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Scott RC, Hsieh J, McTague A, Mahoney JM, Christian-Hinman CA. Merritt-Putnam Symposium | Developmental and Epileptic Encephalopathies-Current Concepts and Novel Approaches. Epilepsy Curr 2025:15357597251320142. [PMID: 40161506 PMCID: PMC11948268 DOI: 10.1177/15357597251320142] [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: 04/02/2025] Open
Abstract
Developmental and epileptic encephalopathies (DEEs) are among the most severe and difficult to treat epilepsies. Two broad strategies for understanding the etiology and impacts of DEEs include genetic and complex adaptive systems approaches. This review, inspired by the 2024 Merritt-Putnam Symposium, describes current perspectives of DEE, identifies limitations of current views, and discusses potential novel ways forward. First, we discuss the rationale for a reevaluation of the role of seizures in the pathogenesis of cognitive and behavioral impairments in DEE. Second, we discuss newly emerging methods employing neural organoids to study brain development and DEE in vitro. Third, we present recent precision therapy approaches for the clinical treatment of DEE. Lastly, we discuss computational systems approaches to understanding the genetic landscape of DEE. The severe and multifaceted impacts of DEE and associated comorbidities underscore the necessity of novel interdisciplinary approaches to produce an improved understanding of etiology and more effective treatment strategies.
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Affiliation(s)
- Rodney C. Scott
- Division of Neuroscience, Nemours Children's Hospital-Delaware, Wilmington, Delaware, USA
- Department of Neurology, Great Ormond Street Hospital, London, UK
| | - Jenny Hsieh
- Department of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, San Antonio, TX, USA
| | - Amy McTague
- Department of Neurology, Great Ormond Street Hospital, London, UK
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Tegtmeyer M, Liyanage D, Han Y, Hebert KB, Pei R, Way GP, Ryder PV, Hawes D, Tromans-Coia C, Cimini BA, Carpenter AE, Singh S, Nehme R. Combining NeuroPainting with transcriptomics reveals cell-type-specific morphological and molecular signatures of the 22q11.2 deletion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.16.623947. [PMID: 39605350 PMCID: PMC11601450 DOI: 10.1101/2024.11.16.623947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Neuropsychiatric conditions pose substantial challenges for therapeutic development due to their complex and poorly understood underlying mechanisms. High-throughput, unbiased phenotypic assays present a promising path for advancing therapeutic discovery, especially within disease-relevant neural tissues. Here, we introduce NeuroPainting, a novel adaptation of the Cell Painting assay, optimized for high-dimensional morphological phenotyping of neural cell types, including neurons, neuronal progenitor cells, and astrocytes derived from human stem cells. Using NeuroPainting, we quantified cell structure and organelle behavior across various brain cell types, creating a public dataset of over 4,000 cellular traits. This extensive dataset not only sets a new benchmark for phenotypic screening in neuropsychiatric research but also serves as a gold standard for the research community, enabling comparisons and validation of results. We then applied NeuroPainting to identify morphological signatures associated with the 22q11.2 deletion, a major genetic risk factor for schizophrenia. We observed profound cell-type-specific effects of the 22q11.2 deletion, with significant alterations in mitochondrial structure, endoplasmic reticulum organization, and cytoskeletal dynamics, particularly in astrocytes. Transcriptomic analysis revealed reduced expression of cell adhesion genes in 22q11.2 deletion astrocytes, consistent with recent post-mortem findings. Integrating the RNA sequencing data and morphological profiles uncovered a novel biological link between altered expression of specific cell adhesion molecules and observed changes in mitochondrial morphology in 22q11.2 deletion astrocytes. These findings underscore the power of combined phenomic and transcriptomic analyses to reveal mechanistic insights associated with human genetic variants of neuropsychiatric conditions.
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Tegtmeyer M, Arora J, Asgari S, Cimini BA, Nadig A, Peirent E, Liyanage D, Way GP, Weisbart E, Nathan A, Amariuta T, Eggan K, Haghighi M, McCarroll SA, O'Connor L, Carpenter AE, Singh S, Nehme R, Raychaudhuri S. High-dimensional phenotyping to define the genetic basis of cellular morphology. Nat Commun 2024; 15:347. [PMID: 38184653 PMCID: PMC10771466 DOI: 10.1038/s41467-023-44045-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 11/28/2023] [Indexed: 01/08/2024] Open
Abstract
The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10-6) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.
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Affiliation(s)
- Matthew Tegtmeyer
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
- Centre for Gene Therapy and Regenerative Medicine, King's College, London, UK
| | - Jatin Arora
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samira Asgari
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ajay Nadig
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Emily Peirent
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dhara Liyanage
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gregory P Way
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Erin Weisbart
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Tiffany Amariuta
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Halıcıoğlu Data Science Institute, University of California, La Jolla, CA, USA
- Department of Medicine, University of California, La Jolla, CA, USA
| | - Kevin Eggan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Marzieh Haghighi
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven A McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Luke O'Connor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Anne E Carpenter
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Shantanu Singh
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Ralda Nehme
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Centre for Genetics and Genomics Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
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