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Gao J, Gunasekar S, Xia ZJ, Shalin K, Jiang C, Chen H, Lee D, Lee S, Pisal ND, Luo JN, Griciuc A, Karp JM, Tanzi R, Joshi N. Gene therapy for CNS disorders: modalities, delivery and translational challenges. Nat Rev Neurosci 2024:10.1038/s41583-024-00829-7. [PMID: 38898231 DOI: 10.1038/s41583-024-00829-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/23/2024] [Indexed: 06/21/2024]
Abstract
Gene therapy is emerging as a powerful tool to modulate abnormal gene expression, a hallmark of most CNS disorders. The transformative potentials of recently approved gene therapies for the treatment of spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and active cerebral adrenoleukodystrophy are encouraging further development of this approach. However, most attempts to translate gene therapy to the clinic have failed to make it to market. There is an urgent need not only to tailor the genes that are targeted to the pathology of interest but to also address delivery challenges and thereby maximize the utility of genetic tools. In this Review, we provide an overview of gene therapy modalities for CNS diseases, emphasizing the interconnectedness of different delivery strategies and routes of administration. Important gaps in understanding that could accelerate the clinical translatability of CNS genetic interventions are addressed, and we present lessons learned from failed clinical trials that may guide the future development of gene therapies for the treatment and management of CNS disorders.
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Affiliation(s)
- Jingjing Gao
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA.
- Center for Bioactive Delivery, Institute for Applied Life Sciences, University of Massachusetts, Amherst, MA, USA.
| | - Swetharajan Gunasekar
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ziting Judy Xia
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Kiruba Shalin
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA
| | - Christopher Jiang
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hao Chen
- Marine College, Shandong University, Weihai, China
| | - Dongtak Lee
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sohyung Lee
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Nishkal D Pisal
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA
| | - James N Luo
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Ana Griciuc
- Harvard Medical School, Boston, MA, USA.
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease and Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Jeffrey M Karp
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Rudolph Tanzi
- Harvard Medical School, Boston, MA, USA.
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease and Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Nitin Joshi
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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Zeighami Y, Bakken TE, Nickl-Jockschat T, Peterson Z, Jegga AG, Miller JA, Schulkin J, Evans AC, Lein ES, Hawrylycz M. A comparison of anatomic and cellular transcriptome structures across 40 human brain diseases. PLoS Biol 2023; 21:e3002058. [PMID: 37079537 PMCID: PMC10118126 DOI: 10.1371/journal.pbio.3002058] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 03/02/2023] [Indexed: 04/21/2023] Open
Abstract
Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular-based signature, based on differential co-expression, that is often unique to that disease. Brain diseases can be compared and aggregated based on the similarity of their signatures which often associates diseases from diverse phenotypic classes. Analysis of 40 common human brain diseases identifies 5 major transcriptional patterns, representing tumor-related, neurodegenerative, psychiatric and substance abuse, and 2 mixed groups of diseases affecting basal ganglia and hypothalamus. Further, for diseases with enriched expression in cortex, single-nucleus data in the middle temporal gyrus (MTG) exhibits a cell type expression gradient separating neurodegenerative, psychiatric, and substance abuse diseases, with unique excitatory cell type expression differentiating psychiatric diseases. Through mapping of homologous cell types between mouse and human, most disease risk genes are found to act in common cell types, while having species-specific expression in those types and preserving similar phenotypic classification within species. These results describe structural and cellular transcriptomic relationships of disease risk genes in the adult brain and provide a molecular-based strategy for classifying and comparing diseases, potentially identifying novel disease relationships.
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Affiliation(s)
- Yashar Zeighami
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, Canada
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Trygve E. Bakken
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa, United States of America
| | - Zeru Peterson
- Department of Psychiatry, Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa, United States of America
| | - Anil G. Jegga
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Jeremy A. Miller
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Jay Schulkin
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington, United States of America
| | - Alan C. Evans
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Ed S. Lein
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Michael Hawrylycz
- Allen Institute for Brain Science, Seattle, Washington, United States of America
- University of Washington, Department of Genome Sciences, Seattle, Washington, United States of America
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Liu L, Zhang Y, Niu G, Li Q, Li Z, Zhu T, Feng C, Liu X, Zhang Y, Xu T, Chen R, Teng X, Zhang R, Zou D, Ma L, Zhang Z. BrainBase: a curated knowledgebase for brain diseases. Nucleic Acids Res 2021; 50:D1131-D1138. [PMID: 34718720 PMCID: PMC8728122 DOI: 10.1093/nar/gkab987] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 10/01/2021] [Accepted: 10/07/2021] [Indexed: 12/23/2022] Open
Abstract
Brain is the central organ of the nervous system and any brain disease can seriously affect human health. Here we present BrainBase (https://ngdc.cncb.ac.cn/brainbase), a curated knowledgebase for brain diseases that aims to provide a whole picture of brain diseases and associated genes. Specifically, based on manual curation of 2768 published articles along with information retrieval from several public databases, BrainBase features comprehensive collection of 7175 disease–gene associations spanning a total of 123 brain diseases and linking with 5662 genes, 16 591 drug–target interactions covering 2118 drugs/chemicals and 623 genes, and five types of specific genes in light of expression specificity in brain tissue/regions/cerebrospinal fluid/cells. In addition, considering the severity of glioma among brain tumors, the current version of BrainBase incorporates 21 multi-omics datasets, presents molecular profiles across various samples/conditions and identifies four groups of glioma featured genes with potential clinical significance. Collectively, BrainBase integrates not only valuable curated disease–gene associations and drug–target interactions but also molecular profiles through multi-omics data analysis, accordingly bearing great promise to serve as a valuable knowledgebase for brain diseases.
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Affiliation(s)
- Lin Liu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China
| | - Yang Zhang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guangyi Niu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qianpeng Li
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhao Li
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tongtong Zhu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changrui Feng
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaonan Liu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuansheng Zhang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianyi Xu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China
| | - Ruru Chen
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xufei Teng
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rongqin Zhang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dong Zou
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China
| | - Lina Ma
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhang Zhang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,China National Center for Bioinformation, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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