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Chu D, Lei L, Gu S, Liu F, Wu F. Dual-specificity tyrosine phosphorylation-regulated kinase 1A promotes the inclusion of amyloid precursor protein exon 7. Biochem Pharmacol 2024; 224:116233. [PMID: 38663682 DOI: 10.1016/j.bcp.2024.116233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 03/27/2024] [Accepted: 04/22/2024] [Indexed: 04/29/2024]
Abstract
Extracellular amyloid plaques made of Amyloid-β (Aβ) derived from amyloid precursor protein (APP) is one of the major neuropathological hallmarks of Alzheimer's disease (AD). There are three major isoforms of APP, APP770, APP751, and APP695 generated by alternative splicing of exons 7 and 8. Exon 7 encodes the Kunitz protease inhibitor (KPI) domain. Its inclusion generates APP isoforms containing KPI, APPKPI+, which is elevated in AD and Down syndrome (DS) brains and associated with increased Aβ deposition. Dual-specificity tyrosine phosphorylation-regulated kinase 1A (Dyrk1A) phosphorylates many splicing factors and regulates the alternative splicing of pre-mRNA. It is upregulated in DS and AD brain. However, it is not yet clear whether Dyrk1A could regulate APP alternative splicing. In the present study, we overexpressed or knocked down Dyrk1A in cultured cells and observed that Dyrk1A promoted the inclusion of both APP exons 7 and 8. Moreover, a significant increase in APP exon7 inclusion was also detected in the forebrain and hippocampus of human Dyrk1A transgenic mice - Tg/Dyrk1A. Screening for splicing factors regulated by Dyrk1A revealed that serine/arginine-rich protein 9G8 inhibited APP exon7 inclusion and interacted with APP pre-mRNA. In vitro, expression of exon 7 facilitated APP cleavage. In human Dyrk1A transgenic mice, we also found an increase in Aβ production. These findings suggest that Dyrk1A inhibits the splicing factor 9G8 and promotes APP exon 7 inclusion, leading to more APPKPI+ expression and APP cleavage and potentially contributing to Aβ production in vivo.
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Affiliation(s)
- Dandan Chu
- Department of Pharmacology, School of Pharmacy, Nantong University, Nantong 226001, China; Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY 10314, USA; Key Laboratory of Neuroregeneration of Jiangsu and Ministry of Education, NMPA Key Laboratory for Research and Evaluation of Tissue Engineering Technology Products, Co-Innovation Center of Neuroregeneration, Nantong University, Nantong 226001, China
| | - Leyi Lei
- Department of Pharmacology, School of Pharmacy, Nantong University, Nantong 226001, China
| | - Shu Gu
- Nantong No.1 High School of Jiangsu Province, Nantong 226300, China
| | - Fei Liu
- Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY 10314, USA.
| | - Feng Wu
- Department of Pharmacology, School of Pharmacy, Nantong University, Nantong 226001, China; Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY 10314, USA.
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2
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Lin Y, Kwok S, Hein AE, Thai BQ, Alabi Y, Ostrowski MS, Wu K, Floor SN. RNA molecular recording with an engineered RNA deaminase. Nat Methods 2023; 20:1887-1899. [PMID: 37857907 DOI: 10.1038/s41592-023-02046-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 09/13/2023] [Indexed: 10/21/2023]
Abstract
RNA deaminases are powerful tools for base editing and RNA molecular recording. However, the enzymes used in currently available RNA molecular recorders such as TRIBE, DART or STAMP have limitations due to RNA structure and sequence dependence. We designed a platform for directed evolution of RNA molecular recorders. We engineered an RNA A-to-I deaminase (an RNA adenosine base editor, rABE) that has high activity, low bias and low background. Using rABE, we present REMORA (RNA-encoded molecular recording in adenosines), wherein deamination by rABE writes a molecular record of RNA-protein interactions. By combining rABE with the C-to-U deaminase APOBEC1 and long-read RNA sequencing, we measured binding by two RNA-binding proteins on single messenger RNAs. Orthogonal RNA molecular recording of mammalian Pumilio proteins PUM1 and PUM2 shows that PUM1 competes with PUM2 for a subset of sites in cells. Furthermore, we identify transcript isoform-specific RNA-protein interactions driven by isoform changes distal to the binding site. The genetically encodable RNA deaminase rABE enables single-molecule identification of RNA-protein interactions with cell type specificity.
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Affiliation(s)
- Yizhu Lin
- Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA
| | - Samentha Kwok
- Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA
| | - Abigail E Hein
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Bao Quoc Thai
- Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA
- MSTP Program, University of Arizona, Tuscon, AZ, USA
| | - Yewande Alabi
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Megan S Ostrowski
- Gladstone Institute for Data Science and Biotechnology, San Francisco, CA, USA
| | - Ke Wu
- Gladstone Institute for Data Science and Biotechnology, San Francisco, CA, USA
| | - Stephen N Floor
- Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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3
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Sagar R, Azoidis I, Zivko C, Xydia A, Oh ES, Rosenberg PB, Lyketsos CG, Mahairaki V, Avramopoulos D. Excitatory Neurons Derived from Human-Induced Pluripotent Stem Cells Show Transcriptomic Differences in Alzheimer's Patients from Controls. Cells 2023; 12:1990. [PMID: 37566069 PMCID: PMC10417412 DOI: 10.3390/cells12151990] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/27/2023] [Accepted: 07/28/2023] [Indexed: 08/12/2023] Open
Abstract
The recent advances in creating pluripotent stem cells from somatic cells and differentiating them into a variety of cell types is allowing us to study them without the caveats associated with disease-related changes. We generated induced Pluripotent Stem Cells (iPSCs) from eight Alzheimer's disease (AD) patients and six controls and used lentiviral delivery to differentiate them into excitatory glutamatergic neurons. We then performed RNA sequencing on these neurons and compared the Alzheimer's and control transcriptomes. We found that 621 genes show differences in expression levels at adjusted p < 0.05 between the case and control derived neurons. These genes show significant overlap and directional concordance with genes reported from a single-cell transcriptome study of AD patients; they include five genes implicated in AD from genome-wide association studies and they appear to be part of a larger functional network as indicated by an excess of interactions between them observed in the protein-protein interaction database STRING. Exploratory analysis with Uniform Manifold Approximation and Projection (UMAP) suggests distinct clusters of patients, based on gene expression, who may be clinically different. Our research outcomes will enable the precise identification of distinct biological subtypes among individuals with Alzheimer's disease, facilitating the implementation of tailored precision medicine strategies.
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Affiliation(s)
- Ram Sagar
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Ioannis Azoidis
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Cristina Zivko
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Ariadni Xydia
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Esther S. Oh
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Paul B. Rosenberg
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Constantine G. Lyketsos
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Vasiliki Mahairaki
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Dimitrios Avramopoulos
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
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4
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Nikom D, Zheng S. Alternative splicing in neurodegenerative disease and the promise of RNA therapies. Nat Rev Neurosci 2023; 24:457-473. [PMID: 37336982 DOI: 10.1038/s41583-023-00717-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2023] [Indexed: 06/21/2023]
Abstract
Alternative splicing generates a myriad of RNA products and protein isoforms of different functions from a single gene. Dysregulated alternative splicing has emerged as a new mechanism broadly implicated in the pathogenesis of neurodegenerative diseases such as Alzheimer disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson disease and repeat expansion diseases. Understanding the mechanisms and functional outcomes of abnormal splicing in neurological disorders is vital in developing effective therapies to treat mis-splicing pathology. In this Review, we discuss emerging research and evidence of the roles of alternative splicing defects in major neurodegenerative diseases and summarize the latest advances in RNA-based therapeutic strategies to target these disorders.
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Affiliation(s)
- David Nikom
- Neuroscience Graduate Program, University of California, Riverside, Riverside, CA, USA
- Center for RNA Biology and Medicine, University of California, Riverside, Riverside, CA, USA
| | - Sika Zheng
- Neuroscience Graduate Program, University of California, Riverside, Riverside, CA, USA.
- Center for RNA Biology and Medicine, University of California, Riverside, Riverside, CA, USA.
- Division of Biomedical Sciences, University of California, Riverside, Riverside, CA, USA.
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5
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Ellis JA, Hale MA, Cleary JD, Wang E, Andrew Berglund J. Alternative splicing outcomes across an RNA-binding protein concentration gradient. J Mol Biol 2023:168156. [PMID: 37230319 DOI: 10.1016/j.jmb.2023.168156] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/18/2023] [Accepted: 05/17/2023] [Indexed: 05/27/2023]
Abstract
Alternative splicing (AS) is a dynamic RNA processing step that produces multiple RNA isoforms from a single pre-mRNA transcript and contributes to the complexity of the cellular transcriptome and proteome. This process is regulated through a network of cis-regulatory sequence elements and trans-acting factors, most-notably RNA binding proteins (RBPs). The muscleblind-like (MBNL) and RNA binding fox-1 homolog (RBFOX) are two well characterized families of RBPs that regulate fetal to adult AS transitions critical for proper muscle, heart, and central nervous system development. To better understand how the concentration of these RBPs influences AS transcriptome wide, we engineered a MBNL1 and RBFOX1 inducible HEK-293 cell line. Modest induction of exogenous RBFOX1 in this cell line modulated MBNL1-dependent AS outcomes in 3 skipped exon events, despite significant levels of endogenous RBFOX1 and RBFOX2. Due to background RBFOX levels, we conducted a focused analysis of dose-dependent MBNL1 skipped exon AS outcomes and generated transcriptome wide dose-response curves. Analysis of this data demonstrates that MBNL1-regulated exclusion events may require higher concentrations of MBNL1 protein to properly regulate AS outcomes compared to inclusion events and that multiple arrangements of YGCY motifs can produce similar splicing outcomes. These results suggest that rather than a simple relationship between the organization of RBP binding sites and a specific splicing outcome, that complex interaction networks govern both AS inclusion and exclusion events across a RBP gradient.
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Affiliation(s)
- Joseph A Ellis
- Department of Biochemistry & Molecular Biology & Center for NeuroGenetics, College of Medicine, University of Florida, Gainesville, Florida 32610, United States; The RNA Institute, College of Arts and Sciences, University at Albany, SUNY, Albany, NY 12222, United States
| | - Melissa A Hale
- Department of Biochemistry & Molecular Biology & Center for NeuroGenetics, College of Medicine, University of Florida, Gainesville, Florida 32610, United States; Department of Neurology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia 23298, United States
| | - John D Cleary
- The RNA Institute, College of Arts and Sciences, University at Albany, SUNY, Albany, NY 12222, United States
| | - Eric Wang
- Department of Microbiology and Molecular Genetics & Center for NeuroGenetics, College of Medicine, University of Florida, Gainesville, Florida 32610, United States
| | - J Andrew Berglund
- Department of Biochemistry & Molecular Biology & Center for NeuroGenetics, College of Medicine, University of Florida, Gainesville, Florida 32610, United States; The RNA Institute, College of Arts and Sciences, University at Albany, SUNY, Albany, NY 12222, United States; Department of Biological Sciences, College of Arts and Sciences, University at Albany, SUNY, Albany, NY 12222, United States; RNA Institute, State University of New York at Albany, LSRB-2033, 1400 Washington Avenue, Albany, New York, 12222.
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6
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Bhatnagar A, Krick K, Karisetty BC, Armour EM, Heller EA, Elefant F. Tip60's Novel RNA-Binding Function Modulates Alternative Splicing of Pre-mRNA Targets Implicated in Alzheimer's Disease. J Neurosci 2023; 43:2398-2423. [PMID: 36849418 PMCID: PMC10072303 DOI: 10.1523/jneurosci.2331-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/08/2023] [Accepted: 02/13/2023] [Indexed: 03/01/2023] Open
Abstract
The severity of Alzheimer's disease (AD) progression involves a complex interplay of genetics, age, and environmental factors orchestrated by histone acetyltransferase (HAT)-mediated neuroepigenetic mechanisms. While disruption of Tip60 HAT action in neural gene control is implicated in AD, alternative mechanisms underlying Tip60 function remain unexplored. Here, we report a novel RNA binding function for Tip60 in addition to its HAT function. We show that Tip60 preferentially interacts with pre-mRNAs emanating from its chromatin neural gene targets in the Drosophila brain and this RNA binding function is conserved in human hippocampus and disrupted in Drosophila brains that model AD pathology and in AD patient hippocampus of either sex. Since RNA splicing occurs co-transcriptionally and alternative splicing (AS) defects are implicated in AD, we investigated whether Tip60-RNA targeting modulates splicing decisions and whether this function is altered in AD. Replicate multivariate analysis of transcript splicing (rMATS) analysis of RNA-Seq datasets from wild-type and AD fly brains revealed a multitude of mammalian-like AS defects. Strikingly, over half of these altered RNAs are identified as bona-fide Tip60-RNA targets that are enriched for in the AD-gene curated database, with some of these AS alterations prevented against by increasing Tip60 in the fly brain. Further, human orthologs of several Tip60-modulated splicing genes in Drosophila are well characterized aberrantly spliced genes in human AD brains, implicating disruption of Tip60's splicing function in AD pathogenesis. Our results support a novel RNA interaction and splicing regulatory function for Tip60 that may underly AS impairments that hallmark AD etiology.SIGNIFICANCE STATEMENT Alzheimer's disease (AD) has recently emerged as a hotbed for RNA alternative splicing (AS) defects that alter protein function in the brain yet causes remain unclear. Although recent findings suggest convergence of epigenetics with co-transcriptional AS, whether epigenetic dysregulation in AD pathology underlies AS defects remains unknown. Here, we identify a novel RNA interaction and splicing regulatory function for Tip60 histone acetyltransferase (HAT) that is disrupted in Drosophila brains modeling AD pathology and in human AD hippocampus. Importantly, mammalian orthologs of several Tip60-modulated splicing genes in Drosophila are well characterized aberrantly spliced genes in human AD brain. We propose that Tip60-mediated AS modulation is a conserved critical posttranscriptional step that may underlie AS defects now characterized as hallmarks of AD.
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Affiliation(s)
- Akanksha Bhatnagar
- Department of Biology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Keegan Krick
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | | | - Ellen M Armour
- Department of Biology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Elizabeth A Heller
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Felice Elefant
- Department of Biology, Drexel University, Philadelphia, Pennsylvania 19104
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7
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Angarola BL, Anczuków O. Splicing alterations in healthy aging and disease. WILEY INTERDISCIPLINARY REVIEWS. RNA 2021. [PMID: 33565261 DOI: 10.1002/wrna.1643.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Alternative RNA splicing is a key step in gene expression that allows generation of numerous messenger RNA transcripts encoding proteins of varied functions from the same gene. It is thus a rich source of proteomic and functional diversity. Alterations in alternative RNA splicing are observed both during healthy aging and in a number of human diseases, several of which display premature aging phenotypes or increased incidence with age. Age-associated splicing alterations include differential splicing of genes associated with hallmarks of aging, as well as changes in the levels of core spliceosomal genes and regulatory splicing factors. Here, we review the current known links between alternative RNA splicing, its regulators, healthy biological aging, and diseases associated with aging or aging-like phenotypes. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Splicing Regulation/Alternative Splicing.
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Affiliation(s)
| | - Olga Anczuków
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.,Department of Genetics and Genome Sciences, UConn Health, Farmington, Connecticut, USA.,Institute for Systems Genomics, UConn Health, Farmington, Connecticut, USA
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8
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Angarola BL, Anczuków O. Splicing alterations in healthy aging and disease. WILEY INTERDISCIPLINARY REVIEWS-RNA 2021; 12:e1643. [PMID: 33565261 DOI: 10.1002/wrna.1643] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 12/19/2022]
Abstract
Alternative RNA splicing is a key step in gene expression that allows generation of numerous messenger RNA transcripts encoding proteins of varied functions from the same gene. It is thus a rich source of proteomic and functional diversity. Alterations in alternative RNA splicing are observed both during healthy aging and in a number of human diseases, several of which display premature aging phenotypes or increased incidence with age. Age-associated splicing alterations include differential splicing of genes associated with hallmarks of aging, as well as changes in the levels of core spliceosomal genes and regulatory splicing factors. Here, we review the current known links between alternative RNA splicing, its regulators, healthy biological aging, and diseases associated with aging or aging-like phenotypes. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Splicing Regulation/Alternative Splicing.
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Affiliation(s)
| | - Olga Anczuków
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.,Department of Genetics and Genome Sciences, UConn Health, Farmington, Connecticut, USA.,Institute for Systems Genomics, UConn Health, Farmington, Connecticut, USA
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9
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Marques-Coelho D, Iohan LDCC, Melo de Farias AR, Flaig A, Lambert JC, Costa MR. Differential transcript usage unravels gene expression alterations in Alzheimer's disease human brains. NPJ Aging Mech Dis 2021; 7:2. [PMID: 33398016 PMCID: PMC7782705 DOI: 10.1038/s41514-020-00052-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 11/12/2020] [Indexed: 02/07/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.
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Affiliation(s)
- Diego Marques-Coelho
- Brain Institute, Federal University of Rio Grande do Norte, Av. Nascimento de Castro, 2155, Natal, Brazil
- Bioinformatics Multidisciplinary Environment (BioME), Federal University of Rio Grande do Norte, Natal, Brazil
| | - Lukas da Cruz Carvalho Iohan
- Brain Institute, Federal University of Rio Grande do Norte, Av. Nascimento de Castro, 2155, Natal, Brazil
- Bioinformatics Multidisciplinary Environment (BioME), Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ana Raquel Melo de Farias
- Brain Institute, Federal University of Rio Grande do Norte, Av. Nascimento de Castro, 2155, Natal, Brazil
- Unité INSERM 1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Institut Pasteur de Lille, University of Lille, Lille Cedex, France
| | - Amandine Flaig
- Unité INSERM 1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Institut Pasteur de Lille, University of Lille, Lille Cedex, France
| | - Jean-Charles Lambert
- Unité INSERM 1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Institut Pasteur de Lille, University of Lille, Lille Cedex, France
| | - Marcos Romualdo Costa
- Brain Institute, Federal University of Rio Grande do Norte, Av. Nascimento de Castro, 2155, Natal, Brazil.
- Unité INSERM 1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Institut Pasteur de Lille, University of Lille, Lille Cedex, France.
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10
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Kunkle BW, Schmidt M, Klein HU, Naj AC, Hamilton-Nelson KL, Larson EB, Evans DA, De Jager PL, Crane PK, Buxbaum JD, Ertekin-Taner N, Barnes LL, Fallin MD, Manly JJ, Go RCP, Obisesan TO, Kamboh MI, Bennett DA, Hall KS, Goate AM, Foroud TM, Martin ER, Wang LS, Byrd GS, Farrer LA, Haines JL, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. JAMA Neurol 2021; 78:102-113. [PMID: 33074286 PMCID: PMC7573798 DOI: 10.1001/jamaneurol.2020.3536] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/09/2020] [Indexed: 12/11/2022]
Abstract
Importance Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals, ABCA7, TREM2, and an intergenic locus at 5q35 were previously implicated. Objective To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, Setting, and Participants This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main Outcomes and Measures Diagnosis of Alzheimer disease. Results A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (19q13.33; P = 3.5 × 10-7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and Relevance While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.
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Affiliation(s)
- Brian W. Kunkle
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Michael Schmidt
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Hans-Ulrich Klein
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Adam C. Naj
- Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | | - Eric B. Larson
- Department of Medicine, University of Washington, Seattle
- Group Health Research Institute, Group Health, Seattle, Washington
| | - Denis A. Evans
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
| | - Phil L. De Jager
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Paul K. Crane
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Joe D. Buxbaum
- Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
- Department of Genetics and Genomics Sciences, Mount Sinai School of Medicine, New York, New York
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York
- Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York
| | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Lisa L. Barnes
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
- Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - M. Daniele Fallin
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, Maryland
| | - Jennifer J. Manly
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Rodney C. P. Go
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham
| | | | - M. Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania
- Alzheimer’s Disease Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David A. Bennett
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Kathleen S. Hall
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
| | - Alison M. Goate
- Department of Genetics and Genomics Sciences, Mount Sinai School of Medicine, New York, New York
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York
- Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis
| | - Eden R. Martin
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Li-Sao Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Goldie S. Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
- Department of Psychiatry, Columbia University, New York, New York
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Margaret A. Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York
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11
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Raghavan NS, Dumitrescu L, Mormino E, Mahoney ER, Lee AJ, Gao Y, Bilgel M, Goldstein D, Harrison T, Engelman CD, Saykin AJ, Whelan CD, Liu JZ, Jagust W, Albert M, Johnson SC, Yang HS, Johnson K, Aisen P, Resnick SM, Sperling R, De Jager PL, Schneider J, Bennett DA, Schrag M, Vardarajan B, Hohman TJ, Mayeux R. Association Between Common Variants in RBFOX1, an RNA-Binding Protein, and Brain Amyloidosis in Early and Preclinical Alzheimer Disease. JAMA Neurol 2020; 77:1288-1298. [PMID: 32568366 PMCID: PMC7309575 DOI: 10.1001/jamaneurol.2020.1760] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/06/2020] [Indexed: 01/27/2023]
Abstract
Importance Genetic studies of Alzheimer disease have focused on the clinical or pathologic diagnosis as the primary outcome, but little is known about the genetic basis of the preclinical phase of the disease. Objective To examine the underlying genetic basis for brain amyloidosis in the preclinical phase of Alzheimer disease. Design, Setting, and Participants In the first stage of this genetic association study, a meta-analysis was conducted using genetic and imaging data acquired from 6 multicenter cohort studies of healthy older individuals between 1994 and 2019: the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study, the Berkeley Aging Cohort Study, the Wisconsin Registry for Alzheimer's Prevention, the Biomarkers of Cognitive Decline Among Normal Individuals cohort, the Baltimore Longitudinal Study of Aging, and the Alzheimer Disease Neuroimaging Initiative, which included Alzheimer disease and mild cognitive impairment. The second stage was designed to validate genetic observations using pathologic and clinical data from the Religious Orders Study and Rush Memory and Aging Project. Participants older than 50 years with amyloid positron emission tomographic (PET) imaging data and DNA from the 6 cohorts were included. The largest cohort, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study (n = 3154), was the PET screening cohort used for a secondary prevention trial designed to slow cognitive decline associated with brain amyloidosis. Six smaller, longitudinal cohort studies (n = 1160) provided additional amyloid PET imaging data with existing genetic data. The present study was conducted from March 29, 2019, to February 19, 2020. Main Outcomes and Measures A genome-wide association study of PET imaging amyloid levels. Results From the 4314 analyzed participants (age, 52-96 years; 2478 participants [57%] were women), a novel locus for amyloidosis was noted within RBFOX1 (β = 0.61, P = 3 × 10-9) in addition to APOE. The RBFOX1 protein localized around plaques, and reduced expression of RBFOX1 was correlated with higher amyloid-β burden (β = -0.008, P = .002) and worse cognition (β = 0.007, P = .006) during life in the Religious Orders Study and Rush Memory and Aging Project cohort. Conclusions and Relevance RBFOX1 encodes a neuronal RNA-binding protein known to be expressed in neuronal tissues and may play a role in neuronal development. The findings of this study suggest that RBFOX1 is a novel locus that may be involved in the pathogenesis of Alzheimer disease.
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Affiliation(s)
- Neha S. Raghavan
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | - Emily R. Mahoney
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Annie J. Lee
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Yizhe Gao
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - David Goldstein
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Theresa Harrison
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin, School of Medicine and Public Health, Madison
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, School of Medicine, Indiana University, Indianapolis
- Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis
| | | | - Jimmy Z. Liu
- Research and Early Development, Biogen Inc, Cambridge, Massachusetts
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Sterling C. Johnson
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - Hyun-Sik Yang
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Keith Johnson
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Philip L. De Jager
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York
- Cell Circuits Program, Broad Institute, Cambridge, Massachusetts
| | - Julie Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Matthew Schrag
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Badri Vardarajan
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Richard Mayeux
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
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12
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Carter CJ. Autism genes and the leukocyte transcriptome in autistic toddlers relate to pathogen interactomes, infection and the immune system. A role for excess neurotrophic sAPPα and reduced antimicrobial Aβ. Neurochem Int 2019; 126:36-58. [PMID: 30862493 DOI: 10.1016/j.neuint.2019.03.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Revised: 02/22/2019] [Accepted: 03/06/2019] [Indexed: 12/20/2022]
Abstract
Prenatal and early childhood infections have been implicated in autism. Many autism susceptibility genes (206 Autworks genes) are localised in the immune system and are related to immune/infection pathways. They are enriched in the host/pathogen interactomes of 18 separate microbes (bacteria/viruses and fungi) and to the genes regulated by bacterial toxins, mycotoxins and Toll-like receptor ligands. This enrichment was also observed for misregulated genes from a microarray study of leukocytes from autistic toddlers. The upregulated genes from this leukocyte study also matched the expression profiles in response to numerous infectious agents from the Broad Institute molecular signatures database. They also matched genes related to sudden infant death syndrome and autism comorbid conditions (autoimmune disease, systemic lupus erythematosus, diabetes, epilepsy and cardiomyopathy) as well as to estrogen and thyrotropin responses and to those upregulated by different types of stressors including oxidative stress, hypoxia, endoplasmic reticulum stress, ultraviolet radiation or 2,4-dinitrofluorobenzene, a hapten used to develop allergic skin reactions in animal models. The oxidative/integrated stress response is also upregulated in the autism brain and may contribute to myelination problems. There was also a marked similarity between the expression signatures of autism and Alzheimer's disease, and 44 shared autism/Alzheimer's disease genes are almost exclusively expressed in the blood-brain barrier. However, in contrast to Alzheimer's disease, levels of the antimicrobial peptide beta-amyloid are decreased and the levels of the neurotrophic/myelinotrophic soluble APP alpha are increased in autism, together with an increased activity of α-secretase. sAPPα induces an increase in glutamatergic and a decrease in GABA-ergic synapses creating and excitatory/inhibitory imbalance that has also been observed in autism. A literature survey showed that multiple autism genes converge on APP processing and that many are able to increase sAPPalpha at the expense of beta-amyloid production. A genetically programmed tilt of this axis towards an overproduction of neurotrophic/gliotrophic sAPPalpha and underproduction of antimicrobial beta-amyloid may explain the brain overgrowth and myelination dysfunction, as well as the involvement of pathogens in autism.
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Affiliation(s)
- C J Carter
- PolygenicPathways, 41C Marina, Saint Leonard's on Sea, TN38 0BU, East Sussex, UK.
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13
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Alkallas R, Fish L, Goodarzi H, Najafabadi HS. Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease. Nat Commun 2017; 8:909. [PMID: 29030541 PMCID: PMC5714957 DOI: 10.1038/s41467-017-00867-z] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 07/28/2017] [Indexed: 12/24/2022] Open
Abstract
The abundance of mRNA is mainly determined by the rates of RNA transcription and decay. Here, we present a method for unbiased estimation of differential mRNA decay rate from RNA-sequencing data by modeling the kinetics of mRNA metabolism. We show that in all primary human tissues tested, and particularly in the central nervous system, many pathways are regulated at the mRNA stability level. We present a parsimonious regulatory model consisting of two RNA-binding proteins and four microRNAs that modulate the mRNA stability landscape of the brain, which suggests a new link between RBFOX proteins and Alzheimer’s disease. We show that downregulation of RBFOX1 leads to destabilization of mRNAs encoding for synaptic transmission proteins, which may contribute to the loss of synaptic function in Alzheimer’s disease. RBFOX1 downregulation is more likely to occur in older and female individuals, consistent with the association of Alzheimer’s disease with age and gender. “mRNA abundance is determined by the rates of transcription and decay. Here, the authors propose a method for estimating the rate of differential mRNA decay from RNA-seq data and model mRNA stability in the brain, suggesting a link between mRNA stability and Alzheimer’s disease.”
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Affiliation(s)
- Rached Alkallas
- Department of Human Genetics, McGill University, Montreal, QC, Canada, H3A 0C7.,McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada, H3A 0G1
| | - Lisa Fish
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, 94158, USA.,Department of Urology, University of California, San Francisco, CA, 94158, USA.,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, 94158, USA
| | - Hani Goodarzi
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, 94158, USA.,Department of Urology, University of California, San Francisco, CA, 94158, USA.,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, 94158, USA
| | - Hamed S Najafabadi
- Department of Human Genetics, McGill University, Montreal, QC, Canada, H3A 0C7. .,McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada, H3A 0G1.
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14
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Babenko VN, Gubanova NV, Bragin AO, Chadaeva IV, Vasiliev GV, Medvedeva IV, Gaytan AS, Krivoshapkin AL, Orlov YL. Computer Analysis of Glioma Transcriptome Profiling: Alternative Splicing Events. J Integr Bioinform 2017; 14:/j/jib.ahead-of-print/jib-2017-0022/jib-2017-0022.xml. [PMID: 28918420 PMCID: PMC6042819 DOI: 10.1515/jib-2017-0022] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 07/28/2017] [Indexed: 01/02/2023] Open
Abstract
Here we present the analysis of alternative splicing events on an example of glioblastoma cell culture samples using a set of computer tools in combination with database integration. The gene expression profiles of glioblastoma were obtained from cell culture samples of primary glioblastoma which were isolated and processed for RNA extraction. Transcriptome profiling of normal brain samples and glioblastoma were done by Illumina sequencing. The significant differentially expressed exon-level probes and their corresponding genes were identified using a combination of the splicing index method. Previous studies indicated that tumor-specific alternative splicing is important in the regulation of gene expression and corresponding protein functions during cancer development. Multiple alternative splicing transcripts have been identified as progression markers, including generalized splicing abnormalities and tumor- and stage-specific events. We used a set of computer tools which were recently applied to analysis of gene expression in laboratory animals to study differential splicing events. We found 69 transcripts that are differentially alternatively spliced. Three cancer-associated genes were considered in detail, in particular: APP (amyloid beta precursor protein), CASC4 (cancer susceptibility candidate 4) and TP53. Such alternative splicing opens new perspectives for cancer research.
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15
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Fragkouli A, Koukouraki P, Vlachos IS, Paraskevopoulou MD, Hatzigeorgiou AG, Doxakis E. Neuronal ELAVL proteins utilize AUF-1 as a co-partner to induce neuron-specific alternative splicing of APP. Sci Rep 2017; 7:44507. [PMID: 28291226 PMCID: PMC5349543 DOI: 10.1038/srep44507] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 02/08/2017] [Indexed: 12/18/2022] Open
Abstract
Aβ peptide that accumulates in Alzheimer’s disease brain, derives from proteolytic processing of the amyloid precursor protein (APP) that exists in three main isoforms derived by alternative splicing. The isoform APP695, lacking exons 7 and 8, is predominately expressed in neurons and abnormal neuronal splicing of APP has been observed in the brain of patients with Alzheimer’s disease. Herein, we demonstrate that expression of the neuronal members of the ELAVL protein family (nELAVLs) correlate with APP695 levels in vitro and in vivo. Moreover, we provide evidence that nELAVLs regulate the production of APP695; by using a series of reporters we show that concurrent binding of nELAVLs to sequences located both upstream and downstream of exon 7 is required for its skipping, whereas nELAVL-binding to a highly conserved U-rich sequence upstream of exon 8, is sufficient for its exclusion. Finally, we report that nELAVLs block APP exon 7 or 8 definition by reducing the binding of the essential splicing factor U2AF65, an effect facilitated by the concurrent binding of AUF-1. Our study provides new insights into the regulation of APP pre-mRNA processing, supports the role for nELAVLs as neuron-specific splicing regulators and reveals a novel function of AUF1 in alternative splicing.
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Affiliation(s)
- Apostolia Fragkouli
- Center for Basic Research, Biomedical Research Foundation Academy of Athens, 4 Soranou Efesiou str, 11527, Athens Greece
| | - Pelagia Koukouraki
- Center for Basic Research, Biomedical Research Foundation Academy of Athens, 4 Soranou Efesiou str, 11527, Athens Greece
| | - Ioannis S Vlachos
- Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521 Athens, Greece.,DIANA-Lab, Department of Electrical &Computer Engineering, University of Thessaly, 38221 Volos, Greece
| | - Maria D Paraskevopoulou
- Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521 Athens, Greece.,DIANA-Lab, Department of Electrical &Computer Engineering, University of Thessaly, 38221 Volos, Greece
| | - Artemis G Hatzigeorgiou
- Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521 Athens, Greece.,DIANA-Lab, Department of Electrical &Computer Engineering, University of Thessaly, 38221 Volos, Greece
| | - Epaminondas Doxakis
- Center for Basic Research, Biomedical Research Foundation Academy of Athens, 4 Soranou Efesiou str, 11527, Athens Greece
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16
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Min H, Kim J, Kim YJ, Yoon MS, Pratley RE, Lee YH. Measurement of altered APP isoform expression in adipose tissue of diet-induced obese mice by absolute quantitative real-time PCR. Anim Cells Syst (Seoul) 2017; 21:100-107. [PMID: 30460057 PMCID: PMC6138354 DOI: 10.1080/19768354.2017.1290679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Revised: 01/12/2017] [Accepted: 01/18/2017] [Indexed: 11/06/2022] Open
Abstract
Obesity is associated with increased risk of Alzheimer’s disease. Previous studies have demonstrated that amyloid-beta precursor protein (APP) is expressed in subcutaneous adipose tissue (SAT), upregulated with obesity, and correlates with insulin resistance and adipose tissue inflammation. APP is alternatively spliced into several isoforms, which may be indicative of the pathogenesis of APP-related diseases, but the accurate quantification has been difficult to standardize and reproduce. In light of this, we developed isoform-specific absolute cDNA standards for absolute quantitative real-time PCR (AQ-PCR), and measured transcript copy numbers for three major APP isoforms (APP770, APP751, and APP695), in SAT from C57BL/6 mice fed either a normal or high-fat diet. Expression of all three major APP isoforms was increased in diet-induced obese mice. Transcript copy numbers of APP770 and APP695 correlated with plasma insulin and CCL2 gene expression. The ratios of APP770 and APP751 to APP695 gradually decreased with aging, and correlated with plasma glucose levels. In addition, APP770 was significantly decreased in thiazolidinedione-treated mice. We describe quantification of APP isoform transcripts by AQ-PCR, which allows for direct comparison of gene copy number across isoforms, between experiments, and across studies conducted by independent research groups, which relative quantitative PCR does not allow. Our results suggest a possible role of differential expression of APP isoforms in the development of obesity-related insulin resistance and adipose tissue inflammation. In addition, it is important to determine if altered ratios of APP isoforms in SAT contribute to higher circulating Aβ peptides and increased risk of abnormalities in obesity.
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Affiliation(s)
- Hansol Min
- Department of Biomedical Science, Catholic University of Daegu, Gyeongsan, Korea
| | - Jinil Kim
- Department of Biomedical Science, Catholic University of Daegu, Gyeongsan, Korea
| | - Young-Jin Kim
- Department of Biomedical Engineering, Catholic University of Daegu, Gyeongsan, Korea
| | - Mi-Sook Yoon
- Division of Beauty Coordination, Keimyung College University, Daegu, Korea
| | - Richard E Pratley
- Florida Hospital Sanford/Burnham Translational Research Institute for Metabolism and Diabetes, Orlando, FL, USA
| | - Yong-Ho Lee
- Department of Biomedical Science, Catholic University of Daegu, Gyeongsan, Korea
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17
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Abstract
Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.
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Affiliation(s)
- Xuhua Xia
- Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Ottawa Institute of Systems Biology, Ottawa K1H 8M5, Canada
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18
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Suzuki H, Aoki Y, Kameyama T, Saito T, Masuda S, Tanihata J, Nagata T, Mayeda A, Takeda S, Tsukahara T. Endogenous Multiple Exon Skipping and Back-Splicing at the DMD Mutation Hotspot. Int J Mol Sci 2016; 17:ijms17101722. [PMID: 27754374 PMCID: PMC5085753 DOI: 10.3390/ijms17101722] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 09/26/2016] [Accepted: 09/30/2016] [Indexed: 12/15/2022] Open
Abstract
Duchenne muscular dystrophy (DMD) is a severe muscular disorder. It was reported that multiple exon skipping (MES), targeting exon 45–55 of the DMD gene, might improve patients’ symptoms because patients who have a genomic deletion of all these exons showed very mild symptoms. Thus, exon 45–55 skipping treatments for DMD have been proposed as a potential clinical cure. Herein, we detected the expression of endogenous exons 44–56 connected mRNA transcript of the DMD using total RNAs derived from human normal skeletal muscle by reverse transcription polymerase chain reaction (RT-PCR), and identified a total of eight types of MES products around the hotspot. Surprisingly, the 5′ splice sites of recently reported post-transcriptional introns (remaining introns after co-transcriptional splicing) act as splicing donor sites for MESs. We also tested exon combinations to generate DMD circular RNAs (circRNAs) and determined the preferential splice sites of back-splicing, which are involved not only in circRNA generation, but also in MESs. Our results fit the current circRNA-generation model, suggesting that upstream post-transcriptional introns trigger MES and generate circRNA because its existence is critical for the intra-intronic interaction or for extremely distal splicing.
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Affiliation(s)
- Hitoshi Suzuki
- School of Materials Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa 923-1292, Japan.
| | - Yoshitsugu Aoki
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
| | - Toshiki Kameyama
- Division of Gene Expression Mechanism, Institute for Comprehensive Medical Science, Fujita Health University, Toyoake, Aichi 470-1192, Japan.
| | - Takashi Saito
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
| | - Satoru Masuda
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
| | - Jun Tanihata
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
| | - Tetsuya Nagata
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
- Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Bunkyoku, Tokyo 113-0034, Japan.
| | - Akila Mayeda
- Division of Gene Expression Mechanism, Institute for Comprehensive Medical Science, Fujita Health University, Toyoake, Aichi 470-1192, Japan.
| | - Shin'ichi Takeda
- Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), Kodaira, Tokyo 187-8502, Japan.
| | - Toshifumi Tsukahara
- School of Materials Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa 923-1292, Japan.
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19
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Abstract
Neurodegenerative diseases have a variety of different genes contributing to their underlying pathology. Unfortunately, for many of these diseases it is not clear how changes in gene expression affect pathology. Transcriptome analysis of neurodegenerative diseases using ribonucleic acid sequencing (RNA Seq) and real time quantitative polymerase chain reaction (RT-qPCR) provides for a platform to allow investigators to determine the contribution of various genes to the disease phenotype. In Alzheimer's disease (AD) there are several candidate genes reported that may be associated with the underlying pathology and are, in addition, alternatively spliced. Thus, AD is an ideal disease to examine how alternative splicing may affect pathology. In this context, genes of particular interest to AD pathology include the amyloid precursor protein (APP), TAU, and apolipoprotein E (APOE). Here, we review the evidence of alternative splicing of these genes in normal and AD patients, and recent therapeutic approaches to control splicing.
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Affiliation(s)
- Julia E Love
- Department of Biological Sciences, Science Building, Boise State University, USA
| | - Eric J Hayden
- Department of Biological Sciences, Science Building, Boise State University, USA
| | - Troy T Rohn
- Department of Biological Sciences, Science Building, Boise State University, USA
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