1
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Mustafin RN, Khusnutdinova EK. Involvement of transposable elements in Alzheimer's disease pathogenesis. Vavilovskii Zhurnal Genet Selektsii 2024; 28:228-238. [PMID: 38680184 PMCID: PMC11043511 DOI: 10.18699/vjgb-24-27] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 10/30/2023] [Accepted: 11/02/2023] [Indexed: 05/01/2024] Open
Abstract
Alzheimer's disease affects an average of 5 % of the population with a significant increase in prevalence with age, suggesting that the same mechanisms that underlie aging may influence this pathology. Investigation of these mechanisms is promising for effective methods of treatment and prevention of the disease. Possible participants in these mechanisms are transposons, which serve as drivers of epigenetic regulation, since they form species-specific distributions of non-coding RNA genes in genomes in evolution. Study of miRNA involvement in Alzheimer's disease pathogenesis is relevant, since the associations of protein-coding genes (APOE4, ABCA7, BIN1, CLU, CR1, PICALM, TREM2) with the disease revealed as a result of GWAS make it difficult to explain its complex pathogenesis. Specific expression changes of many genes were found in different brain parts of Alzheimer's patients, which may be due to global regulatory changes under the influence of transposons. Experimental and clinical studies have shown pathological activation of retroelements in Alzheimer's disease. Our analysis of scientific literature in accordance with MDTE DB revealed 28 miRNAs derived from transposons (17 from LINE, 5 from SINE, 4 from HERV, 2 from DNA transposons), the expression of which specifically changes in this disease (decreases in 17 and increases in 11 microRNA). Expression of 13 out of 28 miRNAs (miR-151a, -192, -211, -28, -31, -320c, -335, -340, -378a, -511, -576, -708, -885) also changes with aging and cancer development, which indicates the presence of possible common pathogenetic mechanisms. Most of these miRNAs originated from LINE retroelements, the pathological activation of which is associated with aging, carcinogenesis, and Alzheimer's disease, which supports the hypothesis that these three processes are based on the primary dysregulation of transposons that serve as drivers of epigenetic regulation of gene expression in ontogeny.
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Affiliation(s)
| | - E K Khusnutdinova
- Bashkir State Medical University, Ufa, Russia Institute of Biochemistry and Genetics - Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
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2
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Erdogdu B, Varabyou A, Hicks SC, Salzberg SL, Pertea M. Detecting differential transcript usage in complex diseases with SPIT. CELL REPORTS METHODS 2024; 4:100736. [PMID: 38508189 PMCID: PMC10985272 DOI: 10.1016/j.crmeth.2024.100736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 12/21/2023] [Accepted: 02/27/2024] [Indexed: 03/22/2024]
Abstract
Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and developmental stages, contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function and underpin disease pathogenesis. Analyzing DTU via RNA sequencing (RNA-seq) data is vital, but the genetic heterogeneity in populations with complex diseases presents an intricate challenge due to diverse causal events and undetermined subtypes. Although the majority of common diseases in humans are categorized as complex, state-of-the-art DTU analysis methods often overlook this heterogeneity in their models. We therefore developed SPIT, a statistical tool that identifies predominant subgroups in transcript usage within a population along with their distinctive sets of DTU events. This study provides comprehensive assessments of SPIT's methodology and applies it to analyze brain samples from individuals with schizophrenia, revealing previously unreported DTU events in six candidate genes.
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Affiliation(s)
- Beril Erdogdu
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA.
| | - Ales Varabyou
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie C Hicks
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
| | - Steven L Salzberg
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Mihaela Pertea
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA; Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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3
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Zhang Q, Liu J, Liu H, Ao L, Xi Y, Chen D. Genome-wide epistasis analysis reveals gene-gene interaction network on an intermediate endophenotype P-tau/Aβ 42 ratio in ADNI cohort. Sci Rep 2024; 14:3984. [PMID: 38368488 PMCID: PMC10874417 DOI: 10.1038/s41598-024-54541-8] [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: 10/22/2023] [Accepted: 02/14/2024] [Indexed: 02/19/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly worldwide. The exact etiology of AD, particularly its genetic mechanisms, remains incompletely understood. Traditional genome-wide association studies (GWAS), which primarily focus on single-nucleotide polymorphisms (SNPs) with main effects, provide limited explanations for the "missing heritability" of AD, while there is growing evidence supporting the important role of epistasis. In this study, we performed a genome-wide SNP-SNP interaction detection using a linear regression model and employed multiple GPUs for parallel computing, significantly enhancing the speed of whole-genome analysis. The cerebrospinal fluid (CSF) phosphorylated tau (P-tau)/amyloid-[Formula: see text] (A[Formula: see text]) ratio was used as a quantitative trait (QT) to enhance statistical power. Age, gender, and clinical diagnosis were included as covariates to control for potential non-genetic factors influencing AD. We identified 961 pairs of statistically significant SNP-SNP interactions, explaining a high-level variance of P-tau/A[Formula: see text] level, all of which exhibited marginal main effects. Additionally, we replicated 432 previously reported AD-related genes and found 11 gene-gene interaction pairs overlapping with the protein-protein interaction (PPI) network. Our findings may contribute to partially explain the "missing heritability" of AD. The identified subnetwork may be associated with synaptic dysfunction, Wnt signaling pathway, oligodendrocytes, inflammation, hippocampus, and neuronal cells.
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Affiliation(s)
- Qiushi Zhang
- School of Computer Science, Northeast Electric Power University, 169 Changchun Street, Jilin, 132012, China
| | - Junfeng Liu
- School of Computer Science, Northeast Electric Power University, 169 Changchun Street, Jilin, 132012, China
| | - Hongwei Liu
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, 145 Nantong Street, Harbin, China
| | - Lang Ao
- School of Computer Science, Northeast Electric Power University, 169 Changchun Street, Jilin, 132012, China
| | - Yang Xi
- School of Computer Science, Northeast Electric Power University, 169 Changchun Street, Jilin, 132012, China
| | - Dandan Chen
- School of Automation Engineering, Northeast Electric Power University, 169 Changchun Street, Jilin, 132012, China.
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, 145 Nantong Street, Harbin, China.
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4
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Rezaei Z, Tahmasebi A, Pourabbas B. Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. PLoS Negl Trop Dis 2024; 18:e0011892. [PMID: 38190401 PMCID: PMC10798641 DOI: 10.1371/journal.pntd.0011892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 01/19/2024] [Accepted: 12/29/2023] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Leishmaniasis is a parasitic disease caused by the Leishmania protozoan affecting millions of people worldwide, especially in tropical and subtropical regions. The immune response involves the activation of various cells to eliminate the infection. Understanding the complex interplay between Leishmania and the host immune system is crucial for developing effective treatments against this disease. METHODS This study collected extensive transcriptomic data from macrophages, dendritic, and NK cells exposed to Leishmania spp. Our objective was to determine the Leishmania-responsive genes in immune system cells by applying meta-analysis and feature selection algorithms, followed by co-expression analysis. RESULTS As a result of meta-analysis, we discovered 703 differentially expressed genes (DEGs), primarily associated with the immune system and cellular metabolic processes. In addition, we have substantiated the significance of transcription factor families, such as bZIP and C2H2 ZF, in response to Leishmania infection. Furthermore, the feature selection techniques revealed the potential of two genes, namely G0S2 and CXCL8, as biomarkers and therapeutic targets for Leishmania infection. Lastly, our co-expression analysis has unveiled seven hub genes, including PFKFB3, DIAPH1, BSG, BIRC3, GOT2, EIF3H, and ATF3, chiefly related to signaling pathways. CONCLUSIONS These findings provide valuable insights into the molecular mechanisms underlying the response of immune system cells to Leishmania infection and offer novel potential targets for the therapeutic goals.
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Affiliation(s)
- Zahra Rezaei
- Professor Alborzi Clinical Microbiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ahmad Tahmasebi
- Professor Alborzi Clinical Microbiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Bahman Pourabbas
- Professor Alborzi Clinical Microbiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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5
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Bettencourt C, Skene N, Bandres-Ciga S, Anderson E, Winchester LM, Foote IF, Schwartzentruber J, Botia JA, Nalls M, Singleton A, Schilder BM, Humphrey J, Marzi SJ, Toomey CE, Kleifat AA, Harshfield EL, Garfield V, Sandor C, Keat S, Tamburin S, Frigerio CS, Lourida I, Ranson JM, Llewellyn DJ. Artificial intelligence for dementia genetics and omics. Alzheimers Dement 2023; 19:5905-5921. [PMID: 37606627 PMCID: PMC10841325 DOI: 10.1002/alz.13427] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/23/2023]
Abstract
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
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Affiliation(s)
- Conceicao Bettencourt
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
| | - Nathan Skene
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - 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, Maryland, USA
| | - Emma Anderson
- Department of Mental Health of Older People, Division of Psychiatry, University College London, London, UK
| | | | - Isabelle F Foote
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jeremy Schwartzentruber
- Open Targets, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
- Illumina Artificial Intelligence Laboratory, Illumina Inc, Foster City, California, USA
| | - Juan A Botia
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Mike 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, Maryland, USA
- Data Tecnica International LLC, Washington, DC, 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, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Brian M Schilder
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Sarah J Marzi
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Christina E Toomey
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
- The Francis Crick Institute, London, UK
| | - Ahmad Al Kleifat
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eric L Harshfield
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Cynthia Sandor
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Samuel Keat
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, Neurology Section, University of Verona, Verona, Italy
| | - Carlo Sala Frigerio
- UK Dementia Research Institute, Queen Square Institute of Neurology, University College London, London, UK
| | | | | | - David J Llewellyn
- University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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6
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Qin Y, Chen J, Li J, Wu N. Relationship between hippocampal gene expression and cognitive performance differences in visual discrimination learning task of male rats. Behav Brain Res 2023; 454:114659. [PMID: 37690703 DOI: 10.1016/j.bbr.2023.114659] [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: 07/18/2023] [Revised: 09/01/2023] [Accepted: 09/07/2023] [Indexed: 09/12/2023]
Abstract
Learning to discriminate between environmental visual stimuli is essential to make right decisions and guide appropriate behaviors. Moreover, impairments in visual discrimination learning are observed in several neuropsychiatric disorders. Visual discrimination learning requires perception and memory processing, in which the hippocampus critically involved. To understand the molecular mechanisms underpinning hippocampus function in visual discrimination learning, we examined the hippocampal gene expression profiles of Sprague-Dawley rats with different cognitive performance (high cognition group vs. low cognition group) in the modified visual discrimination learning task, using high-throughput RNA sequencing technology. Compared with the low cognition group, bioinformatics analysis indicated that 319 genes were differentially expressed in the high cognition group with statistical significance, of which 253 genes were down-regulated and 66 genes were up-regulated. The functional enrichment analysis showed that protein translation and energy metabolism were up-regulated pathways, while transforming growth factor beta receptor signaling pathway, bone morphogenetic protein signaling pathway, apoptosis, inflammation response, transport, and glycosaminoglycan metabolism were down-regulated pathways, which were related to good cognitive performance in the visual discrimination learning task. Taken together, our finding reveals the differential gene expression and enrichment biological pathways related to cognitive performance differences in visual discrimination learning of rats, which provides us direct insight into the molecular mechanisms of hippocampus function in visual discrimination learning and may contribute to developing potential treatment strategies for neuropsychiatric disorders accompanied with cognitive impairments.
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Affiliation(s)
- Yihan Qin
- Beijing Key Laboratory of Neuropsychopharmacology, State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, 27th Taiping Road, Beijing 100850, China
| | - Jianmin Chen
- Beijing Key Laboratory of Neuropsychopharmacology, State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, 27th Taiping Road, Beijing 100850, China
| | - Jin Li
- Beijing Key Laboratory of Neuropsychopharmacology, State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, 27th Taiping Road, Beijing 100850, China.
| | - Ning Wu
- Beijing Key Laboratory of Neuropsychopharmacology, State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, 27th Taiping Road, Beijing 100850, China.
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7
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Widjaya MA, Liu CH, Lee SD, Cheng WC. Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer's Disease Mouse Strains. J Mol Neurosci 2023; 73:773-786. [PMID: 37733230 DOI: 10.1007/s12031-023-02152-9] [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: 07/05/2023] [Accepted: 08/30/2023] [Indexed: 09/22/2023]
Abstract
Immune-related pathways can affect the immune system directly, such as the chemokine signaling pathway, or indirectly, such as the phagosome pathway. Alzheimer's disease (AD) is reportedly associated with several immune-related pathways. However, exploring its underlying mechanism is challenging in animal studies because AD mouse strains differentially express immune-related pathway characteristics. To overcome this problem, we performed a meta-analysis to identify significant and consistent immune-related AD pathways that are expressed in different AD mouse strains. Next-generation RNA sequencing (RNA-seq) and microarray datasets for the cortex of AD mice from different strains such as APP/PSEN1, APP/PS2, 3xTg, TREM, and 5xFAD were collected from the NCBI GEO database. Each dataset's quality control and normalization were already processed from each original study source using various methods depending on the high-throughput analysis platform (FastQC, median of ratios, RMA, between array normalization). Datasets were analyzed using DESeq2 for RNA-seq and GEO2R for microarray to identify differentially expressed (DE) genes. Significantly DE genes were meta-analyzed using Stouffer's method, with significant genes further analyzed for functional enrichment. Ten datasets representing 20 conditions were obtained from the NCBI GEO database, comprising 116 control and 120 AD samples. The DE analysis identified 284 significant DE genes. The meta-analysis identified three significantly enriched immune-related AD pathways: phagosome, the complement and coagulation cascade, and chemokine signaling. Phagosomes-related genes correlated with complement and immune system. Meanwhile, phagosomes and chemokine signaling genes overlapped with B cells receptors pathway genes indicating potential correlation between phagosome, chemokines, and adaptive immune system as well. The transcriptomic meta-analysis showed that AD is associated with immune-related pathways in the brain's cortex through the phagosome, complement and coagulation cascade, and chemokine signaling pathways. Interestingly, phagosome and chemokine signaling pathways had potential correlation with B cells receptors pathway.
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Affiliation(s)
- Michael Anekson Widjaya
- Graduate Institute of Biomedical Sciences, College of Medicine, China Medical University, Taichung, 40402, Taiwan
| | - Chia-Hsin Liu
- Cancer Biology and Precision Therapeutics Center, China Medical University and Academia Sinica China Medical University, Taichung, 40403, Taiwan
| | - Shin-Da Lee
- Department of Physical Therapy, PhD program in Healthcare Science, China Medical University, Taichung, 406040, Taiwan.
| | - Wei-Chung Cheng
- Cancer Biology and Precision Therapeutics Center, China Medical University and Academia Sinica China Medical University, Taichung, 40403, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung, Taiwan.
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8
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Ekeuku SO, Mohd Murshid N, Shukri SN, Mohd Sahardi NFN, Makpol S. Effect of Vitamin E on Transcriptomic Alterations in Alzheimer's Disease. Int J Mol Sci 2023; 24:12372. [PMID: 37569747 PMCID: PMC10418953 DOI: 10.3390/ijms241512372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/08/2023] [Accepted: 07/17/2023] [Indexed: 08/13/2023] Open
Abstract
Research into ageing is focused on understanding why some people can maintain cognitive ability and others lose autonomy, affecting their quality of life. Studies have revealed that age-related neurodegenerative disorders like Alzheimer's disease (AD) are now major causes of death among the elderly, surpassing malignancy. This review examines the effects of vitamin E on transcriptomic changes in ageing and neurodegenerative diseases, using AD as an example, and how different transcriptome profiling techniques can shape the results. Despite mixed results from transcriptomic studies on AD patients' brains, we think advanced technologies could offer a more detailed and accurate tool for such analysis. Research has also demonstrated the role of antioxidant modifiers in preventing AD. This review will explore the key findings regarding AD and its modulation by vitamin E, emphasizing the shift in its epidemiology during the ageing process.
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Affiliation(s)
| | | | | | | | - Suzana Makpol
- Department of Biochemistry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Level 17, Preclinical Building, Jalan Yaacob Latif, Bandar Tun Razak, Cheras, Kuala Lumpur 56000, Malaysia
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9
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Yang S, Park JH, Lu HC. Axonal energy metabolism, and the effects in aging and neurodegenerative diseases. Mol Neurodegener 2023; 18:49. [PMID: 37475056 PMCID: PMC10357692 DOI: 10.1186/s13024-023-00634-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 06/08/2023] [Indexed: 07/22/2023] Open
Abstract
Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.
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Affiliation(s)
- Sen Yang
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Jung Hyun Park
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Hui-Chen Lu
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA.
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10
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Erdogdu B, Varabyou A, Hicks SC, Salzberg SL, Pertea M. Detecting differential transcript usage in complex diseases with SPIT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.10.548289. [PMID: 37503064 PMCID: PMC10369883 DOI: 10.1101/2023.07.10.548289] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and different developmental stages, thereby contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function, potentially leading to pathogenesis of diseases. Detecting such events for single-gene genetic traits is relatively uncomplicated; however, the heterogeneity of populations with complex diseases presents an intricate challenge due to the presence of diverse causal events and undetermined subtypes. SPIT is the first statistical tool that quantifies the heterogeneity in transcript usage within a population and identifies predominant subgroups along with their distinctive sets of DTU events. We provide comprehensive assessments of SPIT's methodology in both single-gene and complex traits and report the results of applying SPIT to analyze brain samples from individuals with schizophrenia. Our analysis reveals previously unreported DTU events in six candidate genes.
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Affiliation(s)
- Beril Erdogdu
- Center for Computational Biology, Johns Hopkins University; Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering; Baltimore, MD, United States
| | - Ales Varabyou
- Center for Computational Biology, Johns Hopkins University; Baltimore, MD, United States
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, United States
| | - Stephanie C Hicks
- Center for Computational Biology, Johns Hopkins University; Baltimore, MD, United States
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, MD, USA
| | - Steven L Salzberg
- Center for Computational Biology, Johns Hopkins University; Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering; Baltimore, MD, United States
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, United States
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, MD, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine; Baltimore, MD, United States
| | - Mihaela Pertea
- Center for Computational Biology, Johns Hopkins University; Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering; Baltimore, MD, United States
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, United States
- Department of Genetic Medicine, Johns Hopkins School of Medicine; Baltimore, MD, United States
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11
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Mei T, Li Y, Orduña Dolado A, Li Z, Andersson R, Berliocchi L, Rasmussen LJ. Pooled analysis of frontal lobe transcriptomic data identifies key mitophagy gene changes in Alzheimer's disease brain. Front Aging Neurosci 2023; 15:1101216. [PMID: 37358952 PMCID: PMC10288858 DOI: 10.3389/fnagi.2023.1101216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 05/18/2023] [Indexed: 06/28/2023] Open
Abstract
Background The growing prevalence of Alzheimer's disease (AD) is becoming a global health challenge without effective treatments. Defective mitochondrial function and mitophagy have recently been suggested as etiological factors in AD, in association with abnormalities in components of the autophagic machinery like lysosomes and phagosomes. Several large transcriptomic studies have been performed on different brain regions from AD and healthy patients, and their data represent a vast source of important information that can be utilized to understand this condition. However, large integration analyses of these publicly available data, such as AD RNA-Seq data, are still missing. In addition, large-scale focused analysis on mitophagy, which seems to be relevant for the aetiology of the disease, has not yet been performed. Methods In this study, publicly available raw RNA-Seq data generated from healthy control and sporadic AD post-mortem human samples of the brain frontal lobe were collected and integrated. Sex-specific differential expression analysis was performed on the combined data set after batch effect correction. From the resulting set of differentially expressed genes, candidate mitophagy-related genes were identified based on their known functional roles in mitophagy, the lysosome, or the phagosome, followed by Protein-Protein Interaction (PPI) and microRNA-mRNA network analysis. The expression changes of candidate genes were further validated in human skin fibroblast and induced pluripotent stem cells (iPSCs)-derived cortical neurons from AD patients and matching healthy controls. Results From a large dataset (AD: 589; control: 246) based on three different datasets (i.e., ROSMAP, MSBB, & GSE110731), we identified 299 candidate mitophagy-related differentially expressed genes (DEG) in sporadic AD patients (male: 195, female: 188). Among these, the AAA ATPase VCP, the GTPase ARF1, the autophagic vesicle forming protein GABARAPL1 and the cytoskeleton protein actin beta ACTB were selected based on network degrees and existing literature. Changes in their expression were further validated in AD-relevant human in vitro models, which confirmed their down-regulation in AD conditions. Conclusion Through the joint analysis of multiple publicly available data sets, we identify four differentially expressed key mitophagy-related genes potentially relevant for the pathogenesis of sporadic AD. Changes in expression of these four genes were validated using two AD-relevant human in vitro models, primary human fibroblasts and iPSC-derived neurons. Our results provide foundation for further investigation of these genes as potential biomarkers or disease-modifying pharmacological targets.
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Affiliation(s)
- Taoyu Mei
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
- Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Yuan Li
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Anna Orduña Dolado
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Zhiquan Li
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Robin Andersson
- Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Laura Berliocchi
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Health Sciences, University Magna Græcia of Catanzaro, Catanzaro, Italy
| | - Lene Juel Rasmussen
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
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12
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Wong TS, Li G, Li S, Gao W, Chen G, Gan S, Zhang M, Li H, Wu S, Du Y. G protein-coupled receptors in neurodegenerative diseases and psychiatric disorders. Signal Transduct Target Ther 2023; 8:177. [PMID: 37137892 PMCID: PMC10154768 DOI: 10.1038/s41392-023-01427-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 02/17/2023] [Accepted: 03/30/2023] [Indexed: 05/05/2023] Open
Abstract
Neuropsychiatric disorders are multifactorial disorders with diverse aetiological factors. Identifying treatment targets is challenging because the diseases are resulting from heterogeneous biological, genetic, and environmental factors. Nevertheless, the increasing understanding of G protein-coupled receptor (GPCR) opens a new possibility in drug discovery. Harnessing our knowledge of molecular mechanisms and structural information of GPCRs will be advantageous for developing effective drugs. This review provides an overview of the role of GPCRs in various neurodegenerative and psychiatric diseases. Besides, we highlight the emerging opportunities of novel GPCR targets and address recent progress in GPCR drug development.
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Affiliation(s)
- Thian-Sze Wong
- Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China
- School of Medicine, Tsinghua University, 100084, Beijing, China
| | - Guangzhi Li
- Institute of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, 518000, Shenzhen, Guangdong, China
| | - Shiliang Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 200237, Shanghai, China
- Innovation Center for AI and Drug Discovery, East China Normal University, 200062, Shanghai, China
| | - Wei Gao
- Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China
- Innovation Center for AI and Drug Discovery, East China Normal University, 200062, Shanghai, China
| | - Geng Chen
- Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China
| | - Shiyi Gan
- Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China
| | - Manzhan Zhang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 200237, Shanghai, China
- Innovation Center for AI and Drug Discovery, East China Normal University, 200062, Shanghai, China
| | - Honglin Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 200237, Shanghai, China.
- Innovation Center for AI and Drug Discovery, East China Normal University, 200062, Shanghai, China.
| | - Song Wu
- Institute of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, 518000, Shenzhen, Guangdong, China.
- Department of Urology, South China Hospital, Health Science Center, Shenzhen University, 518116, Shenzhen, Guangdong, China.
| | - Yang Du
- Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China.
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13
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Mishra S, Sarkar S, Pandey A, Yadav SK, Negi R, Yadav S, Pant AB. Crosstalk Between miRNA and Protein Expression Profiles in Nitrate-Exposed Brain Cells. Mol Neurobiol 2023; 60:3855-3872. [DOI: 10.1007/s12035-023-03316-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 03/09/2023] [Indexed: 03/29/2023]
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14
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Chehimi SN, Crist RC, Reiner BC. Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches. Genes (Basel) 2023; 14:genes14030771. [PMID: 36981041 PMCID: PMC10047992 DOI: 10.3390/genes14030771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson's and Alzheimer's disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.
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Affiliation(s)
- Samar N Chehimi
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Richard C Crist
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Benjamin C Reiner
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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15
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Felsky D, Santa-Maria I, Cosacak MI, French L, Schneider JA, Bennett DA, De Jager PL, Kizil C, Tosto G. The Caribbean-Hispanic Alzheimer's disease brain transcriptome reveals ancestry-specific disease mechanisms. Neurobiol Dis 2023; 176:105938. [PMID: 36462719 PMCID: PMC10039465 DOI: 10.1016/j.nbd.2022.105938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 09/21/2022] [Accepted: 11/29/2022] [Indexed: 12/05/2022] Open
Abstract
Identifying ancestry-specific molecular profiles of late-onset Alzheimer's Disease (LOAD) in brain tissue is crucial to understand novel mechanisms and develop effective interventions in non-European, high-risk populations. We performed gene differential expression (DE) and consensus network-based analyses in RNA-sequencing data of postmortem brain tissue from 39 Caribbean Hispanics (CH). To identify ancestry-concordant and -discordant expression profiles, we compared our results to those from two independent non-Hispanic White (NHW) samples (n = 731). In CH, we identified 2802 significant DE genes, including several LOAD known-loci. DE effects were highly concordant across ethnicities, with 373 genes transcriptome-wide significant in all three cohorts. Cross-ancestry meta-analysis found NPNT to be the top DE gene. We replicated over 82% of meta-analyses genome-wide signals in single-nucleus RNA-seq data (including NPNT and LOAD known-genes SORL1, FBXL7, CLU, ABCA7). Increasing representation in genetic studies will allow for deeper understanding of ancestry-specific mechanisms and improving precision treatment options in understudied groups.
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Affiliation(s)
- Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, 250 College St., M5T 1R8, Canada; Department of Psychiatry, University of Toronto, 27 King's College Circle, Toronto, Ontario M5S 1A1, Canada; Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA
| | - Ismael Santa-Maria
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA
| | - Mehmet Ilyas Cosacak
- German Center for Neurodegenerative Diseases (DZNE) Dresden, Helmholtz Association, Tatzberg 41, 01307 Dresden, Germany
| | - Leon French
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, 250 College St., M5T 1R8, Canada; Department of Psychiatry, University of Toronto, 27 King's College Circle, Toronto, Ontario M5S 1A1, Canada
| | - Julie A Schneider
- Department of Neurology, Rush University Medical Center, 1653 West Congress Parkway, Chicago, IL 60612, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, 1653 West Congress Parkway, Chicago, IL 60612, USA
| | - David A Bennett
- Department of Neurology, Rush University Medical Center, 1653 West Congress Parkway, Chicago, IL 60612, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, 1653 West Congress Parkway, Chicago, IL 60612, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA; The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA
| | - Caghan Kizil
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA; German Center for Neurodegenerative Diseases (DZNE) Dresden, Helmholtz Association, Tatzberg 41, 01307 Dresden, Germany; The Department of Neurology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA
| | - Giuseppe Tosto
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA; The Department of Neurology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA; Gertrude H. Sergievsky Centre, Columbia University Medical Center, 630 West 168th St., New York, NY 10032, USA.
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16
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Zanotti A, Coelho JPL, Kaylani D, Singh G, Tauber M, Hitzenberger M, Avci D, Zacharias M, Russell RB, Lemberg MK, Feige MJ. The human signal peptidase complex acts as a quality control enzyme for membrane proteins. Science 2022; 378:996-1000. [DOI: 10.1126/science.abo5672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Cells need to detect and degrade faulty membrane proteins to maintain homeostasis. In this study, we identify a previously unknown function of the human signal peptidase complex (SPC)—the enzyme that removes endoplasmic reticulum (ER) signal peptides—as a membrane protein quality control factor. We show that the SPC cleaves membrane proteins that fail to correctly fold or assemble into their native complexes at otherwise hidden cleavage sites, which our study reveals to be abundant in the human membrane proteome. This posttranslocational cleavage synergizes with ER-associated degradation to sustain membrane protein homeostasis and contributes to cellular fitness. Cryptic SPC cleavage sites thus serve as predetermined breaking points that, when exposed, help to target misfolded or surplus proteins for degradation, thereby maintaining a healthy membrane proteome.
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Affiliation(s)
- Andrea Zanotti
- Center for Molecular Biology of Heidelberg University (ZMBH), 69120 Heidelberg, Germany
| | - João P. L. Coelho
- Center for Functional Protein Assemblies (CPA), Department of Bioscience, TUM School of Natural Sciences, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Dinah Kaylani
- Center for Functional Protein Assemblies (CPA), Department of Bioscience, TUM School of Natural Sciences, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Gurdeep Singh
- BioQuant and Biochemistry Center (BZH), Heidelberg University, 69120 Heidelberg, Germany
| | - Marina Tauber
- Center for Biochemistry and Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Faculty of Medicine, University of Cologne, 50931 Cologne, Germany
| | - Manuel Hitzenberger
- Center for Functional Protein Assemblies (CPA), Department of Bioscience, TUM School of Natural Sciences, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Dönem Avci
- Center for Molecular Biology of Heidelberg University (ZMBH), 69120 Heidelberg, Germany
- Center for Biochemistry and Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Faculty of Medicine, University of Cologne, 50931 Cologne, Germany
| | - Martin Zacharias
- Center for Functional Protein Assemblies (CPA), Department of Bioscience, TUM School of Natural Sciences, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Robert B. Russell
- BioQuant and Biochemistry Center (BZH), Heidelberg University, 69120 Heidelberg, Germany
| | - Marius K. Lemberg
- Center for Molecular Biology of Heidelberg University (ZMBH), 69120 Heidelberg, Germany
- Center for Biochemistry and Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Faculty of Medicine, University of Cologne, 50931 Cologne, Germany
| | - Matthias J. Feige
- Center for Functional Protein Assemblies (CPA), Department of Bioscience, TUM School of Natural Sciences, Technical University of Munich (TUM), 85748 Garching, Germany
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17
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Jang HY, Oh JM, Kim IW. Drug repurposing using meta-analysis of gene expression in Alzheimer's disease. Front Neurosci 2022; 16:989174. [PMID: 36440278 PMCID: PMC9684643 DOI: 10.3389/fnins.2022.989174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/19/2022] [Indexed: 01/25/2023] Open
Abstract
INTRODUCTION Alzheimer's disease and other forms of dementia are disease that bring an increased global burden. However, the medicine developed to date remains limited. The purpose of this study is to predict drug repositioning candidates using a computational method that integrates gene expression profiles on Alzheimer's disease and compound-induced changes in gene expression levels. METHODS Gene expression data on Alzheimer's disease were obtained from the Gene Expression Omnibus (GEO) and we conducted a meta-analysis of their gene expression levels. The reverse scores of compound-induced gene expressions were computed based on the reversal relationship between disease and drug gene expression profiles. RESULTS Reversal genes and the candidate compounds were identified by the leave-one-out cross-validation procedure. Additionally, the half-maximal inhibitory concentration (IC50) values and the blood-brain barrier (BBB) permeability of candidate compounds were obtained from ChEMBL and PubChem, respectively. CONCLUSION New therapeutic target genes and drug candidates against Alzheimer's disease were identified by means of drug repositioning.
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Affiliation(s)
- Ha Young Jang
- Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, South Korea
| | - Jung Mi Oh
- Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, South Korea,College of Pharmacy, Seoul National University, Seoul, South Korea
| | - In-Wha Kim
- Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, South Korea,*Correspondence: In-Wha Kim,
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18
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An Alzheimer’s Disease Patient-Derived Olfactory Stem Cell Model Identifies Gene Expression Changes Associated with Cognition. Cells 2022; 11:cells11203258. [PMID: 36291125 PMCID: PMC9601087 DOI: 10.3390/cells11203258] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 11/25/2022] Open
Abstract
An early symptom of Alzheimer’s disease (AD) is an impaired sense of smell, for which the molecular basis remains elusive. Here, we generated human olfactory neurosphere-derived (ONS) cells from people with AD and mild cognitive impairment (MCI), and performed global RNA sequencing to determine gene expression changes. ONS cells expressed markers of neuroglial differentiation, providing a unique cellular model to explore changes of early AD-associated pathways. Our transcriptomics data from ONS cells revealed differentially expressed genes (DEGs) associated with cognitive processes in AD cells compared to MCI, or matched healthy controls (HC). A-Kinase Anchoring Protein 6 (AKAP6) was the most significantly altered gene in AD compared to both MCI and HC, and has been linked to cognitive function. The greatest change in gene expression of all DEGs occurred between AD and MCI. Gene pathway analysis revealed defects in multiple cellular processes with aging, intellectual deficiency and alternative splicing being the most significantly dysregulated in AD ONS cells. Our results demonstrate that ONS cells can provide a cellular model for AD that recapitulates disease-associated differences. We have revealed potential novel genes, including AKAP6 that may have a role in AD, particularly MCI to AD transition, and should be further examined.
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19
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Alzheimer's disease large-scale gene expression portrait identifies exercise as the top theoretical treatment. Sci Rep 2022; 12:17189. [PMID: 36229643 PMCID: PMC9561721 DOI: 10.1038/s41598-022-22179-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 10/11/2022] [Indexed: 01/05/2023] Open
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects multiple brain regions and is difficult to treat. In this study we used 22 AD large-scale gene expression datasets to identify a consistent underlying portrait of AD gene expression across multiple brain regions. Then we used the portrait as a platform for identifying treatments that could reverse AD dysregulated expression patterns. Enrichment of dysregulated AD genes included multiple processes, ranging from cell adhesion to CNS development. The three most dysregulated genes in the AD portrait were the inositol trisphosphate kinase, ITPKB (upregulated), the astrocyte specific intermediate filament protein, GFAP (upregulated), and the rho GTPase, RHOQ (upregulated). 41 of the top AD dysregulated genes were also identified in a recent human AD GWAS study, including PNOC, C4B, and BCL11A. 42 transcription factors were identified that were both dysregulated in AD and that in turn affect expression of other AD dysregulated genes. Male and female AD portraits were highly congruent. Out of over 250 treatments, three datasets for exercise or activity were identified as the top three theoretical treatments for AD via reversal of large-scale gene expression patterns. Exercise reversed expression patterns of hundreds of AD genes across multiple categories, including cytoskeleton, blood vessel development, mitochondrion, and interferon-stimulated related genes. Exercise also ranked as the best treatment across a majority of individual region-specific AD datasets and meta-analysis AD datasets. Fluoxetine also scored well and a theoretical combination of fluoxetine and exercise reversed 549 AD genes. Other positive treatments included curcumin. Comparisons of the AD portrait to a recent depression portrait revealed a high congruence of downregulated genes in both. Together, the AD portrait provides a new platform for understanding AD and identifying potential treatments for AD.
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Marmolejo-Garza A, Medeiros-Furquim T, Rao R, Eggen BJL, Boddeke E, Dolga AM. Transcriptomic and epigenomic landscapes of Alzheimer's disease evidence mitochondrial-related pathways. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2022; 1869:119326. [PMID: 35839870 DOI: 10.1016/j.bbamcr.2022.119326] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 02/06/2023]
Abstract
Alzheimers disease (AD) is the main cause of dementia and it is defined by cognitive decline coupled to extracellular deposit of amyloid-beta protein and intracellular hyperphosphorylation of tau protein. Historically, efforts to target such hallmarks have failed in numerous clinical trials. In addition to these hallmark-targeted approaches, several clinical trials focus on other AD pathological processes, such as inflammation, mitochondrial dysfunction, and oxidative stress. Mitochondria and mitochondrial-related mechanisms have become an attractive target for disease-modifying strategies, as mitochondrial dysfunction prior to clinical onset has been widely described in AD patients and AD animal models. Mitochondrial function relies on both the nuclear and mitochondrial genome. Findings from omics technologies have shed light on AD pathophysiology at different levels (e.g., epigenome, transcriptome and proteome). Most of these studies have focused on the nuclear-encoded components. The first part of this review provides an updated overview of the mechanisms that regulate mitochondrial gene expression and function. The second part of this review focuses on evidence of mitochondrial dysfunction in AD. We have focused on published findings and datasets that study AD. We analyzed published data and provide examples for mitochondrial-related pathways. These pathways are strikingly dysregulated in AD neurons and glia in sex-, cell- and disease stage-specific manners. Analysis of mitochondrial omics data highlights the involvement of mitochondria in AD, providing a rationale for further disease modeling and drug targeting.
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Affiliation(s)
- Alejandro Marmolejo-Garza
- Department of Molecular Pharmacology, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy (GRIP), University of Groningen, the Netherlands; Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, Faculty of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Tiago Medeiros-Furquim
- Department of Molecular Pharmacology, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy (GRIP), University of Groningen, the Netherlands; Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, Faculty of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ramya Rao
- Department of Molecular Pharmacology, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy (GRIP), University of Groningen, the Netherlands
| | - Bart J L Eggen
- Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, Faculty of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Erik Boddeke
- Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, Faculty of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen N, Denmark.
| | - Amalia M Dolga
- Department of Molecular Pharmacology, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy (GRIP), University of Groningen, the Netherlands.
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Ramos-Campoy O, Lladó A, Bosch B, Ferrer M, Pérez-Millan A, Vergara M, Molina-Porcel L, Fort-Aznar L, Gonzalo R, Moreno-Izco F, Fernandez-Villullas G, Balasa M, Sánchez-Valle R, Antonell A. Differential Gene Expression in Sporadic and Genetic Forms of Alzheimer's Disease and Frontotemporal Dementia in Brain Tissue and Lymphoblastoid Cell Lines. Mol Neurobiol 2022; 59:6411-6428. [PMID: 35962298 DOI: 10.1007/s12035-022-02969-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/21/2022] [Indexed: 10/15/2022]
Abstract
Sporadic early-onset Alzheimer's disease (EOAD) and autosomal dominant Alzheimer's disease (ADAD) provide the opportunity to investigate the physiopathological mechanisms in the absence of aging, present in late-onset forms. Frontotemporal dementia (FTD) causes early-onset dementia associated to tau or TDP43 protein deposits. A 15% of FTD cases are caused by mutations in C9orf72, GRN, or MAPT genes. Lymphoblastoid cell lines (LCLs) have been proposed as an alternative to brain tissue for studying earlier phases of neurodegenerative diseases. The aim of this study is to investigate the expression profile in EOAD, ADAD, and sporadic and genetic FTD (sFTD and gFTD, respectively), using brain tissue and LCLs. Sixty subjects of the following groups were included: EOAD, ADAD, sFTD, gFTD, and controls. Gene expression was analyzed with Clariom D microarray (Affymetrix). Brain tissue pairwise comparisons revealed six common differentially expressed genes (DEG) for all the patients' groups compared with controls: RGS20, WIF1, HSPB1, EMP3, S100A11 and GFAP. Common up-regulated biological pathways were identified both in brain and LCLs (including inflammation and glial cell differentiation), while down-regulated pathways were detected mainly in brain tissue (including synaptic signaling, metabolism and mitochondrial dysfunction). CD163, ADAMTS9 and LIN7A gene expression disruption was validated by qPCR in brain tissue and NrCAM in LCLs in their respective group comparisons. In conclusion, our study highlights neuroinflammation, metabolism and synaptic signaling disturbances as common altered pathways in different AD and FTD forms. The use of LCLs might be appropriate for studying early immune system and inflammation, and some neural features in neurodegenerative dementias.
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Affiliation(s)
- Oscar Ramos-Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Mireia Ferrer
- Statistics and Bioinformatics Unit, Vall d'Hebrón Institut de Recerca, Passeig Vall d'Hebrón, Barcelona, Spain
| | - Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain.,Institute of Neurosciences, Department of Biomedicine, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - Miguel Vergara
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Laura Molina-Porcel
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain.,Neurological Tissue Bank, Biobank-Hospital Clinic-IDIBAPS, Barcelona, Spain
| | - Laura Fort-Aznar
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Ricardo Gonzalo
- Statistics and Bioinformatics Unit, Vall d'Hebrón Institut de Recerca, Passeig Vall d'Hebrón, Barcelona, Spain
| | - Fermín Moreno-Izco
- Cognitive Disorders Unit, Department of Neurology, Hospital Universitario Donostia, 20014, Donostia-San Sebastián, Spain.,Biodonostia, Neurosciences Area, Group of Neurodegenerative Diseases, 20014, San Sebastián, Spain
| | - Guadalupe Fernandez-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain.
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain.
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22
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Kowalski TW, Lord VO, Sgarioni E, Gomes JDA, Mariath LM, Recamonde-Mendoza M, Vianna FSL. Transcriptome meta-analysis of valproic acid exposure in human embryonic stem cells. Eur Neuropsychopharmacol 2022; 60:76-88. [PMID: 35635998 DOI: 10.1016/j.euroneuro.2022.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 04/02/2022] [Accepted: 04/11/2022] [Indexed: 11/04/2022]
Abstract
Valproic acid (VPA) is a widely used antiepileptic drug not recommended in pregnancy because it is teratogenic. Many assays have assessed the impact of the VPA exposure on the transcriptome of human embryonic stem-cells (hESC), but the molecular perturbations that VPA exerts in neurodevelopment are not completely understood. This study aimed to perform a transcriptome meta-analysis of VPA-exposed hESC to elucidate the main biological mechanisms altered by VPA effects on the gene expression. Publicly available microarray and RNA-seq transcriptomes were selected in the Gene Expression Omnibus (GEO) repository. Samples were processed according to the standard pipelines for each technology in the Galaxy server and R. Meta-analysis was performed using the Fisher-P method. Overrepresented genes were obtained by evaluating ontologies, pathways, and phenotypes' databases. The meta-analysis performed in seven datasets resulted in 61 perturbed genes, 54 upregulated. Ontology and pathway enrichments suggested neurodevelopment and neuroinflammatory effects; phenotype overrepresentation included epilepsy-related genes, such as SCN1A and GABRB2. The NDNF gene upregulation was also identified; this gene is involved in neuron migration and survival during development. Sub-network analysis proposed TGFβ and BMP pathways activation. These results suggest VPA exerts effects in epilepsy-related genes even in embryonic cells. Neurodevelopmental genes, such as NDNF were upregulated and VPA might also disturb several development pathways. These mechanisms might help to explain the spectrum of VPA-induced congenital anomalies and the molecular effects on neurodevelopment.
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Affiliation(s)
- Thayne Woycinck Kowalski
- Post-Graduation Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; National Institute of Medical Population Genetics (INAGEMP), Porto Alegre, Brazil; Bioinformatics Core, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Centro Universitário CESUCA, Cachoeirinha, Brazil.
| | - Vinícius Oliveira Lord
- Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Centro Universitário CESUCA, Cachoeirinha, Brazil
| | - Eduarda Sgarioni
- Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil
| | - Julia do Amaral Gomes
- Post-Graduation Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; National Institute of Medical Population Genetics (INAGEMP), Porto Alegre, Brazil
| | - Luiza Monteavaro Mariath
- Post-Graduation Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Mariana Recamonde-Mendoza
- Bioinformatics Core, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Fernanda Sales Luiz Vianna
- Post-Graduation Program in Genetics and Molecular Biology, Genetics Department, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Laboratory of Genomic Medicine, Center of Experimental Research, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; National Institute of Medical Population Genetics (INAGEMP), Porto Alegre, Brazil.
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23
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Delport A, Hewer R. The amyloid precursor protein: a converging point in Alzheimer's disease. Mol Neurobiol 2022; 59:4501-4516. [PMID: 35579846 DOI: 10.1007/s12035-022-02863-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 04/30/2022] [Indexed: 11/30/2022]
Abstract
The decades of evidence that showcase the role of amyloid precursor protein (APP), and its fragment amyloidβ (Aβ), in Alzheimer's disease (AD) pathogenesis are irrefutable. However, the absolute focus on the single APP metabolite Aβ as the cause for AD has resulted in APP and its other fragments that possess toxic propensity, to be overlooked as targets for treatment. The complexity of its processing and its association with systematic metabolism suggests that, if misregulated, APP has the potential to provoke an array of metabolic dysfunctions. This review discusses APP and several of its cleaved products with a particular focus on their toxicity and ability to disrupt healthy cellular function, in relation to AD development. We subsequently argue that the reduction of APP, which would result in a concurrent decrease in Aβ as well as all other toxic APP metabolites, would alleviate the toxic environment associated with AD and slow disease progression. A discussion of those drug-like compounds already identified to possess this capacity is also included.
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Affiliation(s)
- Alexandré Delport
- Discipline of Biochemistry, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, 3201, South Africa.
| | - Raymond Hewer
- Discipline of Biochemistry, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, 3201, South Africa
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24
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Belonwu SA, Li Y, Bunis DG, Rao AA, Solsberg CW, Oskotsky T, Taubes AL, Grone B, Zalocusky KA, Fragiadakis GK, Huang Y, Sirota M. Bioinformatics Analysis of Publicly Available Single-Nuclei Transcriptomics Alzheimer’s Disease Datasets Reveals APOE Genotype-Specific Changes Across Cell Types in Two Brain Regions. Front Aging Neurosci 2022; 14:749991. [PMID: 35572130 PMCID: PMC9093608 DOI: 10.3389/fnagi.2022.749991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer’s Disease (AD) is a complex neurodegenerative disease that gravely affects patients and imposes an immense burden on caregivers. Apolipoprotein E4 (APOE4) has been identified as the most common genetic risk factor for AD, yet the molecular mechanisms connecting APOE4 to AD are not well understood. Past transcriptomic analyses in AD have revealed APOE genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level. To elucidate more complex APOE genotype-specific disease-relevant changes masked by the bulk analysis, we leverage the first two single-nucleus RNA sequencing AD datasets from human brain samples, including nearly 55,000 cells from the prefrontal and entorhinal cortices. In each brain region, we performed a case versus control APOE genotype-stratified differential gene expression analysis and pathway network enrichment in astrocytes, microglia, neurons, oligodendrocytes, and oligodendrocyte progenitor cells. We observed more global transcriptomic changes in APOE4 positive AD cells and identified differences across APOE genotypes primarily in glial cell types. Our findings highlight the differential transcriptomic perturbations of APOE isoforms at a single-cell level in AD pathogenesis and have implications for precision medicine development in the diagnosis and treatment of AD.
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Affiliation(s)
- Stella A. Belonwu
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, United States
| | - Yaqiao Li
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, United States
| | - Daniel G. Bunis
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- CoLabs, University of California, San Francisco, San Francisco, CA, United States
- Bakar ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, United States
| | - Arjun Arkal Rao
- CoLabs, University of California, San Francisco, San Francisco, CA, United States
- Bakar ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, United States
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
| | - Caroline Warly Solsberg
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, United States
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
| | - Alice L. Taubes
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
| | - Brian Grone
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
| | - Kelly A. Zalocusky
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
| | - Gabriela K. Fragiadakis
- CoLabs, University of California, San Francisco, San Francisco, CA, United States
- Bakar ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, United States
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Yadong Huang
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
- *Correspondence: Marina Sirota,
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25
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Xia LY, Tang L, Huang H, Luo J. Identification of Potential Driver Genes and Pathways Based on Transcriptomics Data in Alzheimer's Disease. Front Aging Neurosci 2022; 14:752858. [PMID: 35401145 PMCID: PMC8985410 DOI: 10.3389/fnagi.2022.752858] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 02/21/2022] [Indexed: 01/16/2023] Open
Abstract
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. To identify AD-related genes from transcriptomics and help to develop new drugs to treat AD. In this study, firstly, we obtained differentially expressed genes (DEG)-enriched coexpression networks between AD and normal samples in multiple transcriptomics datasets by weighted gene co-expression network analysis (WGCNA). Then, a convergent genomic approach (CFG) integrating multiple AD-related evidence was used to prioritize potential genes from DEG-enriched modules. Subsequently, we identified candidate genes in the potential genes list. Lastly, we combined deepDTnet and SAveRUNNER to predict interaction among candidate genes, drug and AD. Experiments on five datasets show that the CFG score of GJA1 is the highest among all potential driver genes of AD. Moreover, we found GJA1 interacts with AD from target-drugs-diseases network prediction. Therefore, candidate gene GJA1 is the most likely to be target of AD. In summary, identification of AD-related genes contributes to the understanding of AD pathophysiology and the development of new drugs.
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26
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Hou CD, Yang TS. Distribution of weighted Lancaster’s statistic for combining independent or dependent P-values, with applications to human genetic studies. COMMUN STAT-THEOR M 2022. [DOI: 10.1080/03610926.2022.2046088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Chia-Ding Hou
- Department of Statistics and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Ti-Sung Yang
- Department of Statistics and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan
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27
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Zhang H, Elefant F. Exploring the Alzheimer's disease neuroepigenome: recent advances and future trends. Neural Regen Res 2022; 17:325-327. [PMID: 34269202 PMCID: PMC8463995 DOI: 10.4103/1673-5374.317978] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 03/15/2021] [Accepted: 04/27/2021] [Indexed: 11/08/2022] Open
Affiliation(s)
- Haolin Zhang
- Department of Biology, Drexel University, Philadelphia, PA, USA
| | - Felice Elefant
- Department of Biology, Drexel University, Philadelphia, PA, USA
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28
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A missense variant in SHARPIN mediates Alzheimer's disease-specific brain damages. Transl Psychiatry 2021; 11:590. [PMID: 34785643 PMCID: PMC8595886 DOI: 10.1038/s41398-021-01680-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 08/04/2021] [Accepted: 08/27/2021] [Indexed: 01/23/2023] Open
Abstract
Established genetic risk factors for Alzheimer's disease (AD) account for only a portion of AD heritability. The aim of this study was to identify novel associations between genetic variants and AD-specific brain atrophy. We conducted genome-wide association studies for brain magnetic resonance imaging measures of hippocampal volume and entorhinal cortical thickness in 2643 Koreans meeting the clinical criteria for AD (n = 209), mild cognitive impairment (n = 1449) or normal cognition (n = 985). A missense variant, rs77359862 (R274W), in the SHANK-associated RH Domain Interactor (SHARPIN) gene was associated with entorhinal cortical thickness (p = 5.0 × 10-9) and hippocampal volume (p = 5.1 × 10-12). It revealed an increased risk of developing AD in the mediation analyses. This variant was also associated with amyloid-β accumulation (p = 0.03) and measures of memory (p = 1.0 × 10-4) and executive function (p = 0.04). We also found significant association of other SHARPIN variants with hippocampal volume in the Alzheimer's Disease Neuroimaging Initiative (rs3417062, p = 4.1 × 10-6) and AddNeuroMed (rs138412600, p = 5.9 × 10-5) cohorts. Further, molecular dynamics simulations and co-immunoprecipitation indicated that the variant significantly reduced the binding of linear ubiquitination assembly complex proteins, SHPARIN and HOIL-1 Interacting Protein (HOIP), altering the downstream NF-κB signaling pathway. These findings suggest that SHARPIN plays an important role in the pathogenesis of AD.
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29
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Tan MS, Cheah PL, Chin AV, Looi LM, Chang SW. A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach. Comput Biol Med 2021; 139:104947. [PMID: 34678481 DOI: 10.1016/j.compbiomed.2021.104947] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/12/2021] [Accepted: 10/12/2021] [Indexed: 12/26/2022]
Abstract
Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the most common cause of dementia in the elderly. As the number of elderly individuals increases globally, the incidence and prevalence of AD are expected to increase. At present, AD is diagnosed clinically, according to accepted criteria. The essential elements in the diagnosis of AD include a patients history, a physical examination and neuropsychological testing, in addition to appropriate investigations such as neuroimaging. The omics-based approach is an emerging field of study that may not only aid in the diagnosis of AD but also facilitate the exploration of factors that influence the development of the disease. Omics techniques, including genomics, transcriptomics, proteomics and metabolomics, may reveal the pathways that lead to neuronal death and identify biomolecular markers associated with AD. This will further facilitate an understanding of AD neuropathology. In this review, omics-based approaches that were implemented in studies on AD were assessed from a bioinformatics perspective. Current state-of-the-art statistical and machine learning approaches used in the single omics analysis of AD were compared based on correlations of variants, differential expression, functional analysis and network analysis. This was followed by a review of the approaches used in the integration and analysis of multi-omics of AD. The strengths and limitations of multi-omics analysis methods were explored and the issues and challenges associated with omics studies of AD were highlighted. Lastly, future studies in this area of research were justified.
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Affiliation(s)
- Mei Sze Tan
- Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
| | - Phaik-Leng Cheah
- Department of Pathology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Ai-Vyrn Chin
- Division of Geriatric Medicine, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Lai-Meng Looi
- Department of Pathology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Siow-Wee Chang
- Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.
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30
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Guo L, Liu Y, Wang J. Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease. Front Aging Neurosci 2021; 13:727928. [PMID: 34539387 PMCID: PMC8446362 DOI: 10.3389/fnagi.2021.727928] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 08/12/2021] [Indexed: 12/04/2022] Open
Abstract
The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.
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Affiliation(s)
- Liyuan Guo
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yushan Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jing Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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31
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Zhang L, Du Rietz E, Kuja-Halkola R, Dobrosavljevic M, Johnell K, Pedersen NL, Larsson H, Chang Z. Attention-deficit/hyperactivity disorder and Alzheimer's disease and any dementia: A multi-generation cohort study in Sweden. Alzheimers Dement 2021; 18:1155-1163. [PMID: 34498801 DOI: 10.1002/alz.12462] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 02/01/2021] [Accepted: 07/30/2021] [Indexed: 11/10/2022]
Abstract
INTRODUCTION We examined the extent to which attention-deficit/hyperactivity disorder (ADHD), a neurodevelopmental disorder, is linked with Alzheimer's disease (AD) and any dementia, neurodegenerative diseases, across generations. METHODS A nationwide cohort born between 1980 and 2001 (index persons) were linked to their biological relatives (parents, grandparents, uncles/aunts) using Swedish national registers. We used Cox models to examine the cross-generation associations. RESULTS Among relatives of 2,132,929 index persons, 3042 parents, 171,732 grandparents, and 1369 uncles/aunts had a diagnosis of AD. Parents of individuals with ADHD had an increased risk of AD (hazard ratio 1.55, 95% confidence interval 1.26-1.89). The associations attenuated but remained elevated in grandparents and uncles/aunts. The association for early-onset AD was stronger than late-onset AD. Similar results were observed for any dementia. DISCUSSION ADHD is associated with AD and any dementia across generations. The associations attenuated with decreasing genetic relatedness, suggesting shared familial risk between ADHD and AD.
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Affiliation(s)
- Le Zhang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Kristina Johnell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Zheng Chang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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32
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Beaver M, Karisetty BC, Zhang H, Bhatnagar A, Armour E, Parmar V, Brown R, Xiang M, Elefant F. Chromatin and transcriptomic profiling uncover dysregulation of the Tip60 HAT/HDAC2 epigenomic landscape in the neurodegenerative brain. Epigenetics 2021; 17:786-807. [PMID: 34369292 PMCID: PMC9336495 DOI: 10.1080/15592294.2021.1959742] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Disruption of histone acetylation-mediated gene control is a critical step in Alzheimer’s Disease (AD), yet chromatin analysis of antagonistic histone acetyltransferases (HATs) and histone deacetylases (HDACs) causing these alterations remains uncharacterized. We report the first Tip60 HAT versus HDAC2 chromatin (ChIP-seq) and transcriptional (RNA-seq) profiling study in Drosophila melanogaster brains that model early human AD. We find Tip60 and HDAC2 predominantly recruited to identical neuronal genes. Moreover, AD brains exhibit robust genome-wide early alterations that include enhanced HDAC2 and reduced Tip60 binding and transcriptional dysregulation. Orthologous human genes to co-Tip60/HDAC2 D. melanogaster neural targets exhibit conserved disruption patterns in AD patient hippocampi. Notably, we discovered distinct transcription factor binding sites close or within Tip60/HDAC2 co-peaks in neuronal genes, implicating them in coenzyme recruitment. Increased Tip60 protects against transcriptional dysregulation and enhanced HDAC2 enrichment genome-wide. We advocate Tip60 HAT/HDAC2 mediated epigenetic neuronal gene disruption as a genome-wide initial causal event in AD.
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Affiliation(s)
- Mariah Beaver
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | | | - Haolin Zhang
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Akanksha Bhatnagar
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Ellen Armour
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Visha Parmar
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Reshma Brown
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Merry Xiang
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
| | - Felice Elefant
- Department of Biology, Drexel University, Philadelphia, Pennsylvania, USA
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33
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Preprocessing of Public RNA-Sequencing Datasets to Facilitate Downstream Analyses of Human Diseases. DATA 2021. [DOI: 10.3390/data6070075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Publicly available RNA-sequencing (RNA-seq) data are a rich resource for elucidating the mechanisms of human disease; however, preprocessing these data requires considerable bioinformatic expertise and computational infrastructure. Analyzing multiple datasets with a consistent computational workflow increases the accuracy of downstream meta-analyses. This collection of datasets represents the human intracellular transcriptional response to disorders and diseases such as acute lymphoblastic leukemia (ALL), B-cell lymphomas, chronic obstructive pulmonary disease (COPD), colorectal cancer, lupus erythematosus; as well as infection with pathogens including Borrelia burgdorferi, hantavirus, influenza A virus, Middle East respiratory syndrome coronavirus (MERS-CoV), Streptococcus pneumoniae, respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We calculated the statistically significant differentially expressed genes and Gene Ontology terms for all datasets. In addition, a subset of the datasets also includes results from splice variant analyses, intracellular signaling pathway enrichments as well as read mapping and quantification. All analyses were performed using well-established algorithms and are provided to facilitate future data mining activities, wet lab studies, and to accelerate collaboration and discovery.
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34
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Deolankar SC, Patil AH, Rex DAB, Subba P, Mahadevan A, Prasad TSK. Mapping Post-Translational Modifications in Brain Regions in Alzheimer's Disease Using Proteomics Data Mining. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2021; 25:525-536. [PMID: 34255573 DOI: 10.1089/omi.2021.0054] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Alzheimer's disease (AD) is a leading cause of dementia and a neurodegenerative disease. Proteomics and post-translational modification (PTM) analyses offer new opportunities for a comprehensive understanding of pathophysiology of brain in AD. We report here multiple PTMs in patients with AD, harnessing publicly available proteomics data from nine brain regions and at three different Braak stages of disease progression. Specifically, we identified 7190 peptides with PTMs, corresponding to 2545 proteins from brain regions with intermediate tangles, and 6864 peptides with PTMs corresponding to 2465 proteins from brain regions with severe tangles. A total of 103 proteins with PTMs were expressed uniquely to intermediate tangles and severe tangles compared to no tangles. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis suggested the association of these proteins in AD progression through platelet activation. These modified proteins were also found to be enriched for the tricarboxylic acid (TCA) cycle, respiratory electron cycle, and detoxification of reactive oxygen species. The multi-PTM data reported here contribute to our understanding of the neurobiology of AD and highlight the prospects of omics systems science research in neurodegenerative diseases. The present study provides a region-wise classification for the proteins with PTMs along with their differential expression patterns, providing insights into the localization of these proteins upon modification. The catalog of multi-PTMs identified in the context of AD from different brain regions provides a unique platform for generating newer hypotheses in understanding the putative role of specific PTMs in AD pathogenesis.
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Affiliation(s)
- Sayali Chandrashekhar Deolankar
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Arun H Patil
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Devasahayam Arokia Balaya Rex
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Pratigya Subba
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Anita Mahadevan
- Department of Neuropathology, National Institute of Mental Health and Neurosciences, Bangalore, India.,Human Brain Tissue Repository, National Institute of Mental Health and Neurosciences, Bangalore, India
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Weighted Gene Coexpression Network Analysis Uncovers Critical Genes and Pathways for Multiple Brain Regions in Parkinson's Disease. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6616434. [PMID: 33791366 PMCID: PMC7984900 DOI: 10.1155/2021/6616434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/21/2021] [Accepted: 02/08/2021] [Indexed: 12/13/2022]
Abstract
Objective In this study, we aimed to identify critical genes and pathways for multiple brain regions in Parkinson's disease (PD) by weighted gene coexpression network analysis (WGCNA). Methods From the GEO database, differentially expressed genes (DEGs) were separately identified between the substantia nigra, putamen, prefrontal cortex area, and cingulate gyrus of PD and normal samples with the screening criteria of p value < 0.05 and ∣log2fold change (FC) | >0.585. Then, a coexpression network was presented by the WGCNA package. Gene modules related to PD were constructed. Then, PD-related DEGs were used for construction of PPI networks. Hub genes were determined by the cytoHubba plug-in. Functional enrichment analysis was then performed. Results DEGs were identified for the substantia nigra (17 upregulated and 52 downregulated genes), putamen (317 upregulated and 317 downregulated genes), prefrontal cortex area (39 upregulated and 72 downregulated genes), and cingulate gyrus (116 upregulated and 292 downregulated genes) of PD compared to normal samples. Gene modules were separately built for the four brain regions of PD. PPI networks revealed hub genes for the substantia nigra (SLC6A3, SLC18A2, and TH), putamen (BMP4 and SNAP25), prefrontal cortex area (SNAP25), and cingulate gyrus (CTGF, CDH1, and COL5A1) of PD. These DEGs in multiple brain regions were involved in distinct biological functions and pathways. GSEA showed that these DEGs were all significantly enriched in electron transport chain, proteasome degradation, and synaptic vesicle pathway. Conclusion Our findings revealed critical genes and pathways for multiple brain regions in PD, which deepened the understanding of PD-related molecular mechanisms.
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Pellegrini C, Pirazzini C, Sala C, Sambati L, Yusipov I, Kalyakulina A, Ravaioli F, Kwiatkowska KM, Durso DF, Ivanchenko M, Monti D, Lodi R, Franceschi C, Cortelli P, Garagnani P, Bacalini MG. A Meta-Analysis of Brain DNA Methylation Across Sex, Age, and Alzheimer's Disease Points for Accelerated Epigenetic Aging in Neurodegeneration. Front Aging Neurosci 2021; 13:639428. [PMID: 33790779 PMCID: PMC8006465 DOI: 10.3389/fnagi.2021.639428] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/05/2021] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by specific alterations of brain DNA methylation (DNAm) patterns. Age and sex, two major risk factors for AD, are also known to largely affect the epigenetic profiles in brain, but their contribution to AD-associated DNAm changes has been poorly investigated. In this study we considered publicly available DNAm datasets of four brain regions (temporal, frontal, entorhinal cortex, and cerebellum) from healthy adult subjects and AD patients, and performed a meta-analysis to identify sex-, age-, and AD-associated epigenetic profiles. In one of these datasets it was also possible to distinguish 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) profiles. We showed that DNAm differences between males and females tend to be shared between the four brain regions, while aging differently affects cortical regions compared to cerebellum. We found that the proportion of sex-dependent probes whose methylation is modified also during aging is higher than expected, but that differences between males and females tend to be maintained, with only a few probes showing age-by-sex interaction. We did not find significant overlaps between AD- and sex-associated probes, nor disease-by-sex interaction effects. On the contrary, we found that AD-related epigenetic modifications are significantly enriched in probes whose DNAm varies with age and that there is a high concordance between the direction of changes (hyper or hypo-methylation) in aging and AD, supporting accelerated epigenetic aging in the disease. In summary, our results suggest that age-associated DNAm patterns concur to the epigenetic deregulation observed in AD, providing new insights on how advanced age enables neurodegeneration.
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Affiliation(s)
- Camilla Pellegrini
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Chiara Pirazzini
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Claudia Sala
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Luisa Sambati
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Igor Yusipov
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Alena Kalyakulina
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Francesco Ravaioli
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Katarzyna M. Kwiatkowska
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Danielle F. Durso
- Department of Neurology, University of Massachusetts Medical School, Worcester, MA, United States
| | - Mikhail Ivanchenko
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Daniela Monti
- Department of Experimental and Clinical Biomedical Sciences “Mario Serio,” University of Florence, Florence, Italy
| | - Raffaele Lodi
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Claudio Franceschi
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Pietro Cortelli
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
- Department of Laboratory Medicine, Clinical Chemistry, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Applied Biomedical Research Center, Policlinico S.Orsola-Malpighi Polyclinic, Bologna, Italy
- National Research Council of Italy Institute of Molecular Genetics “Luigi Luca Cavalli-Sforza,” Unit of Bologna, Bologna, Italy
| | - Maria Giulia Bacalini
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
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Stojakovic A, Trushin S, Sheu A, Khalili L, Chang SY, Li X, Christensen T, Salisbury JL, Geroux RE, Gateno B, Flannery PJ, Dehankar M, Funk CC, Wilkins J, Stepanova A, O'Hagan T, Galkin A, Nesbitt J, Zhu X, Tripathi U, Macura S, Tchkonia T, Pirtskhalava T, Kirkland JL, Kudgus RA, Schoon RA, Reid JM, Yamazaki Y, Kanekiyo T, Zhang S, Nemutlu E, Dzeja P, Jaspersen A, Kwon YIC, Lee MK, Trushina E. Partial inhibition of mitochondrial complex I ameliorates Alzheimer's disease pathology and cognition in APP/PS1 female mice. Commun Biol 2021; 4:61. [PMID: 33420340 PMCID: PMC7794523 DOI: 10.1038/s42003-020-01584-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 12/08/2020] [Indexed: 12/11/2022] Open
Abstract
Alzheimer's Disease (AD) is a devastating neurodegenerative disorder without a cure. Here we show that mitochondrial respiratory chain complex I is an important small molecule druggable target in AD. Partial inhibition of complex I triggers the AMP-activated protein kinase-dependent signaling network leading to neuroprotection in symptomatic APP/PS1 female mice, a translational model of AD. Treatment of symptomatic APP/PS1 mice with complex I inhibitor improved energy homeostasis, synaptic activity, long-term potentiation, dendritic spine maturation, cognitive function and proteostasis, and reduced oxidative stress and inflammation in brain and periphery, ultimately blocking the ongoing neurodegeneration. Therapeutic efficacy in vivo was monitored using translational biomarkers FDG-PET, 31P NMR, and metabolomics. Cross-validation of the mouse and the human transcriptomic data from the NIH Accelerating Medicines Partnership-AD database demonstrated that pathways improved by the treatment in APP/PS1 mice, including the immune system response and neurotransmission, represent mechanisms essential for therapeutic efficacy in AD patients.
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Affiliation(s)
- Andrea Stojakovic
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Sergey Trushin
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Anthony Sheu
- Institute for Translational Neuroscience, University of Minnesota Twin Cities, 2101 6th Street SE, Minneapolis, MN, 55455, USA
| | - Layla Khalili
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Su-Youne Chang
- Department of Neurologic Surgery, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Xing Li
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Trace Christensen
- Microscopy and Cell Analysis Core, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Jeffrey L Salisbury
- Microscopy and Cell Analysis Core, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Rachel E Geroux
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Benjamin Gateno
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Padraig J Flannery
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Mrunal Dehankar
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Cory C Funk
- Institute for Systems Biology, Seattle, WA, 98109-5263, USA
| | - Jordan Wilkins
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Anna Stepanova
- Division of Neonatology, Department of Pediatrics, Columbia University, 116th St & Broadway, New York, NY, 10027, USA
| | - Tara O'Hagan
- Division of Neonatology, Department of Pediatrics, Columbia University, 116th St & Broadway, New York, NY, 10027, USA
| | - Alexander Galkin
- Division of Neonatology, Department of Pediatrics, Columbia University, 116th St & Broadway, New York, NY, 10027, USA
| | - Jarred Nesbitt
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Xiujuan Zhu
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Utkarsh Tripathi
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Slobodan Macura
- Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Tamar Tchkonia
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Tamar Pirtskhalava
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - James L Kirkland
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Rachel A Kudgus
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Renee A Schoon
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Joel M Reid
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Yu Yamazaki
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Takahisa Kanekiyo
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Song Zhang
- Department of Cardiovascular Medicine, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Emirhan Nemutlu
- Faculty of Pharmacy, Department of Analytical Chemistry, Hacettepe University, Sihhiye, Ankara, 06100, Turkey
| | - Petras Dzeja
- Department of Cardiovascular Medicine, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Adam Jaspersen
- Microscopy and Cell Analysis Core, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Ye In Christopher Kwon
- Institute for Translational Neuroscience, University of Minnesota Twin Cities, 2101 6th Street SE, Minneapolis, MN, 55455, USA
| | - Michael K Lee
- Institute for Translational Neuroscience, University of Minnesota Twin Cities, 2101 6th Street SE, Minneapolis, MN, 55455, USA
| | - Eugenia Trushina
- Department of Neurology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA.
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA.
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Patel R, Aschner M. Commonalities between Copper Neurotoxicity and Alzheimer's Disease. TOXICS 2021; 9:4. [PMID: 33430181 PMCID: PMC7825595 DOI: 10.3390/toxics9010004] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 12/25/2020] [Accepted: 01/05/2021] [Indexed: 12/17/2022]
Abstract
Alzheimer's disease, a highly prevalent form of dementia, targets neuron function beginning from the hippocampal region and expanding outwards. Alzheimer's disease is caused by elevated levels of heavy metals, such as lead, zinc, and copper. Copper is found in many areas of daily life, raising a concern as to how this metal and Alzheimer's disease are related. Previous studies have not identified the common pathways between excess copper and Alzheimer's disease etiology. Our review corroborates that both copper and Alzheimer's disease target the hippocampus, cerebral cortex, cerebellum, and brainstem, affecting motor skills and critical thinking. Additionally, Aβ plaque formation was analyzed beginning from synthesis at the APP parent protein site until Aβ plaque formation was completed. Structural changes were also noted. Further analysis revealed a relationship between amyloid-beta plaques and copper ion concentration. As copper ion levels increased, it bound to the Aβ monomer, expediting the plaque formation process, and furthering neurodegeneration. These conclusions can be utilized in the medical community to further research on the etiology of Alzheimer's disease and its relationships to copper and other metal-induced neurotoxicity.
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Affiliation(s)
| | - Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA;
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Bochukova EG. Transcriptomics of the Prader-Willi syndrome hypothalamus. HANDBOOK OF CLINICAL NEUROLOGY 2021; 181:369-379. [PMID: 34238471 DOI: 10.1016/b978-0-12-820683-6.00027-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Prader-Willi syndrome (PWS) is a complex neurodevelopmental disorder, arising from a loss of paternity expressed genetic material on the imprinted chromosome locus 15q11-q13. Despite increasing clarity on the underlying genetic defects, the molecular basis of the condition remains poorly understood. Hypothalamic dysfunction is widely recognized as the basis of the core symptoms of PWS, which include a deficiency in growth hormone and reproductive hormones, circadian rhythm abnormalities, and a lack of satiety, leading to an extreme obesity, among others. Genome-wide gene expression analysis (transcriptomics) offers an unbiased interrogation of complex disease pathogenesis and a potential window into the dysregulated pathways involved in disease. In this chapter, we review the findings from recent work investigating the PWS hypothalamic transcriptome, discuss the significance of the findings in relation to the clinical presentation and molecular underpinnings of PWS, and highlight future research directions.
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Affiliation(s)
- Elena G Bochukova
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.
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40
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Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration. Neurobiol Dis 2020; 149:105225. [PMID: 33347974 PMCID: PMC7856076 DOI: 10.1016/j.nbd.2020.105225] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/11/2020] [Accepted: 12/16/2020] [Indexed: 12/11/2022] Open
Abstract
Neurodegenerative disorders such as Alzheimer's disease (AD), Lewy body diseases (LBD), and the amyotrophic lateral sclerosis and frontotemporal dementia (ALS-FTD) spectrum are defined by the accumulation of specific misfolded protein aggregates. However, the mechanisms by which each proteinopathy leads to neurodegeneration remain elusive. We hypothesized that there is a common "pan-neurodegenerative" gene expression signature driving pathophysiology across these clinically and pathologically diverse proteinopathies. To test this hypothesis, we performed a systematic review of human CNS transcriptomics datasets from AD, LBD, and ALS-FTD patients and age-matched controls in the Gene Expression Omnibus (GEO) and ArrayExpress databases, followed by consistent processing of each dataset, meta-analysis, pathway enrichment, and overlap analyses. After applying pre-specified eligibility criteria and stringent data pre-processing, a total of 2600 samples from 26 AD, 21 LBD, and 13 ALS-FTD datasets were included in the meta-analysis. The pan-neurodegenerative gene signature is characterized by an upregulation of innate immunity, cytoskeleton, and transcription and RNA processing genes, and a downregulation of the mitochondrial electron transport chain. Pathway enrichment analyses also revealed the upregulation of neuroinflammation (including Toll-like receptor, TNF, and NFκB signaling) and phagocytosis, and the downregulation of mitochondrial oxidative phosphorylation, lysosomal acidification, and ubiquitin-proteasome pathways. Our findings suggest that neuroinflammation and a failure in both neuronal energy metabolism and protein degradation systems are consistent features underlying neurodegenerative diseases, despite differences in the extent of neuronal loss and brain regions involved.
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Almeida-Silva F, Moharana KC, Machado FB, Venancio TM. Exploring the complexity of soybean (Glycine max) transcriptional regulation using global gene co-expression networks. PLANTA 2020; 252:104. [PMID: 33196909 DOI: 10.1007/s00425-020-03499-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 10/15/2020] [Indexed: 06/11/2023]
Abstract
MAIN CONCLUSION We report a soybean gene co-expression network built with data from 1284 RNA-Seq experiments, which was used to identify important regulators, modules and to elucidate the fates of gene duplicates. Soybean (Glycine max (L.) Merr.) is one of the most important crops worldwide, constituting a major source of protein and edible oil. Gene co-expression networks (GCN) have been extensively used to study transcriptional regulation and evolution of genes and genomes. Here, we report a soybean GCN using 1284 publicly available RNA-Seq samples from 15 distinct tissues. We found modules that are differentially regulated in specific tissues, comprising processes such as photosynthesis, gluconeogenesis, lignin metabolism, and response to biotic stress. We identified transcription factors among intramodular hubs, which probably integrate different pathways and shape the transcriptional landscape in different conditions. The top hubs for each module tend to encode proteins with critical roles, such as succinate dehydrogenase and RNA polymerase subunits. Importantly, gene essentiality was strongly correlated with degree centrality and essential hubs were enriched in genes involved in nucleic acids metabolism and regulation of cell replication. Using a guilt-by-association approach, we predicted functions for 93 of 106 hubs without functional description in soybean. Most of the duplicated genes had different transcriptional profiles, supporting their functional divergence, although paralogs originating from whole-genome duplications (WGD) are more often preserved in the same module than those from other mechanisms. Together, our results highlight the importance of GCN analysis in unraveling key functional aspects of the soybean genome, in particular those associated with hub genes and WGD events.
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Affiliation(s)
- Fabricio Almeida-Silva
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil
| | - Kanhu C Moharana
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil
| | - Fabricio B Machado
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil
| | - Thiago M Venancio
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil.
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Zhang H, Karisetty BC, Bhatnagar A, Armour EM, Beaver M, Roach TV, Mortazavi S, Mandloi S, Elefant F. Tip60 protects against amyloid-β-induced transcriptomic alterations via different modes of action in early versus late stages of neurodegeneration. Mol Cell Neurosci 2020; 109:103570. [PMID: 33160016 DOI: 10.1016/j.mcn.2020.103570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 10/24/2020] [Accepted: 10/31/2020] [Indexed: 10/23/2022] Open
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disorder hallmarked by amyloid-β (Aβ) plaque accumulation, neuronal cell death, and cognitive deficits that worsen during disease progression. Histone acetylation dysregulation, caused by an imbalance between reduced histone acetyltransferases (HAT) Tip60 and increased histone deacetylase 2 (HDAC2) levels, can directly contribute to AD pathology. However, whether such AD-associated neuroepigenetic alterations occur in response to Aβ peptide production and can be protected against by increasing Tip60 levels over the course of neurodegenerative progression remains unknown. Here we profile Tip60 HAT/HDAC2 dynamics and transcriptome-wide changes across early and late stage AD pathology in the Drosophila brain produced solely by human amyloid-β42. We show that early Aβ42 induction leads to disruption of Tip60 HAT/HDAC2 balance during early neurodegenerative stages preceding Aβ plaque accumulation that persists into late AD stages. Correlative transcriptome-wide studies reveal alterations in biological processes we classified as transient (early-stage only), late-onset (late-stage only), and constant (both). Increasing Tip60 HAT levels in the Aβ42 fly brain protects against AD functional pathologies that include Aβ plaque accumulation, neural cell death, cognitive deficits, and shorter life-span. Strikingly, Tip60 protects against Aβ42-induced transcriptomic alterations via distinct mechanisms during early and late stages of neurodegeneration. Our findings reveal distinct modes of neuroepigenetic gene changes and Tip60 neuroprotection in early versus late stages in AD that can serve as early biomarkers for AD, and support the therapeutic potential of Tip60 over the course of AD progression.
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Affiliation(s)
- Haolin Zhang
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | | | - Akanksha Bhatnagar
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Ellen M Armour
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Mariah Beaver
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Tiffany V Roach
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Sina Mortazavi
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Shreya Mandloi
- Department of Biology, Drexel University, Philadelphia, PA, United States
| | - Felice Elefant
- Department of Biology, Drexel University, Philadelphia, PA, United States.
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Arzouni N, Matloff W, Zhao L, Ning K, Toga AW. Identification of Dysregulated Genes for Late-Onset Alzheimer's Disease Using Gene Expression Data in Brain. JOURNAL OF ALZHEIMER'S DISEASE & PARKINSONISM 2020; 10:498. [PMID: 33282526 PMCID: PMC7717689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Alzheimer's Disease (AD) is a neurodegenerative complex brain disease that represents a public health concern. AD is considered the fifth leading cause of death in Americans who are older than 65 years which prioritizes the importance of understanding the etiology of AD in its early stages before the onset of symptoms. This study attempted to further understand Alzheimer's disease (AD) etiology by investigating the dysregulated genes using gene expression data from multiple brain regions. METHODS A linear mixed-effects model for differential gene expression analysis was used in a sample of 15 AD and 30 control subjects, each with data from four different brain regions, in order to deal with the hierarchical multilevel data. Post-hoc Gene Ontology and pathway enrichment analyses provided insights on the biological implications in AD progression. Supervised machine learning algorithms were used to assess the discriminative power of the top 10 candidate genes in distinguishing between the two groups. RESULTS Enrichment analyses revealed biological processes and pathways that are related to structural constituents and organization of the axons and synapses. These biological processes and pathways imply dysfunctional axon and synaptic transmission between neuronal cells in AD. Random Forest classification algorithm gave the best accuracy on the test data with F1-score of 0.88. CONCLUSION The differentially expressed genes were associated with axon and synaptic transmissions which affect the neuronal connectivity in cognitive systems involved in AD pathophysiology. These genes may open ways to explore new effective treatments and early diagnosis before the onset of clinical symptoms.
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Affiliation(s)
- Nibal Arzouni
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, USA
- Computational Biology and Bioinformatics Program, University of Southern California, USA
| | - Will Matloff
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, USA
- Neuroscience Graduate Program, University of Southern California, USA
| | - Lu Zhao
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, USA
| | - Kaida Ning
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, USA
- Computational Biology and Bioinformatics Program, University of Southern California, USA
| | - Arthur W Toga
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, USA
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Navarro JF, Croteau DL, Jurek A, Andrusivova Z, Yang B, Wang Y, Ogedegbe B, Riaz T, Støen M, Desler C, Rasmussen LJ, Tønjum T, Galas MC, Lundeberg J, Bohr VA. Spatial Transcriptomics Reveals Genes Associated with Dysregulated Mitochondrial Functions and Stress Signaling in Alzheimer Disease. iScience 2020; 23:101556. [PMID: 33083725 PMCID: PMC7522123 DOI: 10.1016/j.isci.2020.101556] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/24/2020] [Accepted: 09/09/2020] [Indexed: 12/15/2022] Open
Abstract
Alzheimer disease (AD) is a devastating neurological disease associated with progressive loss of mental skills and cognitive and physical functions whose etiology is not completely understood. Here, our goal was to simultaneously uncover novel and known molecular targets in the structured layers of the hippocampus and olfactory bulbs that may contribute to early hippocampal synaptic deficits and olfactory dysfunction in AD mice. Spatially resolved transcriptomics was used to identify high-confidence genes that were differentially regulated in AD mice relative to controls. A diverse set of genes that modulate stress responses and transcription were predominant in both hippocampi and olfactory bulbs. Notably, we identify Bok, implicated in mitochondrial physiology and cell death, as a spatially downregulated gene in the hippocampus of mouse and human AD brains. In summary, we provide a rich resource of spatially differentially expressed genes, which may contribute to understanding AD pathology. Spatial transcriptomics identifies differentially expressed genes with spatial patterns Early application of spatial transcriptomics to olfactory bulbs from AD models Bok gene is spatially differentially expressed in AD mouse and patient brains Paip1 and Homer1 genes are regulated in a PolB-dependent manner
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Affiliation(s)
- José Fernández Navarro
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Stockholm, Sweden
| | - Deborah L Croteau
- Laboratory of Molecular Gerontology, National Institute on Aging, Baltimore, MD 21224, USA
| | - Aleksandra Jurek
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Stockholm, Sweden
| | - Zaneta Andrusivova
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Stockholm, Sweden
| | - Beimeng Yang
- Laboratory of Molecular Gerontology, National Institute on Aging, Baltimore, MD 21224, USA
| | - Yue Wang
- Laboratory of Molecular Gerontology, National Institute on Aging, Baltimore, MD 21224, USA
| | - Benjamin Ogedegbe
- Laboratory of Molecular Gerontology, National Institute on Aging, Baltimore, MD 21224, USA
| | - Tahira Riaz
- Unit for Genome Dynamics, Department of Microbiology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Mari Støen
- Unit for Genome Dynamics, Department of Microbiology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Claus Desler
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Lene Juel Rasmussen
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Tone Tønjum
- Unit for Genome Dynamics, Department of Microbiology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Marie-Christine Galas
- University of Lille, Inserm, CHU Lille, UMR-S 1172 - Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer, 59000 Lille, France
| | - Joakim Lundeberg
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Stockholm, Sweden
| | - Vilhelm A Bohr
- Laboratory of Molecular Gerontology, National Institute on Aging, Baltimore, MD 21224, USA.,Unit for Genome Dynamics, Department of Microbiology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
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A meta-analysis of gene expression data highlights synaptic dysfunction in the hippocampus of brains with Alzheimer's disease. Sci Rep 2020; 10:8384. [PMID: 32433480 PMCID: PMC7239885 DOI: 10.1038/s41598-020-64452-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 04/16/2020] [Indexed: 12/29/2022] Open
Abstract
Since the world population is ageing, dementia is going to be a growing concern. Alzheimer’s disease is the most common form of dementia. The pathogenesis of Alzheimer’s disease is extensively studied, yet unknown remains. Therefore, we aimed to extract new knowledge from existing data. We analysed about 2700 upregulated genes and 2200 downregulated genes from three studies on the CA1 of the hippocampus of brains with Alzheimer’s disease. We found that only the calcium signalling pathway enriched by 48 downregulated genes was consistent between all three studies. We predicted miR-129 to target nine out of 48 genes. Then, we validated miR-129 to regulate six out of nine genes in HEK cells. We noticed that four out of six genes play a role in synaptic plasticity. Finally, we confirmed the upregulation of miR-129 in the hippocampus of brains of rats with scopolamine-induced amnesia as a model of Alzheimer’s disease. We suggest that future research should investigate the possible role of miR-129 in synaptic plasticity and Alzheimer’s disease. This paper presents a novel framework to gain insight into potential biomarkers and targets for diagnosis and treatment of diseases.
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46
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Bagyinszky E, Giau VV, An SA. Transcriptomics in Alzheimer's Disease: Aspects and Challenges. Int J Mol Sci 2020; 21:E3517. [PMID: 32429229 PMCID: PMC7278930 DOI: 10.3390/ijms21103517] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 05/12/2020] [Accepted: 05/14/2020] [Indexed: 02/07/2023] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. Although the heritability of AD is high, the knowledge of the disease-associated genes, their expression, and their disease-related pathways remain limited. Hence, finding the association between gene dysfunctions and pathological mechanisms, such as neuronal transports, APP processing, calcium homeostasis, and impairment in mitochondria, should be crucial. Emerging studies have revealed that changes in gene expression and gene regulation may have a strong impact on neurodegeneration. The mRNA-transcription factor interactions, non-coding RNAs, alternative splicing, or copy number variants could also play a role in disease onset. These facts suggest that understanding the impact of transcriptomes in AD may improve the disease diagnosis and also the therapies. In this review, we highlight recent transcriptome investigations in multifactorial AD, with emphasis on the insights emerging at their interface.
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Affiliation(s)
- Eva Bagyinszky
- Department of Industrial and Environmental Engineering, Graduate School of Environment, Gachon University, Seongnam 13120, Korea;
- Department of Bionano Technology, Gachon University, Seongnam 13120, Korea
| | - Vo Van Giau
- Department of Industrial and Environmental Engineering, Graduate School of Environment, Gachon University, Seongnam 13120, Korea;
- Department of Bionano Technology, Gachon University, Seongnam 13120, Korea
| | - SeongSoo A. An
- Department of Bionano Technology, Gachon University, Seongnam 13120, Korea
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47
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Yan Z, Zhou Z, Wu Q, Chen ZB, Koo EH, Zhong S. Presymptomatic Increase of an Extracellular RNA in Blood Plasma Associates with the Development of Alzheimer’s Disease. Curr Biol 2020; 30:1771-1782.e3. [DOI: 10.1016/j.cub.2020.02.084] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 01/18/2020] [Accepted: 02/26/2020] [Indexed: 12/12/2022]
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Sleegers K. Expression of ABCA7 in Alzheimer's disease. Acta Neuropathol 2020; 139:941-942. [PMID: 32112170 DOI: 10.1007/s00401-020-02136-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 02/18/2020] [Indexed: 11/25/2022]
Affiliation(s)
- Kristel Sleegers
- Neurodegenerative Brain Diseases Group, VIB-Center for Molecular Neurology, University of Antwerp-CDE, Universiteitsplein 1, 2610, Antwerp, Belgium.
- Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
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49
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Golriz Khatami S, Mubeen S, Hofmann-Apitius M. Data science in neurodegenerative disease: its capabilities, limitations, and perspectives. Curr Opin Neurol 2020; 33:249-254. [PMID: 32073441 PMCID: PMC7077964 DOI: 10.1097/wco.0000000000000795] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE OF REVIEW With the advancement of computational approaches and abundance of biomedical data, a broad range of neurodegenerative disease models have been developed. In this review, we argue that computational models can be both relevant and useful in neurodegenerative disease research and although the current established models have limitations in clinical practice, artificial intelligence has the potential to overcome deficiencies encountered by these models, which in turn can improve our understanding of disease. RECENT FINDINGS In recent years, diverse computational approaches have been used to shed light on different aspects of neurodegenerative disease models. For example, linear and nonlinear mixed models, self-modeling regression, differential equation models, and event-based models have been applied to provide a better understanding of disease progression patterns and biomarker trajectories. Additionally, the Cox-regression technique, Bayesian network models, and deep-learning-based approaches have been used to predict the probability of future incidence of disease, whereas nonnegative matrix factorization, nonhierarchical cluster analysis, hierarchical agglomerative clustering, and deep-learning-based approaches have been employed to stratify patients based on their disease subtypes. Furthermore, the interpretation of neurodegenerative disease data is possible through knowledge-based models which use prior knowledge to complement data-driven analyses. These knowledge-based models can include pathway-centric approaches to establish pathways perturbed in a given condition, as well as disease-specific knowledge maps, which elucidate the mechanisms involved in a given disease. Collectively, these established models have revealed high granular details and insights into neurodegenerative disease models. SUMMARY In conjunction with increasingly advanced computational approaches, a wide spectrum of neurodegenerative disease models, which can be broadly categorized into data-driven and knowledge-driven, have been developed. We review the state of the art data and knowledge-driven models and discuss the necessary steps which are vital to bring them into clinical application.
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Affiliation(s)
- Sepehr Golriz Khatami
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Sarah Mubeen
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin
| | - Martin Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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50
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Toro-Domínguez D, Villatoro-García JA, Martorell-Marugán J, Román-Montoya Y, Alarcón-Riquelme ME, Carmona-Sáez P. A survey of gene expression meta-analysis: methods and applications. Brief Bioinform 2020; 22:1694-1705. [PMID: 32095826 DOI: 10.1093/bib/bbaa019] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 01/09/2020] [Accepted: 02/04/2020] [Indexed: 02/07/2023] Open
Abstract
The increasing use of high-throughput gene expression quantification technologies over the last two decades and the fact that most of the published studies are stored in public databases has triggered an explosion of studies available through public repositories. All this information offers an invaluable resource for reuse to generate new knowledge and scientific findings. In this context, great interest has been focused on meta-analysis methods to integrate and jointly analyze different gene expression datasets. In this work, we describe the main steps in the gene expression meta-analysis, from data preparation to the state-of-the art statistical methods. We also analyze the main types of applications and problems that can be approached in gene expression meta-analysis studies and provide a comparative overview of the available software and bioinformatics tools. Moreover, a practical guide for choosing the most appropriate method in each case is also provided.
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Affiliation(s)
- Daniel Toro-Domínguez
- GENYO (Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración, 114, 18016 Granada, Spain
| | - Juan Antonio Villatoro-García
- GENYO (Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración, 114, 18016 Granada, Spain
| | - Jordi Martorell-Marugán
- GENYO (Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración, 114, 18016 Granada, Spain
| | - Yolanda Román-Montoya
- Department of Statistics and Operations Research, University of Granada, Granada, Spain
| | - Marta E Alarcón-Riquelme
- GENYO (Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración, 114, 18016 Granada, Spain.,Unit of Inflammatory Diseases, Department of Environmental Medicine, Karolinska Institute, 171 67, Solna, Sweden
| | - Pedro Carmona-Sáez
- GENYO (Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración, 114, 18016 Granada, Spain
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