition to clinical, pathological, and genetic overlap, evidence also suggests that tau and alpha-synuclein may interact on the molecular level, and thus might collaborate in the neurodegenerative process. Understanding the role of MAPT variations in tauopathies and synucleinopathies is therefore essential to elucidate the role of tau in the pathogenesis and phenotype of those disorders, and ultimately to develop targeted therapies. In this review, we describe the role of MAPT genetic variations in tauopathies and synucleinopathies, several genotype-phenotype and pathological features, and discuss their implications for the classification and treatment of those disorders.
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Affiliation(s)
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA; Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-hospital), McGill University, Montréal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada; Department of Human Genetics, McGill University, Montréal, QC, Canada.
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10
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The role of frontotemporal dementia associated genes in patients with Alzheimer's disease. Neurobiol Aging 2021; 107:153-158. [PMID: 34172279 DOI: 10.1016/j.neurobiolaging.2021.05.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/16/2021] [Accepted: 05/23/2021] [Indexed: 01/25/2023]
Abstract
Alzheimer's disease (AD) and frontotemporal dementia (FTD) overlap clinically and pathologically. However, the role of FTD-associated genes in patients with AD remained unclear. To explore the relationship between FTD-associated genes and AD risk, we investigated 14 FTD-associated genes via targeted next-generation sequencing panel or whole-genome sequencing in a total of 721 AD patients and 1391 controls. Common variant-based association analysis and gene-based association test of rare variants were performed by PLINK 1.9 and Sequence Kernel Association Test-Optimal (SKAT-O test) respectively. As a result, 2 common variants, UBQLN1 rs1044175 (p value = 2.76 × 10-4) and MAPT rs2258689 (p value = 5.71 × 10-4), differed significantly between AD patients and controls. Additionally, gene-based analysis aggregating rare variants demonstrated that HNRNPA1 reached statistical significance in the SKAT-O test (p value = 2.24 × 10-3). Protein-protein interaction analysis showed that UBQLN1, MAPT, and HNRNPA1 interacted with proteins encoded by well-recognized AD-associated genes. Our study indicated that UBQLN1, MAPT, and HNRNPA1 are implicated in the pathogenesis of AD in the mainland Chinese population.
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11
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Prendecki M, Kowalska M, Toton E, Kozubski W. Genetic Editing and Pharmacogenetics in Current And Future Therapy Of Neurocognitive Disorders. Curr Alzheimer Res 2021; 17:238-258. [PMID: 32321403 DOI: 10.2174/1567205017666200422152440] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 02/05/2020] [Accepted: 03/25/2020] [Indexed: 12/11/2022]
Abstract
Dementia is an important issue in western societies, and in the following years, this problem will also rise in the developing regions, such as Africa and Asia. The most common types of dementia in adults are Alzheimer's Disease (AD), Dementia with Lewy Bodies (DLB), Frontotemporal Dementia (FTD) and Vascular Dementia (VaD), of which, AD accounts for more than half of the cases. The most prominent symptom of AD is cognitive impairment, currently treated with four drugs: Donepezil, rivastigmine, and galantamine, enhancing cholinergic transmission; as well as memantine, protecting neurons against glutamate excitotoxicity. Despite ongoing efforts, no new drugs in the treatment of AD have been registered for the last ten years, thus multiple studies have been conducted on genetic factors affecting the efficacy of antidementia pharmacotherapy. The researchers investigate the effects of variants in multiple genes, such as ABCB1, ACE, CHAT, CHRNA7, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP3A7, NR1I2, NR1I3, POR, PPAR, RXR, SLC22A1/2/5, SLC47A1, UGT1A6, UGT1A9 and UGT2B7, associated with numerous pathways: the development of pathological proteins, formation and metabolism of acetylcholine, transport, metabolism and excretion of antidementia drugs and transcription factors regulating the expression of genes responsible for metabolism and transport of drugs. The most promising results have been demonstrated for APOE E4, dementia risk variant, BCHE-K, reduced butyrylcholinesterase activity variant, and CYP2D6 UM, ultrarapid hepatic metabolism. Further studies investigate the possibilities of the development of emerging drugs or genetic editing by CRISPR/Cas9 for causative treatment. In conclusion, the pharmacogenetic studies on dementia diseases may improve the efficacy of pharmacotherapy in some patients with beneficial genetic variants, at the same time, identifying the carriers of unfavorable alleles, the potential group of novel approaches to the treatment and prevention of dementia.
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Affiliation(s)
- Michal Prendecki
- Laboratory of Neurobiology, Department of Neurology, Poznan University of Medical Sciences, 60-355 Poznan, Poland
| | - Marta Kowalska
- Laboratory of Neurobiology, Department of Neurology, Poznan University of Medical Sciences, 60-355 Poznan, Poland
| | - Ewa Toton
- Department of Clinical Chemistry and Molecular Diagnostics, Poznan University of Medical Sciences, 60-355 Poznan, Poland
| | - Wojciech Kozubski
- Department of Neurology, Poznan University of Medical Sciences, 60-355 Poznan, Poland
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12
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Gharahkhani P, Jorgenson E, Hysi P, Khawaja AP, Pendergrass S, Han X, Ong JS, Hewitt AW, Segrè AV, Rouhana JM, Hamel AR, Igo RP, Choquet H, Qassim A, Josyula NS, Cooke Bailey JN, Bonnemaijer PWM, Iglesias A, Siggs OM, Young TL, Vitart V, Thiadens AAHJ, Karjalainen J, Uebe S, Melles RB, Nair KS, Luben R, Simcoe M, Amersinghe N, Cree AJ, Hohn R, Poplawski A, Chen LJ, Rong SS, Aung T, Vithana EN, Tamiya G, Shiga Y, Yamamoto M, Nakazawa T, Currant H, Birney E, Wang X, Auton A, Lupton MK, Martin NG, Ashaye A, Olawoye O, Williams SE, Akafo S, Ramsay M, Hashimoto K, Kamatani Y, Akiyama M, Momozawa Y, Foster PJ, Khaw PT, Morgan JE, Strouthidis NG, Kraft P, Kang JH, Pang CP, Pasutto F, Mitchell P, Lotery AJ, Palotie A, van Duijn C, Haines JL, Hammond C, Pasquale LR, Klaver CCW, Hauser M, Khor CC, Mackey DA, Kubo M, Cheng CY, Craig JE, MacGregor S, Wiggs JL. Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries. Nat Commun 2021; 12:1258. [PMID: 33627673 PMCID: PMC7904932 DOI: 10.1038/s41467-020-20851-4] [Citation(s) in RCA: 167] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.
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Affiliation(s)
- Puya Gharahkhani
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California (KPNC), Oakland, CA, USA
| | - Pirro Hysi
- Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Anthony P Khawaja
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Sarah Pendergrass
- Geisinger Research, Biomedical and Translational Informatics Institute, Danville, PA, USA
| | - Xikun Han
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jue Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Alex W Hewitt
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, Australia
| | - Ayellet V Segrè
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - John M Rouhana
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Andrew R Hamel
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Robert P Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Helene Choquet
- Division of Research, Kaiser Permanente Northern California (KPNC), Oakland, CA, USA
| | - Ayub Qassim
- Department of Ophthalmology, Flinders University, Bedford Park, SA, Australia
| | - Navya S Josyula
- Geisinger Research, Biomedical and Translational Informatics Institute, Rockville, MD, USA
| | - Jessica N Cooke Bailey
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Pieter W M Bonnemaijer
- Depatment of Ophthalmology, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- The Rotterdam Eye Hospital, Rotterdam, The Netherlands
| | - Adriana Iglesias
- Depatment of Ophthalmology, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
| | - Owen M Siggs
- Department of Ophthalmology, Flinders University, Bedford Park, SA, Australia
| | - Terri L Young
- Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Alberta A H J Thiadens
- Depatment of Ophthalmology, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Steffen Uebe
- Institute of Human Genetics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Erlangen, Germany
| | | | - K Saidas Nair
- Department of Ophthalmology, School of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Robert Luben
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Mark Simcoe
- Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Ophthalmology, Kings College London, London, United Kingdom
- Institute of Ophthalmology, University College London, London, UK
| | | | - Angela J Cree
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Rene Hohn
- Department of Ophthalmology, Inselspital, University Hospital Bern, University of Bern, Bern, Germany
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Alicia Poplawski
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany
| | - Li Jia Chen
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Shi-Song Rong
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Certre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Eranga Nishanthie Vithana
- Singapore Eye Research Institute, Singapore National Eye Certre, Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore, Republic of Singapore
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
- RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, Japan
| | - Yukihiro Shiga
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
| | - Toru Nakazawa
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
- Department of Retinal Disease Control, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
- Department of Advanced Ophthalmic Medicine, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
- Department of Ophthalmic Imaging and Information Analytics, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
| | - Hannah Currant
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ewan Birney
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Xin Wang
- 23 and Me Inc., San Francisco, CA, USA
| | | | | | | | - Adeyinka Ashaye
- Department of Ophthalmology, University of Ibadan, Ibadan, Nigeria
| | - Olusola Olawoye
- Department of Ophthalmology, University of Ibadan, Ibadan, Nigeria
| | - Susan E Williams
- Division of Ophthalmology, Department of Neurosciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stephen Akafo
- Unit of Ophthalmology, Department of Surgery, University of Ghana Medical School, Accra, Ghana
| | - Michele Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kazuki Hashimoto
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Paul J Foster
- National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital National Health Service Foundation Trust & UCL Institute of Ophthalmology, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Peng T Khaw
- National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital National Health Service Foundation Trust & UCL Institute of Ophthalmology, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - James E Morgan
- Cardiff Centre for Vision Sciences, College of Biomedical and Life Sciences, Maindy Road, Cardiff University, Cardiff, UK
| | - Nicholas G Strouthidis
- National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital National Health Service Foundation Trust & UCL Institute of Ophthalmology, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jae H Kang
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Chi Pui Pang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Francesca Pasutto
- Institute of Human Genetics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Erlangen, Germany
| | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and Westmead Institute for Medical Research, University of Sydney, Sydney, NSW, Australia
| | - Andrew J Lotery
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Psychiatric & Neurodevelopmental Genetics Unit, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Chris Hammond
- Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Louis R Pasquale
- Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Caroline C W Klaver
- Depatment of Ophthalmology, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands
- Institute for Molecular and Clinical Ophthalmology, Basel, Switzerland
| | - Michael Hauser
- Department of Medicine, Duke University, Durham, NC, USA
- Department of Ophthalmology, Duke University, Durham, NC, USA
- Singapore Eye Research Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Chiea Chuen Khor
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - David A Mackey
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, Australia
- Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, Nedlands, WA, Australia
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Certre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jamie E Craig
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Janey L Wiggs
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
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13
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Xie X, Li L, Wu H, Hou F, Chen Y, Xue Q, Zhou Y, Zhang J, Gong J, Song R. Comprehensive Integrative Analyses Identify TIGD5 rs75547282 as a Risk Variant for Autism Spectrum Disorder. Autism Res 2021; 14:631-644. [PMID: 33393181 DOI: 10.1002/aur.2466] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 12/16/2020] [Accepted: 12/21/2020] [Indexed: 12/12/2022]
Abstract
Although recent genome-wide association studies have identified risk loci that strongly associates with autism spectrum disorder (ASD), how to pinpoint the causal genes remains a challenge. We aimed to pinpoint the potential causal genes and explore the possible susceptibility and mechanism. A convergent functional genomics (CFG) method was used to prioritize the candidate genes by combining lines of evidence, including Sherlock analysis, spatio-temporal expression patterns, expression analysis, protein-protein interactions, co-expression and association with brain structure. A higher score in the CFG approach suggested that more evidence supported this gene as an ASD risk gene. We screened genes with higher CFG scores for candidate functional single nucleotide polymorphisms (SNPs). A genotyping experiment (602 ASD children and 604 healthy sex-matched children) and the dual-luciferase reporter gene assay were followed to validate the effects of SNPs. We identified three genes (MAPT, ZNF285, and TIGD5) as candidate causal genes using the CFG approach. The genotyping experiment showed that TIGD5 rs75547282 was associated with an increased risk of ASD under the dominant model (OR = 1.37, 95% CI = 1.09-1.72, P = 0.006) though the statistical power was limited (5.2%). The T allele of rs75547282 activated the expression of TIGD5 compared with the C allele in the dual-luciferase reporter assay. Our study indicates that such comprehensive integrative analyses may be an effective way to explore promising ASD susceptibility variants and needs to be further investigated in future research. Genotyping experiments should, however, be based on a larger population sample to increase statistical power. LAY SUMMARY: We set out to pinpoint the potential causal genes of ASD and explore the possible susceptibility and mechanism by combining lines of evidence from different analyses. Our results show that TIGD5 rs75547282 is associated with the risk of ASD in the Han Chinese population. In addition, a similar framework to seek promising ASD risk variants could be further investigated in future research Autism Res 2021, 14: 631-644. © 2021 International Society for Autism Research and Wiley Periodicals LLC.
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Affiliation(s)
- Xinyan Xie
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Li
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen, China
| | - Hao Wu
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang Hou
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen, China
| | - Yanlin Chen
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen, China
| | - Qi Xue
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Zhou
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiajia Zhang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA
| | - Jianhua Gong
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen, China
| | - Ranran Song
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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14
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Truong DJJ, Phlairaharn T, Eßwein B, Gruber C, Tümen D, Baligács E, Armbrust N, Vaccaro FL, Lederer EM, Beck EM, Geilenkeuser J, Göppert S, Krumwiede L, Grätz C, Raffl G, Schwarz D, Zirngibl M, Živanić M, Beyer M, Körner JD, Santl T, Evsyukov V, Strauß T, Schwarz SC, Höglinger GU, Heutink P, Doll S, Conrad M, Giesert F, Wurst W, Westmeyer GG. Non-invasive and high-throughput interrogation of exon-specific isoform expression. Nat Cell Biol 2021; 23:652-663. [PMID: 34083785 PMCID: PMC8189919 DOI: 10.1038/s41556-021-00678-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 04/01/2021] [Indexed: 02/05/2023]
Abstract
Expression of exon-specific isoforms from alternatively spliced mRNA is a fundamental mechanism that substantially expands the proteome of a cell. However, conventional methods to assess alternative splicing are either consumptive and work-intensive or do not quantify isoform expression longitudinally at the protein level. Here, we therefore developed an exon-specific isoform expression reporter system (EXSISERS), which non-invasively reports the translation of exon-containing isoforms of endogenous genes by scarlessly excising reporter proteins from the nascent polypeptide chain through highly efficient, intein-mediated protein splicing. We applied EXSISERS to quantify the inclusion of the disease-associated exon 10 in microtubule-associated protein tau (MAPT) in patient-derived induced pluripotent stem cells and screened Cas13-based RNA-targeting effectors for isoform specificity. We also coupled cell survival to the inclusion of exon 18b of FOXP1, which is involved in maintaining pluripotency of embryonic stem cells, and confirmed that MBNL1 is a dominant factor for exon 18b exclusion. EXSISERS enables non-disruptive and multimodal monitoring of exon-specific isoform expression with high sensitivity and cellular resolution, and empowers high-throughput screening of exon-specific therapeutic interventions.
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Affiliation(s)
- Dong-Jiunn Jeffery Truong
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Teeradon Phlairaharn
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Bianca Eßwein
- grid.4567.00000 0004 0483 2525Institute of Developmental Genetics, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Christoph Gruber
- grid.4567.00000 0004 0483 2525Institute of Developmental Genetics, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Deniz Tümen
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.411941.80000 0000 9194 7179Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany
| | - Enikő Baligács
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Niklas Armbrust
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Francesco Leandro Vaccaro
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Eva-Maria Lederer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Eva Magdalena Beck
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Julian Geilenkeuser
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Simone Göppert
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Luisa Krumwiede
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Grätz
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Gerald Raffl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Dominic Schwarz
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Martin Zirngibl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Milica Živanić
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Maren Beyer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Johann Dietmar Körner
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Santl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Valentin Evsyukov
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.6936.a0000000123222966Department of Neurology, Technical University Munich, Munich, Germany ,grid.10423.340000 0000 9529 9877Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Tabea Strauß
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.6936.a0000000123222966Department of Neurology, Technical University Munich, Munich, Germany
| | - Sigrid C. Schwarz
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.6936.a0000000123222966Department of Neurology, Technical University Munich, Munich, Germany
| | - Günter U. Höglinger
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.6936.a0000000123222966Department of Neurology, Technical University Munich, Munich, Germany ,grid.10423.340000 0000 9529 9877Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Peter Heutink
- grid.10392.390000 0001 2190 1447Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Sebastian Doll
- grid.4567.00000 0004 0483 2525Institute of Metabolism and Cell Death, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Marcus Conrad
- grid.4567.00000 0004 0483 2525Institute of Metabolism and Cell Death, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.78028.350000 0000 9559 0613Laboratory of Experimental Oncology, National Research Medical University, Moscow, Russia
| | - Florian Giesert
- grid.4567.00000 0004 0483 2525Institute of Developmental Genetics, Helmholtz Zentrum München, Oberschleißheim, Germany
| | - Wolfgang Wurst
- grid.4567.00000 0004 0483 2525Institute of Developmental Genetics, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.6936.a0000000123222966TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Gil Gregor Westmeyer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Oberschleißheim, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
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15
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Wu Q, Chen Y, Gu Y, Fang S, Li W, Wang Q, Fang J, Cai C. Systems pharmacology-based approach to investigate the mechanisms of Danggui-Shaoyao-san prescription for treatment of Alzheimer's disease. BMC Complement Med Ther 2020; 20:282. [PMID: 32948180 PMCID: PMC7501700 DOI: 10.1186/s12906-020-03066-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 08/30/2020] [Indexed: 02/06/2023] Open
Abstract
Background Alzheimer’s disease (AD) is the most common cause of dementia in the elderly, characterized by a progressive and irreversible loss of memory and cognitive abilities. Currently, the prevention and treatment of AD still remains a huge challenge. As a traditional Chinese medicine (TCM) prescription, Danggui-Shaoyao-san decoction (DSS) has been demonstrated to be effective for alleviating AD symptoms in animal experiments and clinical applications. However, due to the complex components and biological actions, its underlying molecular mechanism and effective substances are not yet fully elucidated. Methods In this study, we firstly systematically reviewed and summarized the molecular effects of DSS against AD based on current literatures of in vivo studies. Furthermore, an integrated systems pharmacology framework was proposed to explore the novel anti-AD mechanisms of DSS and identify the main active components. We further developed a network-based predictive model for identifying the active anti-AD components of DSS by mapping the high-quality AD disease genes into the global drug-target network. Results We constructed a global drug-target network of DSS consisting 937 unique compounds and 490 targets by incorporating experimental and computationally predicted drug–target interactions (DTIs). Multi-level systems pharmacology analyses revealed that DSS may regulate multiple biological pathways related to AD pathogenesis, such as the oxidative stress and inflammatory reaction processes. We further conducted a network-based statistical model, drug-likeness analysis, human intestinal absorption (HIA) and blood-brain barrier (BBB) penetration prediction to uncover the key ani-AD ingredients in DSS. Finally, we highlighted 9 key ingredients and validated their synergistic role against AD through a subnetwork. Conclusion Overall, this study proposed an integrative systems pharmacology approach to disclose the therapeutic mechanisms of DSS against AD, which also provides novel in silico paradigm for investigating the effective substances of complex TCM prescription.
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Affiliation(s)
- Qihui Wu
- Clinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Guangzhou University of Chinese Medicine, Haikou, 570000, China.,Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China
| | - Yunbo Chen
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China
| | - Yong Gu
- Clinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Guangzhou University of Chinese Medicine, Haikou, 570000, China
| | - Shuhuan Fang
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China
| | - Weirong Li
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China
| | - Qi Wang
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
| | - Jiansong Fang
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
| | - Chuipu Cai
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China. .,School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
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16
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Watt G, Chesworth R, Przybyla M, Ittner A, Garner B, Ittner LM, Karl T. Chronic cannabidiol (CBD) treatment did not exhibit beneficial effects in 4-month-old male TAU58/2 transgenic mice. Pharmacol Biochem Behav 2020; 196:172970. [PMID: 32562718 DOI: 10.1016/j.pbb.2020.172970] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 05/27/2020] [Accepted: 06/16/2020] [Indexed: 10/24/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline, motor impairments, and accumulation of hallmark proteins, amyloid-beta (Aβ) and tau. Traditionally, transgenic mouse models for AD have focused on Aβ pathology, however, recently a number of tauopathy transgenic models have been developed, including the TAU58/2 transgenic model. Cannabidiol (CBD), a non-toxic constituent of the Cannabis sativa plant, has been shown to prevent and reverse cognitive deficits in Aβ transgenic mouse models of AD. Importantly, the therapeutic properties of CBD on the behavioural phenotype of tauopathy mouse models have not been investigated. We assessed the impact of chronic CBD treatment (i.e. 50 mg/kg CBD i.p. administration starting 3 weeks prior to behavioural assessments) on disease-relevant behaviours of 4-month-old TAU58/2 transgenic males in paradigms for anxiety, motor functions, and cognition. TAU58/2 transgenic males demonstrated reduced body weight, anxiety and impaired motor functions. Furthermore, they demonstrated increased freezing in fear conditioning compared to wild type-like animals. Interestingly, both sociability and social recognition memory were intact in AD transgenic mice. Chronic CBD treatment did not affect behavioural changes in transgenic males. In summary, 4-month-old TAU58/2 transgenic males exhibited no deficits in social recognition memory, suggesting that motor deficits and changes in anxiety at this age do not impact on social domains. The moderate increase in fear-associated memory needs further investigation but could be related to differences in fear extinction. Future investigations will need to clarify CBD's therapeutic potential for reversing motor deficits in TAU58/2 transgenic mice by considering alternative CBD treatment designs including changed CBD dosing.
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Affiliation(s)
- Georgia Watt
- School of Medicine, Western Sydney University, Campbelltown, Australia
| | - Rose Chesworth
- School of Medicine, Western Sydney University, Campbelltown, Australia
| | - Magdalena Przybyla
- Dementia Research Centre, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Arne Ittner
- Dementia Research Centre, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Brett Garner
- School of Chemistry and Molecular Bioscience, Illawarra Health and Medical Research Institute, University of Wollongong, Australia
| | - Lars M Ittner
- Dementia Research Centre, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Tim Karl
- School of Medicine, Western Sydney University, Campbelltown, Australia; Neuroscience Research Australia (NeuRA), Randwick, Australia.
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17
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Kaeser GE, Chun J. Mosaic Somatic Gene Recombination as a Potentially Unifying Hypothesis for Alzheimer's Disease. Front Genet 2020; 11:390. [PMID: 32457796 PMCID: PMC7221065 DOI: 10.3389/fgene.2020.00390] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 03/27/2020] [Indexed: 12/11/2022] Open
Abstract
The recent identification of somatic gene recombination(SGR) in human neurons affecting the well-known Alzheimer's disease (AD) pathogenic gene, amyloid precursor protein (APP), has implications for the normal and the diseased human brain. The amyloid hypothesis has been the prevailing theory for sporadic AD (SAD) pathogenesis since the discovery of APP gene involvement in familial AD and Down syndrome. Yet, despite enormous scientific and clinical effort, no disease-modifying therapy has emerged. SGR offers a novel mechanism to explain AD pathogenesis and the failures of amyloid-related clinical trials, while maintaining consistency with most aspects of the amyloid hypothesis and additionally supporting possible roles for tau, oxidative stress, inflammation, infection, and prions. SGR retro-inserts novel "genomic complementary DNAs" (gencDNAs) into neuronal genomes and becomes dysregulated in SAD, producing numerous mosaic APP variants, including DNA mutations observed in familial AD. Notably, SGR requires gene transcription, DNA strand-breaks, and reverse transcriptase (RT) activity, all of which may be promoted by well-known AD risk factors and provide a framework for the pursuit of new SGR-based therapeutics. In this perspective, we review evidence for APP SGR in AD pathogenesis and discuss its possible relevance to other AD-related dementias. Further, SGR's requirement for RT activity and the relative absence of AD in aged HIV -infected patients exposed to RT inhibitors suggest that these Food and Drug Administration (FDA)-approved drugs may represent a near-term disease-modifying therapy for AD.
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Affiliation(s)
| | - Jerold Chun
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, United States
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18
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Watt G, Przybyla M, Zak V, van Eersel J, Ittner A, Ittner LM, Karl T. Novel Behavioural Characteristics of Male Human P301S Mutant Tau Transgenic Mice - A Model for Tauopathy. Neuroscience 2020; 431:166-175. [PMID: 32058066 DOI: 10.1016/j.neuroscience.2020.01.047] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 01/30/2020] [Accepted: 01/31/2020] [Indexed: 01/28/2023]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease characterised by progressive cognitive decline and the accumulation of two hallmark proteins, amyloid-beta (Aβ) and tau. Traditionally, transgenic mouse models for AD have generally focused on Aβ pathology, however, in recent years a number of tauopathy transgenic mouse models have been developed, including the TAU58/2 mouse model. These mice develop tau pathology and neurofibrillary tangles from 2 months of age and show motor impairments and alterations in the behavioural response to elevated plus maze (EPM) testing. The cognitive and social phenotype of this model has not yet been assessed comprehensively. Furthermore, the behavioural changes seen in the EPM have previously been linked to both anxiety and disinhibitory phenotypes. Thus, this study assessed 4-month-old TAU58/2 males comprehensively for disinhibitory and social behaviours, social recognition memory, and sensorimotor gating. TAU58/2 males demonstrated reduced exploration and anxiety-like behaviours but no changes to disinhibitory behaviours, reduced sociability in the social preference test and impaired acoustic startle and prepulse inhibition. Aggressive and socio-positive behaviours were not affected except a reduction in the occurrence of nosing and anogenital sniffing. Our study identified new phenotypic characteristics of young adult male TAU58/2 transgenic mice and clarified the nature of changes detected in the behavioural response of these mice to EPM testing. Social withdrawal and inappropriate social behaviours are common symptoms in both AD and FTD patients and impaired sensorimotor gating is seen in moderate-late stage AD, emphasising the relevance of the TAU58/2 model to these diseases.
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Affiliation(s)
- Georgia Watt
- School of Medicine, Western Sydney University, Campbelltown, Australia
| | - Magdalena Przybyla
- Dementia Research Centre and Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Valeria Zak
- School of Medicine, Western Sydney University, Campbelltown, Australia
| | - Janet van Eersel
- Dementia Research Centre and Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Arne Ittner
- Dementia Research Centre and Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Lars M Ittner
- Dementia Research Centre and Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Australia
| | - Tim Karl
- School of Medicine, Western Sydney University, Campbelltown, Australia; Neuroscience Research Australia (NeuRA), Randwick, Australia.
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19
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Tau and TDP-43 proteinopathies: kindred pathologic cascades and genetic pleiotropy. J Transl Med 2019; 99:993-1007. [PMID: 30742063 PMCID: PMC6609463 DOI: 10.1038/s41374-019-0196-y] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 01/04/2019] [Accepted: 01/07/2019] [Indexed: 12/11/2022] Open
Abstract
We review the literature on Tau and TDP-43 proteinopathies in aged human brains and the relevant underlying pathogenetic cascades. Complex interacting pathways are implicated in Alzheimer's disease and related dementias (ADRD), wherein multiple proteins tend to misfold in a manner that is "reactive," but, subsequently, each proteinopathy may contribute strongly to the clinical symptoms. Tau proteinopathy exists in brains of individuals across a broad spectrum of primary underlying conditions-e.g., developmental, traumatic, and inflammatory/infectious diseases. TDP-43 proteinopathy is also expressed in a wide range of clinical disorders. Although TDP-43 proteinopathy was first described in the central nervous system of patients with amyotrophic lateral sclerosis (ALS) and in subtypes of frontotemporal dementia (FTD/FTLD), TDP-43 proteinopathy is also present in chronic traumatic encephalopathy, cognitively impaired persons in advanced age with hippocampal sclerosis, Huntington's disease, and other diseases. We list known Tau and TDP-43 proteinopathies. There is also evidence of cellular co-localization between Tau and TDP-43 misfolded proteins, suggesting common pathways or protein interactions facilitating misfolding in one protein by the other. Multiple pleiotropic gene variants can alter risk for Tau or TDP-43 pathologies, and certain gene variants (e.g., APOE ε4, Huntingtin triplet repeats) are associated with increases of both Tau and TDP-43 proteinopathies. Studies of genetic risk factors have provided insights into multiple nodes of the pathologic cascades involved in Tau and TDP-43 proteinopathies. Variants from a specific gene can be either a low-penetrant risk factor for a group of diseases, or alternatively, a different variant of the same gene may be a disease-driving allele that is associated with a relatively aggressive and early-onset version of a clinically and pathologically specific disease type. Overall, a complex but enlightening paradigm has emerged, wherein both Tau and TDP-43 proteinopathies are linked to numerous overlapping upstream influences, and both are associated with multiple downstream pathologically- and clinically-defined deleterious effects.
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20
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Filippov MA, Vorobyov VV. Detrimental and synergistic role of epilepsy - Alzheimer's disease risk factors. Neural Regen Res 2019; 14:1376-1377. [PMID: 30964059 PMCID: PMC6524520 DOI: 10.4103/1673-5374.253519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
| | - Vasily V Vorobyov
- Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, Russia
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21
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Zhou F, Chen S. Effects of Gender and Other Confounding Factors on Leptin Concentrations in Alzheimer's Disease: Evidence from the Combined Analysis of 27 Case-Control Studies. J Alzheimers Dis 2019; 62:477-486. [PMID: 29439354 DOI: 10.3233/jad-170983] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Leptin, as a link between fat mass and the brain, has been reported to be associated with gender. The gender differences in leptin levels between Alzheimer's disease (AD) and healthy elderly controls are inconclusive so far. To quantitatively summarize the leptin data available from female and male patients with AD, we searched PubMed and EMBASE for articles published from inception to July 20, 2017. Data were extracted from 27 studies, consisting of 3,014 participants. The pooled results showed that the overall leptin levels were lower in AD (Hedges' g = -0.481; p = 0.002) than in controls, and the leptin levels in whole blood and serum were decreased with moderate and large effect sizes (g = -0.677, -0.839; respectively; both of p-values <0.001) in AD compared with controls. In blood, there were significantly lower concentrations of leptin in female AD than in female controls (g = -0.590; p = 0.014), but not in male case-control group (g = -0.666; p = 0.067). Meta-regression analysis demonstrated that the decreased extent of leptin levels in AD paralleled the degree of the severity of dementia symptoms, as well as the alterations of body mass index (p-values ≤0.002). The findings provide strong evidence that 1) the blood concentrations of leptin are lower in female AD patients than in female controls; and 2) the greater the severity of dementia symptoms, the greater the decreases in the blood leptin levels. But more future investigations on the blood leptin levels in male AD patients is warranted.
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Affiliation(s)
- Futao Zhou
- College of Medicine and Health, Lishui University, Lishui Zhejiang, China
| | - Shuangrong Chen
- College of Engineering, Lishui University, Lishui Zhejiang, China
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22
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Babić Leko M, Willumsen N, Nikolac Perković M, Klepac N, Borovečki F, Hof PR, Sonicki Z, Pivac N, de Silva R, Šimić G. Association of MAPT haplotype-tagging polymorphisms with cerebrospinal fluid biomarkers of Alzheimer's disease: A preliminary study in a Croatian cohort. Brain Behav 2018; 8:e01128. [PMID: 30329219 PMCID: PMC6236251 DOI: 10.1002/brb3.1128] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 08/31/2018] [Accepted: 09/03/2018] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Alzheimer's disease (AD) is the world leading cause of dementia. Early detection of AD is essential for faster and more efficacious usage of therapeutics and preventive measures. Even though it is well known that one ε4 allele of apolipoprotein E gene increases the risk for sporadic AD five times, and that two ε4 alleles increase the risk 20 times, reliable genetic markers for AD are not yet available. Previous studies have shown that microtubule-associated protein tau (MAPT) gene polymorphisms could be associated with increased risk for AD. METHODS The present study included 113 AD patients and 53 patients with mild cognitive impairment (MCI), as well as nine healthy controls (HC) and 53 patients with other primary causes of dementia. The study assessed whether six MAPT haplotype-tagging polymorphisms (rs1467967, rs242557, rs3785883, rs2471738, del-In9, and rs7521) and MAPT haplotypes are associated with AD pathology, as measured by cerebrospinal fluid (CSF) AD biomarkers amyloid β1-42 (Aβ1-42 ), total tau (t-tau), tau phosphorylated at epitopes 181 (p-tau181 ), 199 (p-tau199 ), and 231 (p-tau231 ), and visinin-like protein 1 (VILIP-1). RESULTS Significant increases in t-tau and p-tau CSF levels were found in patients with AG and AA MAPT rs1467967 genotype, CC MAPT rs2471738 genotype and in patients with H1H2 or H2H2 MAPT haplotype. CONCLUSIONS These results indicate that MAPT haplotype-tagging polymorphisms and MAPT haplotypes should be further tested as potential genetic biomarkers of AD.
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Affiliation(s)
- Mirjana Babić Leko
- Department for NeuroscienceCroatian Institute for Brain Research, University of Zagreb Medical SchoolZagrebCroatia
| | - Nanet Willumsen
- Reta Lila Weston Institute, UCL Institute of NeurologyLondonUK
- Department of Molecular NeuroscienceUCL Institute of NeurologyLondonUK
| | | | - Nataša Klepac
- Department for Functional Genomics, Center for Translational and Clinical ResearchUniversity of Zagreb Medical School, University Hospital Center ZagrebZagrebCroatia
| | - Fran Borovečki
- Department for Functional Genomics, Center for Translational and Clinical ResearchUniversity of Zagreb Medical School, University Hospital Center ZagrebZagrebCroatia
| | - Patrick R. Hof
- Fishberg Department of NeuroscienceFriedman Brain Institute and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount SinaiNew YorkNew York
| | - Zdenko Sonicki
- Andrija Štampar School of Public HealthUniversity of Zagreb School of MedicineZagrebCroatia
| | - Nela Pivac
- Ruđer Bošković InstituteDivision of Molecular MedicineZagrebCroatia
| | - Rohan de Silva
- Reta Lila Weston Institute, UCL Institute of NeurologyLondonUK
- Department of Molecular NeuroscienceUCL Institute of NeurologyLondonUK
| | - Goran Šimić
- Department for NeuroscienceCroatian Institute for Brain Research, University of Zagreb Medical SchoolZagrebCroatia
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