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Mondal S, Becskei A. Gene choice in cancer cells is exclusive in ion transport but concurrent in DNA replication. Comput Struct Biotechnol J 2024; 23:2534-2547. [PMID: 38974885 PMCID: PMC11226983 DOI: 10.1016/j.csbj.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/04/2024] [Accepted: 06/04/2024] [Indexed: 07/09/2024] Open
Abstract
Cancers share common cellular and physiological features. Little is known about whether distinctive gene expression patterns can be displayed at the single-cell level by gene families in cancer cells. The expression of gene homologs within a family can exhibit concurrence and exclusivity. Concurrence can promote all-or-none expression patterns of related genes and underlie alternative physiological states. Conversely, exclusive gene families express the same or similar number of homologs in each cell, allowing a broad repertoire of cell identities to be generated. We show that gene families involved in the cell-cycle and antigen presentation are expressed concurrently. Concurrence in the DNA replication complex MCM reflects the replicative status of cells, including cell lines and cancer-derived organoids. Exclusive expression requires precise regulatory mechanism, but cancer cells retain this form of control for ion homeostasis and extend it to gene families involved in cell migration. Thus, the cell adhesion-based identity of healthy cells is transformed to an identity based on migration in the population of cancer cells, reminiscent of epithelial-mesenchymal transition.
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Affiliation(s)
- Samuel Mondal
- Biozentrum, University of Basel, Spitalstrasse 41, Basel 4056, Switzerland
| | - Attila Becskei
- Biozentrum, University of Basel, Spitalstrasse 41, Basel 4056, Switzerland
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2
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Bu X, Gong P, Zhang L, Song W, Hou J, Li Q, Wang W, Xia Z. Pharmacological inhibition of cGAS ameliorates postoperative cognitive dysfunction by suppressing caspase-3/GSDME-dependent pyroptosis. Neurochem Int 2024; 178:105788. [PMID: 38843953 DOI: 10.1016/j.neuint.2024.105788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/15/2024] [Accepted: 06/04/2024] [Indexed: 06/10/2024]
Abstract
Neuroinflammation is a major driver of postoperative cognitive dysfunction (POCD). The cyclic GMP-AMP synthase-stimulator of interferon gene (cGAS-STING) signaling is a prominent alarming device for aberrant double-stranded DNA (dsDNA) that has emerged as a key mediator of neuroinflammation in cognitive-related diseases. However, the role of the cGAS-STING pathway in the pathogenesis of POCD remains unclear. A POCD model was developed in male C57BL/6J mice by laparotomy under isoflurane (Iso) anesthesia. The cGAS inhibitor RU.521 and caspase-3 agonist Raptinal were delivered by intraperitoneal administration. BV2 cells were exposed to Iso and lipopolysaccharide (LPS) in the absence or presence of RU.521, and then cocultured with HT22 cells in the absence or presence of Raptinal. Cognitive function was assessed using the Morris water maze test and novel object recognition test. Immunofluorescence assays were used to observe the colocalization of dsDNA and cGAS. The downstream proteins and pro-inflammatory cytokines were detected using the Western blot and enzyme-linked immunosorbent assay (ELISA). Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was used to assess the degree of cell death in the hippocampus following anesthesia/surgery treatment. Isoflurane/laparotomy and Iso + LPS significantly augmented the levels of cGAS in the hippocampus and BV2 cells, accompanied by mislocalized dsDNA accumulation in the cytoplasm. RU.521 alleviated cognitive impairment, diminished the levels of 2'3'-cGAMP, cGAS, STING, phosphorylated NF-κB p65 and NF-κB-pertinent pro-inflammatory cytokines (TNFα and IL-6), and repressed pyroptosis-associated elements containing cleaved caspase-3, N-GSDME, IL-1β and IL-18. These phenotypes could be rescued by Raptinal in vivo and in vitro. These findings suggest that pharmacological inhibition of cGAS mitigates neuroinflammatory burden of POCD by dampening caspase-3/GSDME-dependent pyroptosis, providing a potential therapeutic strategy for POCD.
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Affiliation(s)
- Xueshan Bu
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Ping Gong
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China; State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, Department of Anesthesiology, School & Hospital of Stomatology, Wuhan University, Wuhan, 430079, China
| | - Lei Zhang
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Wenqin Song
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Jiabao Hou
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Qingwen Li
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Wei Wang
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.
| | - Zhongyuan Xia
- Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.
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Rastogi M, Bartolucci M, Nanni M, Aloisio M, Vozzi D, Petretto A, Contestabile A, Cancedda L. Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains. Neuron 2024; 112:2503-2523.e10. [PMID: 38810652 DOI: 10.1016/j.neuron.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/17/2024] [Accepted: 05/01/2024] [Indexed: 05/31/2024]
Abstract
Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.
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Affiliation(s)
- Mohit Rastogi
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy
| | - Martina Bartolucci
- Core Facilities - Clinical Proteomics and Metabolomics, IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
| | - Marina Nanni
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy
| | | | - Diego Vozzi
- Central RNA Laboratory, Istituto Italiano di Tecnologia, Genova 16152, Italy
| | - Andrea Petretto
- Core Facilities - Clinical Proteomics and Metabolomics, IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
| | - Andrea Contestabile
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy.
| | - Laura Cancedda
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy; Dulbecco Telethon Institute, Rome 00185, Italy.
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Hozumi Y, Wei GW. Analyzing Single Cell RNA Sequencing with Topological Nonnegative Matrix Factorization. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2024; 445:115842. [PMID: 38464901 PMCID: PMC10919214 DOI: 10.1016/j.cam.2024.115842] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a relatively new technology that has stimulated enormous interest in statistics, data science, and computational biology due to the high dimensionality, complexity, and large scale associated with scRNA-seq data. Nonnegative matrix factorization (NMF) offers a unique approach due to its meta-gene interpretation of resulting low-dimensional components. However, NMF approaches suffer from the lack of multiscale analysis. This work introduces two persistent Laplacian regularized NMF methods, namely, topological NMF (TNMF) and robust topological NMF (rTNMF). By employing a total of 12 datasets, we demonstrate that the proposed TNMF and rTNMF significantly outperform all other NMF-based methods. We have also utilized TNMF and rTNMF for the visualization of popular Uniform Manifold Approximation and Projection (UMAP) and t -distributed stochastic neighbor embedding (t -SNE).
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Affiliation(s)
- Yuta Hozumi
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
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5
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Martus D, Williams SK, Pichi K, Mannebach-Götz S, Kaiser N, Wardas B, Fecher-Trost C, Meyer MR, Schmitz F, Beck A, Fairless R, Diem R, Flockerzi V, Belkacemi A. Cavβ3 Contributes to the Maintenance of the Blood-Brain Barrier and Alleviates Symptoms of Experimental Autoimmune Encephalomyelitis. Arterioscler Thromb Vasc Biol 2024; 44:1833-1851. [PMID: 38957986 DOI: 10.1161/atvbaha.124.321141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 06/21/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND Tight control of cytoplasmic Ca2+ concentration in endothelial cells is essential for the regulation of endothelial barrier function. Here, we investigated the role of Cavβ3, a subunit of voltage-gated Ca2+ (Cav) channels, in modulating Ca2+ signaling in brain microvascular endothelial cells (BMECs) and how this contributes to the integrity of the blood-brain barrier. METHODS We investigated the function of Cavβ3 in BMECs by Ca2+ imaging and Western blot, examined the endothelial barrier function in vitro and the integrity of the blood-brain barrier in vivo, and evaluated disease course after induction of experimental autoimmune encephalomyelitis in mice using Cavβ3-/- (Cavβ3-deficient) mice as controls. RESULTS We identified Cavβ3 protein in BMECs, but electrophysiological recordings did not reveal significant Cav channel activity. In vivo, blood-brain barrier integrity was reduced in the absence of Cavβ3. After induction of experimental autoimmune encephalomyelitis, Cavβ3-/- mice showed earlier disease onset with exacerbated clinical disability and increased T-cell infiltration. In vitro, the transendothelial resistance of Cavβ3-/- BMEC monolayers was lower than that of wild-type BMEC monolayers, and the organization of the junctional protein ZO-1 (zona occludens-1) was impaired. Thrombin stimulates inositol 1,4,5-trisphosphate-dependent Ca2+ release, which facilitates cell contraction and enhances endothelial barrier permeability via Ca2+-dependent phosphorylation of MLC (myosin light chain). These effects were more pronounced in Cavβ3-/- than in wild-type BMECs, whereas the differences were abolished in the presence of the MLCK (MLC kinase) inhibitor ML-7. Expression of Cacnb3 cDNA in Cavβ3-/- BMECs restored the wild-type phenotype. Coimmunoprecipitation and mass spectrometry demonstrated the association of Cavβ3 with inositol 1,4,5-trisphosphate receptor proteins. CONCLUSIONS Independent of its function as a subunit of Cav channels, Cavβ3 interacts with the inositol 1,4,5-trisphosphate receptor and is involved in the tight control of cytoplasmic Ca2+ concentration and Ca2+-dependent MLC phosphorylation in BMECs, and this role of Cavβ3 in BMECs contributes to blood-brain barrier integrity and attenuates the severity of experimental autoimmune encephalomyelitis disease.
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MESH Headings
- Animals
- Female
- Male
- Mice
- Blood-Brain Barrier/metabolism
- Calcium/metabolism
- Calcium Channels/metabolism
- Calcium Channels/genetics
- Calcium Signaling
- Capillary Permeability
- Cells, Cultured
- Encephalomyelitis, Autoimmune, Experimental/metabolism
- Encephalomyelitis, Autoimmune, Experimental/genetics
- Endothelial Cells/metabolism
- Inositol 1,4,5-Trisphosphate Receptors/metabolism
- Inositol 1,4,5-Trisphosphate Receptors/genetics
- Mice, Inbred C57BL
- Mice, Knockout
- Myosin Light Chains/metabolism
- Myosin-Light-Chain Kinase/metabolism
- Myosin-Light-Chain Kinase/genetics
- Phosphorylation
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Affiliation(s)
- Damian Martus
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Sarah K Williams
- Neurologische Klinik, Universitätsklinikum Heidelberg, Germany (S.K.W., K.P., R.F., R.D.)
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany (R.F., S.K.W.)
| | - Kira Pichi
- Neurologische Klinik, Universitätsklinikum Heidelberg, Germany (S.K.W., K.P., R.F., R.D.)
| | - Stefanie Mannebach-Götz
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Nicolas Kaiser
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Barbara Wardas
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Claudia Fecher-Trost
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Markus R Meyer
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Frank Schmitz
- Institut für Anatomie und Zellbiologie (F.S.), Universität des Saarlandes, Homburg, Germany
| | - Andreas Beck
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Richard Fairless
- Neurologische Klinik, Universitätsklinikum Heidelberg, Germany (S.K.W., K.P., R.F., R.D.)
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany (R.F., S.K.W.)
| | - Ricarda Diem
- Neurologische Klinik, Universitätsklinikum Heidelberg, Germany (S.K.W., K.P., R.F., R.D.)
| | - Veit Flockerzi
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
| | - Anouar Belkacemi
- Experimentelle und Klinische Pharmakologie und Toxikologie, Präklinisches Zentrum für Molekulare Signalverarbeitung, PharmaScienceHub (D.M., S.M.-G., N.K., B.W., C.F.-T., M.R.M., A. Beck, V.F., A. Belkacemi), Universität des Saarlandes, Homburg, Germany
- Now with Pharmakologisches Institut, Ruprecht-Karls-Universität Heidelberg, Germany (A. Belkacemi)
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Bhatt RR, Gadewar SP, Shetty A, Ba Gari I, Haddad E, Javid S, Ramesh A, Nourollahimoghadam E, Zhu AH, de Leeuw C, Thompson PM, Medland SE, Jahanshad N. The Genetic Architecture of the Human Corpus Callosum and its Subregions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.22.603147. [PMID: 39091796 PMCID: PMC11291056 DOI: 10.1101/2024.07.22.603147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.
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7
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Craig GE, Ramos L, Essig SR, Eagles NJ, Jaffe AE, Martinowich K, Hallock HL. Stimulation of locus coeruleus inputs to the frontal cortex in mice induces cell type-specific expression of the Apoe gene. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.22.604695. [PMID: 39091890 PMCID: PMC11291023 DOI: 10.1101/2024.07.22.604695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Deficits in attention are common across a range of neuropsychiatric disorders. A multitude of brain regions, including the frontal cortex (FC) and locus coeruleus (LC), have been implicated in attention. Regulators of these brain regions at the molecular level are not well understood, but might elucidate underlying mechanisms of disorders with attentional deficits. To probe this, we used chemogenetic stimulation of neurons in the LC with axonal projections to the FC, and subsequent bulk RNA-sequencing from the mouse FC. We found that stimulation of this circuit caused an increase in transcription of the Apoe gene. To investigate cell type-specific expression of Apoe in the FC, we used a dual-virus approach to express either the excitatory DREADD receptor hM3Dq in LC neurons with projections to the FC, or a control virus, and found that increases in Apoe expression in the FC following depolarization of LC inputs is enriched in GABAergic neurons in a sex-dependent manner. The results of these experiments yield insights into how Apoe expression affects function in cortical microcircuits that are important for attention-guided behavior, and point to interneuron-specific expression of Apoe as a potential target for the amelioration of attention symptoms in disorders such as attention-deficit hyperactivity disorder (ADHD), schizophrenia, and Alzheimer's disease (AD).
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Affiliation(s)
| | - Lizbeth Ramos
- Neuroscience Program, Lafayette College, Easton, PA, 18042, USA
| | - Samuel R. Essig
- Neuroscience Program, Lafayette College, Easton, PA, 18042, USA
| | - Nicholas J. Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Andrew E. Jaffe
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- The Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA
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8
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Zhao Y, Kohl C, Rosebrock D, Hu Q, Hu Y, Vingron M. CAbiNet: joint clustering and visualization of cells and genes for single-cell transcriptomics. Nucleic Acids Res 2024; 52:e57. [PMID: 38850160 PMCID: PMC11260446 DOI: 10.1093/nar/gkae480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 04/10/2024] [Accepted: 05/27/2024] [Indexed: 06/10/2024] Open
Abstract
A fundamental analysis task for single-cell transcriptomics data is clustering with subsequent visualization of cell clusters. The genes responsible for the clustering are only inferred in a subsequent step. Clustering cells and genes together would be the remit of biclustering algorithms, which are often bogged down by the size of single-cell data. Here we present 'Correspondence Analysis based Biclustering on Networks' (CAbiNet) for joint clustering and visualization of single-cell RNA-sequencing data. CAbiNet performs efficient co-clustering of cells and their respective marker genes and jointly visualizes the biclusters in a non-linear embedding for easy and interactive visual exploration of the data.
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Affiliation(s)
- Yan Zhao
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 63-73, 14195 Berlin, Germany
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, Guangdong, P.R. China
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055 Guangdong, P.R. China
| | - Clemens Kohl
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 63-73, 14195 Berlin, Germany
| | - Daniel Rosebrock
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 63-73, 14195 Berlin, Germany
| | - Qinan Hu
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, Guangdong, P.R. China
- Joint Laboratory of Guangdong-Hong Kong Universities for Vascular Homeostasis and Diseases, School of Medicine, Southern University of Science and Technology,1088 Xueyuan Avenue, Shenzhen 518055 Guangdong, P.R. China
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055 Guangdong, P.R. China
| | - Yuhui Hu
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, Guangdong, P.R. China
- Joint Laboratory of Guangdong-Hong Kong Universities for Vascular Homeostasis and Diseases, School of Medicine, Southern University of Science and Technology,1088 Xueyuan Avenue, Shenzhen 518055 Guangdong, P.R. China
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055 Guangdong, P.R. China
| | - Martin Vingron
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 63-73, 14195 Berlin, Germany
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9
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Cote AC, Young HE, Huckins LM. Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex. HGG ADVANCES 2024; 5:100311. [PMID: 38773772 PMCID: PMC11214266 DOI: 10.1016/j.xhgg.2024.100311] [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: 10/23/2023] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 05/24/2024] Open
Abstract
Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants. Here we broadly define a "module-QTL" as the association of a genetic variant with a summary measure of gene co-expression. This approach aims to reduce the multiple testing burden of a trans-eQTL search through the consolidation of gene-based testing and provide biological context to eQTLs shared between genes. In this article we provide an in-depth examination of the co-expression module eQTL (module-QTL) through literature review, theoretical investigation, and real-data application of the module-QTL to three large prefrontal cortex genotype-RNA sequencing datasets. We find module-QTLs in our study that are disease associated and reproducible are not additionally informative beyond cis- or trans-eQTLs for module genes. Through comparison to prior studies, we highlight promises and limitations of the module-QTL across study designs and provide recommendations for further investigation of the module-QTL framework.
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Affiliation(s)
- Alanna C Cote
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hannah E Young
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Laura M Huckins
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA.
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10
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Ge YJ, Chen SD, Wu BS, Zhang YR, Wang J, He XY, Liu WS, Chen YL, Ou YN, Shen XN, Huang YY, Gan YH, Yang L, Ma LZ, Ma YH, Chen KL, Chen SF, Cui M, Tan L, Dong Q, Zhao QH, Wang YJ, Jia JP, Yu JT. Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease. Alzheimers Dement 2024. [PMID: 39023044 DOI: 10.1002/alz.14121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 07/20/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry. METHODS We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals. RESULTS In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD. DISCUSSION The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology. HIGHLIGHTS Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.
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Affiliation(s)
- Yi-Jun Ge
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Jun Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Xiao-Yu He
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yi-Lin Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yu-Yuan Huang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yi-Han Gan
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ke-Liang Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Shu-Fen Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Mei Cui
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Qian-Hua Zhao
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yan-Jiang Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Jian-Ping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, National Center for Neurological Disorders, Fudan University, Shanghai, China
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11
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Liharska L, Charney A. Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain. Curr Top Behav Neurosci 2024. [PMID: 38972894 DOI: 10.1007/7854_2024_466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.
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Affiliation(s)
- Lora Liharska
- Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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12
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Mohr AE, Ortega-Santos CP, Whisner CM, Klein-Seetharaman J, Jasbi P. Navigating Challenges and Opportunities in Multi-Omics Integration for Personalized Healthcare. Biomedicines 2024; 12:1496. [PMID: 39062068 PMCID: PMC11274472 DOI: 10.3390/biomedicines12071496] [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: 04/15/2024] [Revised: 06/25/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
The field of multi-omics has witnessed unprecedented growth, converging multiple scientific disciplines and technological advances. This surge is evidenced by a more than doubling in multi-omics scientific publications within just two years (2022-2023) since its first referenced mention in 2002, as indexed by the National Library of Medicine. This emerging field has demonstrated its capability to provide comprehensive insights into complex biological systems, representing a transformative force in health diagnostics and therapeutic strategies. However, several challenges are evident when merging varied omics data sets and methodologies, interpreting vast data dimensions, streamlining longitudinal sampling and analysis, and addressing the ethical implications of managing sensitive health information. This review evaluates these challenges while spotlighting pivotal milestones: the development of targeted sampling methods, the use of artificial intelligence in formulating health indices, the integration of sophisticated n-of-1 statistical models such as digital twins, and the incorporation of blockchain technology for heightened data security. For multi-omics to truly revolutionize healthcare, it demands rigorous validation, tangible real-world applications, and smooth integration into existing healthcare infrastructures. It is imperative to address ethical dilemmas, paving the way for the realization of a future steered by omics-informed personalized medicine.
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Affiliation(s)
- Alex E. Mohr
- Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ 85004, USA; (A.E.M.); (C.P.O.-S.); (C.M.W.); (J.K.-S.)
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA
- Biodesign Institute Center for Health Through Microbiomes, Arizona State University, Tempe, AZ 85281, USA
| | - Carmen P. Ortega-Santos
- Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ 85004, USA; (A.E.M.); (C.P.O.-S.); (C.M.W.); (J.K.-S.)
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC 20052, USA
| | - Corrie M. Whisner
- Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ 85004, USA; (A.E.M.); (C.P.O.-S.); (C.M.W.); (J.K.-S.)
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA
- Biodesign Institute Center for Health Through Microbiomes, Arizona State University, Tempe, AZ 85281, USA
| | - Judith Klein-Seetharaman
- Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ 85004, USA; (A.E.M.); (C.P.O.-S.); (C.M.W.); (J.K.-S.)
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA
- School of Molecular Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Paniz Jasbi
- Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ 85004, USA; (A.E.M.); (C.P.O.-S.); (C.M.W.); (J.K.-S.)
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13
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Pu Y, Yang J, Pan Q, Li C, Wang L, Xie X, Chen X, Xiao F, Chen G. MGST3 regulates BACE1 protein translation and amyloidogenesis by controlling the RGS4-mediated AKT signaling pathway. J Biol Chem 2024; 300:107530. [PMID: 38971310 DOI: 10.1016/j.jbc.2024.107530] [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: 03/05/2024] [Revised: 06/03/2024] [Accepted: 06/16/2024] [Indexed: 07/08/2024] Open
Abstract
Microsomal glutathione transferase 3 (MGST3) regulates eicosanoid and glutathione metabolism. These processes are associated with oxidative stress and apoptosis, suggesting that MGST3 might play a role in the pathophysiology of Alzheimer's disease. Here, we report that knockdown (KD) of MGST3 in cell lines reduced the protein level of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) and the resulting amyloidogenesis. Interestingly, MGST3 KD did not alter intracellular reactive oxygen species level but selectively reduced the expression of apoptosis indicators which could be associated with the receptor of cysteinyl leukotrienes, the downstream metabolites of MGST3 in arachidonic acid pathway. We then showed that the effect of MGST3 on BACE1 was independent of cysteinyl leukotrienes but involved a translational mechanism. Further RNA-seq analysis identified that regulator of G-protein signaling 4 (RGS4) was a target gene of MGST3. Silencing of RGS4 inhibited BACE1 translation and prevented MGST3 KD-mediated reduction of BACE1. The potential mechanism was related to AKT activity, as the protein level of phosphorylated AKT was significantly reduced by silencing of MGST3 and RGS4, and the AKT inhibitor abolished the effect of MGST3/RGS4 on phosphorylated AKT and BACE1. Together, MGST3 regulated amyloidogenesis by controlling BACE1 protein expression, which was mediated by RGS4 and downstream AKT signaling pathway.
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Affiliation(s)
- Yalan Pu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China; Department of Neurology, Langzhong People's Hospital, Nanchong, Sichuan, China
| | - Jie Yang
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China; Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan, China
| | - Qiuling Pan
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China
| | - Chenlu Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China
| | - Lu Wang
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China
| | - Xiaoyong Xie
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China
| | - Xue Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China
| | - Fei Xiao
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China.
| | - Guojun Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing, China.
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14
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Badhwar A, Hirschberg Y, Valle‐Tamayo N, Iulita MF, Udeh‐Momoh CT, Matton A, Tarawneh RM, Rissman RA, Ledreux A, Winston CN, Haqqani AS. Assessment of brain-derived extracellular vesicle enrichment for blood biomarker analysis in age-related neurodegenerative diseases: An international overview. Alzheimers Dement 2024; 20:4411-4422. [PMID: 38864416 PMCID: PMC11247682 DOI: 10.1002/alz.13823] [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: 08/17/2023] [Revised: 02/09/2024] [Accepted: 02/17/2024] [Indexed: 06/13/2024]
Abstract
INTRODUCTION Brain-derived extracellular vesicles (BEVs) in blood allows for minimally-invasive investigations of central nervous system (CNS) -specific markers of age-related neurodegenerative diseases (NDDs). Polymer-based EV- and immunoprecipitation (IP)-based BEV-enrichment protocols from blood have gained popularity. We systematically investigated protocol consistency across studies, and determined CNS-specificity of proteins associated with these protocols. METHODS NDD articles investigating BEVs in blood using polymer-based and/or IP-based BEV enrichment protocols were systematically identified, and protocols compared. Proteins used for BEV-enrichment and/or post-enrichment were assessed for CNS- and brain-cell-type-specificity, extracellular domains (ECD+), and presence in EV-databases. RESULTS A total of 82.1% of studies used polymer-based (ExoQuick) EV-enrichment, and 92.3% used L1CAM for IP-based BEV-enrichment. Centrifugation times differed across studies. A total of 26.8% of 82 proteins systematically identified were CNS-specific: 50% ECD+, 77.3% were listed in EV-databases. CONCLUSIONS We identified protocol steps requiring standardization, and recommend additional CNS-specific proteins that can be used for BEV-enrichment or as BEV-biomarkers. HIGHLIGHTS Across NDDs, we identified protocols commonly used for EV/BEV enrichment from blood. We identified protocol steps showing variability that require harmonization. We assessed CNS-specificity of proteins used for BEV-enrichment or found in BEV cargo. CNS-specific EV proteins with ECD+ or without were identified. We recommend evaluation of blood-BEV enrichment using these additional ECD+ proteins.
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Affiliation(s)
- AmanPreet Badhwar
- Département de pharmacologie et physiologieInstitut de Génie BiomédicalFaculté de Médecine, Université de MontréalMontréalQuebecCanada
- Multiomics Investigation of Neurodegenerative Diseases (MIND) lab, Centre de recherche de l'Institut Universitaire de GériatrieMontréalQuebecCanada
| | - Yael Hirschberg
- Centre for ProteomicsUniversity of AntwerpAntwerpBelgium
- Health Unit, Flemish Institute for Technological Research (VITO)MolBelgium
| | - Natalia Valle‐Tamayo
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant PauCalle San QuintíBarcelonaSpain
| | - M. Florencia Iulita
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant PauCalle San QuintíBarcelonaSpain
| | - Chinedu T. Udeh‐Momoh
- Ageing Epidemiology research unit, School of Public Health, Imperial College LondonLondonUK
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and Society, Center for Alzheimer Research, Karolinska InstitutetSolnaSweden
- Global Brain Health InstituteUniversity of San Francisco Joan and Sanford I. Weill Neurosciences buildingSan FranciscoCaliforniaUSA
- Imarisha Centre for Brain Health and AgingBrain and Mind InstituteAga Khan UniversityNairobiKenya
| | - Anna Matton
- Ageing Epidemiology research unit, School of Public Health, Imperial College LondonLondonUK
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and Society, Center for Alzheimer Research, Karolinska InstitutetSolnaSweden
- Division of NeurogeriatricsDepartment of Neurobiology, Care Sciences and SocietyCenter for Alzheimer Research, Karolinska Institutet, SolnaNobels vägSweden
| | - Rawan M. Tarawneh
- Department of NeurologyCenter for Memory and AgingUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Robert A. Rissman
- VA San Diego Healthcare SystemSan DiegoCaliforniaUSA
- Department of Physiology and NeuroscienceAlzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Aurélie Ledreux
- Department of NeurosurgerySchool of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Charisse N. Winston
- Department of Physiology and NeuroscienceAlzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
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15
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Feng G, Wang Y, Huang W, Chen H, Cheng J, Shu N. Spatial and temporal pattern of structure-function coupling of human brain connectome with development. eLife 2024; 13:RP93325. [PMID: 38900563 PMCID: PMC11189631 DOI: 10.7554/elife.93325] [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] [Indexed: 06/21/2024] Open
Abstract
Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7-21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.
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Affiliation(s)
- Guozheng Feng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Yiwen Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Haojie Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Jian Cheng
- School of Computer Science and Engineering, Beihang UniversityBeijingChina
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
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16
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Tisoncik-Go J, Stokes C, Whitmore LS, Newhouse DJ, Voss K, Gustin A, Sung CJ, Smith E, Stencel-Baerenwald J, Parker E, Snyder JM, Shaw DW, Rajagopal L, Kapur RP, Adams Waldorf KM, Gale M. Disruption of myelin structure and oligodendrocyte maturation in a macaque model of congenital Zika infection. Nat Commun 2024; 15:5173. [PMID: 38890352 PMCID: PMC11189406 DOI: 10.1038/s41467-024-49524-2] [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: 10/17/2023] [Accepted: 06/06/2024] [Indexed: 06/20/2024] Open
Abstract
Zika virus (ZikV) infection during pregnancy can cause congenital Zika syndrome (CZS) and neurodevelopmental delay in infants, of which the pathogenesis remains poorly understood. We utilize an established female pigtail macaque maternal-to-fetal ZikV infection/exposure model to study fetal brain pathophysiology of CZS manifesting from ZikV exposure in utero. We find prenatal ZikV exposure leads to profound disruption of fetal myelin, with extensive downregulation in gene expression for key components of oligodendrocyte maturation and myelin production. Immunohistochemical analyses reveal marked decreases in myelin basic protein intensity and myelinated fiber density in ZikV-exposed animals. At the ultrastructural level, the myelin sheath in ZikV-exposed animals shows multi-focal decompaction, occurring concomitant with dysregulation of oligodendrocyte gene expression and maturation. These findings define fetal neuropathological profiles of ZikV-linked brain injury underlying CZS resulting from ZikV exposure in utero. Because myelin is critical for cortical development, ZikV-related perturbations in oligodendrocyte function may have long-term consequences on childhood neurodevelopment, even in the absence of overt microcephaly.
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Affiliation(s)
- Jennifer Tisoncik-Go
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA.
- Washington National Primate Research Center, University of Washington, Seattle, WA, USA.
| | - Caleb Stokes
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA.
- Department of Pediatrics, University of Washington, Seattle, WA, USA.
| | - Leanne S Whitmore
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Daniel J Newhouse
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Kathleen Voss
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Andrew Gustin
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Cheng-Jung Sung
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Elise Smith
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Jennifer Stencel-Baerenwald
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA
| | - Edward Parker
- Department of Ophthalmology, NEI Core for Vision Research, University of Washington, Seattle, WA, USA
| | - Jessica M Snyder
- Department of Comparative Medicine, University of Washington, Seattle, WA, USA
| | - Dennis W Shaw
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Lakshmi Rajagopal
- Department of Pediatrics, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA
| | - Raj P Kapur
- Department of Pathology, University of Washington, Seattle, WA, USA
- Department of Pathology, Seattle Children's Hospital, Seattle, WA, USA
| | - Kristina M Adams Waldorf
- Department of Global Health, University of Washington, Seattle, WA, USA
- Department of Obstetrics & Gynecology, University of Washington, Seattle, WA, USA
| | - Michael Gale
- Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington, Seattle, WA, USA.
- Washington National Primate Research Center, University of Washington, Seattle, WA, USA.
- Department of Global Health, University of Washington, Seattle, WA, USA.
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17
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Ganglberger F, Kargl D, Töpfer M, Hernandez-Lallement J, Lawless N, Fernandez-Albert F, Haubensak W, Bühler K. BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource. Commun Biol 2024; 7:730. [PMID: 38877144 PMCID: PMC11178817 DOI: 10.1038/s42003-024-06355-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/20/2024] [Indexed: 06/16/2024] Open
Abstract
Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.
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Affiliation(s)
- Florian Ganglberger
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Dominic Kargl
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
| | - Markus Töpfer
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
| | - Julien Hernandez-Lallement
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Nathan Lawless
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Francesc Fernandez-Albert
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Wulf Haubensak
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
| | - Katja Bühler
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria.
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18
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Ma Y, Guo S, Chen Y, Peng Y, Su X, Jiang H, Lin X, Zhang J. Single-nucleus chromatin landscape dataset of mouse brain development and aging. Sci Data 2024; 11:616. [PMID: 38866804 PMCID: PMC11169343 DOI: 10.1038/s41597-024-03382-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/15/2024] [Indexed: 06/14/2024] Open
Abstract
The development and aging of the brain constitute a lifelong dynamic process, marked by structural and functional changes that entail highly coordinated cellular differentiation and epigenetic regulatory mechanisms. Chromatin accessibility serves as the foundational basis for genetic activity. However, the holistic and dynamic chromatin landscape that spans various brain regions throughout development and ageing remains predominantly unexplored. In this study, we employed single-nucleus ATAC-seq to generate comprehensive chromatin accessibility maps, incorporating data from 69,178 cells obtained from four distinct brain regions - namely, the olfactory bulb (OB), cerebellum (CB), prefrontal cortex (PFC), and hippocampus (HP) - across key developmental time points at 7 P, 3 M, 12 M, and 18 M. We delineated the distribution of cell types across different age stages and brain regions, providing insight into chromatin accessible regions and key transcription factors specific to different cell types. Our data contribute to understanding the epigenetic basis of the formation of different brain regions, providing a dynamic landscape and comprehensive resource for revealing gene regulatory programs during brain development and aging.
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Affiliation(s)
- Yuting Ma
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Sicheng Guo
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Yixi Chen
- BGI Research, Shenzhen, 518083, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | | | - Xi Su
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Hui Jiang
- BGI Genomics, Shenzhen, 518083, China
| | - Xiumei Lin
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
- BGI Research, Shenzhen, 518083, China.
| | - Jianguo Zhang
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China.
- BGI Genomics, Shenzhen, 518083, China.
- BGI Research, Shenzhen, 518083, China.
- School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China.
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19
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Hoedjes KM, Grath S, Posnien N, Ritchie MG, Schlötterer C, Abbott JK, Almudi I, Coronado-Zamora M, Durmaz Mitchell E, Flatt T, Fricke C, Glaser-Schmitt A, González J, Holman L, Kankare M, Lenhart B, Orengo DJ, Snook RR, Yılmaz VM, Yusuf L. From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology. Mol Ecol 2024:e17382. [PMID: 38856653 DOI: 10.1111/mec.17382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/09/2024] [Accepted: 04/29/2024] [Indexed: 06/11/2024]
Abstract
RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.
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Affiliation(s)
- Katja M Hoedjes
- Amsterdam Institute for Life and Environment, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sonja Grath
- Division of Evolutionary Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Nico Posnien
- Department of Developmental Biology, Göttingen Center for Molecular Biosciences (GZMB), University of Göttingen, Göttingen, Germany
| | - Michael G Ritchie
- Centre for Biological Diversity, University of St Andrews, St Andrews, UK
| | | | | | - Isabel Almudi
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | | | - Esra Durmaz Mitchell
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Functional Genomics and Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Thomas Flatt
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Claudia Fricke
- Institute for Zoology/Animal Ecology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Josefa González
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain
| | - Luke Holman
- School of Applied Sciences, Edinburgh Napier University, Edinburgh, UK
| | - Maaria Kankare
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland
| | - Benedict Lenhart
- Department of Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Dorcas J Orengo
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | - Rhonda R Snook
- Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Vera M Yılmaz
- Division of Evolutionary Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Leeban Yusuf
- Centre for Biological Diversity, University of St Andrews, St Andrews, UK
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20
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Almeida MC, Eger SJ, He C, Audouard M, Nikitina A, Glasauer SMK, Han D, Mejía-Cupajita B, Acosta-Uribe J, Villalba-Moreno ND, Littau JL, Elcheikhali M, Rivera EK, Carrettiero DC, Villegas-Lanau CA, Sepulveda-Falla D, Lopera F, Kosik KS. Single-nucleus RNA sequencing demonstrates an autosomal dominant Alzheimer's disease profile and possible mechanisms of disease protection. Neuron 2024; 112:1778-1794.e7. [PMID: 38417436 PMCID: PMC11156559 DOI: 10.1016/j.neuron.2024.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 01/07/2024] [Accepted: 02/09/2024] [Indexed: 03/01/2024]
Abstract
Highly penetrant autosomal dominant Alzheimer's disease (ADAD) comprises a distinct disease entity as compared to the far more prevalent form of AD in which common variants collectively contribute to risk. The downstream pathways that distinguish these AD forms in specific cell types have not been deeply explored. We compared single-nucleus transcriptomes among a set of 27 cases divided among PSEN1-E280A ADAD carriers, sporadic AD, and controls. Autophagy genes and chaperones clearly defined the PSEN1-E280A cases compared to sporadic AD. Spatial transcriptomics validated the activation of chaperone-mediated autophagy genes in PSEN1-E280A. The PSEN1-E280A case in which much of the brain was spared neurofibrillary pathology and harbored a homozygous APOE3-Christchurch variant revealed possible explanations for protection from AD pathology including overexpression of LRP1 in astrocytes, increased expression of FKBP1B, and decreased PSEN1 expression in neurons. The unique cellular responses in ADAD and sporadic AD require consideration when designing clinical trials.
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Affiliation(s)
- Maria Camila Almeida
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Center for Natural and Humans Sciences, Federal University of ABC, Sao Bernardo do Campo, SP 09608020, Brazil
| | - Sarah J Eger
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Caroline He
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Morgane Audouard
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Arina Nikitina
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Stella M K Glasauer
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Dasol Han
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Barbara Mejía-Cupajita
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Grupo de Neurociencias de Antioquia, School of Medicine, Universidad de Antioquia, Medellín 050010, Colombia
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Grupo de Neurociencias de Antioquia, School of Medicine, Universidad de Antioquia, Medellín 050010, Colombia
| | - Nelson David Villalba-Moreno
- Molecular Neuropathology of Alzheimer's Disease, Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Jessica Lisa Littau
- Molecular Neuropathology of Alzheimer's Disease, Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Megan Elcheikhali
- Department of Statistics and Applied Probability, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Erica Keane Rivera
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Daniel Carneiro Carrettiero
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Center for Natural and Humans Sciences, Federal University of ABC, Sao Bernardo do Campo, SP 09608020, Brazil
| | | | - Diego Sepulveda-Falla
- Molecular Neuropathology of Alzheimer's Disease, Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, School of Medicine, Universidad de Antioquia, Medellín 050010, Colombia.
| | - Kenneth S Kosik
- Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA.
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21
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Wojtas AM, Dammer EB, Guo Q, Ping L, Shantaraman A, Duong DM, Yin L, Fox EJ, Seifar F, Lee EB, Johnson ECB, Lah JJ, Levey AI, Levites Y, Rangaraju S, Golde TE, Seyfried NT. Proteomic changes in the human cerebrovasculature in Alzheimer's disease and related tauopathies linked to peripheral biomarkers in plasma and cerebrospinal fluid. Alzheimers Dement 2024; 20:4043-4065. [PMID: 38713744 PMCID: PMC11180878 DOI: 10.1002/alz.13821] [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: 01/25/2024] [Revised: 02/21/2024] [Accepted: 03/02/2024] [Indexed: 05/09/2024]
Abstract
INTRODUCTION Cerebrovascular dysfunction is a pathological hallmark of Alzheimer's disease (AD). Nevertheless, detecting cerebrovascular changes within bulk tissues has limited our ability to characterize proteomic alterations from less abundant cell types. METHODS We conducted quantitative proteomics on bulk brain tissues and isolated cerebrovasculature from the same individuals, encompassing control (N = 28), progressive supranuclear palsy (PSP) (N = 18), and AD (N = 21) cases. RESULTS Protein co-expression network analysis identified unique cerebrovascular modules significantly correlated with amyloid plaques, cerebrovascular amyloid angiopathy (CAA), and/or tau pathology. The protein products within AD genetic risk loci were concentrated within cerebrovascular modules. The overlap between differentially abundant proteins in AD cerebrospinal fluid (CSF) and plasma with cerebrovascular network highlighted a significant increase of matrisome proteins, SMOC1 and SMOC2, in CSF, plasma, and brain. DISCUSSION These findings enhance our understanding of cerebrovascular deficits in AD, shedding light on potential biomarkers associated with CAA and vascular dysfunction in neurodegenerative diseases.
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Affiliation(s)
- Aleksandra M. Wojtas
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Eric B. Dammer
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Qi Guo
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Lingyan Ping
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Ananth Shantaraman
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Duc M. Duong
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Luming Yin
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Edward J. Fox
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Fatemeh Seifar
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Edward B. Lee
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPennsylvaniaUSA
| | - Erik C. B. Johnson
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - James J. Lah
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Allan I. Levey
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Yona Levites
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of Pharmacology and Chemical BiologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Srikant Rangaraju
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Todd E. Golde
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
- Department of Pharmacology and Chemical BiologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Nicholas T. Seyfried
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
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22
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Cai X, Zhang W, Zheng X, Xu Y, Li Y. scEM: A New Ensemble Framework for Predicting Cell Type Composition Based on scRNA-Seq Data. Interdiscip Sci 2024; 16:304-317. [PMID: 38368575 DOI: 10.1007/s12539-023-00601-y] [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: 06/12/2023] [Revised: 12/22/2023] [Accepted: 12/24/2023] [Indexed: 02/19/2024]
Abstract
With the advent of single-cell RNA sequencing (scRNA-seq) technology, many scRNA-seq data have become available, providing an unprecedented opportunity to explore cellular composition and heterogeneity. Recently, many computational algorithms for predicting cell type composition have been developed, and these methods are typically evaluated on different datasets and performance metrics using diverse techniques. Consequently, the lack of comprehensive and standardized comparative analysis makes it difficult to gain a clear understanding of the strengths and weaknesses of these methods. To address this gap, we reviewed 20 cutting-edge unsupervised cell type identification methods and evaluated these methods comprehensively using 24 real scRNA-seq datasets of varying scales. In addition, we proposed a new ensemble cell-type identification method, named scEM, which learns the consensus similarity matrix by applying the entropy weight method to the four representative methods are selected. The Louvain algorithm is adopted to obtain the final classification of individual cells based on the consensus matrix. Extensive evaluation and comparison with 11 other similarity-based methods under real scRNA-seq datasets demonstrate that the newly developed ensemble algorithm scEM is effective in predicting cellular type composition.
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Affiliation(s)
- Xianxian Cai
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| | - Wei Zhang
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China.
| | - Xiaoying Zheng
- Operations research and planning department, Naval University of Engineering, Wuhan, 430033, China
| | - Yaxin Xu
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| | - Yuanyuan Li
- School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China
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23
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Lee AT, Chang EF, Paredes MF, Nowakowski TJ. Large-scale neurophysiology and single-cell profiling in human neuroscience. Nature 2024; 630:587-595. [PMID: 38898291 DOI: 10.1038/s41586-024-07405-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 04/09/2024] [Indexed: 06/21/2024]
Abstract
Advances in large-scale single-unit human neurophysiology, single-cell RNA sequencing, spatial transcriptomics and long-term ex vivo tissue culture of surgically resected human brain tissue have provided an unprecedented opportunity to study human neuroscience. In this Perspective, we describe the development of these paradigms, including Neuropixels and recent brain-cell atlas efforts, and discuss how their convergence will further investigations into the cellular underpinnings of network-level activity in the human brain. Specifically, we introduce a workflow in which functionally mapped samples of human brain tissue resected during awake brain surgery can be cultured ex vivo for multi-modal cellular and functional profiling. We then explore how advances in human neuroscience will affect clinical practice, and conclude by discussing societal and ethical implications to consider. Potential findings from the field of human neuroscience will be vast, ranging from insights into human neurodiversity and evolution to providing cell-type-specific access to study and manipulate diseased circuits in pathology. This Perspective aims to provide a unifying framework for the field of human neuroscience as we welcome an exciting era for understanding the functional cytoarchitecture of the human brain.
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Affiliation(s)
- Anthony T Lee
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Mercedes F Paredes
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA.
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
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24
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Chang K, Lin L, Cui T, Zhao H, Li J, Liu C, Gao D, Lu S. Zinc-a2-Glycoprotein Acts as a Component of PNN to Protect Hippocampal Neurons from Apoptosis. Mol Neurobiol 2024; 61:3607-3618. [PMID: 38001359 DOI: 10.1007/s12035-023-03771-4] [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: 06/06/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023]
Abstract
In the adult mouse brain, perineuronal net (PNN), a highly structured extracellular matrix, surrounds subsets of neurons. The AZGP1 gene encodes zinc-2-glycoprotein (ZAG) is a lipid-mobilizing factor. However, its expression and distribution in the adult brain have been controversial. Here, for the first time, we demonstrate that the secreted ZAG is localized to Wisteria floribunda agglutinin (WFA)-positive PNNs around parvalbumin (PV)-expressing interneurons in the hippocampus, cortex, and a number of other PNN-bearing neurons and co-localizes with aggrecan, one of the components of PNNs. Few ZAG-positive nets were seen in the area without WFA staining by chondroitinase ABC (ChABC) which degrades glycosaminoglycans (GAGs) from the chondroitin sulfate proteoglycans (CSPGs) in the PNN. Reanalysis of single-cell sequencing data revealed that ZAG mRNA was mainly expressed in oligodendrocyte lineages, specifically in olfactory sheathing cells. The ZAG receptor β3 adrenergic receptor (β3AR) is also selectively co-localized with PV interneurons and CA2 pyramidal neurons in the hippocampus. In addition, molecular docking provides valuable new insights on how GAGs interfere with ZAG and ZAG/β3AR complex. Finally, our results indicated that human recombinant ZAG could significantly inhibit serum derivation-induced cell apoptosis in HT22 cells. Our combined experimental and theoretical approach raises a unique hypothesis namely that ZAG may be a crucial functional attribute of PNNs in the brain to protect neuronal cell from apoptosis.
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Affiliation(s)
- Kewei Chang
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
- Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education of China, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Liyan Lin
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Tingting Cui
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Hao Zhao
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Jiaxin Li
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Chang Liu
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China
| | - Dan Gao
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China.
- Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education of China, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China.
| | - Shemin Lu
- Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education of China, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China.
- Department of Biochemistry and Molecular Biology, Institute of Molecular and Translational Medicine, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Xi'an, 710061, Shaanxi, China.
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25
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Cottrell S, Hozumi Y, Wei GW. K-nearest-neighbors induced topological PCA for single cell RNA-sequence data analysis. Comput Biol Med 2024; 175:108497. [PMID: 38678944 PMCID: PMC11090715 DOI: 10.1016/j.compbiomed.2024.108497] [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: 03/02/2024] [Revised: 04/08/2024] [Accepted: 04/21/2024] [Indexed: 05/01/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given us insights into cell-cell communication, cell differentiation, and differential gene expression. However, analyzing scRNA-seq data is a challenge due to sparsity and the large number of genes involved. Therefore, dimensionality reduction and feature selection are important for removing spurious signals and enhancing downstream analysis. Traditional PCA, a main workhorse in dimensionality reduction, lacks the ability to capture geometrical structure information embedded in the data, and previous graph Laplacian regularizations are limited by the analysis of only a single scale. We propose a topological Principal Components Analysis (tPCA) method by the combination of persistent Laplacian (PL) technique and L2,1 norm regularization to address multiscale and multiclass heterogeneity issues in data. We further introduce a k-Nearest-Neighbor (kNN) persistent Laplacian technique to improve the robustness of our persistent Laplacian method. The proposed kNN-PL is a new algebraic topology technique which addresses the many limitations of the traditional persistent homology. Rather than inducing filtration via the varying of a distance threshold, we introduced kNN-tPCA, where filtrations are achieved by varying the number of neighbors in a kNN network at each step, and find that this framework has significant implications for hyper-parameter tuning. We validate the efficacy of our proposed tPCA and kNN-tPCA methods on 11 diverse benchmark scRNA-seq datasets, and showcase that our methods outperform other unsupervised PCA enhancements from the literature, as well as popular Uniform Manifold Approximation (UMAP), t-Distributed Stochastic Neighbor Embedding (tSNE), and Projection Non-Negative Matrix Factorization (NMF) by significant margins. For example, tPCA provides up to 628%, 78%, and 149% improvements to UMAP, tSNE, and NMF, respectively on classification in the F1 metric, and kNN-tPCA offers 53%, 63%, and 32% improvements to UMAP, tSNE, and NMF, respectively on clustering in the ARI metric.
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Affiliation(s)
- Sean Cottrell
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Yuta Hozumi
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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26
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Dear R, Wagstyl K, Seidlitz J, Markello RD, Arnatkevičiūtė A, Anderson KM, Bethlehem RAI, Raznahan A, Bullmore ET, Vértes PE. Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia. Nat Neurosci 2024; 27:1075-1086. [PMID: 38649755 PMCID: PMC11156586 DOI: 10.1038/s41593-024-01624-4] [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: 10/01/2022] [Accepted: 03/18/2024] [Indexed: 04/25/2024]
Abstract
Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.
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Affiliation(s)
- Richard Dear
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | | | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Aurina Arnatkevičiūtė
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | | | | | - Armin Raznahan
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, USA
| | | | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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27
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Jovanovic VM, Mesch KT, Tristan CA. hPSC-Derived Astrocytes at the Forefront of Translational Applications in Neurological Disorders. Cells 2024; 13:903. [PMID: 38891034 PMCID: PMC11172187 DOI: 10.3390/cells13110903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/17/2024] [Accepted: 05/23/2024] [Indexed: 06/20/2024] Open
Abstract
Astrocytes, the most abundant glial cell type in the brain, play crucial roles in maintaining homeostasis within the central nervous system (CNS). Impairment or abnormalities of typical astrocyte functions in the CNS serve as a causative or contributing factor in numerous neurodevelopmental, neurodegenerative, and neuropsychiatric disorders. Currently, disease-modeling and drug-screening approaches, primarily focused on human astrocytes, rely on human pluripotent stem cell (hPSC)-derived astrocytes. However, it is important to acknowledge that these hPSC-derived astrocytes exhibit notable differences across studies and when compared to their in vivo counterparts. These differences may potentially compromise translational outcomes if not carefully accounted for. This review aims to explore state-of-the-art in vitro models of human astrocyte development, focusing on the developmental processes, functional maturity, and technical aspects of various hPSC-derived astrocyte differentiation protocols. Additionally, it summarizes their successful application in modeling neurological disorders. The discussion extends to recent advancements in the large-scale production of human astrocytes and their application in developing high-throughput assays conducive to therapeutic drug discovery.
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Affiliation(s)
- Vukasin M. Jovanovic
- Stem Cell Translation Laboratory (SCTL), Division of Preclinical Innovation (DPI), National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, MD 20850, USA (C.A.T.)
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28
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Dai R, Chu T, Zhang M, Wang X, Jourdon A, Wu F, Mariani J, Vaccarino FM, Lee D, Fullard JF, Hoffman GE, Roussos P, Wang Y, Wang X, Pinto D, Wang SH, Zhang C, Chen C, Liu C. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. SCIENCE ADVANCES 2024; 10:eadh2588. [PMID: 38781336 PMCID: PMC11114236 DOI: 10.1126/sciadv.adh2588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 01/05/2024] [Indexed: 05/25/2024]
Abstract
Sample-wise deconvolution methods estimate cell-type proportions and gene expressions in bulk tissue samples, yet their performance and biological applications remain unexplored, particularly in human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk tissue RNA sequencing (RNA-seq), single-cell/nuclei (sc/sn) RNA-seq, and immunohistochemistry. A total of 1,130,767 nuclei per cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expressions. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk tissue or single-cell eQTLs did alone. Differential gene expressions associated with Alzheimer's disease, schizophrenia, and brain development were also examined using the deconvoluted data. Our findings, which were replicated in bulk tissue and single-cell data, provided insights into the biological applications of deconvoluted data in multiple brain disorders.
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Affiliation(s)
- Rujia Dai
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Tianyao Chu
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ming Zhang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xuan Wang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | | | - Feinan Wu
- Child Study Center, Yale University, New Haven, CT, USA
| | | | - Flora M. Vaccarino
- Child Study Center, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Departments of Psychiatry and Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F. Fullard
- Center for Disease Neurogenomics, Departments of Psychiatry and Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriel E. Hoffman
- Center for Disease Neurogenomics, Departments of Psychiatry and Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Departments of Psychiatry and Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yue Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Xusheng Wang
- Department of Biology, University of North Dakota, Grand Forks, ND, USA
| | - Dalila Pinto
- Departments of Psychiatry and Genetics and Genomic Sciences, Mindich Child Health and Development Institute, and Icahn Genomics Institute for Data Science and Genomic Technology, Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sidney H. Wang
- Center for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Chunling Zhang
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | | | - Chao Chen
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
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29
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Tang C, Sun Q, Zeng X, Yang X, Liu F, Zhao J, Shen Y, Liu B, Wen J, Li Y. Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595514. [PMID: 38826297 PMCID: PMC11142188 DOI: 10.1101/2024.05.23.595514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.
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Affiliation(s)
- Chenwei Tang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xinyue Zeng
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xiaoyu Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Fei Liu
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Bixiang Liu
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore
- Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
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30
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Collier L, Seah C, Hicks EM, Holtzheimer PE, Krystal JH, Girgenti MJ, Huckins LM, Johnston KJA. The impact of chronic pain on brain gene expression. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.20.24307630. [PMID: 38826319 PMCID: PMC11142271 DOI: 10.1101/2024.05.20.24307630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background Chronic pain affects one fifth of American adults, contributing significant public health burden. Chronic pain mechanisms can be further understood through investigating brain gene expression. Methods We tested differentially expressed genes (DEGs) in chronic pain, migraine, lifetime fentanyl and oxymorphone use, and with chronic pain genetic risk in four brain regions (dACC, DLPFC, MeA, BLA) and imputed cell type expression data from 304 postmortem donors. We compared findings across traits and with independent transcriptomics resources, and performed gene-set enrichment. Results We identified two chronic pain DEGs: B4GALT and VEGFB in bulk dACC. We found over 2000 (primarily BLA microglia) chronic pain cell type DEGs. Findings were enriched for mouse microglia pain genes, and for hypoxia and immune response. Cross-trait DEG overlap was minimal. Conclusions Chronic pain-associated gene expression is heterogeneous across cell type, largely distinct from that in pain-related traits, and shows BLA microglia are a key cell type.
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Affiliation(s)
- Lily Collier
- Department of Biological Sciences, Columbia University, New York City, NY
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University, New Haven, CT
| | - Carina Seah
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY
| | - Emily M Hicks
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY
| | - Paul E Holtzheimer
- National Center for PTSD, U.S. Department of Veterans Affairs
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
| | - John H Krystal
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University, New Haven, CT
- Clinical Neuroscience Division, National Center for PTSD, VA Connecticut Healthcare System, West Haven, CT
| | - Matthew J Girgenti
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University, New Haven, CT
- Clinical Neuroscience Division, National Center for PTSD, VA Connecticut Healthcare System, West Haven, CT
| | - Laura M Huckins
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University, New Haven, CT
| | - Keira J A Johnston
- Department of Psychiatry, Division of Molecular Psychiatry, Yale University, New Haven, CT
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31
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Cui W, Yang J, Tu C, Zhang Z, Zhao H, Qiao Y, Li Y, Yang W, Lim KL, Ma Q, Zhang C, Lu L. Seipin deficiency-induced lipid dysregulation leads to hypomyelination-associated cognitive deficits via compromising oligodendrocyte precursor cell differentiation. Cell Death Dis 2024; 15:350. [PMID: 38773070 PMCID: PMC11109229 DOI: 10.1038/s41419-024-06737-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 05/05/2024] [Accepted: 05/09/2024] [Indexed: 05/23/2024]
Abstract
Seipin is one key mediator of lipid metabolism that is highly expressed in adipose tissues as well as in the brain. Lack of Seipin gene, Bscl2, leads to not only severe lipid metabolic disorders but also cognitive impairments and motor disabilities. Myelin, composed mainly of lipids, facilitates nerve transmission and is important for motor coordination and learning. Whether Seipin deficiency-leaded defects in learning and motor coordination is underlined by lipid dysregulation and its consequent myelin abnormalities remains to be elucidated. In the present study, we verified the expression of Seipin in oligodendrocytes (OLs) and their precursors, oligodendrocyte precursor cells (OPCs), and demonstrated that Seipin deficiency compromised OPC differentiation, which led to decreased OL numbers, myelin protein, myelinated fiber proportion and thickness of myelin. Deficiency of Seipin resulted in impaired spatial cognition and motor coordination in mice. Mechanistically, Seipin deficiency suppressed sphingolipid metabolism-related genes in OPCs and caused morphological abnormalities in lipid droplets (LDs), which markedly impeded OPC differentiation. Importantly, rosiglitazone, one agonist of PPAR-gamma, substantially restored phenotypes resulting from Seipin deficiency, such as aberrant LDs, reduced sphingolipids, obstructed OPC differentiation, and neurobehavioral defects. Collectively, the present study elucidated how Seipin deficiency-induced lipid dysregulation leads to neurobehavioral deficits via impairing myelination, which may pave the way for developing novel intervention strategy for treating metabolism-involved neurological disorders.
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Affiliation(s)
- Wenli Cui
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
| | - Jing Yang
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
| | - Chuanyun Tu
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
| | - Ziting Zhang
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
| | - Huifang Zhao
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China
| | - Yan Qiao
- Analytical Instrumentation Center & State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, 030001, Shanxi, China
| | - Yanqiu Li
- Analytical Instrumentation Center & State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, 030001, Shanxi, China
| | - Wulin Yang
- Center of Medical Physics and Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China
| | - Kah-Leong Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Singapore, 308232, Singapore
| | - Quanhong Ma
- Jiangsu Key Laboratory of Neuropsychiatric Diseases, Institute of Neuroscience, Soochow University, Suzhou, Jiangsu, China.
| | - Chengwu Zhang
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
| | - Li Lu
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
- Key Laboratory of Cellular Physiology, Ministry of Education, Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
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32
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Steyn C, Mishi R, Fillmore S, Verhoog MB, More J, Rohlwink UK, Melvill R, Butler J, Enslin JMN, Jacobs M, Sauka-Spengler T, Greco M, Quiñones S, Dulla CG, Raimondo JV, Figaji A, Hockman D. Cell type-specific gene expression dynamics during human brain maturation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.29.560114. [PMID: 37808657 PMCID: PMC10557738 DOI: 10.1101/2023.09.29.560114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.
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Affiliation(s)
- Christina Steyn
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ruvimbo Mishi
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Stephanie Fillmore
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Matthijs B Verhoog
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jessica More
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ursula K Rohlwink
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Roger Melvill
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - James Butler
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Johannes M N Enslin
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Muazzam Jacobs
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- Division of Immunology, Department of Pathology University of Cape Town
- National Health Laboratory Service, South Africa
| | - Tatjana Sauka-Spengler
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Maria Greco
- Single Cell Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Sadi Quiñones
- Department of Neuroscience, Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
- Graduate School of Biomedical Science, Tufts University School of Medicine, Boston, MA, USA
| | - Chris G Dulla
- Department of Neuroscience, Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
| | - Joseph V Raimondo
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Anthony Figaji
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Dorit Hockman
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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Hameed R, Naseer A, Saxena A, Akbar M, Toppo P, Sarkar A, Shukla SK, Nazir A. Functional implications of NHR-210 enrichment in C. elegans cephalic sheath glia: insights into metabolic and mitochondrial disruptions in Parkinson's disease models. Cell Mol Life Sci 2024; 81:202. [PMID: 38691171 PMCID: PMC11063106 DOI: 10.1007/s00018-024-05179-2] [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: 08/23/2023] [Revised: 02/08/2024] [Accepted: 02/18/2024] [Indexed: 05/03/2024]
Abstract
Glial cells constitute nearly half of the mammalian nervous system's cellular composition. The glia in C. elegans perform majority of tasks comparable to those conducted by their mammalian equivalents. The cephalic sheath (CEPsh) glia, which are known to be the counterparts of mammalian astrocytes, are enriched with two nuclear hormone receptors (NHRs)-NHR-210 and NHR-231. This unique enrichment makes the CEPsh glia and these NHRs intriguing subjects of study concerning neuronal health. We endeavored to assess the role of these NHRs in neurodegenerative diseases and related functional processes, using transgenic C. elegans expressing human alpha-synuclein. We employed RNAi-mediated silencing, followed by behavioural, functional, and metabolic profiling in relation to suppression of NHR-210 and 231. Our findings revealed that depleting nhr-210 changes dopamine-associated behaviour and mitochondrial function in human alpha synuclein-expressing strains NL5901 and UA44, through a putative target, pgp-9, a transmembrane transporter. Considering the alteration in mitochondrial function and the involvement of a transmembrane transporter, we performed metabolomics study via HR-MAS NMR spectroscopy. Remarkably, substantial modifications in ATP, betaine, lactate, and glycine levels were seen upon the absence of nhr-210. We also detected considerable changes in metabolic pathways such as phenylalanine, tyrosine, and tryptophan biosynthesis metabolism; glycine, serine, and threonine metabolism; as well as glyoxalate and dicarboxylate metabolism. In conclusion, the deficiency of the nuclear hormone receptor nhr-210 in alpha-synuclein expressing strain of C. elegans, results in altered mitochondrial function, coupled with alterations in vital metabolite levels. These findings underline the functional and physiological importance of nhr-210 enrichment in CEPsh glia.
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Affiliation(s)
- Rohil Hameed
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Anam Naseer
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Ankit Saxena
- Sophisticated Analytical Instrument Facility and Research, CSIR-Central Drug Research Institute, Lucknow, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Mahmood Akbar
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Pranoy Toppo
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Arunabh Sarkar
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India
| | - Sanjeev K Shukla
- Sophisticated Analytical Instrument Facility and Research, CSIR-Central Drug Research Institute, Lucknow, 226031, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Aamir Nazir
- Division of Neuroscience and Ageing Biology, CSIR-Central Drug Research Institute, Lucknow, Uttar Pradesh, 226031, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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34
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Vornholt E, Liharska LE, Cheng E, Hashemi A, Park YJ, Ziafat K, Wilkins L, Silk H, Linares LM, Thompson RC, Sullivan B, Moya E, Nadkarni GN, Sebra R, Schadt EE, Kopell BH, Charney AW, Beckmann ND. Characterizing cell type specific transcriptional differences between the living and postmortem human brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.01.24306590. [PMID: 38746297 PMCID: PMC11092720 DOI: 10.1101/2024.05.01.24306590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Single-nucleus RNA sequencing (snRNA-seq) is often used to define gene expression patterns characteristic of brain cell types as well as to identify cell type specific gene expression signatures of neurological and mental illnesses in postmortem human brains. As methods to obtain brain tissue from living individuals emerge, it is essential to characterize gene expression differences associated with tissue originating from either living or postmortem subjects using snRNA-seq, and to assess whether and how such differences may impact snRNA-seq studies of brain tissue. To address this, human prefrontal cortex single nuclei gene expression was generated and compared between 31 samples from living individuals and 21 postmortem samples. The same cell types were consistently identified in living and postmortem nuclei, though for each cell type, a large proportion of genes were differentially expressed between samples from postmortem and living individuals. Notably, estimation of cell type proportions by cell type deconvolution of pseudo-bulk data was found to be more accurate in samples from living individuals. To allow for future integration of living and postmortem brain gene expression, a model was developed that quantifies from gene expression data the probability a human brain tissue sample was obtained postmortem. These probabilities are established as a means to statistically account for the gene expression differences between samples from living and postmortem individuals. Together, the results presented here provide a deep characterization of both differences between snRNA-seq derived from samples from living and postmortem individuals, as well as qualify and account for their effect on common analyses performed on this type of data.
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Duchateau L, Wawrzyniak N, Sleegers K. The ABC's of Alzheimer risk gene ABCA7. Alzheimers Dement 2024; 20:3629-3648. [PMID: 38556850 PMCID: PMC11095487 DOI: 10.1002/alz.13805] [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: 01/03/2024] [Revised: 02/27/2024] [Accepted: 02/29/2024] [Indexed: 04/02/2024]
Abstract
Alzheimer's disease (AD) is a growing problem worldwide. Since ABCA7's identification as a risk gene, it has been extensively researched for its role in the disease. We review its recently characterized structure and what the mechanistic insights teach us about its function. We furthermore provide an overview of identified ABCA7 mutations, their presence in different ancestries and protein domains and how they might cause AD. For ABCA7 PTC variants and a VNTR expansion, haploinsufficiency is proposed as the most likely mode-of-action, although splice events could further influence disease risk. Overall, the need to better understand expression of canonical ABCA7 and its isoforms in disease is indicated. Finally, ABCA7's potential functions in lipid metabolism, phagocytosis, amyloid deposition, and the interplay between these three, is described. To conclude, in this review, we provide a comprehensive overview and discussion about the current knowledge on ABCA7 in AD, and what research questions remain. HIGHLIGHTS: Alzheimer's risk-increasing variants in ABCA7 can be found in up to 7% of AD patients. We review the recently characterized protein structure of ABCA7. We present latest insights in genetics, expression patterns, and functions of ABCA7.
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Affiliation(s)
- Lena Duchateau
- Complex Genetics of Alzheimer's Disease group, VIB‐UAntwerp Center for Molecular NeurologyWilrijkAntwerpBelgium
- Department of Biomedical SciencesUniversity of AntwerpWilrijkAntwerpBelgium
| | - Nicole Wawrzyniak
- Complex Genetics of Alzheimer's Disease group, VIB‐UAntwerp Center for Molecular NeurologyWilrijkAntwerpBelgium
- Chávez‐Gutiérrez Lab, VIB‐KU Leuven Center for Brain and Disease Research, VIBLeuvenBelgium
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease group, VIB‐UAntwerp Center for Molecular NeurologyWilrijkAntwerpBelgium
- Department of Biomedical SciencesUniversity of AntwerpWilrijkAntwerpBelgium
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Wang X, Liu Q, Yu HT, Xie JZ, Zhao JN, Fang ZT, Qu M, Zhang Y, Yang Y, Wang JZ. A positive feedback inhibition of isocitrate dehydrogenase 3β on paired-box gene 6 promotes Alzheimer-like pathology. Signal Transduct Target Ther 2024; 9:105. [PMID: 38679634 PMCID: PMC11056379 DOI: 10.1038/s41392-024-01812-5] [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: 08/18/2023] [Revised: 02/28/2024] [Accepted: 03/20/2024] [Indexed: 05/01/2024] Open
Abstract
Impaired brain glucose metabolism is an early indicator of Alzheimer's disease (AD); however, the fundamental mechanism is unknown. In this study, we found a substantial decline in isocitrate dehydrogenase 3β (IDH3β) levels, a critical tricarboxylic acid cycle enzyme, in AD patients and AD-transgenic mice's brains. Further investigations demonstrated that the knockdown of IDH3β induced oxidation-phosphorylation uncoupling, leading to reduced energy metabolism and lactate accumulation. The resulting increased lactate, a source of lactyl, was found to promote histone lactylation, thereby enhancing the expression of paired-box gene 6 (PAX6). As an inhibitory transcription factor of IDH3β, the elevated PAX6 in turn inhibited the expression of IDH3β, leading to tau hyperphosphorylation, synapse impairment, and learning and memory deficits resembling those seen in AD. In AD-transgenic mice, upregulating IDH3β and downregulating PAX6 were found to improve cognitive functioning and reverse AD-like pathologies. Collectively, our data suggest that impaired oxidative phosphorylation accelerates AD progression via a positive feedback inhibition loop of IDH3β-lactate-PAX6-IDH3β. Breaking this loop by upregulating IDH3β or downregulating PAX6 attenuates AD neurodegeneration and cognitive impairments.
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Affiliation(s)
- Xin Wang
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qian Liu
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hai-Tao Yu
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Jia-Zhao Xie
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-Ning Zhao
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhi-Ting Fang
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Qu
- Hubei Provincial Key Laboratory for Applied Toxicology, Hubei Provincial Center for Disease Control and Prevention, Hubei Provincial Academy of Preventive Medicine, Wuhan, 430000, China
| | - Yao Zhang
- Endocrine Department of Liyuan Hospital; Key Laboratory of Ministry of Education of China for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430077, China.
| | - Ying Yang
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Jian-Zhi Wang
- Department of Pathophysiology, School of Basic Medicine, Key Laboratory of Education Ministry of China/Hubei Province for Neurological Disorders, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Co-innovation Center of Neuroregeneration, Nantong University, Nantong, 226000, China.
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Wang GF, Shen L. Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis. BMC Bioinformatics 2024; 25:169. [PMID: 38684942 PMCID: PMC11059750 DOI: 10.1186/s12859-024-05797-4] [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: 11/28/2023] [Accepted: 04/24/2024] [Indexed: 05/02/2024] Open
Abstract
Many important biological facts have been found as single-cell RNA sequencing (scRNA-seq) technology has advanced. With the use of this technology, it is now possible to investigate the connections among individual cells, genes, and illnesses. For the analysis of single-cell data, clustering is frequently used. Nevertheless, biological data usually contain a large amount of noise data, and traditional clustering methods are sensitive to noise. However, acquiring higher-order spatial information from the data alone is insufficient. As a result, getting trustworthy clustering findings is challenging. We propose the Cauchy hyper-graph Laplacian non-negative matrix factorization (CHLNMF) as a unique approach to address these issues. In CHLNMF, we replace the measurement based on Euclidean distance in the conventional non-negative matrix factorization (NMF), which can lessen the influence of noise, with the Cauchy loss function (CLF). The model also incorporates the hyper-graph constraint, which takes into account the high-order link among the samples. The CHLNMF model's best solution is then discovered using a half-quadratic optimization approach. Finally, using seven scRNA-seq datasets, we contrast the CHLNMF technique with the other nine top methods. The validity of our technique was established by analysis of the experimental outcomes.
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Affiliation(s)
- Gao-Fei Wang
- School of Computer Science, Qufu Normal University, Rizhao, 276826, Shandong, China.
| | - Longying Shen
- School of Computer Science, Qufu Normal University, Rizhao, 276826, Shandong, China
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38
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Kim H, Chang W, Chae SJ, Park JE, Seo M, Kim JK. scLENS: data-driven signal detection for unbiased scRNA-seq data analysis. Nat Commun 2024; 15:3575. [PMID: 38678050 DOI: 10.1038/s41467-024-47884-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 04/14/2024] [Indexed: 04/29/2024] Open
Abstract
High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning.
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Affiliation(s)
- Hyun Kim
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Won Chang
- Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH, 45221, USA
| | - Seok Joo Chae
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea
| | - Jong-Eun Park
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Minseok Seo
- Department of Computer and Information Science, Korea University, Sejong, 30019, Republic of Korea
| | - Jae Kyoung Kim
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea.
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39
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Song X, Tiek D, Miki S, Huang T, Lu M, Goenka A, Iglesia R, Yu X, Wu R, Walker M, Zeng C, Shah H, Weng SHS, Huff A, Zhang W, Koga T, Hubert C, Horbinski CM, Furnari FB, Hu B, Cheng SY. RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma. J Clin Invest 2024; 134:e173789. [PMID: 38662454 PMCID: PMC11142752 DOI: 10.1172/jci173789] [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: 07/11/2023] [Accepted: 04/16/2024] [Indexed: 06/02/2024] Open
Abstract
Widespread alterations in RNA alternative splicing (AS) have been identified in adult gliomas. However, their regulatory mechanism, biological significance, and therapeutic potential remain largely elusive. Here, using a computational approach with both bulk and single-cell RNA-Seq, we uncover a prognostic AS signature linked with neural developmental hierarchies. Using advanced iPSC glioma models driven by glioma driver mutations, we show that this AS signature could be enhanced by EGFRvIII and inhibited by in situ IDH1 mutation. Functional validations of 2 isoform switching events in CERS5 and MPZL1 show regulations of sphingolipid metabolism and SHP2 signaling, respectively. Analysis of upstream RNA binding proteins reveals PTBP1 as a key regulator of the AS signature where targeting of PTBP1 suppresses tumor growth and promotes the expression of a neuron marker TUJ1 in glioma stem-like cells. Overall, our data highlights the role of AS in affecting glioma malignancy and heterogeneity and its potential as a therapeutic vulnerability for treating adult gliomas.
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Affiliation(s)
- Xiao Song
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Deanna Tiek
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shunichiro Miki
- Department of Medicine, Division of Regenerative Medicine, Sanford Stem Cell Institute, UCSD, La Jolla, California, USA
| | - Tianzhi Huang
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Minghui Lu
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Anshika Goenka
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Rebeca Iglesia
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Xiaozhou Yu
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Runxin Wu
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Maya Walker
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Chang Zeng
- Department of Preventive Medicine, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Hardik Shah
- Metabolomics Platform, Comprehensive Cancer Center, and
| | - Shao Huan Samuel Weng
- Proteomics Platform, Office of Shared Research Facilities, Biological Sciences Division, The University of Chicago, Chicago, Illinois, USA
| | - Allen Huff
- Proteomics Platform, Office of Shared Research Facilities, Biological Sciences Division, The University of Chicago, Chicago, Illinois, USA
| | - Wei Zhang
- Department of Preventive Medicine, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tomoyuki Koga
- Department of Neurosurgery, The University of Minnesota, Minneapolis, Minnesota, USA
| | - Christopher Hubert
- Department of Biochemistry, School of Medicine, Case Western Reserved University, Cleveland, Ohio, USA
| | - Craig M. Horbinski
- Departments of Pathology and Neurological Surgery, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Frank B. Furnari
- Department of Medicine, Division of Regenerative Medicine, Sanford Stem Cell Institute, UCSD, La Jolla, California, USA
| | - Bo Hu
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shi-Yuan Cheng
- The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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40
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Qian Z, Wang Z, Li B, Meng X, Kuang Z, Li Y, Yang Y, Ye K. Thy1-ApoE4/C/EBPβ double transgenic mice act as a sporadic model with Alzheimer's disease. Mol Psychiatry 2024:10.1038/s41380-024-02565-x. [PMID: 38658772 DOI: 10.1038/s41380-024-02565-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024]
Abstract
Early onset familial Alzheimer's disease (FAD) with APP, PS1/2 (presenilins) mutation accounts for only a small portion of AD cases, and most are late-onset sporadic. However, majority of AD mouse models are developed to mimic the genetic cause of human AD by overexpressing mutated forms of human APP, PS1/2, and/or Tau protein, though there is no Tau mutation in AD, and no single mouse model recapitulates all aspects of AD pathology. Here, we report Thy1-ApoE4/C/EBPβ double transgenic mouse model that demonstrates key AD pathologies in an age-dependent manner in absence of any human APP or PS1/2 mutation. Using the clinical diagnosis criteria, we show that this mouse model exhibits tempo-spatial features in AD patient brains, including progressive cognitive decline associated with brain atrophy, which is accompanied with extensive neuronal degeneration. Remarkably, the mice display gradual Aβ aggregation and neurofibrillary tangles formation in the brain validated by Aβ PET and Tau PET. Moreover, the mice reveal widespread neuroinflammation as shown in AD brains. Hence, Thy1-ApoE4/C/EBPβ mouse model acts as a sporadic AD mouse model, reconstituting the major AD pathologies.
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Affiliation(s)
- Zhengjiang Qian
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - ZhiHao Wang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, 430060, China
| | - Bowei Li
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Science, Shenzhen, Guangdong Province, 518055, China
| | - Xin Meng
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Zhonghua Kuang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Yanjiao Li
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Yongfeng Yang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Keqiang Ye
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China.
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Baig S, Nadaf J, Allache R, Le PU, Luo M, Djedid A, Nkili-Meyong A, Safisamghabadi M, Prat A, Antel J, Guiot MC, Petrecca K. Identity and nature of neural stem cells in the adult human subventricular zone. iScience 2024; 27:109342. [PMID: 38495819 PMCID: PMC10940989 DOI: 10.1016/j.isci.2024.109342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/26/2023] [Accepted: 02/22/2024] [Indexed: 03/19/2024] Open
Abstract
The existence of neural stem cells (NSCs) in adult human brain neurogenic regions remains unresolved. To address this, we created a cell atlas of the adult human subventricular zone (SVZ) derived from fresh neurosurgical samples using single-cell transcriptomics. We discovered 2 adult radial glia (RG)-like populations, aRG1 and aRG2. aRG1 shared features with fetal early RG (eRG) and aRG2 were transcriptomically similar to fetal outer RG (oRG). We also captured early neuronal and oligodendrocytic NSC states. We found that the biological programs driven by their transcriptomes support their roles as early lineage NSCs. Finally, we show that these NSCs have the potential to transition between states and along lineage trajectories. These data reveal that multipotent NSCs reside in the adult human SVZ.
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Affiliation(s)
- Salma Baig
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Javad Nadaf
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Redouane Allache
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Phuong U. Le
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Michael Luo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Annisa Djedid
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Andriniaina Nkili-Meyong
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Maryam Safisamghabadi
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Alex Prat
- Neuroimmunology Research Lab, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, QC H2X0A9, Canada
| | - Jack Antel
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Marie-Christine Guiot
- Department of Neuropathology, Montreal Neurological Institute-Hospital, McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
| | - Kevin Petrecca
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital McGill University, 3801 University Avenue, Montreal QC H3A2B4, Canada
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Dai R, Zhang M, Chu T, Kopp R, Zhang C, Liu K, Wang Y, Wang X, Chen C, Liu C. Precision and Accuracy of Single-Cell/Nuclei RNA Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.12.589216. [PMID: 38659857 PMCID: PMC11042208 DOI: 10.1101/2024.04.12.589216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Single-cell/nuclei RNA sequencing (sc/snRNA-Seq) is widely used for profiling cell-type gene expressions in biomedical research. An important but underappreciated issue is the quality of sc/snRNA-Seq data that would impact the reliability of downstream analyses. Here we evaluated the precision and accuracy in 18 sc/snRNA-Seq datasets. The precision was assessed on data from human brain studies with a total of 3,483,905 cells from 297 individuals, by utilizing technical replicates. The accuracy was evaluated with sample-matched scRNA-Seq and pooled-cell RNA-Seq data of cultured mononuclear phagocytes from four species. The results revealed low precision and accuracy at the single-cell level across all evaluated data. Cell number and RNA quality were highlighted as two key factors determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-Seq. This study underscores the necessity of sequencing enough high-quality cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification.
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Affiliation(s)
- Rujia Dai
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Ming Zhang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Tianyao Chu
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Richard Kopp
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Chunling Zhang
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Kefu Liu
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yue Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, VA, USA
| | - Xusheng Wang
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Chao Chen
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Furong Laboratory, Changsha, Hunan, China
- Hunan Key Laboratory of Animal Models for Human Diseases, Central South University, Changsha, China
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
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Davis CN, Khan Y, Toikumo S, Jinwala Z, Boomsma DI, Levey DF, Gelernter J, Kember RL, Kranzler HR. A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.06.24305166. [PMID: 38645045 PMCID: PMC11030494 DOI: 10.1101/2024.04.06.24305166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.
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Affiliation(s)
- Christal N. Davis
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Yousef Khan
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Zeal Jinwala
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Dorret I. Boomsma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, The Netherlands and Amsterdam Reproduction and Development Research Institute, Amsterdam, The Netherlands
| | - Daniel F. Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- VA Connecticut Healthcare Center, West Haven, CT, USA
- Departments of Psychiatry, Genetics, and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Rachel L. Kember
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Henry R. Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
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Hozumi Y, Tanemura KA, Wei GW. Preprocessing of Single Cell RNA Sequencing Data Using Correlated Clustering and Projection. J Chem Inf Model 2024; 64:2829-2838. [PMID: 37402705 PMCID: PMC11009150 DOI: 10.1021/acs.jcim.3c00674] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given us insights into cell-cell communication, cell differentiation, and differential gene expression. However, analyzing scRNA-seq data is a challenge due to sparsity and the large number of genes involved. Therefore, dimensionality reduction and feature selection are important for removing spurious signals and enhancing the downstream analysis. We present Correlated Clustering and Projection (CCP), a new data-domain dimensionality reduction method, for the first time. CCP projects each cluster of similar genes into a supergene defined as the accumulated pairwise nonlinear gene-gene correlations among all cells. Using 14 benchmark data sets, we demonstrate that CCP has significant advantages over classical principal component analysis (PCA) for clustering and/or classification problems with intrinsically high dimensionality. In addition, we introduce the Residue-Similarity index (RSI) as a novel metric for clustering and classification and the R-S plot as a new visualization tool. We show that the RSI correlates with accuracy without requiring the knowledge of the true labels. The R-S plot provides a unique alternative to the uniform manifold approximation and projection (UMAP) and t-distributed stochastic neighbor embedding (t-SNE) for data with a large number of cell types.
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Affiliation(s)
- Yuta Hozumi
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Kiyoto Aramis Tanemura
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
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Fiorini MR, Dilliott AA, Thomas RA, Farhan SMK. Transcriptomics of Human Brain Tissue in Parkinson's Disease: a Comparison of Bulk and Single-cell RNA Sequencing. Mol Neurobiol 2024:10.1007/s12035-024-04124-5. [PMID: 38578357 DOI: 10.1007/s12035-024-04124-5] [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: 10/11/2023] [Accepted: 03/12/2024] [Indexed: 04/06/2024]
Abstract
Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease leading to motor dysfunction and, in some cases, dementia. Transcriptome analysis is one promising approach for characterizing PD and other neurodegenerative disorders by informing how specific disease events influence gene expression and contribute to pathogenesis. With the emergence of single-cell and single-nucleus RNA sequencing (scnRNA-seq) technologies, the transcriptional landscape of neurodegenerative diseases can now be described at the cellular level. As the application of scnRNA-seq is becoming routine, it calls to question how results at a single-cell resolution compare to those obtained from RNA sequencing of whole tissues (bulk RNA-seq), whether the findings are compatible, and how the assays are complimentary for unraveling the elusive transcriptional changes that drive neurodegenerative disease. Herein, we review the studies that have leveraged RNA-seq technologies to investigate PD. Through the integration of bulk and scnRNA-seq findings from human, post-mortem brain tissue, we use the PD literature as a case study to evaluate the compatibility of the results generated from each assay and demonstrate the complementarity of the sequencing technologies. Finally, through the lens of the PD transcriptomic literature, we evaluate the current feasibility of bulk and scnRNA-seq technologies to illustrate the necessity of both technologies for achieving a comprehensive insight into the mechanism by which gene expression promotes neurodegenerative disease. We conclude that the continued application of both assays will provide the greatest insight into neurodegenerative disease pathology, providing both cell-specific and whole-tissue level information.
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Affiliation(s)
- Michael R Fiorini
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Allison A Dilliott
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Rhalena A Thomas
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
| | - Sali M K Farhan
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Human Genetics, McGill University, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
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Das D, Sonthalia S, Stein-O 'Brien G, Wahbeh MH, Feuer K, Goff L, Colantuoni C, Mahairaki V, Avramopoulos D. Insights for disease modeling from single-cell transcriptomics of iPSC-derived Ngn2-induced neurons and astrocytes across differentiation time and co-culture. BMC Biol 2024; 22:75. [PMID: 38566045 PMCID: PMC10985965 DOI: 10.1186/s12915-024-01867-4] [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: 07/18/2023] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. RESULTS Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . CONCLUSIONS While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.
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Affiliation(s)
- D Das
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
| | - S Sonthalia
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, USA
| | - G Stein-O 'Brien
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
| | - M H Wahbeh
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
| | - K Feuer
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
| | - L Goff
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, USA
| | - C Colantuoni
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, USA
- Institute of Genome Sciences, University of Maryland School of Medicine, Baltimore, USA
| | - V Mahairaki
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA
| | - D Avramopoulos
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, 733 E. Broadway, Baltimore, MD, 21205, USA.
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, USA.
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Shen Y, Shao M, Hao ZZ, Huang M, Xu N, Liu S. Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity. Neurosci Bull 2024; 40:517-532. [PMID: 38194157 PMCID: PMC11003949 DOI: 10.1007/s12264-023-01160-4] [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: 03/22/2023] [Accepted: 09/23/2023] [Indexed: 01/10/2024] Open
Abstract
Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.
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Affiliation(s)
- Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mingting Shao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mengyao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
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Huang X, Liu R, Yang S, Chen X, Li H. scAnnoX: an R package integrating multiple public tools for single-cell annotation. PeerJ 2024; 12:e17184. [PMID: 38560451 PMCID: PMC10981883 DOI: 10.7717/peerj.17184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 03/11/2024] [Indexed: 04/04/2024] Open
Abstract
Background Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking. Methods This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms. Ten single-cell annotation algorithms were selected based on the classification of either reference dataset-dependent or marker gene-dependent approaches. These algorithms included SingleR, Seurat, sciBet, scmap, CHETAH, scSorter, sc.type, cellID, scCATCH, and SCINA. Building upon these algorithms, we developed an R package named scAnnoX for the integration and comparative analysis of single-cell annotation algorithms. Results The development of the scAnnoX software package provides a cohesive framework for annotating cells in scRNA-seq data, enabling researchers to more efficiently perform comparative analyses among the cell type annotations contained in scRNA-seq datasets. The integrated environment of scAnnoX streamlines the testing, evaluation, and comparison processes among various algorithms. Among the ten annotation tools evaluated, SingleR, Seurat, sciBet, and scSorter emerged as top-performing algorithms in terms of prediction accuracy, with SingleR and sciBet demonstrating particularly superior performance, offering guidance for users. Interested parties can access the scAnnoX package at https://github.com/XQ-hub/scAnnoX.
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Affiliation(s)
- Xiaoqian Huang
- School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, Yunnan Province, China
| | - Ruiqi Liu
- School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, Yunnan Province, China
| | - Shiwei Yang
- School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, Yunnan Province, China
| | - Xiaozhou Chen
- School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, Yunnan Province, China
| | - Huamei Li
- Department of Hepatobiliary Surgery, the Affiliated Drum Tower Hospital, Medical School, Nanjing University, Nanjing, Jiangsu Province, China
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Patel A, Dharap A. An Emerging Role for Enhancer RNAs in Brain Disorders. Neuromolecular Med 2024; 26:7. [PMID: 38546891 PMCID: PMC11263973 DOI: 10.1007/s12017-024-08776-3] [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: 02/05/2024] [Accepted: 02/23/2024] [Indexed: 04/02/2024]
Abstract
Noncoding DNA undergoes widespread context-dependent transcription to produce noncoding RNAs. In recent decades, tremendous advances in genomics and transcriptomics have revealed important regulatory roles for noncoding DNA elements and the RNAs that they produce. Enhancers are one such element that are well-established drivers of gene expression changes in response to a variety of factors such as external stimuli, cellular responses, developmental cues, and disease states. They are known to act at long distances, interact with multiple target gene loci simultaneously, synergize with other enhancers, and associate with dynamic chromatin architectures to form a complex regulatory network. Recent advances in enhancer biology have revealed that upon activation, enhancers transcribe long noncoding RNAs, known as enhancer RNAs (eRNAs), that have been shown to play important roles in enhancer-mediated gene regulation and chromatin-modifying activities. In the brain, enhancer dysregulation and eRNA transcription has been reported in numerous disorders from acute injuries to chronic neurodegeneration. Because this is an emerging area, a comprehensive understanding of eRNA function has not yet been achieved in brain disorders; however, the findings to date have illuminated a role for eRNAs in activity-driven gene expression and phenotypic outcomes. In this review, we highlight the breadth of the current literature on eRNA biology in brain health and disease and discuss the challenges as well as focus areas and strategies for future in-depth research on eRNAs in brain health and disease.
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Affiliation(s)
- Ankit Patel
- Department of Molecular Medicine, University of South Florida, Tampa, FL, USA
- Byrd Alzheimer's Center & Research Institute, USF Health Neuroscience Institute, Tampa, FL, USA
| | - Ashutosh Dharap
- Department of Molecular Medicine, University of South Florida, Tampa, FL, USA.
- Byrd Alzheimer's Center & Research Institute, USF Health Neuroscience Institute, Tampa, FL, USA.
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Huang Y, Jiang H, Ching WK. scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data. Brief Bioinform 2024; 25:bbae203. [PMID: 38701413 PMCID: PMC11066953 DOI: 10.1093/bib/bbae203] [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: 09/04/2023] [Revised: 02/19/2024] [Accepted: 04/17/2024] [Indexed: 05/05/2024] Open
Abstract
With the emergence of large amount of single-cell RNA sequencing (scRNA-seq) data, the exploration of computational methods has become critical in revealing biological mechanisms. Clustering is a representative for deciphering cellular heterogeneity embedded in scRNA-seq data. However, due to the diversity of datasets, none of the existing single-cell clustering methods shows overwhelming performance on all datasets. Weighted ensemble methods are proposed to integrate multiple results to improve heterogeneity analysis performance. These methods are usually weighted by considering the reliability of the base clustering results, ignoring the performance difference of the same base clustering on different cells. In this paper, we propose a high-order element-wise weighting strategy based self-representative ensemble learning framework: scEWE. By assigning different base clustering weights to individual cells, we construct and optimize the consensus matrix in a careful and exquisite way. In addition, we extracted the high-order information between cells, which enhanced the ability to represent the similarity relationship between cells. scEWE is experimentally shown to significantly outperform the state-of-the-art methods, which strongly demonstrates the effectiveness of the method and supports the potential applications in complex single-cell data analytical problems.
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Affiliation(s)
- Yixiang Huang
- School of Mathematics, Renmin University of China, No. 59 Zhong guancun Street, 100872, Beijing, China
| | - Hao Jiang
- School of Mathematics, Renmin University of China, No. 59 Zhong guancun Street, 100872, Beijing, China
| | - Wai-Ki Ching
- Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong
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