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Zhang Y, Li F, Wu H, Du W, Shu J, Wang A, Xu C, Li C, Wang Y, Hu S. Genetic neurocognitive profile of autism unveiled with gene transcription. Neurobiol Dis 2025; 210:106925. [PMID: 40288424 DOI: 10.1016/j.nbd.2025.106925] [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: 12/24/2024] [Revised: 04/17/2025] [Accepted: 04/17/2025] [Indexed: 04/29/2025] Open
Abstract
How neurocognitive processes elaborate phenotypic heterogeneity within autism spectrum disorder (ASD) remains unknown. Applying the principal component analysis to the Neurosynth database, we established neurocognitive profiles to characterize the phenotypic heterogeneity of ASD, revealing a cortical hierarchical axis that separates the temporal cortex from other networks. By integrating neurocognitive profiles with transcriptomic data, we found that gene sets shaping the patterns of neurocognitive profiles are enriched in ASD-related biological processes and ASD pathogenic risk. Using a data-driven approach, we identified a topographic network for ASD, comprising the temporal, frontal, somatosensory, and visual cortices, with its transcriptomic signatures differentiating between regions over neurodevelopment. Additionally, functional reorganization in ASD within the topographic network has occurred with the temporal cortex as the central node. Collectively, our results reveal spatially covarying transcriptomic and neurocognitive profiles, emphasizing the influence of functional reorganization and its underlying genetic mechanism on phenotypic heterogeneity in ASD.
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Affiliation(s)
- Yingxing Zhang
- Child Healthcare Department, Anhui Provincial Children's Hospital, Hefei, Anhui 230022, PR China
| | - Fangfang Li
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui 230012, PR China
| | - Hongli Wu
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui 230012, PR China
| | - Wei Du
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui 230012, PR China
| | - Jianhua Shu
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui 230012, PR China
| | - Anqing Wang
- Medical Imaging Center, First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, PR China
| | - Chunsheng Xu
- Medical Imaging Center, First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, PR China
| | - Chuanfu Li
- Medical Imaging Center, First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, PR China
| | - Ya Wang
- Child Healthcare Department, Anhui Provincial Children's Hospital, Hefei, Anhui 230022, PR China.
| | - Sheng Hu
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui 230012, PR China; Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui 230026, PR China; Institute of Advanced Technology, University of Science and Technology of China, Hefei, Anhui 230000, PR China.
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2
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Duy PQ, Dylik B, Deniz E. Precision medicine in the pediatric and neonatal intensive care units through genomics. Curr Opin Pediatr 2025; 37:211-215. [PMID: 40298123 PMCID: PMC12055474 DOI: 10.1097/mop.0000000000001471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/30/2025]
Abstract
PURPOSE OF REVIEW Genome-wide sequencing technologies have revolutionized the understanding of human disorders and advanced precision medicine, especially for pediatric disorders. Here, we discuss the utility of genomic technologies in advancing the care of children admitted to the pediatric and neonatal intensive care units. RECENT FINDINGS Rapid molecular diagnosis permitted by genomic medicine has yielded clinically actionable findings that influence decision-making and facilitate timely therapeutic interventions. Identifying a genetic association provides a causal anchor to understanding disease biology at the single nucleotide resolution, revealing hidden biological heterogeneity that may be obscured by traditional imaging, laboratory, and pathological workup. The importance of a genetic diagnosis is further highlighted by the promise of gene therapy to correct the underlying genetic perturbation, as evidenced by the recent emergence of FDA-approved gene therapies for childhood genetic conditions. SUMMARY We predict that whole-genome sequencing, in conjunction with other omic technologies, will become critical diagnostic adjuncts in the clinical workup of critically ill children.
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Affiliation(s)
- Phan Q. Duy
- Department of Neuroscience, University of Virginia School of Medicine, Charlottesville, VA, USA
- Center for Brain Immunology and Glia, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Benjamin Dylik
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | - Engin Deniz
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
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3
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Sun Y, Li M, Ning C, Gao L, Liu Z, Zhong S, Lv J, Ke Y, Wang X, Ma Q, Liu Z, Wu S, Yu H, Zhao F, Zhang J, Gong Q, Liu J, Wu Q, Wang X, Chen X. Spatiotemporal 3D chromatin organization across multiple brain regions during human fetal development. Cell Discov 2025; 11:50. [PMID: 40374600 DOI: 10.1038/s41421-025-00798-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 02/21/2025] [Indexed: 05/17/2025] Open
Abstract
Elucidating the regulatory mechanisms underlying the development of different brain regions in humans is essential for understanding advanced cognition and neuropsychiatric disorders. However, the spatiotemporal organization of three-dimensional (3D) chromatin structure and its regulatory functions across different brain regions remain poorly understood. Here, we generated an atlas of high-resolution 3D chromatin structure across six developing human brain regions, including the prefrontal cortex (PFC), primary visual cortex (V1), cerebellum (CB), subcortical corpus striatum (CS), thalamus (TL), and hippocampus (HP), spanning gestational weeks 11-26. We found that the spatial and temporal dynamics of 3D chromatin organization play a key role in regulating brain region development. We also identified H3K27ac-marked super-enhancers as key contributors to shaping brain region-specific 3D chromatin structures and gene expression patterns. Finally, we uncovered hundreds of neuropsychiatric GWAS SNP-linked genes, shedding light on critical molecules in various neuropsychiatric disorders. In summary, our findings provide important insights into the 3D chromatin regulatory mechanisms governing brain region-specific development and can serve as a valuable resource for advancing our understanding of neuropsychiatric disorders.
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Affiliation(s)
- Yaoyu Sun
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Min Li
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Chao Ning
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Lei Gao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Zhenbo Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Suijuan Zhong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China
| | - Junjie Lv
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
- College of Biological Science, China Agricultural University, Beijing, China
| | - Yuwen Ke
- College of Biological Science, China Agricultural University, Beijing, China
| | - Xinxin Wang
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
| | - Qiang Ma
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | | | - Shuaishuai Wu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Hao Yu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Fangqi Zhao
- Obstetrics and Gynecology Medical Center of Severe Cardiovascular of Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jun Zhang
- Obstetrics and Gynecology Medical Center of Severe Cardiovascular of Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Qian Gong
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
| | - Jiang Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China
| | - Xiaoqun Wang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China.
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China.
- Changping Laboratory, Beijing, China.
| | - Xuepeng Chen
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China.
- The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangdong, China.
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4
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Gao Y, Dong Q, Arachchilage KH, Risgaard RD, Syed M, Sheng J, Schmidt DK, Jin T, Liu S, Sandoval SO, Knaack S, Eckholm MT, Chen RJ, Guo Y, Doherty D, Glass I, Levine JE, Wang D, Chang Q, Zhao X, Sousa AMM. Multimodal analyses reveal genes driving electrophysiological maturation of neurons in the primate prefrontal cortex. Neuron 2025:S0896-6273(25)00308-3. [PMID: 40398411 DOI: 10.1016/j.neuron.2025.04.025] [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: 05/09/2024] [Revised: 10/21/2024] [Accepted: 04/25/2025] [Indexed: 05/23/2025]
Abstract
The prefrontal cortex (PFC) is critical for myriad high-cognitive functions and is associated with several neuropsychiatric disorders. Here, using Patch-seq and single-nucleus multiomic analyses, we identified genes and regulatory networks governing the maturation of distinct neuronal populations in the PFC of rhesus macaque. We discovered that specific electrophysiological properties exhibited distinct maturational kinetics and identified key genes underlying these properties. We unveiled that RAPGEF4 is important for the maturation of resting membrane potential and inward sodium current in both macaque and human. We demonstrated that knockdown of CHD8, a high-confidence autism risk gene, in human and macaque organotypic slices led to impaired maturation, via downregulation of key genes, including RAPGEF4. Restoring the expression of RAPGEF4 rescued the proper electrophysiological maturation of CHD8-deficient neurons. Our study revealed regulators of neuronal maturation during a critical period of PFC development in primates and implicated such regulators in molecular processes underlying autism.
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Affiliation(s)
- Yu Gao
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Qiping Dong
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Ryan D Risgaard
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Moosa Syed
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jie Sheng
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Danielle K Schmidt
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ting Jin
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Soraya O Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Sara Knaack
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Magnus T Eckholm
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Rachel J Chen
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Yu Guo
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Dan Doherty
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Ian Glass
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Jon E Levine
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA; Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Daifeng Wang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
| | - Qiang Chang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neurology, University of Wisconsin-Madison, Madison, WI 53705, USA.
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA.
| | - Andre M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA.
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5
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Owen MJ, Bray NJ, Walters JTR, O'Donovan MC. Genomics of schizophrenia, bipolar disorder and major depressive disorder. Nat Rev Genet 2025:10.1038/s41576-025-00843-0. [PMID: 40355602 DOI: 10.1038/s41576-025-00843-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/10/2025] [Indexed: 05/14/2025]
Abstract
Schizophrenia, bipolar disorder and major depressive disorder - which are the most common adult disorders requiring psychiatric care - contribute substantially to premature mortality and morbidity globally. Treatments for these disorders are suboptimal, there are no diagnostic pathologies or biomarkers and their pathophysiologies are poorly understood. Novel therapeutic and diagnostic approaches are thus badly needed. Given the high heritability of psychiatric disorders, psychiatry has potentially much to gain from the application of genomics to identify molecular risk mechanisms and to improve diagnosis. Recent large-scale, genome-wide association studies and sequencing studies, together with advances in functional genomics, have begun to illuminate the genetic architectures of schizophrenia, bipolar disorder and major depressive disorder and to identify potential biological mechanisms. Genomic findings also point to the aetiological relationships between different diagnoses and to the relationships between adult psychiatric disorders and childhood neurodevelopmental conditions.
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Affiliation(s)
- Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Nicholas J Bray
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
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6
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Pérez Baca MDR, Palomares-Bralo M, Vanhooydonck M, Hamerlinck L, D'haene E, Leimbacher S, Jacobs EZ, De Cock L, D'haenens E, Dheedene A, Malfait Z, Vantomme L, Silva A, Rooney K, Zhao X, Saeidian AH, Owen NM, Santos-Simarro F, Lleuger-Pujol R, García-Miñaúr S, Losantos-García I, Menten B, Gestri G, Ragge N, Sadikovic B, Bogaert E, Vleminckx K, Naert T, Syx D, Callewaert B, Vergult S. Loss of function of the zinc finger homeobox 4 gene, ZFHX4, underlies a neurodevelopmental disorder. Am J Hum Genet 2025:S0002-9297(25)00149-1. [PMID: 40367947 DOI: 10.1016/j.ajhg.2025.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 04/18/2025] [Accepted: 04/18/2025] [Indexed: 05/16/2025] Open
Abstract
8q21.11 microdeletions involving ZFHX4 have previously been associated with a syndromic form of intellectual disability, hypotonia, unstable gait, and hearing loss. We report on 63 individuals-57 probands and 6 affected family members-with protein-truncating variants (n = 41), (micro)deletions (n = 21), or an inversion (n = 1) affecting ZFHX4. Probands display variable developmental delay and intellectual disability, distinctive facial characteristics, morphological abnormalities of the central nervous system, behavioral alterations, short stature, hypotonia, and occasionally cleft palate and anterior segment dysgenesis. The phenotypes associated with 8q21.11 microdeletions and ZFHX4 intragenic loss-of-function (LoF) variants largely overlap, although leukocyte-derived DNA shows a mild common methylation profile for (micro)deletions. ZFHX4 shows increased expression during human brain development and neuronal differentiation. Furthermore, ZFHX4-interacting factors identified via immunoprecipitation followed by mass spectrometry (IP-MS) suggest an important role for ZFHX4 in cellular pathways, especially during histone modifications, protein trafficking, signal transduction, cytosolic transport, and development. Additionally, using CUT&RUN, we observed that ZFHX4 binds the promoter of genes with crucial roles in embryonic, neuronal, and axonal development. Moreover, we investigated whether the disruption of zfhx4 causes craniofacial abnormalities in zebrafish. First-generation (F0) zfhx4 crispant zebrafish, a (mosaic) mutant for zfhx4 LoF variants, have significantly shorter Meckel's cartilage and smaller ethmoid plates compared to control zebrafish. Behavioral assays showed a decreased movement frequency in the zfhx4 crispant zebrafish in comparison with controls. Furthermore, structural abnormalities were found in the zebrafish hindbrain. In conclusion, our findings delineate a ZFHX4-associated neurodevelopmental disorder and suggest a role for zfhx4 in facial skeleton patterning, palatal development, and behavior.
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Affiliation(s)
- María Del Rocío Pérez Baca
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - María Palomares-Bralo
- CIBERER-ISCIII and INGEMM, Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, Madrid, Spain; ITHACA-European Reference Network, Madrid, Spain
| | - Michiel Vanhooydonck
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Lisa Hamerlinck
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Eva D'haene
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Sebastian Leimbacher
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Eva Z Jacobs
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Laurenz De Cock
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium; Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Erika D'haenens
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Annelies Dheedene
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Zoë Malfait
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Lies Vantomme
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Ananilia Silva
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Kathleen Rooney
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, ON, Canada
| | - Xiaonan Zhao
- Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Genetics Laboratories, One Baylor Plaza, R806, Houston, TX 77030, USA
| | - Amir Hossein Saeidian
- Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Genetics Laboratories, One Baylor Plaza, R806, Houston, TX 77030, USA
| | - Nichole Marie Owen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Genetics Laboratories, One Baylor Plaza, R806, Houston, TX 77030, USA
| | - Fernando Santos-Simarro
- Unit of Molecular Diagnostics and Clinical Genetics, Hospital Universitari Son Espases, Health Research Institute of the Balearic Islands (IdiSBa), Palma, Spain
| | - Roser Lleuger-Pujol
- Hereditary Cancer Program, Catalan Institute of Oncology, Doctor Josep Trueta University Hospital, Precision Oncology Group (OncoGIR-Pro), Institut d'Investigació Biomèdica de Girona (IDIGBI), Girona, Spain
| | - Sixto García-Miñaúr
- CIBERER-ISCIII and INGEMM, Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, Madrid, Spain; ITHACA-European Reference Network, Madrid, Spain
| | | | - Björn Menten
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Gaia Gestri
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Nicola Ragge
- Birmingham Women's and Children's NHS Foundation Trust, Clinical Genetics Unit, Birmingham Womens Hospital, Lavender House, Mindelsohn Way, Edgbaston, Birmingham B15 2TG, UK
| | - Bekim Sadikovic
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada; Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, ON, Canada
| | - Elke Bogaert
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Kris Vleminckx
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Thomas Naert
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Delfien Syx
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Bert Callewaert
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
| | - Sarah Vergult
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
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7
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Davis CN, Khan Y, Toikumo S, Jinwala Z, Boomsma DI, Levey DF, Gelernter J, Kember RL, Kranzler HR. Integrating HiTOP and RDoC frameworks part II: shared and distinct biological mechanisms of externalizing and internalizing psychopathology. Psychol Med 2025; 55:e137. [PMID: 40340892 DOI: 10.1017/s0033291725000819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/10/2025]
Abstract
BACKGROUND The Hierarchical Taxonomy of Psychopathology (HiTOP) and Research Domain Criteria (RDoC) frameworks emphasize transdiagnostic and mechanistic aspects of psychopathology. We used a multi-omics approach to examine how HiTOP's psychopathology spectra (externalizing [EXT], internalizing [INT], and shared EXT + INT) map onto RDoC's units of analysis. METHODS We conducted analyses across five RDoC units of analysis: genes, molecules, cells, circuits, and physiology. Using genome-wide association studies from the companion Part I article, we identified genes and tissue-specific expression patterns. We used drug repurposing analyses that integrate gene annotations to identify potential therapeutic targets and single-cell RNA sequencing data to implicate brain cell types. We then used magnetic resonance imaging data to examine brain regions and circuits associated with psychopathology. Finally, we tested causal relationships between each spectrum and physical health conditions. RESULTS Using five gene identification methods, EXT was associated with 1,759 genes, INT with 454 genes, and EXT + INT with 1,138 genes. Drug repurposing analyses identified potential therapeutic targets, including those that affect dopamine and serotonin pathways. Expression of EXT genes was enriched in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT + INT liability was associated with reduced gray matter volume in the amygdala and subcallosal cortex. INT genetic liability showed stronger causal effects on physical health - including chronic pain and cardiovascular diseases - than EXT. CONCLUSIONS Our findings revealed shared and distinct pathways underlying psychopathology. Integrating genomic insights with the RDoC and HiTOP frameworks advanced our understanding of mechanisms that underlie EXT and INT psychopathology.
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Affiliation(s)
- Christal N Davis
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Yousef Khan
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Zeal Jinwala
- Department of Psychiatry, Center for Studies of Addiction, 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, The Netherlands and Amsterdam Reproduction and Development Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Daniel F Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Psychiatry Division, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- Psychiatry Division, 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
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
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8
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Khan Y, Davis CN, Jinwala Z, Feuer KL, Toikumo S, Hartwell EE, Sanchez-Roige S, Peterson RE, Hatoum AS, Kranzler HR, Kember RL. Transdiagnostic and Disorder-Level GWAS Enhance Precision of Substance Use and Psychiatric Genetic Risk Profiles in African and European Ancestries. Biol Psychiatry 2025:S0006-3223(25)01180-1. [PMID: 40345609 DOI: 10.1016/j.biopsych.2025.04.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 02/20/2025] [Accepted: 04/21/2025] [Indexed: 05/11/2025]
Abstract
BACKGROUND Substance use disorders (SUDs) and psychiatric disorders frequently co-occur, and their etiology likely reflects both transdiagnostic (i.e., common/shared) and disorder-level (i.e., independent/nonshared) genetic influences. Understanding the genetic influences that are shared and those that operate independently of the shared risk could enhance precision in diagnosis, prevention, and treatment, but this remains underexplored, particularly in non-European ancestry groups. METHODS We applied genomic structural equation modeling to examine the common and independent genetic architecture among SUDs and psychotic, mood, and anxiety disorders using summary statistics from genome-wide association studies (GWAS) conducted in European- (EUR) and African-ancestry (AFR) individuals. To characterize the biological and phenotypic associations, we used FUMA, conducted genetic correlations, and performed phenome-wide association studies (PheWAS). RESULTS In EUR individuals, transdiagnostic genetic factors represented SUDs, psychotic, and mood/anxiety disorders, with GWAS identifying two novel lead single-nucleotide polymorphisms (SNPs) for the mood factor. In AFR individuals, genetic factors represented SUDs and psychiatric disorders, and GWAS identified one novel lead SNP for the SUD factor. In EUR individuals, second-order factor models showed phenotypic and genotypic associations with a broad range of physical and mental health traits. Finally, genetic correlations and PheWAS highlighted how common and independent genetic factors for SUD and psychotic disorders were differentially associated with psychiatric, sociodemographic, and medical phenotypes. CONCLUSIONS Combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for identifying more effective prevention and treatment strategies to reduce the burden of these disorders.
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Affiliation(s)
- Yousef Khan
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104
| | - Christal N Davis
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104
| | - Zeal Jinwala
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104
| | - Kyra L Feuer
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104
| | - Sylvanus Toikumo
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104
| | - Emily E Hartwell
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, United States; Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37235, United States; Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Roseann E Peterson
- Institute for Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, United States
| | - Alexander S Hatoum
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104.
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9
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Zhao Q, Xu J, Shi Z, Zhang Y, Du X, Zhai Y, Xu J, Liu F, Zhang Q. Genome-wide Pleiotropy Analysis Reveals Shared Genetic Associations between Type 2 Diabetes Mellitus and Subcortical Brain Volumes. RESEARCH (WASHINGTON, D.C.) 2025; 8:0688. [PMID: 40330659 PMCID: PMC12053431 DOI: 10.34133/research.0688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2025] [Revised: 03/31/2025] [Accepted: 04/07/2025] [Indexed: 05/08/2025]
Abstract
Type 2 diabetes mellitus (T2DM), a prevalent metabolic disorder marked by insulin resistance and hyperglycemia, has been linked to volumetric changes in subcortical regions, yet the genetic basis of this relationship remains unclear. We analyzed genome-wide association study summary data for T2DM and 14 subcortical volumetric traits, using MiXeR to quantify shared genetic architecture and applying conditional/conjunctional false discovery rate analyses to detect novel and shared genomic loci. Enrichment and gene expression analyses were subsequently performed to explore the biological functions and mechanisms of genes associated with these loci. We observed a substantial proportion of trait-influencing variants shared between T2DM and subcortical structures, with Dice coefficients ranging from 22.4% to 49.6%. Additionally, 70 distinct loci were identified as being jointly associated with T2DM and subcortical volumes, 5 and 22 of which were novel for T2DM and subcortical volumes, respectively. The 769 protein-coding genes mapped to these shared loci are enriched in metabolic and neurodevelopmental pathways and exhibit specific developmental trajectories, with 117 genes showing expression levels linked to both T2DM and subcortical structures. This study uncovered polygenic overlap between T2DM and subcortical structures, deepening our comprehension of the genetic factors linking metabolic disorders and brain health.
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Affiliation(s)
| | | | | | - Yang Zhang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Xin Du
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ying Zhai
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jinglei Xu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Feng Liu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Quan Zhang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology,
Tianjin Medical University General Hospital, Tianjin 300052, China
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10
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Rios A, Fujita K, Isomura Y, Sato N. Adaptive circuits for action and value information in rodent operant learning. Neurosci Res 2025; 214:62-68. [PMID: 39341460 DOI: 10.1016/j.neures.2024.09.003] [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: 09/18/2024] [Revised: 09/18/2024] [Accepted: 09/19/2024] [Indexed: 10/01/2024]
Abstract
Operant learning is a behavioral paradigm where animals learn to associate their actions with consequences, adapting their behavior accordingly. This review delves into the neural circuits that underpin operant learning in rodents, emphasizing the dynamic interplay between neural pathways, synaptic plasticity, and gene expression changes. We explore the cortico-basal ganglia circuits, highlighting the pivotal role of dopamine in modulating these pathways to reinforce behaviors that yield positive outcomes. We include insights from recent studies, which reveals the intricate roles of midbrain dopamine neurons in integrating action initiation and reward feedback, thereby enhancing movement-related activities in the dorsal striatum. Additionally, we discuss the molecular diversity of striatal neurons and their specific roles in reinforcement learning. The review also covers advances in transcriptome analysis techniques, such as single-cell RNA sequencing, which have provided deeper insights into the gene expression profiles associated with different neuronal populations during operant learning.
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Affiliation(s)
- Alain Rios
- Department of Physiology and Cell Biology, Tokyo Medical and Dental University (TMDU), Japan.
| | - Kyohei Fujita
- Department of Physiology and Cell Biology, Tokyo Medical and Dental University (TMDU), Japan
| | - Yoshikazu Isomura
- Department of Physiology and Cell Biology, Tokyo Medical and Dental University (TMDU), Japan.
| | - Nobuya Sato
- Department of Psychological Sciences Kwansei Gakuin University, Japan.
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11
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da Silva Castanheira J, Poli J, Hansen JY, Misic B, Baillet S. Genetic Foundations of Inter-individual Neurophysiological Variability. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.07.19.604292. [PMID: 39071281 PMCID: PMC11275903 DOI: 10.1101/2024.07.19.604292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Neurophysiological brain activity shapes cognitive functions and individual traits. Here, we investigated the extent to which individual neurophysiological properties are genetically determined and how these adult traits align with cortical gene expression patterns across development. Using task-free magnetoencephalography in monozygotic and dizygotic twins, as well as unrelated individuals, we found that neurophysiological traits were significantly more similar between monozygotic twins, indicating a genetic influence, although individual-specific variability remained predominant. These heritable brain dynamics were predominantly associated with genes involved in neurotransmission, expressed along a topographical gradient that mirrors psychological functions, including attention, planning, and emotional processes. Furthermore, the cortical expression patterns of genes associated with individual differentiation aligned most strongly with gene expression profiles observed during adulthood in previously published longitudinal datasets. These findings underscore a persistent genetic influence on neurophysiological activity, supporting individual cognitive and behavioral variability.
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12
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Gao X, Wang X, Zheng X, Zhao Y, Wang N, Chang S, Yang L. Chemical Pollutant Exposure in Neurodevelopmental Disorders: Integrating Toxicogenomic and Transcriptomic Evidence to Elucidate Shared Biological Mechanisms and Developmental Signatures. TOXICS 2025; 13:282. [PMID: 40278598 PMCID: PMC12031255 DOI: 10.3390/toxics13040282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2025] [Revised: 03/19/2025] [Accepted: 03/27/2025] [Indexed: 04/26/2025]
Abstract
Rapid industrialization has introduced a range of chemicals into the environment, posing significant risks to fetal and child brain development. Using the Comparative Toxicogenomics Database (CTD), we constructed chemical exposome frameworks for seven neurodevelopmental disorders (NDDs) and identified chemical pollutants of epidemiological concern, including air pollutants (n = 8), toxic elements (n = 14), pesticides and related compounds (n = 18), synthetic organic chemicals (n = 16), and solvents (n = 5). Gene set enrichment analysis validated and revealed significant toxicogenomic associations between these chemical pollutants and NDDs, including autism spectrum disorder (ASD) (12 pollutants, proportional reporting ratio (PRR) 3.56-7.21) and intellectual disability (ID) (9 pollutants, PRR 3.13-5.59). Functional annotation of pollutant-specific gene sets highlighted shared biological processes, such as metabolic processes (e.g., xenobiotic metabolic process, xenobiotic catabolic process, and cytochrome P450 pathway) for ASD and cognitive processes (e.g., cognition, social behavior, and synapse assembly) for ID (Bonferroni-corrected p-values < 0.05). Time trajectory analysis of developmental transcriptomic data from the BrainSpan database for ASD (275 genes) and ID (93 genes) revealed three distinct expression patterns of chemical-pollutant-associated genes-higher prenatal, postnatal, and perinatal expression-indicating common and divergent underlying mechanisms across critical windows of chemical pollutant exposure.
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Affiliation(s)
- Xuping Gao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 HuayuanBei Road, Beijing 100191, China; (X.G.)
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No. 601 Huangpu Road West, Guangzhou 510632, China
| | - Xinyue Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 HuayuanBei Road, Beijing 100191, China; (X.G.)
| | - Xiangyu Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 HuayuanBei Road, Beijing 100191, China; (X.G.)
| | - Yilu Zhao
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, No. 305 Tianmushan Street, Hangzhou 310007, China
| | - Ning Wang
- Department of Clinical Psychology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Road, Beijing 100029, China
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 HuayuanBei Road, Beijing 100191, China; (X.G.)
| | - Li Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 HuayuanBei Road, Beijing 100191, China; (X.G.)
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13
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Genc S, Ball G, Chamberland M, Raven EP, Tax CMW, Ward I, Yang JYM, Palombo M, Jones DK. MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression. Nat Commun 2025; 16:3317. [PMID: 40195348 PMCID: PMC11977195 DOI: 10.1038/s41467-025-58604-w] [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: 08/08/2024] [Accepted: 03/27/2025] [Indexed: 04/09/2025] Open
Abstract
Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss. Recent advances in MRI hardware and biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. Using ultra-strong gradient MRI, this study quantifies cortical neurite and soma microstructure in typically developing youth. Across domain-specific networks, cortical neurite signal fraction, attributed to neuronal and glial processes, increases with age. The apparent soma radius, attributed to the apparent radius of glial and neuronal cell bodies, decreases with age. Analyses of two independent post-mortem datasets reveal that genes increasing in expression through adolescence are significantly enriched in cortical oligodendrocytes and Layer 5-6 neurons. In our study, we show spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes, suggesting that ongoing cortical myelination processes drive adolescent cortical development.
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Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK.
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, VIC, Australia.
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, VIC, Australia.
| | - Gareth Ball
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Institute for Translational Neuroscience, NYU Grossman School of Medicine, New York, NY, USA
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Isobel Ward
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Joseph Y M Yang
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Neuroscience Research, Clinical Sciences, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
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14
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Hu B, Yin MY, Zhang CY, Shi Z, Wang L, Lei X, Li M, Li SW, Tuo QH. The INO80E at 16p11.2 locus increases risk of schizophrenia in humans and induces schizophrenia-like phenotypes in mice. EBioMedicine 2025; 114:105645. [PMID: 40088626 PMCID: PMC11957503 DOI: 10.1016/j.ebiom.2025.105645] [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: 05/21/2024] [Revised: 02/28/2025] [Accepted: 02/28/2025] [Indexed: 03/17/2025] Open
Abstract
BACKGROUND Chromosome 16p11.2 is one of the most significant loci in the genome-wide association studies (GWAS) of schizophrenia. Despite several integrative analyses and functional genomics studies having been carried out to identify possible risk genes, their impacts in the pathogenesis of schizophrenia remain to be fully characterized. METHODS We performed expression quantitative trait loci (eQTL) and summary-data-based Mendelian randomization (SMR) analyses to identify schizophrenia risk genes in the 16p11.2 GWAS locus. We constructed a murine model with dysregulated expression of risk gene in the medial prefrontal cortex (mPFC) using stereotaxic injection of adeno-associated virus (AAV), followed by behavioural assessments, dendritic spine analyses and RNA sequencing. FINDINGS We identified significant associations between elevated INO80E mRNA expression in the frontal cortex and risk of schizophrenia. The mice overexpressing Ino80e in mPFC (Ino80e-OE) exhibited schizophrenia-like behaviours, including increased anxiety behaviour, anhedonia, and impaired prepulse inhibition (PPI) when compared with control group. The neuronal sparse labelling assay showed that the density of stubby spines in the pyramidal neurons of mPFC was significantly increased in Ino80e-OE mice compared with control mice. Transcriptomic analysis in the mPFC revealed significant alterations in the mRNA levels of schizophrenia-related genes and processes related to synapses upon overexpressing Ino80e. INTERPRETATION Our results suggest that upregulation of the Ino80e gene in mPFC may induce schizophrenia-like behaviours in mice, further supporting the hypothesis that INO80E is an authentic risk gene. FUNDING This project received support from the National Key Research and Development Program of China, National Natural Science Foundation of China, Key Research and Development Projects of Hunan Provincial Science and Technology Department, Science and Technology Innovation team of Hunan Province, etc.
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Affiliation(s)
- Bo Hu
- Hunan Key Laboratory of Vascular Biology and Translational Medicine, Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Mei-Yu Yin
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chu-Yi Zhang
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Zhe Shi
- Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Pharmacy of School, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Lu Wang
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiaoming Lei
- Hunan Key Laboratory of Vascular Biology and Translational Medicine, Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Ming Li
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Shi-Wu Li
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Qin-Hui Tuo
- Hunan Key Laboratory of Vascular Biology and Translational Medicine, Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, China.
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15
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McCluskey KE, Stovell KM, Law K, Kostyanovskaya E, Schmidt JD, Exner CRT, Dea J, Brimble E, State MW, Willsey AJ, Willsey HR. Autism gene variants disrupt enteric neuron migration and cause gastrointestinal dysmotility. Nat Commun 2025; 16:2238. [PMID: 40050271 PMCID: PMC11885846 DOI: 10.1038/s41467-025-57342-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 02/12/2025] [Indexed: 03/09/2025] Open
Abstract
The co-occurrence of autism and gastrointestinal distress is well-established, yet the molecular underpinnings remain unknown. The identification of high-confidence, large-effect autism genes offers the opportunity to identify convergent, underlying biology by studying these genes in the context of the gastrointestinal system. Here we show that the expression of these genes is enriched in human prenatal gut neurons and their migratory progenitors, suggesting that the development and/or function of these neurons may be disrupted by autism-associated genetic variants, leading to gastrointestinal dysfunction. Here we document the prevalence of gastrointestinal issues in patients with large-effect variants in sixteen autism genes, highlighting dysmotility, consistent with potential enteric neuron dysfunction. Using Xenopus tropicalis, we individually target five of these genes (SYNGAP1, CHD8, SCN2A, CHD2, and DYRK1A) and observe disrupted enteric neuronal progenitor migration for each. Further analysis of DYRK1A reveals that perturbation causes gut dysmotility in vivo, which can be ameliorated by treatment with either of two serotonin signaling modulators, identified by in vivo drug screening. This work suggests that atypical development of enteric neurons contributes to the gastrointestinal distress commonly seen in individuals with autism and that serotonin signaling may be a productive therapeutic pathway.
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Affiliation(s)
- Kate E McCluskey
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Katherine M Stovell
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Karen Law
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Elina Kostyanovskaya
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - James D Schmidt
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Cameron R T Exner
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Jeanselle Dea
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | | | - Matthew W State
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - A Jeremy Willsey
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Helen Rankin Willsey
- Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
- Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, USA.
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16
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Clarence T, Bendl J, Cao X, Wang X, Zheng S, Hoffman GE, Kozlenkov A, Hong A, Iskhakova M, Jaiswal MK, Murphy S, Yu A, Haroutunian V, Dracheva S, Akbarian S, Fullard JF, Yuan GC, Lee D, Roussos P. Multiomic single-cell profiling identifies critical regulators of postnatal brain. Nat Genet 2025; 57:591-603. [PMID: 39962241 DOI: 10.1038/s41588-025-02083-8] [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: 02/25/2024] [Accepted: 01/08/2025] [Indexed: 03/15/2025]
Abstract
Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.
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Affiliation(s)
- Tereza Clarence
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, 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.
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Xuan Cao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Xinyi Wang
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Shiwei Zheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Alexey Kozlenkov
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aram Hong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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 Iskhakova
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manoj K Jaiswal
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Sarah Murphy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Alexander Yu
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Stella Dracheva
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Schahram Akbarian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, 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
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, 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.
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA.
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA.
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17
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Li N, Du J, Yang Y, Zhao T, Wu D, Peng F, Wang D, Kong L, Zhou W, Hao A. Microglial PCGF1 alleviates neuroinflammation associated depressive behavior in adolescent mice. Mol Psychiatry 2025; 30:914-926. [PMID: 39215186 PMCID: PMC11835731 DOI: 10.1038/s41380-024-02714-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 08/15/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024]
Abstract
Epigenetics plays a crucial role in regulating gene expression during adolescent brain maturation. In adolescents with depression, microglia-mediated chronic neuroinflammation may contribute to the activation of cellular signaling cascades and cause central synapse loss. However, the exact mechanisms underlying the epigenetic regulation of neuroinflammation leading to adolescent depression remain unclear. In this study, we found that the expression of polycomb group 1 (PCGF1), an important epigenetic regulator, was decreased both in the plasma of adolescent major depressive disorder (MDD) patients and in the microglia of adolescent mice in a mouse model of depression. We demonstrated that PCGF1 alleviates neuroinflammation mediated by microglia in vivo and in vitro, reducing neuronal damage and improving depression-like behavior in adolescent mice. Mechanistically, PCGF1 inhibits the transcription of MMP10 by upregulating RING1B/H2AK119ub and EZH2/H3K27me3 in the MMP10 promoter region, specifically inhibiting microglia-mediated neuroinflammation. These results provide valuable insights into the pathogenesis of adolescent depression, highlighting potential links between histone modifications, neuroinflammation and nerve damage. Potential mechanisms of microglial PCGF1 regulates depression-like behavior in adolescent mice. Microglial PCGF1 inhibits NF-κB/MAPK pathway activation through regulation of RING1B/H2AK119ub and EZH2/H3K27me3 in the MMP10 promoter region, which attenuates neuroinflammation and ameliorates depression-like behaviors in adolescent mice.
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Affiliation(s)
- Naigang Li
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jingyi Du
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ying Yang
- Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, China
| | - Tiantian Zhao
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Dong Wu
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Fan Peng
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Dongshuang Wang
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Linghua Kong
- School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, China.
| | - Wenjuan Zhou
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
| | - Aijun Hao
- Key Laboratory for Experimental Teratology of Ministry of Education, Shandong Key Laboratory of Mental Disorders, Department of Anatomy and Histoembryology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
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18
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Zelco A, Joshi A. Single-Cell Analysis of Sex and Gender Differences in the Human Brain During Development and Disease. Cell Mol Neurobiol 2025; 45:20. [PMID: 40016536 PMCID: PMC11868228 DOI: 10.1007/s10571-025-01536-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2024] [Accepted: 02/07/2025] [Indexed: 03/01/2025]
Abstract
Sex and gender (SG) differences in the human brain are of interest to society and science as numerous processes are impacted by them, including brain development, behavior, and diseases. By collecting publicly available single-cell data from the in-utero to elderly age in healthy, Alzheimer's disease and multiple sclerosis samples, we identified and characterized SG-biased genes in ten brain cell types across 9 age and disease groups. Sex and gender differences in the transcriptome were present throughout the lifespan and across all cell types. Although there was limited overlap among SG-biased genes across different age and disease groups, we observed significant functional overlap. Female-biased genes are consistently enriched for brain-related processes, while male-biased genes are enriched for metabolic pathways. Additionally, mitochondrial genes showed a consistent female bias across cell types. We also found that androgen response elements (not estrogen) were significantly enriched in both male- and female-biased genes, and thymosin hormone targets being consistently enriched only in male-biased genes. We systematically characterised SG differences in brain development and brain-related disorders at a single-cell level, by analysing a total of publicly available 419,885 single nuclei from 161 human brain samples (72 females, 89 males). The significant enrichment of androgen (not estrogen) response elements in both male- and female-biased genes suggests that androgens are important regulators likely establishing these SG differences. Finally, we provide full characterization of SG-biased genes at different thresholds for the scientific community as a web resource.
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Affiliation(s)
- Aura Zelco
- Department of Clinical Science, Computational Biology Unit, University of Bergen, Bergen, Norway.
| | - Anagha Joshi
- Department of Clinical Science, Computational Biology Unit, University of Bergen, Bergen, Norway.
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras, Chennai, India.
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19
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Wang J, Zhang J, Li J, Gao Q, Chen J, Jia C, Gu X. Cortex-Specific Tmem169 Deficiency Induces Defects in Cortical Neuron Development and Autism-Like Behaviors in Mice. J Neurosci 2025; 45:e1072242024. [PMID: 39779369 PMCID: PMC11867004 DOI: 10.1523/jneurosci.1072-24.2024] [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: 06/07/2024] [Revised: 11/13/2024] [Accepted: 12/19/2024] [Indexed: 01/11/2025] Open
Abstract
The development of the nervous system is a complex process, with many challenging scientific questions yet to be resolved. Disruptions in brain development are strongly associated with neurodevelopmental disorders, such as intellectual disability and autism. While the genetic basis of autism is well established, the precise pathological mechanisms remain unclear. Variations on chromosome 2q have been linked to autism, yet the specific genes responsible for the disorder have not been identified. This study investigates the role of the transmembrane protein 169 (TMEM169) gene, located on human chromosome 2q35, which has not been previously characterized. Our findings indicate that Tmem169 is highly expressed in the nervous system, and its deletion in the male mouse dorsal forebrain results in neuronal morphological abnormalities and synaptic dysfunction. Notably, Tmem169-deficient mice, irrespective of sex, display behavioral traits resembling those observed in individuals with autism. These results suggest that Tmem169 interacts with several key neuronal proteins, many of which are implicated in neurodevelopmental diseases. Furthermore, we demonstrate that Tmem169 promotes neuronal process and synapse development through its interaction with Shank3.
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Affiliation(s)
- Junhao Wang
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
| | - Jiwen Zhang
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
| | - Jinpeng Li
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
| | - Qiong Gao
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
| | - Jiawei Chen
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
| | - Chunhong Jia
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, China
| | - Xi Gu
- Fujian Key Laboratory for Translational Research in Cancer and Neurodegenerative Diseases, Institute for Translational Medicine, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
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20
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Venkatesan S, Werner JM, Li Y, Gillis J. Cell Type-Agnostic Transcriptomic Signatures Enable Uniform Comparisons of Neurodevelopment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.24.639936. [PMID: 40060479 PMCID: PMC11888278 DOI: 10.1101/2025.02.24.639936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/21/2025]
Abstract
Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a cell type's developmental state from its transcriptome remains a challenge. We perform a meta-analysis of developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors of developmental age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific cell type proportions reliably track developmental time across datasets. Training regularized regression models to infer cell-autonomous maturation, we find that a cell type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing developmental dynamics across diverse cell types and datasets. This model generalizes to human neural organoids, accurately predicting normal developmental trajectories (R = 0.91) and disease-induced shifts in vitro. Furthermore, it extends to the developing mouse brain, revealing an accelerated developmental tempo relative to humans. Our work provides a unified framework for comparing neurodevelopment across contexts, model systems, and species.
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Affiliation(s)
- Sridevi Venkatesan
- Department of Physiology, University of Toronto, Canada
- Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, Canada
- Terrence Donnelly Centre for Cellular and Biomolecular Research, Toronto, Canada
| | - Jonathan M Werner
- Terrence Donnelly Centre for Cellular and Biomolecular Research, Toronto, Canada
| | - Yun Li
- Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, Canada
- Department of Molecular Genetics, University of Toronto, Canada
| | - Jesse Gillis
- Department of Physiology, University of Toronto, Canada
- Terrence Donnelly Centre for Cellular and Biomolecular Research, Toronto, Canada
- Department of Molecular Genetics, University of Toronto, Canada
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21
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Liao Z, Kumar K, Kopal J, Huguet G, Saci Z, Jean-Louis M, Pausova Z, Jurisica I, Bearden CE, Jacquemont S, Paus T. Copy number variants and the tangential expansion of the cerebral cortex. Nat Commun 2025; 16:1697. [PMID: 39962045 PMCID: PMC11833094 DOI: 10.1038/s41467-025-56855-1] [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: 03/29/2024] [Accepted: 02/03/2025] [Indexed: 02/20/2025] Open
Abstract
The tangential expansion of the human cerebral cortex, indexed by its surface area (SA), occurs mainly during prenatal and early postnatal periods, and is influenced by genetic factors. Here we investigate the role of rare copy number variants (CNVs) in shaping SA, and the underlying mechanisms, by aggregating CNVs across the genome in community-based cohorts (N = 39,015). We reveal that genome-wide CNV deletions and duplications are associated with smaller SA. Subsequent analyses with gene expression in fetal cortex suggest that CNVs influence SA by interrupting the proliferation of neural progenitor cells during fetal development. Notably, the deletion of genes with strong (but not weak) coexpression with neural progenitor genes is associated with smaller SA. Follow up analyses reveal similar mechanisms at play in three clinical CNVs, 1q21.1, 16p11.2 and 22q11.2. Together, this study of rare CNVs expands our knowledge about genetic architecture of human cerebral cortex.
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Affiliation(s)
- Zhijie Liao
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada
- Departments of Psychiatry and Addictology, University of Montreal, Montreal, QC, Canada
| | - Kuldeep Kumar
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada
| | - Jakub Kopal
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | | | - Zohra Saci
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada
| | | | - Zdenka Pausova
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Pediatrics, University of Montreal, Montreal, QC, Canada
| | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Departments of Medical Biophysics and Computer Science, and the Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California-Los Angeles, Los Angeles, CA, USA
| | - Sebastien Jacquemont
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada.
- Department of Pediatrics, University of Montreal, Montreal, QC, Canada.
| | - Tomas Paus
- Centre de Recherche du CHU Sainte-Justine, Montreal, QC, Canada.
- Departments of Psychiatry and Addictology, University of Montreal, Montreal, QC, Canada.
- Department of Neuroscience, University of Montreal, Montreal, QC, Canada.
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22
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Liang L, Zhang S, Wang Z, Zhang H, Li C, Duhe AC, Sun X, Zhong X, Kozlova A, Jamison B, Wood W, Pang ZP, Sanders AR, He X, Duan J. Single-cell multiomics of neuronal activation reveals context-dependent genetic control of brain disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.17.638682. [PMID: 40027724 PMCID: PMC11870544 DOI: 10.1101/2025.02.17.638682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Despite hundreds of genetic risk loci identified for neuropsychiatric disorders (NPD), most causal variants/genes remain unknown. A major hurdle is that disease risk variants may act in specific biological contexts, e.g., during neuronal activation, which is difficult to study in vivo at the population level. Here, we conducted a single-cell multiomics study of neuronal activation (stimulation) in human iPSC-induced excitatory and inhibitory neurons from 100 donors, and uncovered abundant neuronal stimulation-specific causal variants/genes for NPD. We surveyed NPD-relevant transcriptomic and epigenomic landscape of neuronal activation and identified thousands of genetic variants associated with activity-dependent gene expression (i.e., eQTL) and chromatin accessibility (i.e., caQTL). These caQTL explained considerably larger proportions of NPD heritability than the eQTL. Integrating the multiomic data with GWAS further revealed NPD risk variants/genes whose effects were only detected upon stimulation. Interestingly, multiple lines of evidence support a role of activity-dependent cholesterol metabolism in NPD. Our work highlights the power of cell stimulation to reveal context-dependent "hidden" genetic effects.
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Affiliation(s)
- Lifan Liang
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Siwei Zhang
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, IL 60637, USA
| | - Zicheng Wang
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Hanwen Zhang
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
| | - Chuxuan Li
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra C. Duhe
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
| | - Xiaotong Sun
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Xiaoyuan Zhong
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Alena Kozlova
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
| | - Brendan Jamison
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
| | - Whitney Wood
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
| | - Zhiping P. Pang
- Department of Neuroscience and Cell Biology, Child Health Institute of New Jersey, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA
| | - Alan R. Sanders
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, IL 60637, USA
| | - Xin He
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, IL 60637, USA
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23
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Parker N, Ching CRK. Mapping Structural Neuroimaging Trajectories in Bipolar Disorder: Neurobiological and Clinical Implications. Biol Psychiatry 2025:S0006-3223(25)00107-6. [PMID: 39956253 DOI: 10.1016/j.biopsych.2025.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 01/23/2025] [Accepted: 02/11/2025] [Indexed: 02/18/2025]
Abstract
Neuroimaging is a powerful noninvasive method for studying brain alterations in bipolar disorder (BD). To date, most neuroimaging studies of BD have included smaller cross-sectional samples reporting case versus control comparisons, revealing small to moderate effect sizes. In this narrative review, we discuss the current state of structural neuroimaging studies using magnetic resonance imaging, which inform our understanding of altered brain trajectories in BD across the lifespan. Alternative methodologies such as those that model patient deviations from age-specific norms are discussed, which may help derive new markers of BD pathophysiology. We discuss evidence from neuroimaging genetics and transcriptomics studies, which attempt to bridge the gap between macroscale brain variations and underlying microscale neurodevelopmental mechanisms. We conclude with a look toward the future and how ambitious investments in longitudinal, deeply phenotyped, population-based cohorts can improve modeling of complex clinical factors and provide more clinically actionable brain markers for BD.
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Affiliation(s)
- Nadine Parker
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, Los Angeles, California.
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24
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Hu S, Wang Y, Wang X, Ji Y, Li C, Qiu B. Transcriptomic profiles link corticostriatal microarchitecture to genetics of neurodevelopment and neuropsychiatric risks. Transl Psychiatry 2025; 15:48. [PMID: 39934135 PMCID: PMC11814317 DOI: 10.1038/s41398-025-03260-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 12/18/2024] [Accepted: 01/24/2025] [Indexed: 02/13/2025] Open
Abstract
Many studies on macroscale organization have focused on only the cerebral cortex or striatum, leaving a large gap in the microstructural gradient of corticostriatal covariance. Here, we partitioned the striatum into seven distinct parcels and computed the microstructural covariance between each parcel and the cerebral cortex using T1-weighted/T2-weighted mapping. We found that corticostriatal microstructural covariance exhibited a microstructural gradient along the anterior-posterior axis of the striatum. The patterns of corticostriatal microstructural covariance are linked to geodesic distance and cell type-specific gene expression profiles, revealing a gradually attenuated relationship along the anterior-posterior axis of the striatum. Linking gene expression profile to corticostriatal microstructural patterns showed that the transcriptional variations in cell type-specific genes are different between the anterior and posterior striatum and suggested that anterior striatum are more enriched in psychiatric disorders. Moreover, at the genetic level, the corticostriatal microarchitecture showed a spatiotemporal trait during neurodevelopment. Finally, we identified the neural circuits from limbic and medial frontal cortex to striatum that contributes to the common neuropsychiatric disorders. Collectively, our findings reveal spatially covarying of transcriptional specializations with microarchitecture of corticostriatal covariance, highlighting the mechanisms underlying that neurodevelopmental corticostriatal circuits may be involved in neuropsychiatric disorders.
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Affiliation(s)
- Sheng Hu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China
- Institute of Advanced Technology, University of Science and Technology of China, Hefei, Anhui, China
- School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Yanming Wang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China
| | - Xiaoxiao Wang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China
| | - Yang Ji
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China
| | - Chuanfu Li
- Medical Imaging Center, First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
| | - Bensheng Qiu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China.
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25
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Davis CN, Khan Y, Toikumo S, Jinwala Z, Boomsma DI, Levey DF, Gelernter J, Kember RL, Kranzler HR. Integrating HiTOP and RDoC Frameworks Part I: Genetic Architecture of Externalizing and Internalizing Psychopathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.04.06.24305166. [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP). Methods We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Traits included clinical (e.g., major depressive disorder, alcohol use disorder) and subclinical measures (e.g., risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors. Results A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits. Conclusions The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.
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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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Liu Y, Luo X, Sun Y, Chen K, Hu T, You B, Xu J, Zhang F, Cheng Q, Meng X, Yan T, Li X, Qi X, He X, Guo X, Li C, Su B. Comparative single-cell multiome identifies evolutionary changes in neural progenitor cells during primate brain development. Dev Cell 2025; 60:414-428.e8. [PMID: 39481377 DOI: 10.1016/j.devcel.2024.10.005] [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: 11/03/2023] [Revised: 05/17/2024] [Accepted: 10/03/2024] [Indexed: 11/02/2024]
Abstract
Understanding the cellular and genetic mechanisms driving human-specific features of cortical development remains a challenge. We generated a cell-type resolved atlas of transcriptome and chromatin accessibility in the developing macaque and mouse prefrontal cortex (PFC). Comparing with published human data, our findings demonstrate that although the cortex cellular composition is overall conserved across species, progenitor cells show significant evolutionary divergence in cellular properties. Specifically, human neural progenitors exhibit extensive transcriptional rewiring in growth factor and extracellular matrix (ECM) pathways. Expression of the human-specific progenitor marker ITGA2 in the fetal mouse cortex increases the progenitor proliferation and the proportion of upper-layer neurons. These transcriptional divergences are primarily driven by altered activity in the distal regulatory elements. The chromatin regions with human-gained accessibility are enriched with human-specific sequence changes and polymorphisms linked to intelligence and neuropsychiatric disorders. Our results identify evolutionary changes in neural progenitors and putative gene regulatory mechanisms shaping primate brain evolution.
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Affiliation(s)
- Yuting Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing 100871, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China.
| | - Yiming Sun
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing 100871, China
| | - Kaimin Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Ting Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Benhui You
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Jiahao Xu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Fengyun Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qing Cheng
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing 210004, China
| | - Xiaoyu Meng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Tong Yan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Department of Histology and Embryology, Nanjing Medical University, Nanjing 211166, China
| | - Xiang Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Xiaoxuan Qi
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing 210004, China
| | - Xiechao He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Xuejiang Guo
- State Key Laboratory of Reproductive Medicine and Offspring Health, Department of Histology and Embryology, Nanjing Medical University, Nanjing 211166, China
| | - Cheng Li
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing 100871, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Yunnan Key Laboratory of Integrative Anthropology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.
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Degner KN, Bell JL, Jones SD, Won H. Just a SNP away: The future of in vivo massively parallel reporter assay. CELL INSIGHT 2025; 4:100214. [PMID: 39618480 PMCID: PMC11607654 DOI: 10.1016/j.cellin.2024.100214] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 10/03/2024] [Accepted: 10/06/2024] [Indexed: 04/03/2025]
Abstract
The human genome is largely noncoding, yet the field is still grasping to understand how noncoding variants impact transcription and contribute to disease etiology. The massively parallel reporter assay (MPRA) has been employed to characterize the function of noncoding variants at unprecedented scales, but its application has been largely limited by the in vitro context. The field will benefit from establishing a systemic platform to study noncoding variant function across multiple tissue types under physiologically relevant conditions. However, to date, MPRA has been applied to only a handful of in vivo conditions. Given the complexity of the central nervous system and its widespread interactions with all other organ systems, our understanding of neuropsychiatric disorder-associated noncoding variants would be greatly advanced by studying their functional impact in the intact brain. In this review, we discuss the importance, technical considerations, and future applications of implementing MPRA in the in vivo space with the focus on neuropsychiatric disorders.
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Affiliation(s)
- Katherine N. Degner
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica L. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sean D. Jones
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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28
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Jiang Z, Sullivan PF, Li T, Zhao B, Wang X, Luo T, Huang S, Guan PY, Chen J, Yang Y, Stein JL, Li Y, Liu D, Sun L, Zhu H. The X chromosome's influences on the human brain. SCIENCE ADVANCES 2025; 11:eadq5360. [PMID: 39854466 PMCID: PMC11759047 DOI: 10.1126/sciadv.adq5360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Accepted: 12/23/2024] [Indexed: 01/26/2025]
Abstract
Genes on the X chromosome are extensively expressed in the human brain. However, little is known for the X chromosome's impact on the brain anatomy, microstructure, and functional networks. We examined 1045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X chromosome interactions while proposing an atlas outlining dosage compensation for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we found unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.
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Affiliation(s)
- Zhiwen Jiang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Shuai Huang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Peter Y. Guan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jie Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Dajiang Liu
- Department of Public Health Sciences, Penn State University, Hershey, PA 17033, USA
- Department of Biochemistry and Molecular Biology, Penn State University, Hershey, PA 17033, USA
| | - Lei Sun
- Department of Statistical Sciences, University of Toronto, Toronto, ON M5G 1Z5, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Feng X, Gao Y, Chu F, Shan Y, Liu M, Wang Y, Zhu Y, Lu Q, Li M. Cortical arealization of interneurons defines shared and distinct molecular programs in developing human and macaque brains. Nat Commun 2025; 16:672. [PMID: 39809789 PMCID: PMC11733295 DOI: 10.1038/s41467-025-56058-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 01/06/2025] [Indexed: 01/16/2025] Open
Abstract
Cortical interneurons generated from ganglionic eminence via a long-distance journey of tangential migration display evident cellular and molecular differences across brain regions, which seeds the heterogeneous cortical circuitry in primates. However, whether such regional specifications in interneurons are intrinsically encoded or gained through interactions with the local milieu remains elusive. Here, we recruit 685,692 interneurons from cerebral cortex and subcortex including ganglionic eminence within the developing human and macaque species. Our integrative and comparative analyses reveal that less transcriptomic alteration is accompanied by interneuron migration within the ganglionic eminence subdivisions, in contrast to the dramatic changes observed in cortical tangential migration, which mostly characterize the transcriptomic specification for different destinations and for species divergence. Moreover, the in-depth survey of temporal regulation illustrates species differences in the developmental dynamics of cell types, e.g., the employment of CRH in primate interneurons during late-fetal stage distinguishes from their postnatal emergence in mice, and our entropy quantifications manifest the interneuron diversities gradually increase along the developmental ages in human and macaque cerebral cortices. Overall, our analyses depict the spatiotemporal features appended to cortical interneurons, providing a new proxy for understanding the relationship between cellular diversity and functional progression.
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Affiliation(s)
- Xiangling Feng
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yingjie Gao
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fan Chu
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuwen Shan
- National Demonstration Center for Experimental Basic Medical Education, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Meicheng Liu
- National Demonstration Center for Experimental Basic Medical Education, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaoyi Wang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Qing Lu
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mingfeng Li
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- The Key Laboratory for Drug Target Researches and Pharmacodynamic Evaluation of Hubei Province, Wuhan, China.
- Innovation center for Brain Medical Sciences, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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30
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Lee KS, Lee T, Kim M, Ignatova E, Ban HJ, Sung MK, Kim Y, Kim YJ, Han JH, Choi JK. Shared rare genetic variants in multiplex autism families suggest a social memory gene under selection. Sci Rep 2025; 15:696. [PMID: 39753649 PMCID: PMC11698849 DOI: 10.1038/s41598-024-83839-w] [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: 10/02/2023] [Accepted: 12/17/2024] [Indexed: 01/06/2025] Open
Abstract
Autism spectrum disorder (ASD) affects up to 1 in 59 children, and is one of the most common neurodevelopmental disorders. Recent genomic studies have highlighted the role of rare variants in ASD. This study aimed to identify genes affected by rare variants shared by siblings with ASD and validate the function of a candidate gene FRRS1L. By integrating the whole genome sequencing data of 866 multiplex families from the Hartwell Foundation's Autism Research and Technology Initiative and Autism Speaks MSSNG project, we identified rare variants shared by two or more siblings with ASD. Using shared rare variants (SRVs), we selected candidate genes for ASD. Gene prioritization by evolutionary features and expression alterations on autism identified FRRS1L in two families, including one with impaired social behaviors. One variant in this family was 6 bp away from human-specific trinucleotide fixation. Additionally, CRISPR/Cas9 experiments demonstrated downregulation by a family variant and upregulation by a fixed site. Population genetics further demonstrated that upregulation of this gene has been favored during human evolution. Various mouse behavioral tests showed that Frrs1l knockout specifically impairs social novelty recognition without altering other behavioral phenotypes. Furthermore, we constructed humanized mice by introducing human sequences into a mouse genome. These knockin mice showed improved abilities to retain social memory over time. The results of our population genetic and evolutionary analyses, behavior experiments, and genome editing propose a molecular mechanism that may confer a selective advantage through social memory enhancement and may cause autism-related social impairment when disrupted in humans. These findings highlight the role of FRRS1L, the AMPA receptor subunit, in social behavior and evolution.
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Affiliation(s)
- Kang Seon Lee
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Taeyeop Lee
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, 34141, Republic of Korea
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505, Republic of Korea
- Translational Biomedical Research Group, Asan Institute for Life Science, Asan Medical Center, Seoul, 05505, Republic of Korea
| | - Mujun Kim
- Department of Biological Sciences, KAIST, Daejeon, 34141, Republic of Korea
| | - Elizaveta Ignatova
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Hyo-Jeong Ban
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Min Kyung Sung
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Younghoon Kim
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Youn-Jae Kim
- Specific Organs Cancer Branch, National Cancer Center, Gyeonggi, 10408, Republic of Korea
| | - Jin-Hee Han
- Department of Biological Sciences, KAIST, Daejeon, 34141, Republic of Korea.
| | - Jung Kyoon Choi
- Department of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea.
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Sebenius I, Dorfschmidt L, Seidlitz J, Alexander-Bloch A, Morgan SE, Bullmore E. Structural MRI of brain similarity networks. Nat Rev Neurosci 2025; 26:42-59. [PMID: 39609622 DOI: 10.1038/s41583-024-00882-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2024] [Indexed: 11/30/2024]
Abstract
Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network.
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Affiliation(s)
- Isaac Sebenius
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
| | - Lena Dorfschmidt
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
| | - Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah E Morgan
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Edward Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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32
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Wagstyl K, Raznahan A. Converging cortical axes. Nat Neurosci 2025; 28:8-10. [PMID: 39572741 DOI: 10.1038/s41593-024-01722-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Affiliation(s)
- Konrad Wagstyl
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Armin Raznahan
- Section on Developmental Neurogenomics, NIMH Intramural Research Program, Bethesda, MD, USA.
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Rosoff DB, Wagner J, Bell AS, Mavromatis LA, Jung J, Lohoff FW. A multi-omics Mendelian randomization study identifies new therapeutic targets for alcohol use disorder and problem drinking. Nat Hum Behav 2025; 9:188-207. [PMID: 39528761 DOI: 10.1038/s41562-024-02040-1] [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: 07/13/2022] [Accepted: 10/01/2024] [Indexed: 11/16/2024]
Abstract
Integrating proteomic and transcriptomic data with genetic architectures of problematic alcohol use and alcohol consumption behaviours can advance our understanding and help identify therapeutic targets. We conducted systematic screens using genome-wise association study data from ~3,500 cortical proteins (N = 722) and ~6,100 genes in 8 canonical brain cell types (N = 192) with 4 alcohol-related outcomes (N ≤ 537,349), identifying 217 cortical proteins and 255 cell-type genes associated with these behaviours, with 36 proteins and 37 cell-type genes being new. Although there was limited overlap between proteome and transcriptome targets, downstream neuroimaging revealed shared neurophysiological pathways. Colocalization with independent genome-wise association study data further prioritized 16 proteins, including CAB39L and NRBP1, and 12 cell-type genes, implicating mechanisms such as mTOR signalling. In addition, genes such as SAMHD1, VIPAS39, NUP160 and INO80E were identified as having favourable neuropsychiatric profiles. These findings provide insights into the genetic landscapes governing problematic alcohol use and alcohol consumption behaviours, highlighting promising therapeutic targets for future research.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH Oxford-Cambridge Scholars Program, National Institutes of Health, Bethesda, MD, USA
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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Yi G, Li Z, Sun Y, Ma X, Wang Z, Chen J, Cai D, Zhang Z, Chen Z, Wu F, Cao M, Fu M. Integration of multi-omics transcriptome-wide analysis for the identification of novel therapeutic drug targets in diabetic retinopathy. J Transl Med 2024; 22:1146. [PMID: 39719581 DOI: 10.1186/s12967-024-05856-7] [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: 08/21/2024] [Accepted: 11/02/2024] [Indexed: 12/26/2024] Open
Abstract
BACKGROUND Diabetic retinopathy (DR) is the most important complication of Type 2 Diabetes (T2D) in eyes. Despite its prevalence, the early detection and management of DR continue to pose considerable challenges. Our research aims to elucidate potent drug targets that could facilitate the identification of DR and propel advancements in its therapeutic strategies. METHODS A broad multi-omics exploration of DR was presented to decipher the drug targets of DR and proliferative diabetic retinopathy (PDR). Transcriptome-Wide Association Studies (TWAS), fine-mapping and conditional analysis were applied to unearth potential tissue-specific gene associations with DR. Summary Data-based Mendelian Randomization (SMR) provided secondary analysis of high confidence genes. Cis-instrument of druggable genes were extracted from the eQTLGen Consortium and PsychENCODE, facilitating drug-target MR supported by colocalization analysis. Phenome-Wide Association Studies (PheWAS) was conducted on the high confidence genes. Metabolomic and immunomic MR-profiling further augmented our research as complement. RESULTS TWAS identified multiple robust genetic loci in both DR and PDR (WFS1, RPS26, and SRPK1) through genetic associations across different tissues. Meanwhile, we have delineated both the commonalities and discrepancies between DR and PDR at the transcriptomic level, represented by DCLRE1B as the hub gene that DR progressed into PDR. SMR revealed 92 key DR-related genes and 55 PDR-related genes. HLA-DQ family genes have a frequent occurrence, while RPS26, WFS1 and SRPK1 were validated as the genetic network's linchpins. Drug-target MR casted ERBB3 and SRPK1 as candidate effector genes for DR and PDR susceptibility. In addition, metabolomics and immunomics analyses also revealed multifaceted pathogenic factors for DR. CONCLUSIONS Our research offers targeted therapeutic insights for early-stage DR and facilitates multi-omic comparisons of it and PDR.
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Affiliation(s)
- Guoguo Yi
- Department of Ophthalmology, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China
- The Department of Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhengran Li
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Yuxin Sun
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Xinyu Ma
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China
| | - Zijin Wang
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Jinken Chen
- School of Architecture, South China University of Technology, Guangzhou, Guangdong, China
| | - Dong Cai
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China
| | - Ziran Zhang
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Zejun Chen
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Fanye Wu
- The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China
| | - Mingzhe Cao
- Department of Ophthalmology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, Guangdong Province, China
| | - Min Fu
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China.
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Al-Soufi L, Arana ÁJ, Facal F, Flórez G, Vázquez FL, Arrojo M, Sánchez L, Costas J. Identification of gene co-expression modules from zebrafish brain data: Applications in psychiatry illustrated through alcohol-related traits. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111136. [PMID: 39237023 DOI: 10.1016/j.pnpbp.2024.111136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 09/02/2024] [Indexed: 09/07/2024]
Abstract
Cumulative evidence suggests that zebrafish is a useful model in psychiatric research. Weighted Gene Co-expression Network Analysis (WGCNA) enables the reduction of genome-wide expression data to modules of highly co-expressed genes, which are hypothesized to interact within molecular networks. In this study, we first applied WGCNA to zebrafish brain expression data across different experimental conditions. Then, we characterized the different co-expression modules by gene-set enrichment analysis and hub gene-phenotype association. Finally, we analyzed association of polygenic risk scores (PRSs) based on genes of some interesting co-expression modules with alcohol dependence in 524 patients and 729 controls from Galicia, using competitive tests. Our approach revealed 34 co-expression modules in the zebrafish brain, with some showing enrichment in human synaptic genes, brain tissues, or brain developmental stages. Moreover, certain co-expression modules were enriched in psychiatry-related GWAS and comprised hub genes associated with psychiatry-related traits in both human GWAS and zebrafish models. Expression patterns of some co-expression modules were associated with the tested experimental conditions, mainly with substance withdrawal and cold stress. Notably, a PRS based on genes from co-expression modules exclusively associated with substance withdrawal in zebrafish showed a stronger association with human alcohol dependence than PRSs based on randomly selected brain-expressed genes. In conclusion, our analysis led to the identification of co-expressed gene modules that may model human brain gene networks involved in psychiatry-related traits. Specifically, we detected a cluster of co-expressed genes whose expression was exclusively associated with substance withdrawal in zebrafish, which significantly contributed to alcohol dependence susceptibility in humans.
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Affiliation(s)
- Laila Al-Soufi
- Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Psychiatric Genetics Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain; Department of Zoology, Genetics and Physical Anthropology, Faculty of Veterinary, University of Santiago de Compostela, Lugo, Spain
| | - Álvaro J Arana
- Department of Zoology, Genetics and Physical Anthropology, Faculty of Veterinary, University of Santiago de Compostela, Lugo, Spain
| | - Fernando Facal
- Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Psychiatric Genetics Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain; Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Gerardo Flórez
- Addictive Treatment Unit, Ourense University Hospital, Ourense, Galicia, Spain; Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Oviedo, Spain
| | - Fernando L Vázquez
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Manuel Arrojo
- Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Laura Sánchez
- Department of Zoology, Genetics and Physical Anthropology, Faculty of Veterinary, University of Santiago de Compostela, Lugo, Spain
| | - Javier Costas
- Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Psychiatric Genetics Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain; Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.
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Huang X, Kumarage P, Sandoval S, Zhao X, Wang D. Protocol for comparative gene expression data analysis between brains and organoids using a cloud-based web app. STAR Protoc 2024; 5:103375. [PMID: 39392746 PMCID: PMC11736003 DOI: 10.1016/j.xpro.2024.103375] [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: 05/14/2024] [Revised: 07/18/2024] [Accepted: 09/18/2024] [Indexed: 10/13/2024] Open
Abstract
Here, we present a protocol for using Brain and Organoid Manifold Alignment (BOMA), a cloud-based web app for comparative gene expression data analysis between brains and organoids. We describe steps for performing a global alignment of developmental gene expression data from both brains and organoids. We then detail procedures for investigating both shared and distinctive developmental pathways across brains and organoids by refining alignment locally using manifold learning. This protocol is applicable for working with single-cell and bulk RNA sequencing data. For complete details on the use and execution of this protocol, please refer to He et al.1.
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Affiliation(s)
- Xiang Huang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Pubudu Kumarage
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Soraya Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Neuroscience, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Daifeng Wang
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
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Amin ND, Kelley KW, Kaganovsky K, Onesto M, Hao J, Miura Y, McQueen JP, Reis N, Narazaki G, Li T, Kulkarni S, Pavlov S, Pașca SP. Generating human neural diversity with a multiplexed morphogen screen in organoids. Cell Stem Cell 2024; 31:1831-1846.e9. [PMID: 39642864 DOI: 10.1016/j.stem.2024.10.016] [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: 07/24/2023] [Revised: 07/31/2024] [Accepted: 10/28/2024] [Indexed: 12/09/2024]
Abstract
Morphogens choreograph the generation of remarkable cellular diversity in the developing nervous system. Differentiation of stem cells in vitro often relies upon the combinatorial modulation of these signaling pathways. However, the lack of a systematic approach to understand morphogen-directed differentiation has precluded the generation of many neural cell populations, and the general principles of regional specification and maturation remain incomplete. Here, we developed an arrayed screen of 14 morphogen modulators in human neural organoids cultured for over 70 days. Deconvolution of single-cell-multiplexed RNA sequencing data revealed design principles of brain region specification. We tuned neural subtype diversity to generate a tachykinin 3 (TAC3)-expressing striatal interneuron type within assembloids. To circumvent limitations of in vitro neuronal maturation, we used a neonatal rat transplantation strategy that enabled human Purkinje neurons to develop their hallmark complex dendritic branching. This comprehensive platform yields insights into the factors influencing stem cell-derived neural diversification and maturation.
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Affiliation(s)
- Neal D Amin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Kevin W Kelley
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Konstantin Kaganovsky
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Massimo Onesto
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Jin Hao
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Yuki Miura
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - James P McQueen
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Noah Reis
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Genta Narazaki
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Tommy Li
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Shravanti Kulkarni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Sergey Pavlov
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA
| | - Sergiu P Pașca
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute & Bio-X, Stanford, CA, USA.
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38
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Matoba N, Le BD, Valone JM, Wolter JM, Mory JT, Liang D, Aygün N, Broadaway KA, Bond ML, Mohlke KL, Zylka MJ, Love MI, Stein JL. Stimulating Wnt signaling reveals context-dependent genetic effects on gene regulation in primary human neural progenitors. Nat Neurosci 2024; 27:2430-2442. [PMID: 39349663 PMCID: PMC11633645 DOI: 10.1038/s41593-024-01773-6] [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: 05/04/2023] [Accepted: 08/28/2024] [Indexed: 10/09/2024]
Abstract
Gene regulatory effects have been difficult to detect at many non-coding loci associated with brain-related traits, likely because some genetic variants have distinct functions in specific contexts. To explore context-dependent gene regulation, we measured chromatin accessibility and gene expression after activation of the canonical Wnt pathway in primary human neural progenitors (n = 82 donors). We found that TCF/LEF motifs and brain-structure-associated and neuropsychiatric-disorder-associated variants were enriched within Wnt-responsive regulatory elements. Genetically influenced regulatory elements were enriched in genomic regions under positive selection along the human lineage. Wnt pathway stimulation increased detection of genetically influenced regulatory elements/genes by 66%/53% and enabled identification of 397 regulatory elements primed to regulate gene expression. Stimulation also increased identification of shared genetic effects on molecular and complex brain traits by up to 70%, suggesting that genetic variant function during neurodevelopmental patterning can lead to differences in adult brain and behavioral traits.
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Affiliation(s)
- Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brandon D Le
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jordan M Valone
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Justin M Wolter
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, Carrboro, NC, USA
| | - Jessica T Mory
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dan Liang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marielle L Bond
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mark J Zylka
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, Carrboro, NC, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Carolina Institute for Developmental Disabilities, Carrboro, NC, USA.
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39
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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. A temporal cortex cell atlas highlights gene expression dynamics during human brain maturation. Nat Genet 2024; 56:2718-2730. [PMID: 39567748 PMCID: PMC11631765 DOI: 10.1038/s41588-024-01990-6] [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: 09/22/2023] [Accepted: 10/15/2024] [Indexed: 11/22/2024]
Abstract
The human brain undergoes protracted postnatal 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 RNA sequencing on temporal lobe tissue, including samples of African ancestry, we build a joint pediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between pediatric and adult cell subtypes, 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 pediatric tissue. The 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, Cape Town, South Africa
- National Health Laboratory Service, Cape Town, 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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Yu L, Hu D, Luo Y, Lin W, Xu H, Xiao X, Xia Z, Dou Z, Zhao G, Yang L, Peng D, Zhang Q, Yu S. Transcriptional signatures of cortical structural changes in chronic insomnia disorder. Psychophysiology 2024; 61:e14671. [PMID: 39160694 DOI: 10.1111/psyp.14671] [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: 02/21/2024] [Revised: 06/30/2024] [Accepted: 08/05/2024] [Indexed: 08/21/2024]
Abstract
Chronic insomnia disorder (CID) is a multidimensional disease that may influence various levels of brain organization, spanning the macroscopic structural connectome to microscopic gene expression. However, the connection between genomic variations and morphological alterations in CID remains unclear. Here, we investigated brain structural changes in CID patients at the whole-brain level and whether these link to transcriptional characteristics. Brain structural data from 104 CID patients and 102 matched healthy controls (HC) were acquired to examine cortical structural alterations using morphometric similarity (MS) analysis. Partial least squares (PLS) regression and transcriptome data from the Allen Human Brain Atlas were used to extract genomes related to MS changes. Gene-category enrichment analysis (GCEA) was used to identify potential molecular mechanisms behind the observed structural changes. We found that CID patients exhibited MS reductions in the parietal and limbic regions, along with enhancements in the temporal and frontal regions compared to HCs (pFDR < .05). Subsequently, PLS and GCEA revealed that these MS alterations were spatially correlated with a set of genes, especially those significantly correlated with excitatory and inhibitory neurons and chronic neuroinflammation. This neuroimaging-transcriptomic study bridges the gap between cortical structural changes and the molecular mechanisms in CID patients, providing novel insight into the pathophysiology of insomnia and targeted treatments.
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Affiliation(s)
- Liyong Yu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Daijie Hu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of Traditional Chinese Medicine Rehabilitation, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Yucai Luo
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Wenting Lin
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Hao Xu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Xiangwen Xiao
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zihao Xia
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zeyang Dou
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Guangli Zhao
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Lu Yang
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Dezhong Peng
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Qi Zhang
- Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Siyi Yu
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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41
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Brusini L, Dolci G, Pini L, Cruciani F, Pizzagalli F, Provero P, Menegaz G, Boscolo Galazzo I. Morphometric Similarity Patterning of Amyloid- β and Tau Proteins Correlates with Transcriptomics in the Alzheimer's Disease Continuum. Int J Mol Sci 2024; 25:12871. [PMID: 39684582 DOI: 10.3390/ijms252312871] [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: 11/08/2024] [Revised: 11/23/2024] [Accepted: 11/26/2024] [Indexed: 12/18/2024] Open
Abstract
Bridging the gap between cortical morphometric remodeling and gene expression can help to clarify the effects of the selective brain accumulation of Amyloid-β (Aβ) and tau proteins occurring in the Alzheimer's disease (AD). To this aim, we derived morphometric similarity (MS) networks from 126 Aβ- and tau-positive (Aβ+/tau+) and 172 Aβ-/tau- subjects, and we investigated the association between group-wise regional MS differences and transcriptional correlates thanks to an imaging transcriptomics approach grounded in the Allen Human Brain Atlas (AHBA). The expressed gene with the highest correlation with MS alterations was BCHE, a gene related to Aβ homeostasis. In addition, notably, among the most promising results derived from the enrichment analysis, we found the immune response to be a biological process and astrocytes, microglia, and oligodendrocyte precursors for the cell types. In summary, by relating cortical MS and AHBA-derived transcriptomics, we were able to retrieve findings suggesting the biological mechanisms underlying the Aβ- and tau- induced cortical MS alterations in the AD continuum.
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Affiliation(s)
- Lorenza Brusini
- Department of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy
| | - Giorgio Dolci
- Department of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy
- Department of Computer Science, University of Verona, 37134 Verona, Italy
| | - Lorenzo Pini
- Department of Neuroscience, University of Padova, 35121 Padova, Italy
| | - Federica Cruciani
- Department of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy
- Istituto Fondazione Oncologia Molecolare Ente del Terzo Settore (IFOM ETS)-The Associazione Italiana per la Ricerca sul Cancro (AIRC) Institute of Molecular Oncology, 20139 Milano, Italy
| | - Fabrizio Pizzagalli
- Department of Neurosciences "Rita Levi Montalcini", University of Turin, 10126 Turin, Italy
| | - Paolo Provero
- Department of Neurosciences "Rita Levi Montalcini", University of Turin, 10126 Turin, Italy
| | - Gloria Menegaz
- Department of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy
| | - Ilaria Boscolo Galazzo
- Department of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy
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42
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Pang Y, Ruan X, Liu W, Hou L, Yin B, Shu P, Peng X. MicroRNA-495 Modulates Neuronal Layer Fate Determination by Targeting Tcf4. Int J Biol Sci 2024; 20:6207-6221. [PMID: 39664574 PMCID: PMC11628341 DOI: 10.7150/ijbs.94739] [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: 01/26/2024] [Accepted: 10/25/2024] [Indexed: 12/13/2024] Open
Abstract
During cortical development, the differentiation potential of neural progenitor cells (NPCs) is one of the most critical steps in normal cortical formation and function. Defects in this process can lead to many brain disorders. MicroRNA dysregulation in the dorsolateral prefrontal cortex is associated with risk for a variety of developmental and psychiatric conditions. However, the molecular mechanisms underlying this process remain largely unknown. In this study, we found that microRNA-495-3p (miR-495) is expressed in NPCs of the developing mouse cerebral cortex. Furthermore, aberrant expression of miR-495 promotes the formation of superficial neurons. Our results suggest that miR-495 can target transcription factor 4 (TCF4), a gene linked to the neurodevelopmental disorder Pitt-Hopkins syndrome (PTHS), to ensure normal differentiation of NPCs in the developing cerebral cortex. Furthermore, TCF4 loss-of-function and gain-of-function experiments show opposite effects on miR-495 regulation of neural progenitor differentiation potential. Together, these results demonstrated that miR-495 regulates cortical development through TCF4 for the first time.
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Affiliation(s)
- Yunli Pang
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Xiangbin Ruan
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Wei Liu
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Lin Hou
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Bin Yin
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Pengcheng Shu
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Xiaozhong Peng
- State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry & Molecular Biology, Medical Primate Research Center, Neuroscience Center, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
- State Key Laboratory of Respiratory Health and Multimorbidity, Beijing 100005, China
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China
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43
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Ball G, Oldham S, Kyriakopoulou V, Williams LZJ, Karolis V, Price A, Hutter J, Seal ML, Alexander-Bloch A, Hajnal JV, Edwards AD, Robinson EC, Seidlitz J. Molecular signatures of cortical expansion in the human foetal brain. Nat Commun 2024; 15:9685. [PMID: 39516464 PMCID: PMC11549424 DOI: 10.1038/s41467-024-54034-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 10/29/2024] [Indexed: 11/16/2024] Open
Abstract
The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. Recent studies have revealed a remarkable molecular diversity across the prenatal cortex but little is known about how this diversity translates into the differential rates of cortical expansion observed during gestation. We present a digital resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal brain. Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions, quantified in utero using magnetic resonance imaging. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of neocortical expansion during gestation. We identify genes, upregulated from mid-gestation, that are highly expressed in rapidly expanding neocortex and implicated in genetic disorders with cognitive sequelae. The μBrain atlas provides a tool to comprehensively map early brain development across domains, model systems and resolution scales.
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Affiliation(s)
- G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
- Department of Paediatrics, University of Melbourne, Melbourne, Australia.
| | - S Oldham
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - V Kyriakopoulou
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - L Z J Williams
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - V Karolis
- Centre for the Developing Brain, King's College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - A Price
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - J Hutter
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - M L Seal
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - A Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - J V Hajnal
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - E C Robinson
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - J Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
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44
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Chen Y, Li W, Lv L, Yue W. Shared Genetic Determinants of Schizophrenia and Autism Spectrum Disorder Implicate Opposite Risk Patterns: A Genome-Wide Analysis of Common Variants. Schizophr Bull 2024; 50:1382-1395. [PMID: 38616054 PMCID: PMC11548934 DOI: 10.1093/schbul/sbae044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
BACKGROUND AND HYPOTHESIS The synaptic pruning hypothesis posits that schizophrenia (SCZ) and autism spectrum disorder (ASD) may represent opposite ends of neurodevelopmental disorders: individuals with ASD exhibit an overabundance of synapses and connections while SCZ was characterized by excessive pruning of synapses and a reduction. Given the strong genetic predisposition of both disorders, we propose a shared genetic component, with certain loci having differential regulatory impacts. STUDY DESIGN Genome-Wide single nucleotide polymorphism (SNP) data of European descent from SCZ (N cases = 53 386, N controls = 77 258) and ASD (N cases = 18 381, N controls = 27 969) were analyzed. We used genetic correlation, bivariate causal mixture model, conditional false discovery rate method, colocalization, Transcriptome-Wide Association Study (TWAS), and Phenome-Wide Association Study (PheWAS) to investigate the genetic overlap and gene expression pattern. STUDY RESULTS We found a positive genetic correlation between SCZ and ASD (rg = .26, SE = 0.01, P = 7.87e-14), with 11 genomic loci jointly influencing both conditions (conjFDR <0.05). Functional analysis highlights a significant enrichment of shared genes during early to mid-fetal developmental stages. A notable genetic region on chromosome 17q21.31 (lead SNP rs2696609) showed strong evidence of colocalization (PP.H4.abf = 0.85). This SNP rs2696609 is linked to many imaging-derived brain phenotypes. TWAS indicated opposing gene expression patterns (primarily pseudogenes and long noncoding RNAs [lncRNAs]) for ASD and SCZ in the 17q21.31 region and some genes (LRRC37A4P, LINC02210, and DND1P1) exhibit considerable variation in the cerebellum across the lifespan. CONCLUSIONS Our findings support a shared genetic basis for SCZ and ASD. A common genetic variant, rs2696609, located in the Chr17q21.31 locus, may exert differential risk regulation on SCZ and ASD by altering brain structure. Future studies should focus on the role of pseudogenes, lncRNAs, and cerebellum in synaptic pruning and neurodevelopmental disorders.
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Affiliation(s)
- Yu Chen
- Department of Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China
- Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, Henan, China
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Wenqiang Li
- Department of Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China
- Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, Henan, China
| | - Luxian Lv
- Department of Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China
- Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, Henan, China
- Henan Province People’s Hospital, Zhengzhou, Henan, China
| | - Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, China
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45
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Chen X. Reimagining Cortical Connectivity by Deconstructing Its Molecular Logic into Building Blocks. Cold Spring Harb Perspect Biol 2024; 16:a041509. [PMID: 38621822 PMCID: PMC11529856 DOI: 10.1101/cshperspect.a041509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Comprehensive maps of neuronal connectivity provide a foundation for understanding the structure of neural circuits. In a circuit, neurons are diverse in morphology, electrophysiology, gene expression, activity, and other neuronal properties. Thus, constructing a comprehensive connectivity map requires associating various properties of neurons, including their connectivity, at cellular resolution. A commonly used approach is to use the gene expression profiles as an anchor to which all other neuronal properties are associated. Recent advances in genomics and anatomical techniques dramatically improved the ability to determine and associate the long-range projections of neurons with their gene expression profiles. These studies revealed unprecedented details of the gene-projection relationship, but also highlighted conceptual challenges in understanding this relationship. In this article, I delve into the findings and the challenges revealed by recent studies using state-of-the-art neuroanatomical and transcriptomic techniques. Building upon these insights, I propose an approach that focuses on understanding the gene-projection relationship through basic features in gene expression profiles and projections, respectively, that associate with underlying cellular processes. I then discuss how the developmental trajectories of projections and gene expression profiles create additional challenges and necessitate interrogating the gene-projection relationship across time. Finally, I explore complementary strategies that, together, can provide a comprehensive view of the gene-projection relationship.
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Affiliation(s)
- Xiaoyin Chen
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
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46
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Muhtaseb AW, Duan J. Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells. Schizophr Res 2024; 273:39-61. [PMID: 35459617 PMCID: PMC9735430 DOI: 10.1016/j.schres.2022.04.003] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/05/2022] [Accepted: 04/07/2022] [Indexed: 12/13/2022]
Abstract
Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.
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Affiliation(s)
- Abdurrahman W Muhtaseb
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, United States of America; Department of Human Genetics, The University of Chicago, Chicago, IL 60637, United States of America
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, United States of America; Department of Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, IL 60637, United States of America.
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47
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Russo ML, Sousa AMM, Bhattacharyya A. Consequences of trisomy 21 for brain development in Down syndrome. Nat Rev Neurosci 2024; 25:740-755. [PMID: 39379691 PMCID: PMC11834940 DOI: 10.1038/s41583-024-00866-2] [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] [Accepted: 09/09/2024] [Indexed: 10/10/2024]
Abstract
The appearance of cognitive deficits and altered brain morphology in newborns with Down syndrome (DS) suggests that these features are driven by disruptions at the earliest stages of brain development. Despite its high prevalence and extensively characterized cognitive phenotypes, relatively little is known about the cellular and molecular mechanisms that drive the changes seen in DS. Recent technical advances, such as single-cell omics and the development of induced pluripotent stem cell (iPSC) models of DS, now enable in-depth analyses of the biochemical and molecular drivers of altered brain development in DS. Here, we review the current state of knowledge on brain development in DS, focusing primarily on data from human post-mortem brain tissue. We explore the biological mechanisms that have been proposed to lead to intellectual disability in DS, assess the extent to which data from studies using iPSC models supports these hypotheses, and identify current gaps in the field.
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Affiliation(s)
- Matthew L Russo
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - André M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Anita Bhattacharyya
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
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48
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Heffel MG, Zhou J, Zhang Y, Lee DS, Hou K, Pastor-Alonso O, Abuhanna KD, Galasso J, Kern C, Tai CY, Garcia-Padilla C, Nafisi M, Zhou Y, Schmitt AD, Li T, Haeussler M, Wick B, Zhang MJ, Xie F, Ziffra RS, Mukamel EA, Eskin E, Nowakowski TJ, Dixon JR, Pasaniuc B, Ecker JR, Zhu Q, Bintu B, Paredes MF, Luo C. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature 2024; 635:481-489. [PMID: 39385032 PMCID: PMC11560841 DOI: 10.1038/s41586-024-08030-7] [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: 10/24/2022] [Accepted: 09/06/2024] [Indexed: 10/11/2024]
Abstract
The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.
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Affiliation(s)
- Matthew G Heffel
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Arc Institute, Palo Alto, CA, USA
| | - Yi Zhang
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Dong-Sung Lee
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oier Pastor-Alonso
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Kevin D Abuhanna
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph Galasso
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Colin Kern
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Chu-Yi Tai
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Carlos Garcia-Padilla
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mahsa Nafisi
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Yi Zhou
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Terence Li
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Brittney Wick
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Martin Jinye Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Fangming Xie
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Ryan S Ziffra
- Department of Neurological Surgery, 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
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Eleazar Eskin
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, 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
| | - Jesse R Dixon
- Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Quan Zhu
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Bogdan Bintu
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mercedes F Paredes
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
- Developmental Stem Cell Biology, University of California, San Francisco, San Francisco, CA, USA.
| | - Chongyuan Luo
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
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49
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Lin Q, Li W, Zhang Y, Li Y, Liu P, Huang X, Huang K, Cao D, Gong Q, Zhou D, An D. Brain Morphometric Alterations in Focal to Bilateral Tonic-Clonic Seizures in Epilepsy Associated With Excitatory/Inhibitory Imbalance. CNS Neurosci Ther 2024; 30:e70129. [PMID: 39582215 PMCID: PMC11586465 DOI: 10.1111/cns.70129] [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: 07/20/2024] [Revised: 10/31/2024] [Accepted: 11/05/2024] [Indexed: 11/26/2024] Open
Abstract
BACKGROUND Focal to bilateral tonic-clonic seizures (FBTCS) represent the most severe seizure type in temporal lobe epilepsy (TLE), associated with extensive network abnormalities. Nevertheless, the genetic and cellular factors predispose specific TLE patients to FBTCS remain poorly understood. This study aimed to elucidate the relationship between brain morphometric alterations and transcriptional profiles in TLE patients with FBTCS (FBTCS+) compared to those without FBTCS (FBTCS-). METHODS We enrolled 126 unilateral TLE patients (89 FBTCS+ and 37 FBTCS-) along with 60 age- and gender-matched healthy controls (HC). We assessed gray matter volume to identify morphometric differences between patients and HC. Partial least squares regression was employed to investigate the association between the morphometric disparities and human brain transcriptomic data obtained from the Allen Human Brain Atlas. RESULTS Compared with HC, FBTCS+ patients exhibited morphometric alterations in bilateral cortical and subcortical regions. Conversely, FBTCS- patients exhibited more localized alterations. Imaging transcriptomic analysis revealed both FBTCS- and FBTCS+ groups harbored genes that spatially correlated with morphometric alterations. Additionally, pathway enrichment analysis identified common pathways involved in neural development and synaptic function in both groups. The FBTCS- group displayed unique pathway enrichment in catabolic processes. Furthermore, mapping these genes to specific cell types indicated enrichment in excitatory and inhibitory neurons in the FBTCS- group, while FBTCS+ group only enriched in excitatory neurons. The distinct cellular expression differences between FBTCS- and FBTCS+ groups are consistent with the distribution patterns of GABAergic expression. CONCLUSION We applied imaging transcriptomic analysis linking the morphometric changes and neurobiology in TLE patients with and without FBTCS, including gene expression, biological pathways, cell types, and neurotransmitter receptors. Our findings revealed abnormalities in inhibitory neurons and altered distribution patterns of GABAergic receptors in FBTCS+, suggesting that an excitatory/inhibitory imbalance may contribute to the increased susceptibility of certain individuals to FBTCS.
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Affiliation(s)
- Qiuxing Lin
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Wei Li
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Yingying Zhang
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Yuming Li
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Peiwen Liu
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Xiang Huang
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Kailing Huang
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Danyang Cao
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center, West China HospitalSichuan UniversityChengduSichuanChina
| | - Dong Zhou
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Dongmei An
- Department of Neurology, West China HospitalSichuan UniversityChengduSichuanChina
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He S, Zhang X, Zhu H. Human-specific protein-coding and lncRNA genes cast sex-biased genes in the brain and their relationships with brain diseases. Biol Sex Differ 2024; 15:86. [PMID: 39472939 PMCID: PMC11520681 DOI: 10.1186/s13293-024-00659-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Accepted: 10/07/2024] [Indexed: 11/02/2024] Open
Abstract
BACKGROUND Gene expression shows sex bias in the brain as it does in other organs. Since female and male humans exhibit noticeable differences in emotions, logical thinking, movement, spatial orientation, and even the incidence of neurological disorders, sex biases in the brain are especially interesting, but how they are determined, whether they are conserved or lineage specific, and what the consequences of the biases are, remain poorly explored and understood. METHODS Based on RNA-seq datasets from 16 and 14 brain regions in humans and macaques across developmental periods and from patients with brain diseases, we used linear mixed models (LMMs) to differentiate variations in gene expression caused by factors of interest and confounding factors and identify four types of sex-biased genes. Effect size and confidence in each effect were measured upon the local false sign rate (LFSR). We utilized the biomaRt R package to acquire orthologous genes in humans and macaques from the BioMart Ensembl website. Transcriptional regulation of sex-biased genes by sex hormones and lncRNAs were analyzed using the CellOracle, GENIE3, and Longtarget programs. Sex-biased genes' functions were revealed by gene set enrichment analysis using multiple methods. RESULTS Lineage-specific sex-biased genes greatly determine the distinct sex biases in human and macaque brains. In humans, those encoding proteins contribute directly to immune-related functions, and those encoding lncRNAs intensively regulate the expression of other sex-biased genes, especially genes with immune-related functions. The identified sex-specific differentially expressed genes (ssDEGs) upon gene expression in disease and normal samples also indicate that protein-coding ssDEGs are conserved in humans and macaques but that lncRNA ssDEGs are not conserved. The results answer the above questions, reveal an intrinsic relationship between sex biases in the brain and sex-biased susceptibility to brain diseases, and will help researchers investigate human- and sex-specific ncRNA targets for brain diseases. CONCLUSIONS Human-specific genes greatly cast sex-biased genes in the brain and their relationships with brain diseases, with protein-coding genes contributing to immune response related functions and lncRNA genes critically regulating sex-biased genes. The high proportions of lineage-specific lncRNAs in mammalian genomes indicate that sex biases may have evolved rapidly in not only the brain but also other organs.
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Affiliation(s)
- Sha He
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Xuecong Zhang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
- Shenzhen Clinical Research Center for Tuberculosis, National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, Guangdong, China
| | - Hao Zhu
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, 510515, China.
- Guangdong Provincial Key Lab of Single Cell Technology and Application, Southern Medical University, Guangzhou, 510515, China.
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