1
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Santiago RMM, Lopes-Dos-Santos V, Aery Jones EA, Huang Y, Dupret D, Tort ABL. Waveform-based classification of dentate spikes. Sci Rep 2024; 14:2989. [PMID: 38316828 PMCID: PMC10844627 DOI: 10.1038/s41598-024-53075-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 01/27/2024] [Indexed: 02/07/2024] Open
Abstract
Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.
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Affiliation(s)
- Rodrigo M M Santiago
- Computational Neurophysiology Lab, Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, 59078-900, Brazil.
| | - Vítor Lopes-Dos-Santos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Emily A Aery Jones
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, 94158, USA
| | - David Dupret
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adriano B L Tort
- Computational Neurophysiology Lab, Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, 59078-900, Brazil
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2
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Santiago RM, Lopes-dos-Santos V, Jones EAA, Huang Y, Dupret D, Tort AB. Waveform-based classification of dentate spikes. bioRxiv 2023:2023.10.24.563826. [PMID: 37961150 PMCID: PMC10634814 DOI: 10.1101/2023.10.24.563826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.
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Affiliation(s)
- Rodrigo M.M. Santiago
- Computational Neurophysiology Lab, Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, 59078-900, Brazil
| | - Vítor Lopes-dos-Santos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Emily A. Aery Jones
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - David Dupret
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adriano B.L. Tort
- Computational Neurophysiology Lab, Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, 59078-900, Brazil
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3
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Masuda FK, Aery Jones EA, Sun Y, Giocomo LM. Ketamine evoked disruption of entorhinal and hippocampal spatial maps. Nat Commun 2023; 14:6285. [PMID: 37805575 PMCID: PMC10560293 DOI: 10.1038/s41467-023-41750-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 09/15/2023] [Indexed: 10/09/2023] Open
Abstract
Ketamine, a rapid-acting anesthetic and acute antidepressant, carries undesirable spatial cognition side effects including out-of-body experiences and spatial memory impairments. The neural substrates that underlie these alterations in spatial cognition however, remain incompletely understood. Here, we used electrophysiology and calcium imaging to examine ketamine's impacts on the medial entorhinal cortex and hippocampus, which contain neurons that encode an animal's spatial position, as mice navigated virtual reality and real world environments. Ketamine acutely increased firing rates, degraded cell-pair temporal firing-rate relationships, and altered oscillations, leading to longer-term remapping of spatial representations. In the reciprocally connected hippocampus, the activity of neurons that encode the position of the animal was suppressed after ketamine administration. Together, these findings demonstrate ketamine-induced dysfunction of the MEC-hippocampal circuit at the single cell, local-circuit population, and network levels, connecting previously demonstrated physiological effects of ketamine on spatial cognition to alterations in the spatial navigation circuit.
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Affiliation(s)
- Francis Kei Masuda
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Emily A Aery Jones
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Yanjun Sun
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
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4
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Masuda FK, Sun Y, Aery Jones EA, Giocomo LM. Ketamine evoked disruption of entorhinal and hippocampal spatial maps. bioRxiv 2023:2023.02.05.527227. [PMID: 36798242 PMCID: PMC9934572 DOI: 10.1101/2023.02.05.527227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Ketamine, a rapid-acting anesthetic and acute antidepressant, carries undesirable spatial cognition side effects including out-of-body experiences and spatial memory impairments. The neural substrates that underlie these alterations in spatial cognition however, remain incompletely understood. Here, we used electrophysiology and calcium imaging to examine ketamine's impacts on the medial entorhinal cortex and hippocampus, which contain neurons that encode an animal's spatial position, as mice navigated virtual reality and real world environments. Ketamine induced an acute disruption and long-term re-organization of entorhinal spatial representations. This acute ketamine-induced disruption reflected increased excitatory neuron firing rates and degradation of cell-pair temporal firing rate relationships. In the reciprocally connected hippocampus, the activity of neurons that encode the position of the animal was suppressed after ketamine administration. Together, these findings point to disruption in the spatial coding properties of the entorhinal-hippocampal circuit as a potential neural substrate for ketamine-induced changes in spatial cognition.
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Affiliation(s)
- Francis Kei Masuda
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yanjun Sun
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Emily A Aery Jones
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
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5
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Aery Jones EA, Giocomo LM. Neural ensembles in navigation: From single cells to population codes. Curr Opin Neurobiol 2023; 78:102665. [PMID: 36542882 PMCID: PMC9845194 DOI: 10.1016/j.conb.2022.102665] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/27/2022] [Accepted: 11/21/2022] [Indexed: 12/23/2022]
Abstract
The brain can represent behaviorally relevant information through the firing of individual neurons as well as the coordinated firing of ensembles of neurons. Neurons in the hippocampus and associated cortical regions participate in a variety of types of ensembles to support navigation. These ensemble types include single cell codes, population codes, time-compressed sequences, behavioral sequences, and engrams. We present the physiological basis and behavioral relevance of ensemble firing. We discuss how these traditional definitions of ensembles can constrain or expand potential analyses due to the underlying assumptions and abstractions made. We highlight how coding can change at the ensemble level while underlying single cell codes remain intact. Finally, we present how ensemble definitions could be broadened to better understand the full complexity of the brain.
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Affiliation(s)
- Emily A Aery Jones
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
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6
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Jones EAA, Rao A, Zilberter M, Djukic B, Bant JS, Gillespie AK, Koutsodendris N, Nelson M, Yoon SY, Huang K, Yuan H, Gill TM, Huang Y, Frank LM. Dentate gyrus and CA3 GABAergic interneurons bidirectionally modulate signatures of internal and external drive to CA1. Cell Rep 2021; 37:110159. [PMID: 34965435 PMCID: PMC9069800 DOI: 10.1016/j.celrep.2021.110159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 10/04/2021] [Accepted: 12/01/2021] [Indexed: 01/19/2023] Open
Abstract
Specific classes of GABAergic neurons play specific roles in regulating information processing in the brain. In the hippocampus, two major classes, parvalbumin-expressing (PV+) and somatostatin-expressing (SST+), differentially regulate endogenous firing patterns and target subcellular compartments of principal cells. How these classes regulate the flow of information throughout the hippocampus is poorly understood. We hypothesize that PV+ and SST+ interneurons in the dentate gyrus (DG) and CA3 differentially modulate CA3 patterns of output, thereby altering the influence of CA3 on CA1. We find that while suppressing either interneuron class increases DG and CA3 output, the effects on CA1 were very different. Suppressing PV+ interneurons increases local field potential signatures of coupling from CA3 to CA1 and decreases signatures of coupling from entorhinal cortex to CA1; suppressing SST+ interneurons has the opposite effect. Thus, DG and CA3 PV+ and SST+ interneurons bidirectionally modulate the flow of information through the hippocampal circuit.
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Affiliation(s)
- Emily A. Aery Jones
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA.,Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Antara Rao
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA.,Developmental & Stem Cell Biology Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Misha Zilberter
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Biljana Djukic
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Jason S. Bant
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Anna K. Gillespie
- Kavli Institute for Fundamental Neuroscience and Department of Physiology, University of California, San Francisco, CA 94143, USA
| | - Nicole Koutsodendris
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA.,Developmental & Stem Cell Biology Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Maxine Nelson
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA.,Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Ky Huang
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Heidi Yuan
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Theodore M. Gill
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA.,Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA,Developmental & Stem Cell Biology Graduate Program, University of California, San Francisco, CA 94143, USA,Departments of Neurology and Pathology, University of California, San Francisco, CA 94143, USA,Gladstone Center for Translational Advancement, San Francisco, CA 94158, USA,Correspondence should be addressed to: Loren Frank () or Yadong Huang ()
| | - Loren M. Frank
- Kavli Institute for Fundamental Neuroscience and Department of Physiology, University of California, San Francisco, CA 94143, USA,Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA,Lead contact,Correspondence should be addressed to: Loren Frank () or Yadong Huang ()
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7
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Taubes A, Nova P, Zalocusky KA, Kosti I, Bicak M, Zilberter MY, Hao Y, Yoon SY, Oskotsky T, Pineda S, Chen B, Aery Jones EA, Choudhary K, Grone B, Balestra ME, Chaudhry F, Paranjpe I, De Freitas J, Koutsodendris N, Chen N, Wang C, Chang W, An A, Glicksberg BS, Sirota M, Huang Y. Author Correction: Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer's disease. Nat Aging 2021; 1:1202. [PMID: 37117528 DOI: 10.1038/s43587-021-00144-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Affiliation(s)
- Alice Taubes
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Phil Nova
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Kelly A Zalocusky
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Pediatrics, University of California, San Francisco, CA, USA
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Misha Y Zilberter
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
| | - Yanxia Hao
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Pediatrics, University of California, San Francisco, CA, USA
| | - Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Surgery, University of California, San Francisco, CA, USA
| | - Bin Chen
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
| | - Emily A Aery Jones
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Krishna Choudhary
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
| | - Brian Grone
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Maureen E Balestra
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Fayzan Chaudhry
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ishan Paranjpe
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica De Freitas
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicole Koutsodendris
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Development and Stem Cell Biology Graduate Program, University of California, San Francisco, CA, USA
| | - Nuo Chen
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Celine Wang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - William Chang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Alice An
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Benjamin S Glicksberg
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
- Department of Pediatrics, University of California, San Francisco, CA, USA.
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA.
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA.
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, CA, USA.
- Department of Pathology, University of California, San Francisco, CA, USA.
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8
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Taubes A, Nova P, Zalocusky KA, Kosti I, Bicak M, Zilberter MY, Hao Y, Yoon SY, Oskotsky T, Pineda S, Chen B, Jones EAA, Choudhary K, Grone B, Balestra ME, Chaudhry F, Paranjpe I, De Freitas J, Koutsodendris N, Chen N, Wang C, Chang W, An A, Glicksberg BS, Sirota M, Huang Y. Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer's disease. Nat Aging 2021; 1:932-947. [PMID: 36172600 PMCID: PMC9514594 DOI: 10.1038/s43587-021-00122-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
The evident genetic, pathological, and clinical heterogeneity of Alzheimer's disease (AD) poses challenges for traditional drug development. We conducted a computational drug repurposing screen for drugs to treat apolipoprotein (apo) E4-related AD. We first established apoE-genotype-dependent transcriptomic signatures of AD by analyzing publicly-available human brain database. We then queried these signatures against the Connectivity Map database containing transcriptomic perturbations of >1300 drugs to identify those that best reverse apoE-genotype-specific AD signatures. Bumetanide was identified as a top drug for apoE4 AD. Bumetanide treatment of apoE4 mice without or with Aβ accumulation rescued electrophysiological, pathological, or cognitive deficits. Single-nucleus RNA-sequencing revealed transcriptomic reversal of AD signatures in specific cell types in these mice, a finding confirmed in apoE4-iPSC-derived neurons. In humans, bumetanide exposure was associated with a significantly lower AD prevalence in individuals over the age of 65 in two electronic health record databases, suggesting effectiveness of bumetanide in preventing AD.
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Affiliation(s)
- Alice Taubes
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Phil Nova
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Kelly A. Zalocusky
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Misha Y. Zilberter
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Yanxia Hao
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
| | - Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Surgery, University of California, San Francisco, CA 94143, USA
| | - Bin Chen
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
| | - Emily A. Aery Jones
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Krishna Choudhary
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Brian Grone
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Maureen E. Balestra
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Fayzan Chaudhry
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Ishan Paranjpe
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Jessica De Freitas
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Nicole Koutsodendris
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Development and Stem Cell Biology Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Nuo Chen
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Celine Wang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - William Chang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Alice An
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Benjamin S. Glicksberg
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
- Correspondence: Yadong Huang () or Marina Sirota ()
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
- Department of Pathology, University of California, San Francisco, CA 94143, USA
- Correspondence: Yadong Huang () or Marina Sirota ()
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