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Shabani K, Krupp J, Lemesre E, Lévy N, Tran H. Voltage-Gated Ion Channel Compensatory Effect in DEE: Implications for Future Therapies. Cells 2024; 13:1763. [PMID: 39513870 PMCID: PMC11544952 DOI: 10.3390/cells13211763] [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: 09/09/2024] [Revised: 10/02/2024] [Accepted: 10/11/2024] [Indexed: 11/16/2024] Open
Abstract
Developmental and Epileptic Encephalopathies (DEEs) represent a clinically and genetically heterogeneous group of rare and severe epilepsies. DEEs commonly begin early in infancy with frequent seizures of various types associated with intellectual disability and leading to a neurodevelopmental delay or regression. Disease-causing genomic variants have been identified in numerous genes and are implicated in over 100 types of DEEs. In this context, genes encoding voltage-gated ion channels (VGCs) play a significant role, and part of the large phenotypic variability observed in DEE patients carrying VGC mutations could be explained by the presence of genetic modifier alleles that can compensate for these mutations. This review will focus on the current knowledge of the compensatory effect of DEE-associated voltage-gated ion channels and their therapeutic implications in DEE. We will enter into detailed considerations regarding the sodium channels SCN1A, SCN2A, and SCN8A; the potassium channels KCNA1, KCNQ2, and KCNT1; and the calcium channels CACNA1A and CACNA1G.
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Affiliation(s)
- Khadijeh Shabani
- Institut de Recherches Servier, Rue Francis Perrin, 91190 Gif-sur-Yvette, France; (J.K.); (E.L.); (N.L.)
| | | | | | | | - Helene Tran
- Institut de Recherches Servier, Rue Francis Perrin, 91190 Gif-sur-Yvette, France; (J.K.); (E.L.); (N.L.)
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52
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Snyder WE, Vértes PE, Kyriakopoulou V, Wagstyl K, Williams LZJ, Moraczewski D, Thomas AG, Karolis VR, Seidlitz J, Rivière D, Robinson EC, Mangin JF, Raznahan A, Bullmore ET. A bimodal taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients. Neuron 2024; 112:3396-3411.e6. [PMID: 39178859 PMCID: PMC11502256 DOI: 10.1016/j.neuron.2024.07.023] [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: 11/18/2023] [Revised: 05/22/2024] [Accepted: 07/29/2024] [Indexed: 08/26/2024]
Abstract
We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.
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Affiliation(s)
- William E Snyder
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA.
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Logan Z J Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Adam G Thomas
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette 91191, France
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Jean-Francois Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette 91191, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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53
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Burette AC, Vihma H, Smith AL, Ozarkar SS, Bennett J, Amaral DG, Philpot BD. Transcription factor 4 expression in the developing non-human primate brain: a comparative analysis with the mouse brain. Front Neuroanat 2024; 18:1478689. [PMID: 39502395 PMCID: PMC11534587 DOI: 10.3389/fnana.2024.1478689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2024] [Accepted: 10/04/2024] [Indexed: 11/08/2024] Open
Abstract
Transcription factor 4 (TCF4) has been implicated in a range of neuropsychiatric disorders, including major depressive disorder, bipolar disorder, and schizophrenia. Mutations or deletions in TCF4 cause Pitt-Hopkins syndrome (PTHS), a rare neurodevelopmental disorder. A detailed understanding of its spatial expression across the developing brain is necessary for comprehending TCF4 biology and, by extension, to develop effective treatments for TCF4-associated disorders. However, most current knowledge is derived from mouse models, which are invaluable for preclinical studies but may not fully capture the complexities of human neuropsychiatric phenotypes. This study compared TCF4 expression in the developing mouse brain to its regional and cellular expression patterns in normal prenatal, neonatal, and young adult rhesus macaque brains, a species more relevant to human neurodevelopment. While the general developmental expression of TCF4 is largely conserved between macaques and mice, we saw several interspecies differences. Most notably, a distinct layered pattern of TCF4 expression was clear in the developing macaque neocortex but largely absent in the mouse brain. High TCF4 expression was seen in the inner dentate gyrus of adult mice but not in macaques. Conversely, TCF4 expression was higher in the adult macaque striatum compared to the mouse striatum. Further research is needed to show the significance of these interspecies differences. Still, they underscore the importance of integrating rodent and primate studies to comprehensively understand TCF4 function and its implications for human disorders. Moreover, the primate-specific expression patterns of TCF4 will inform genetic and other therapeutic strategies to treat TCF4-associated disorders.
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Affiliation(s)
- Alain C. Burette
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Hanna Vihma
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Audrey L. Smith
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Siddhi S. Ozarkar
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jeff Bennett
- Department of Psychiatry and Behavioral Sciences, MIND Institute, University of California, Davis, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, Davis, CA, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, MIND Institute, University of California, Davis, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, Davis, CA, United States
| | - Benjamin D. Philpot
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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54
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Ma JQ, Wang L, Zhang Y, Bian YQ, Qu XP, Song LJ, Wang C, Gao L, Fang QX, Zhao DC, Shen LL, Liu B. Single-nucleus RNA sequencing-based construction of a hippocampal neuron atlas in mice with epileptic cognitive impairment. iScience 2024; 27:111065. [PMID: 39635132 PMCID: PMC11615225 DOI: 10.1016/j.isci.2024.111065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/13/2024] [Accepted: 09/25/2024] [Indexed: 12/07/2024] Open
Abstract
The hippocampus plays a critical role in learning and memory, and mice with epileptic cognitive impairment exhibit hippocampal atrophy. However, there is still a lack of research on the hippocampal cell atlas related to these disorders. Here, we utilized snRNA-seq to characterize the transcriptomic changes in hippocampal neurons of drug-resistant epilepsy (DRE) cognitive-impaired mice. The intercellular heterogeneity of 20 subpopulations of neurons was analyzed, focusing on aspects such as cell communication, gene expressions, GO and KEGG enrichment analysis, and module gene set analysis. Based on the degree of relevance to synaptic biological functions, the subpopulations associated with cognitive impairment (ExN1, 3, 8 and InN1, 6) were preliminarily identified. We also identified some key biomarkers in DRE cognitive-impaired mice, such as Ptprz1 and Calb1. Finally, we integrate and validate our dataset using identified well-annotated marker genes in the hippocampal region, further supporting the functional annotation of neuronal subpopulations.
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Affiliation(s)
- Jia-Qi Ma
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Lu Wang
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
- College of Life Sciences, Northwest University, Xi’an, Shaanxi 710069, China
| | - Yue Zhang
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Yong-Qian Bian
- Department of Plastic and Burn Surgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Xiao-Peng Qu
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Li-Jia Song
- Department of Pediatrics, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Chao Wang
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Li Gao
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Qi-Xing Fang
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - De-Chang Zhao
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
| | - Liang-Liang Shen
- Department of Biochemistry and Molecular Biology, Airforce Military Medical University, Xi’an, China
| | - Bei Liu
- Department of Neurosurgery, Tangdu Hospital, Airforce Military Medical University, Xi’an, China
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55
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Chettle J, Louie RJ, Larner O, Best R, Chen K, Morris J, Dedeic Z, Childers A, Rogers RC, DuPont BR, Skinner C, Küry S, Uguen K, Planes M, Monteil D, Li M, Eliyahu A, Greenbaum L, Mor N, Besnard T, Isidor B, Cogné B, Blesson A, Comi A, Wentzensen IM, Vuocolo B, Lalani SR, Sierra R, Berry L, Carter K, Sanders SJ, Blagden SP. LARP1 haploinsufficiency is associated with an autosomal dominant neurodevelopmental disorder. HGG ADVANCES 2024; 5:100345. [PMID: 39182167 PMCID: PMC11418108 DOI: 10.1016/j.xhgg.2024.100345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 08/21/2024] [Accepted: 08/21/2024] [Indexed: 08/27/2024] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) that affects approximately 4% of males and 1% of females in the United States. While causes of ASD are multi-factorial, single rare genetic variants contribute to around 20% of cases. Here, we report a case series of seven unrelated probands (6 males, 1 female) with ASD or another variable NDD phenotype attributed to de novo heterozygous loss of function or missense variants in the gene LARP1 (La ribonucleoprotein 1). LARP1 encodes an RNA-binding protein that post-transcriptionally regulates the stability and translation of thousands of mRNAs, including those regulating cellular metabolism and metabolic plasticity. Using lymphocytes collected and immortalized from an index proband who carries a truncating variant in one allele of LARP1, we demonstrated that lower cellular levels of LARP1 protein cause reduced rates of aerobic respiration and glycolysis. As expression of LARP1 increases during neurodevelopment, with higher levels in neurons and astrocytes, we propose that LARP1 haploinsufficiency contributes to ASD or related NDDs through attenuated metabolic activity in the developing fetal brain.
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Affiliation(s)
- James Chettle
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Olivia Larner
- University of South Carolina School of Medicine Greenville, Greenville, SC, USA
| | - Robert Best
- University of South Carolina School of Medicine Greenville, Greenville, SC, USA
| | | | | | - Zinaida Dedeic
- Department of Oncology, University of Oxford, Oxford, UK
| | | | | | | | | | - Sébastien Küry
- Nantes Université, CHU Nantes, Service de Génétique Médicale, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, L'institut du thorax, 44000 Nantes, France
| | - Kevin Uguen
- Service de Génétique Médicale et Biologie de la Reproduction, CHRU de Brest, Brest, France
| | - Marc Planes
- Service de Génétique Médicale et Biologie de la Reproduction, CHRU de Brest, Brest, France
| | | | - Megan Li
- Invitae, San Francisco Corp., San Francisco, CA, USA
| | - Aviva Eliyahu
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lior Greenbaum
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Nofar Mor
- The Genomic Unit, Sheba Cancer Research Centre, Sheba Medical Center, Tel Hashomer, Israel
| | - Thomas Besnard
- Nantes Université, CHU Nantes, Service de Génétique Médicale, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, L'institut du thorax, 44000 Nantes, France
| | - Bertrand Isidor
- Nantes Université, CHU Nantes, Service de Génétique Médicale, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, L'institut du thorax, 44000 Nantes, France
| | - Benjamin Cogné
- Nantes Université, CHU Nantes, Service de Génétique Médicale, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, L'institut du thorax, 44000 Nantes, France
| | | | - Anne Comi
- Kennedy Krieger Institute, Baltimore, MD, USA
| | | | | | | | | | - Lori Berry
- Baylor College of Medicine, Houston, TX, USA
| | - Kent Carter
- University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - Stephan J Sanders
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, UK; Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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56
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Hosseini SM, Panahi-Azar A, Sheybani-Arani M, Morovatshoar R, Mirzadeh M, Salimi Asl A, Naghdipour Mirsadeghi M, Khajavi-Mayvan F. Vitamins, minerals and their maternal levels' role in brain development: An updated literature-review. Clin Nutr ESPEN 2024; 63:31-45. [PMID: 38907995 DOI: 10.1016/j.clnesp.2024.05.011] [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: 07/17/2023] [Revised: 03/26/2024] [Accepted: 05/16/2024] [Indexed: 06/24/2024]
Abstract
One's neurobehavioural and mental health are built during the exact and complex process of brain development. It is thought that fetal development is where neuropsychiatric disorders first emerged. Behavioural patterns can change as a result of neuropsychiatric illnesses. The incidence is rising quickly; nevertheless, providing exceptional care remains a significant challenge for families and healthcare systems. It has been demonstrated that one of the main factors causing the transmission of these diseases is maternal exposure. Through physiologic pathways, maternal health and intrauterine exposures can affect brain development. Our attention has been focused on epigenetic factors, particularly in the gestational environment, which may be responsible for human neurodegenerative diseases since our main mental development occurs during the nine months of intrauterine life. After thoroughly searching numerous databases, this study examined the effect of fat-soluble vitamins, water-soluble vitamins, and minerals and their maternal-level effect on brain development.
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Affiliation(s)
| | - Ava Panahi-Azar
- Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
| | | | - Reza Morovatshoar
- Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
| | - Mahdieh Mirzadeh
- Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
| | - Ali Salimi Asl
- Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
| | - Misa Naghdipour Mirsadeghi
- Department of Gynecology, School of Medicine, Reproductive Health Research Center, Alzahra Hospital, Guilan University of Medical Sciences, Rasht, Iran.
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57
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Chundru VK, Zhang Z, Walter K, Lindsay SJ, Danecek P, Eberhardt RY, Gardner EJ, Malawsky DS, Wigdor EM, Torene R, Retterer K, Wright CF, Ólafsdóttir H, Guillen Sacoto MJ, Ayaz A, Akbeyaz IH, Türkdoğan D, Al Balushi AI, Bertoli-Avella A, Bauer P, Szenker-Ravi E, Reversade B, McWalter K, Sheridan E, Firth HV, Hurles ME, Samocha KE, Ustach VD, Martin HC. Federated analysis of autosomal recessive coding variants in 29,745 developmental disorder patients from diverse populations. Nat Genet 2024; 56:2046-2053. [PMID: 39313616 PMCID: PMC11525179 DOI: 10.1038/s41588-024-01910-8] [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: 07/24/2023] [Accepted: 08/14/2024] [Indexed: 09/25/2024]
Abstract
Autosomal recessive coding variants are well-known causes of rare disorders. We quantified the contribution of these variants to developmental disorders in a large, ancestrally diverse cohort comprising 29,745 trios, of whom 20.4% had genetically inferred non-European ancestries. The estimated fraction of patients attributable to exome-wide autosomal recessive coding variants ranged from ~2-19% across genetically inferred ancestry groups and was significantly correlated with average autozygosity. Established autosomal recessive developmental disorder-associated (ARDD) genes explained 84.0% of the total autosomal recessive coding burden, and 34.4% of the burden in these established genes was explained by variants not already reported as pathogenic in ClinVar. Statistical analyses identified two novel ARDD genes: KBTBD2 and ZDHHC16. This study expands our understanding of the genetic architecture of developmental disorders across diverse genetically inferred ancestry groups and suggests that improving strategies for interpreting missense variants in known ARDD genes may help diagnose more patients than discovering the remaining genes.
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Affiliation(s)
- V Kartik Chundru
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, UK
| | - Zhancheng Zhang
- GeneDx, Gaithersburg, MD, USA
- Deka Biosciences, Germantown, MD, USA
| | - Klaudia Walter
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Sarah J Lindsay
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Petr Danecek
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Eugene J Gardner
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- MRC Epidemiology Unit, Cambridge, UK
| | | | - Emilie M Wigdor
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Rebecca Torene
- GeneDx, Gaithersburg, MD, USA
- Geisinger, Danville, PA, USA
| | - Kyle Retterer
- GeneDx, Gaithersburg, MD, USA
- Geisinger, Danville, PA, USA
| | - Caroline F Wright
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, UK
| | | | | | - Akif Ayaz
- Istanbul Medipol University, Medical School, Department of Medical Genetics, Istanbul, Turkey
| | - Ismail Hakki Akbeyaz
- Marmara University Medical Faculty, Pendik Training and Research Hospital, Department of Pediatric Neurology, Istanbul, Turkey
| | - Dilşad Türkdoğan
- Marmara University Medical Faculty, Pendik Training and Research Hospital, Department of Pediatric Neurology, Istanbul, Turkey
| | | | | | - Peter Bauer
- Medical Genetics, CENTOGENE GmbH, Rostock, Germany
- Clinic of Internal Medicine, Department of Hematology, Oncology, and Palliative Medicine, University Medicine Rostock, Rostock, Germany
| | | | - Bruno Reversade
- Laboratory of Human Genetics & Therapeutics, BESE, KAUST, Thuwal, Saudi Arabia
| | | | - Eamonn Sheridan
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Leeds Institute of Medical Research, University of Leeds, St. James's University Hospital, Leeds, UK
- Yorkshire Regional Genetics Service, Chapel Allerton Hospital, Leeds, UK
| | - Helen V Firth
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Cambridge University Hospitals Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | | | - Kaitlin E Samocha
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
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58
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Hakizimana O, Hitayezu J, Uyisenga JP, Onohuean H, Palmeira L, Bours V, Alagbonsi AI, Uwineza A. Genetic etiology of autism spectrum disorder in the African population: a scoping review. Front Genet 2024; 15:1431093. [PMID: 39391062 PMCID: PMC11464363 DOI: 10.3389/fgene.2024.1431093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Accepted: 08/28/2024] [Indexed: 10/12/2024] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by significant impairments in social, communicative, and behavioral abilities. However, only a limited number of studies address the genetic basis of ASD in the African population. This study aims to document the genes associated with ASD in Africa and the techniques used to identify them. Additionally, genes identified elsewhere but not yet in Africa are also noted. Methods Online databases such as Wiley Online Library, PubMed, and Africa Journal Online were used. The review was conducted using the keyword related to genetic and genomic ASD study in the African population. Result In this scoping review, 40 genetic studies on ASD in Africa were reviewed. The Egyptian and South African populations were the most studied, with 25 and 5 studies, respectively. Countries with fewer studies included Tunisia (4), East African countries (3), Libya (1), Nigeria (1), and Morocco (1). Some 61 genes responsible for ASD were identified in the African population: 26 were identified using a polymerase chain reaction (PCR)-based method, 22 were identified using sequencing technologies, and 12 genes and one de novo chromosomal aberration were identified through other techniques. No African study identified any ASD gene with genome-wide association studies (GWAS). Notably, at least 20 ASD risk genes reported in non-African countries were yet to be confirmed in Africa's population. Conclusion There are insufficient genetic studies on ASD in the African population, with sample size being a major limitation in most genetic association studies, leading to inconclusive results. Thus, there is a need to conduct more studies with large sample sizes to identify other genes associated with ASD in Africa's population using high-throughput sequencing technology.
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Affiliation(s)
- Olivier Hakizimana
- Department of Biochemistry, Molecular Biology and Genetics, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
- Center for Human Genetics, Centre Hospitalier Universitaire Sart-Tilman, University of Liege, Liege, Belgium
| | - Janvier Hitayezu
- Department of Pediatrics, University Teaching Hospital of Kigali (CHUK), Kigali, Rwanda
| | - Jeanne P. Uyisenga
- Department of Biology, College of Science and Technology, University of Rwanda, Kigali, Rwanda
| | - Hope Onohuean
- Biopharmaceutics Unit, Department of Pharmacology and Toxicology, School of Pharmacy, Kampala International University, Bushenyi, Uganda
| | - Leonor Palmeira
- Center for Human Genetics, Centre Hospitalier Universitaire Sart-Tilman, University of Liege, Liege, Belgium
| | - Vincent Bours
- Center for Human Genetics, Centre Hospitalier Universitaire Sart-Tilman, University of Liege, Liege, Belgium
| | - Abdullateef Isiaka Alagbonsi
- Department of Physiology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Annette Uwineza
- Department of Biochemistry, Molecular Biology and Genetics, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
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59
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Griffith EC, West AE, Greenberg ME. Neuronal enhancers fine-tune adaptive circuit plasticity. Neuron 2024; 112:3043-3057. [PMID: 39208805 PMCID: PMC11550865 DOI: 10.1016/j.neuron.2024.08.002] [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: 05/01/2023] [Revised: 07/22/2024] [Accepted: 08/06/2024] [Indexed: 09/04/2024]
Abstract
Neuronal activity-regulated gene expression plays a crucial role in sculpting neural circuits that underpin adaptive brain function. Transcriptional enhancers are now recognized as key components of gene regulation that orchestrate spatiotemporally precise patterns of gene transcription. We propose that the dynamics of enhancer activation uniquely position these genomic elements to finely tune activity-dependent cellular plasticity. Enhancer specificity and modularity can be exploited to gain selective genetic access to specific cell states, and the precise modulation of target gene expression within restricted cellular contexts enabled by targeted enhancer manipulation allows for fine-grained evaluation of gene function. Mounting evidence also suggests that enduring stimulus-induced changes in enhancer states can modify target gene activation upon restimulation, thereby contributing to a form of cell-wide metaplasticity. We advocate for focused exploration of activity-dependent enhancer function to gain new insight into the mechanisms underlying brain plasticity and cognitive dysfunction.
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Affiliation(s)
- Eric C Griffith
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Anne E West
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
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60
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Shan X, Zhang A, Rezzonico MG, Tsai MC, Sanchez-Priego C, Zhang Y, Chen MB, Choi M, Andrade López JM, Phu L, Cramer AL, Zhang Q, Pattison JM, Rose CM, Hoogenraad CC, Jeong CG. Fully defined NGN2 neuron protocol reveals diverse signatures of neuronal maturation. CELL REPORTS METHODS 2024; 4:100858. [PMID: 39255791 PMCID: PMC11440061 DOI: 10.1016/j.crmeth.2024.100858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 04/26/2024] [Accepted: 08/14/2024] [Indexed: 09/12/2024]
Abstract
NGN2-driven induced pluripotent stem cell (iPSC)-to-neuron conversion is a popular method for human neurological disease modeling. In this study, we present a standardized approach for generating neurons utilizing clonal, targeted-engineered iPSC lines with defined reagents. We demonstrate consistent production of excitatory neurons at scale and long-term maintenance for at least 150 days. Temporal omics, electrophysiological, and morphological profiling indicate continued maturation to postnatal-like neurons. Quantitative characterizations through transcriptomic, imaging, and functional assays reveal coordinated actions of multiple pathways that drive neuronal maturation. We also show the expression of disease-related genes in these neurons to demonstrate the relevance of our protocol for modeling neurological disorders. Finally, we demonstrate efficient generation of NGN2-integrated iPSC lines. These workflows, profiling data, and functional characterizations enable the development of reproducible human in vitro models of neurological disorders.
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Affiliation(s)
- Xiwei Shan
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Ai Zhang
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Mitchell G Rezzonico
- Department of OMNI Bioinformatics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Ming-Chi Tsai
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | | | - Yingjie Zhang
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Michelle B Chen
- Department of Cellular and Tissue Genomics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Meena Choi
- Department of Proteomic and Genomic Technologies, Genentech, Inc., South San Francisco, CA 94080, USA
| | | | - Lilian Phu
- Department of Proteomic and Genomic Technologies, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Amber L Cramer
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Qiao Zhang
- Department of Discovery Oncology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Jillian M Pattison
- Advanced Cell Engineering, Department of Molecular Biology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Christopher M Rose
- Department of Proteomic and Genomic Technologies, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Casper C Hoogenraad
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Claire G Jeong
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA 94080, USA.
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61
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Liu M, Wang L, Zhang Y, Dong H, Wang C, Chen Y, Qian Q, Zhang N, Wang S, Zhao G, Zhang Z, Lei M, Wang S, Zhao Q, Liu F. Investigating the shared genetic architecture between depression and subcortical volumes. Nat Commun 2024; 15:7647. [PMID: 39223129 PMCID: PMC11368965 DOI: 10.1038/s41467-024-52121-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024] Open
Abstract
Depression, a widespread and highly heritable mental health condition, profoundly affects millions of individuals worldwide. Neuroimaging studies have consistently revealed volumetric abnormalities in subcortical structures associated with depression. However, the genetic underpinnings shared between depression and subcortical volumes remain inadequately understood. Here, we investigate the extent of polygenic overlap using the bivariate causal mixture model (MiXeR), leveraging summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 14 subcortical volumetric phenotypes (N = 33,224). Additionally, we identify shared genomic loci through conditional/conjunctional FDR analyses. MiXeR shows that subcortical volumetric traits share a substantial proportion of genetic variants with depression, with 44 distinct shared loci identified by subsequent conjunctional FDR analysis. These shared loci are predominantly located in intronic regions (58.7%) and non-coding RNA intronic regions (25.4%). The 269 protein-coding genes mapped by these shared loci exhibit specific developmental trajectories, with the expression level of 55 genes linked to both depression and subcortical volumes, and 30 genes linked to cognitive abilities and behavioral symptoms. These findings highlight a shared genetic architecture between depression and subcortical volumetric phenotypes, enriching our understanding of the neurobiological underpinnings of depression.
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Affiliation(s)
- Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Lu Wang
- Department of Geriatrics and Tianjin Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yujie Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Haoyang Dong
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Caihong Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Qian Qian
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Nannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guoshu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Sijia Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
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Yang S, Gao S, Dong Z. CircVCAN promotes glioma progression through the miR-488-3p/MEF2C-JAGGED1 axis. ENVIRONMENTAL TOXICOLOGY 2024; 39:4417-4430. [PMID: 38842024 DOI: 10.1002/tox.24328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 04/10/2024] [Accepted: 04/29/2024] [Indexed: 06/07/2024]
Abstract
Gliomas are the most prevalent primary malignant brain tumors worldwide. Growing evidences indicate that circular RNAs (circRNAs) play an important role in the regulation of biological behavior of tumors. We aimed to investigate the role and mechanism of circVCAN in glioma. RNase R treatment was utilized to assess the cyclic properties of circVCAN. CircVCAN, miR-488-3p, and myocyte enhancer factor 2C (MEF2C) levels in glioma tissues and cells were detected by reverse transcription real-time polymerase chain reaction (RT-qPCR), and the localization of them in glioma cells was determined with fluorescence in situ hybridization. Furthermore, a variety of biologically functional assessments were used to validate the role of circVCAN in glioma. The regulatory mechanisms of circVCAN, miR-488-3p, and MEF2C were further confirmed by double luciferase reporter gene assay, RNA immunoprecipitation and RNA pull-down assay, and the binding of MEF2C to JAGGED1 was revealed by chromatin immunoprecipitation. Additionally, a xenograft tumor model was constructed to demonstrate the effect of circVCAN on tumor growth in vivo. Our results indicated that circVCAN was more stable than its linear RNA and was significantly upregulated in gliomas. CircVCAN overexpression stimulated glioma cells to proliferate and metastasize, but circVCAN silencing exerted the opposite effect. Meanwhile, silencing circVCAN inhibited tumor growth in vivo. Moreover, we found that circVCAN interacted with miR-488-3p to regulate MEF2C expression, and miR-488-3p inhibition or MEF2C overexpression reversed the inhibitory effect on malignant bio-behaviors mediated by circVCAN knockdown in glioma cells. MEF2C promoted the transcription of JAGGED1, and circVCAN knockdown reduced the binding between MEF2C and JAGGED1. Collectively, circVCAN is a carcinogenic circRNA in glioma, and the circVCAN/miR-488-3p/MEF2C-JAGGED1 axis could serve as a potential target for the management of glioma.
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Affiliation(s)
- Shude Yang
- The Second Clinical Medical School, Lanzhou University, Lanzhou, China
| | - Shuo Gao
- The Second Clinical Medical School, Lanzhou University, Lanzhou, China
| | - Zhiqiang Dong
- The Second Clinical Medical School, Lanzhou University, Lanzhou, China
- Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China
- Key Laboratory of Neurology of Gansu Province, Lanzhou, China
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63
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Sullivan PF, Yao S, Hjerling-Leffler J. Schizophrenia genomics: genetic complexity and functional insights. Nat Rev Neurosci 2024; 25:611-624. [PMID: 39030273 DOI: 10.1038/s41583-024-00837-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/04/2024] [Indexed: 07/21/2024]
Abstract
Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.
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Affiliation(s)
- Patrick F Sullivan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jens Hjerling-Leffler
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
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Yim KM, Baumgartner M, Krenzer M, Rosales Larios MF, Hill-Terán G, Nottoli T, Muhle RA, Noonan JP. Cell type-specific dysregulation of gene expression due to Chd8 haploinsufficiency during mouse cortical development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.14.608000. [PMID: 39185167 PMCID: PMC11343218 DOI: 10.1101/2024.08.14.608000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Disruptive variants in the chromodomain helicase CHD8, which acts as a transcriptional regulator during neurodevelopment, are strongly associated with risk for autism spectrum disorder (ASD). Loss of CHD8 function is hypothesized to perturb gene regulatory networks in the developing brain, thereby contributing to ASD etiology. However, insight into the cell type-specific transcriptional effects of CHD8 loss of function remains limited. We used single-cell and single-nucleus RNA-sequencing to globally profile gene expression and identify dysregulated genes in the embryonic and juvenile wild type and Chd8 +/- mouse cortex, respectively. Chd8 and other ASD risk-associated genes showed a convergent expression trajectory that was largely conserved between the mouse and human developing cortex, increasing from the progenitor zones to the cortical plate. Genes associated with risk for neurodevelopmental disorders and genes involved in neuron projection development, chromatin remodeling, signaling, and migration were dysregulated in Chd8 +/- embryonic day (E) 12.5 radial glia. Genes implicated in synaptic organization and activity were dysregulated in Chd8 +/- postnatal day (P) 25 deep- and upper-layer excitatory cortical neurons, suggesting a delay in synaptic maturation or impaired synaptogenesis due to CHD8 loss of function. Our findings reveal a complex pattern of transcriptional dysregulation in Chd8 +/- developing cortex, potentially with distinct biological impacts on progenitors and maturing neurons in the excitatory neuronal lineage.
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Affiliation(s)
- Kristina M. Yim
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - Martina Krenzer
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
- Present address: Mount Sinai School of Medicine, Brookdale Department of Geriatrics and Palliative Medicine, New York, NY 10029, USA
| | - María F. Rosales Larios
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
- Present address: Social Studies of Science and Technology, Department of Evolutionary Biology, School of Sciences, National Autonomous University of Mexico, 04510 Mexico City, Mexico
| | - Guillermina Hill-Terán
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
- Present address: Higher Institute of Biological Research (INSIBIO, CONICET-UNT), Institute of Biology, National University of Tucumán, T4000 San Miguel de Tucumán, Argentina
| | - Timothy Nottoli
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT 06510, USA
- Yale Genome Editing Center, Yale School of Medicine, New Haven, CT 06510, USA
| | - Rebecca A. Muhle
- Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
- Present address: New York State Psychiatric Institute and Columbia University Department of Psychiatry, New York, NY 10032, USA
| | - James P. Noonan
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06510, USA
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65
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Zhao Z, Shuai Y, Wu Y, Xu X, Li M, Wu D. Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study. Neuroimage 2024; 297:120669. [PMID: 38852805 DOI: 10.1016/j.neuroimage.2024.120669] [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: 12/11/2023] [Revised: 04/01/2024] [Accepted: 06/05/2024] [Indexed: 06/11/2024] Open
Abstract
The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.
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Affiliation(s)
- Zhiyong Zhao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yifan Shuai
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yihan Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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66
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Liu W, Su JP, Zeng LL, Shen H, Hu DW. Gene expression and brain imaging association study reveals gene signatures in major depressive disorder. Brain Commun 2024; 6:fcae258. [PMID: 39185029 PMCID: PMC11342243 DOI: 10.1093/braincomms/fcae258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 06/03/2024] [Accepted: 08/09/2024] [Indexed: 08/27/2024] Open
Abstract
Major depressive disorder is often characterized by changes in the structure and function of the brain, which are influenced by modifications in gene expression profiles. How the depression-related genes work together within the scope of time and space to cause pathological changes remains unclear. By integrating the brain-wide gene expression data and imaging data in major depressive disorder, we identified gene signatures of major depressive disorder and explored their temporal-spatial expression specificity, network properties, function annotations and sex differences systematically. Based on correlation analysis with permutation testing, we found 345 depression-related genes significantly correlated with functional and structural alteration of brain images in major depressive disorder and separated them by directional effects. The genes with negative effect for grey matter density and positive effect for functional indices are enriched in downregulated genes in the post-mortem brain samples of patients with depression and risk genes identified by genome-wide association studies than genes with positive effect for grey matter density and negative effect for functional indices and control genes, confirming their potential association with major depressive disorder. By introducing a parameter of dispersion measure on the gene expression data of developing human brains, we revealed higher spatial specificity and lower temporal specificity of depression-related genes than control genes. Meanwhile, we found depression-related genes tend to be more highly expressed in females than males, which may contribute to the difference in incidence rate between male and female patients. In general, we found the genes with negative effect have lower network degree, more specialized function, higher spatial specificity, lower temporal specificity and more sex differences than genes with positive effect, indicating they may play different roles in the occurrence and development of major depressive disorder. These findings can enhance the understanding of molecular mechanisms underlying major depressive disorder and help develop tailored diagnostic and treatment strategies for patients of depression of different sex.
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Affiliation(s)
- Wei Liu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Jian-Po Su
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
| | - De-Wen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, P.R. China
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67
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María Del Rocío PB, 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, Santos-Simarro F, Lleuger-Pujol R, García-Miñaúr S, Losantos-García I, Menten B, Gestri G, Ragge N, Sadikovic B, Bogaert E, Syx D, Callewaert B, Vergult S. Loss-of-function of the Zinc Finger Homeobox 4 ( ZFHX4) gene underlies a neurodevelopmental disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.07.24311381. [PMID: 39148819 PMCID: PMC11326360 DOI: 10.1101/2024.08.07.24311381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
8q21.11 microdeletions encompassing the gene encoding transcription factor ZFHX4, have previously been associated by us with a syndromic form of intellectual disability, hypotonia, decreased balance and hearing loss. Here, we report on 57 individuals, 52 probands and 5 affected family members, with protein truncating variants (n=36), (micro)deletions (n=20) or an inversion (n=1) affecting ZFHX4 with 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 variants largely overlap, identifying ZFHX4 as the main driver for the microdeletion syndrome, although leukocyte-derived DNA shows a mild common methylation profile for (micro)deletions only. We identify ZFHX4 as a transcription factor that is increasingly expressed during human brain development and neuronal differentiation. Furthermore, ZFHX4 interacting factors identified via IP-MS in neural progenitor cells, suggest an important role for ZFHX4 in cellular and developmental pathways, especially during histone modifications, cytosolic transport and development. Additionally, using CUT&RUN, we observed that ZFHX4 binds with the promoter regions of genes with crucial roles in embryonic, neuron and axon development. Since loss-of-function variants in ZFHX4 are found with consistent dysmorphic facial features, we investigated whether the disruption of zfhx4 causes craniofacial abnormalities in zebrafish. First-generation (F0) zfhx4 crispant zebrafish, (mosaic) mutant for zfhx4 loss-of-function variants, have significantly shorter Meckel's cartilages and smaller ethmoid plates compared to control zebrafish. Furthermore, behavioral assays show a decreased movement frequency in the zfhx4 crispant zebrafish in comparison with control zebrafish larvae. Although further research is needed, our in vivo work suggests a role for zfhx4 in facial skeleton patterning, palatal development and behavior.
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Affiliation(s)
- Pérez Baca María Del Rocío
- 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, 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
| | - 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, Spain
| | | | - Björn Menten
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Gaia Gestri
- University College London, London, England, Great Britain
| | - 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
| | - 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
| | - 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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68
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Wang L, Wang C, Moriano JA, Chen S, Zuo G, Cebrián-Silla A, Zhang S, Mukhtar T, Wang S, Song M, de Oliveira LG, Bi Q, Augustin JJ, Ge X, Paredes MF, Huang EJ, Alvarez-Buylla A, Duan X, Li J, Kriegstein AR. Molecular and cellular dynamics of the developing human neocortex at single-cell resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.16.575956. [PMID: 39131371 PMCID: PMC11312442 DOI: 10.1101/2024.01.16.575956] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.
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Affiliation(s)
- Li Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Cheng Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Juan A. Moriano
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
- University of Barcelona Institute of Complex Systems; Barcelona, 08007, Spain
| | - Songcang Chen
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Guolong Zuo
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Arantxa Cebrián-Silla
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurological Surgery, University of California San Francisco; San Francisco, CA 94143, USA
| | - Shaobo Zhang
- Department of Ophthalmology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Tanzila Mukhtar
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Shaohui Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Mengyi Song
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Lilian Gomes de Oliveira
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Neuro-immune Interactions Laboratory, Institute of Biomedical Sciences, Department of Immunology, University of São Paulo; São Paulo, SP 05508-220, Brazil
| | - Qiuli Bi
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Jonathan J. Augustin
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Xinxin Ge
- Department of Physiology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Mercedes F. Paredes
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Eric J. Huang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Pathology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Arturo Alvarez-Buylla
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurological Surgery, University of California San Francisco; San Francisco, CA 94143, USA
| | - Xin Duan
- Department of Ophthalmology, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Physiology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jingjing Li
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Arnold R. Kriegstein
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
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69
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Ren Z, Tang H, Zhang W, Guo M, Cui J, Wang H, Xie B, Yu J, Chen Y, Zhang M, Han C, Chu T, Liang Q, Zhao S, Huang Y, He X, Liu K, Liu C, Chen C. The Role of KDM2A and H3K36me2 Demethylation in Modulating MAPK Signaling During Neurodevelopment. Neurosci Bull 2024; 40:1076-1092. [PMID: 38060137 PMCID: PMC11306490 DOI: 10.1007/s12264-023-01161-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/13/2023] [Indexed: 12/08/2023] Open
Abstract
Intellectual disability (ID) is a condition characterized by cognitive impairment and difficulties in adaptive functioning. In our research, we identified two de novo mutations (c.955C>T and c.732C>A) at the KDM2A locus in individuals with varying degrees of ID. In addition, by using the Gene4Denovo database, we discovered five additional cases of de novo mutations in KDM2A. The mutations we identified significantly decreased the expression of the KDM2A protein. To investigate the role of KDM2A in neural development, we used both 2D neural stem cell models and 3D cerebral organoids. Our findings demonstrated that the reduced expression of KDM2A impairs the proliferation of neural progenitor cells (NPCs), increases apoptosis, induces premature neuronal differentiation, and affects synapse maturation. Through ChIP-Seq analysis, we found that KDM2A exhibited binding to the transcription start site regions of genes involved in neurogenesis. In addition, the knockdown of KDM2A hindered H3K36me2 binding to the downstream regulatory elements of genes. By integrating ChIP-Seq and RNA-Seq data, we made a significant discovery of the core genes' remarkable enrichment in the MAPK signaling pathway. Importantly, this enrichment was specifically linked to the p38 MAPK pathway. Furthermore, disease enrichment analysis linked the differentially-expressed genes identified from RNA-Seq of NPCs and cerebral organoids to neurodevelopmental disorders such as ID, autism spectrum disorder, and schizophrenia. Overall, our findings suggest that KDM2A plays a crucial role in regulating the H3K36me2 modification of downstream genes, thereby modulating the MAPK signaling pathway and potentially impacting early brain development.
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Affiliation(s)
- Zongyao Ren
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Haiyan Tang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Wendiao Zhang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Minghui Guo
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Jingjie Cui
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Hua Wang
- Department of Medical Genetics, Hunan Children's Hospital, Changsha, 410007, China
| | - Bin Xie
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Jing Yu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Yonghao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Ming Zhang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Cong Han
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Tianyao Chu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Qiuman Liang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Shunan Zhao
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Yingjie Huang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China
| | - Xuelian He
- Precision Medical Center, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan, 430014, China.
| | - Kefu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China.
| | - Chunyu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China.
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, 13210, USA.
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, 410028, China.
- National Clinical Research Center on Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, 410028, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410011, China.
- Furong Laboratory, Changsha, 410000, China.
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70
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Yao Y, Jin C, Liao Y, Huang X, Wei Z, Zhang Y, Li D, Su H, Han W, Qin D. Schizophrenia-Like Behaviors Arising from Dysregulated Proline Metabolism Are Associated with Altered Neuronal Morphology and Function in Mice with Hippocampal PRODH Deficiency. Aging Dis 2024; 15:1952-1968. [PMID: 37815900 PMCID: PMC11272211 DOI: 10.14336/ad.2023.0902] [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: 06/01/2023] [Accepted: 09/02/2023] [Indexed: 10/12/2023] Open
Abstract
Despite decades of research being conducted to understand what physiological deficits in the brain are an underlying basis of psychiatric diseases like schizophrenia, it has remained difficult to establish a direct causal relationship between neuronal dysfunction and specific behavioral phenotypes. Moreover, it remains unclear how metabolic processes, including amino acid metabolism, affect neuronal function and consequently modulate animal behaviors. PRODH, which catalyzes the first step of proline degradation, has been reported as a susceptibility gene for schizophrenia. It has consistently been shown that PRODH knockout mice exhibit schizophrenia-like behaviors. However, whether the loss of PRODH directly impacts neuronal function or whether such neuronal deficits are linked to schizophrenia-like behaviors has not yet been examined. Herein, we first ascertained that dysregulated proline metabolism in humans is associated with schizophrenia. We then found that PRODH was highly expressed in the oreins layer of the mouse dorsal hippocampus. By using AAV-mediated shRNA, we depleted PRODH expression in the mouse dorsal hippocampus and subsequently observed hyperactivity and impairments in the social behaviors, learning, and memory of these mice. Furthermore, the loss of PRODH led to altered neuronal morphology and function both in vivo and in vitro. Our study demonstrates that schizophrenia-like behaviors may arise from dysregulated proline metabolism due to the loss of PRODH and are associated with altered neuronal morphology and function in mice.
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Affiliation(s)
- Yuxiao Yao
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510799, China.
| | - Chenchen Jin
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China.
| | - Yilie Liao
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China.
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore.
| | - Xiang Huang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China.
| | - Ziying Wei
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510799, China.
| | - Yahong Zhang
- Guangzhou Laboratory, Guangzhou, Guangdong, China.
| | - Dongwei Li
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510799, China.
| | - Huanxing Su
- Institute of Chinese Medical Sciences, University of Macau, Macau, China.
| | - Weiping Han
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore.
| | - Dajiang Qin
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510799, China.
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China.
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences; Hong Kong SAR, China.
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71
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Genc S, Ball G, Chamberland M, Raven EP, Tax CM, Ward I, Yang JYM, Palombo M, Jones DK. MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.30.605934. [PMID: 39131383 PMCID: PMC11312524 DOI: 10.1101/2024.07.30.605934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss with age. However, the underlying cellular mechanisms remain elusive with conventional neuroimaging. Recent advances in MRI hardware and new biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. This study used ultra-strong gradient MRI to obtain high-resolution, in vivo estimates of cortical neurite and soma microstructure in sample of typically developing children and adolescents. Cortical neurite signal fraction, attributed to neuronal and glial processes, increased with age (mean R2 fneurite=.53, p<3.3e-11, 11.91% increase over age), while apparent soma radius decreased (mean R2 Rsoma=.48, p<4.4e-10, 1% decrease over age) across domain-specific networks. To complement these findings, developmental patterns of cortical gene expression in two independent post-mortem databases were analysed. This revealed increased expression of genes expressed in oligodendrocytes, and excitatory neurons, alongside a relative decrease in expression of genes expressed in astrocyte, microglia and endothelial cell-types. Age-related genes were significantly enriched in cortical oligodendrocytes, oligodendrocyte progenitors and Layer 5-6 neurons (pFDR<.001) and prominently expressed in adolescence and young adulthood. The spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes suggest that ongoing cortical myelination processes contribute to adolescent cortical development. These findings highlight the role of intra-cortical myelination in cortical maturation during adolescence and into adulthood.
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Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, Victoria, Australia
| | - Gareth Ball
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Eindhoven University of Technology, Department of Mathematics and Computer Science, Eindhoven, The Netherlands
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, USA
| | - Chantal Mw Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Isobel Ward
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Data and Analysis for Social Care and Health, Office for National Statistics, Newport, United Kingdom
| | - Joseph Yuan-Mou Yang
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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72
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Davis CN, Toikumo S, Hatoum AS, Khan Y, Pham BK, Pakala SR, Feuer KL, Gelernter J, Sanchez-Roige S, Kember RL, Kranzler HR. Multivariate, Multi-omic Analysis in 799,429 Individuals Identifies 134 Loci Associated with Somatoform Traits. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.29.24310991. [PMID: 39132487 PMCID: PMC11312645 DOI: 10.1101/2024.07.29.24310991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Somatoform traits, which manifest as persistent physical symptoms without a clear medical cause, are prevalent and pose challenges to clinical practice. Understanding the genetic basis of these disorders could improve diagnostic and therapeutic approaches. With publicly available summary statistics, we conducted a multivariate genome-wide association study (GWAS) and multi-omic analysis of four somatoform traits-fatigue, irritable bowel syndrome, pain intensity, and health satisfaction-in 799,429 individuals genetically similar to Europeans. Using genomic structural equation modeling, GWAS identified 134 loci significantly associated with a somatoform common factor, including 44 loci not significant in the input GWAS and 8 novel loci for somatoform traits. Gene-property analyses highlighted an enrichment of genes involved in synaptic transmission and enriched gene expression in 12 brain tissues. Six genes, including members of the CD300 family, had putatively causal effects mediated by protein abundance. There was substantial polygenic overlap (76-83%) between the somatoform and externalizing, internalizing, and general psychopathology factors. Somatoform polygenic scores were associated most strongly with obesity, Type 2 diabetes, tobacco use disorder, and mood/anxiety disorders in independent biobanks. Drug repurposing analyses suggested potential therapeutic targets, including MEK inhibitors. Mendelian randomization indicated potentially protective effects of gut microbiota, including Ruminococcus bromii. These biological insights provide promising avenues for treatment development.
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Affiliation(s)
- Christal N. Davis
- Mental Illness Research, Education, and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- 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
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Alexander S. Hatoum
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Yousef Khan
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Benjamin K. Pham
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Shreya R. Pakala
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Kyra L. Feuer
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
- Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Rachel L. Kember
- Mental Illness Research, Education, and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- 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
- Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
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73
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Zhang X. Splice-switching antisense oligonucleotides for pediatric neurological disorders. Front Mol Neurosci 2024; 17:1412964. [PMID: 39119251 PMCID: PMC11306167 DOI: 10.3389/fnmol.2024.1412964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 07/12/2024] [Indexed: 08/10/2024] Open
Abstract
Pediatric neurological disorders are frequently devastating and present unmet needs for effective medicine. The successful treatment of spinal muscular atrophy with splice-switching antisense oligonucleotides (SSO) indicates a feasible path to targeting neurological disorders by redirecting pre-mRNA splicing. One direct outcome is the development of SSOs to treat haploinsufficient disorders by targeting naturally occurring non-productive splice isoforms. The development of personalized SSO treatment further inspired the therapeutic exploration of rare diseases. This review will discuss the recent advances that utilize SSOs to treat pediatric neurological disorders.
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Affiliation(s)
- Xiaochang Zhang
- Department of Human Genetics, The Neuroscience Institute, University of Chicago, Chicago, IL, United States
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74
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DeCasien AR, Chiou KL, Testard C, Mercer A, Negrón-Del Valle JE, Bauman Surratt SE, González O, Stock MK, Ruiz-Lambides AV, Martínez MI, Antón SC, Walker CS, Sallet J, Wilson MA, Brent LJN, Montague MJ, Sherwood CC, Platt ML, Higham JP, Snyder-Mackler N. Evolutionary and biomedical implications of sex differences in the primate brain transcriptome. CELL GENOMICS 2024; 4:100589. [PMID: 38942023 PMCID: PMC11293591 DOI: 10.1016/j.xgen.2024.100589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 12/28/2023] [Accepted: 05/31/2024] [Indexed: 06/30/2024]
Abstract
Humans exhibit sex differences in the prevalence of many neurodevelopmental disorders and neurodegenerative diseases. Here, we generated one of the largest multi-brain-region bulk transcriptional datasets for the rhesus macaque and characterized sex-biased gene expression patterns to investigate the translatability of this species for sex-biased neurological conditions. We identify patterns similar to those in humans, which are associated with overlapping regulatory mechanisms, biological processes, and genes implicated in sex-biased human disorders, including autism. We also show that sex-biased genes exhibit greater genetic variance for expression and more tissue-specific expression patterns, which may facilitate rapid evolution of sex-biased genes. Our findings provide insights into the biological mechanisms underlying sex-biased disease and support the rhesus macaque model for the translational study of these conditions.
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Affiliation(s)
- Alex R DeCasien
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA; Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, USA.
| | - Kenneth L Chiou
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Department of Psychology, University of Washington, Seattle, WA, USA; Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA.
| | - Camille Testard
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Arianne Mercer
- Department of Psychology, University of Washington, Seattle, WA, USA
| | | | | | - Olga González
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Michala K Stock
- Department of Sociology and Anthropology, Metropolitan State University of Denver, Denver, CO, USA
| | | | - Melween I Martínez
- Caribbean Primate Research Center, University of Puerto Rico, San Juan, PR, USA
| | - Susan C Antón
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Christopher S Walker
- Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - Jérôme Sallet
- Stem Cell and Brain Research Institute, Université Lyon, Lyon, France
| | - Melissa A Wilson
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behavior, University of Exeter, Exeter, UK
| | - Michael J Montague
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Marketing, University of Pennsylvania, Philadelphia, PA, USA
| | - James P Higham
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA.
| | - Noah Snyder-Mackler
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Department of Psychology, University of Washington, Seattle, WA, USA; Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA; ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ, USA.
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75
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Kang J, Deng YT, Wu BS, Liu WS, Li ZY, Xiang S, Yang L, You J, Gong X, Jia T, Yu JT, Cheng W, Feng J. Whole exome sequencing analysis identifies genes for alcohol consumption. Nat Commun 2024; 15:5777. [PMID: 38982111 PMCID: PMC11233704 DOI: 10.1038/s41467-024-50132-3] [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: 05/15/2023] [Accepted: 06/26/2024] [Indexed: 07/11/2024] Open
Abstract
Alcohol consumption is a heritable behavior seriously endangers human health. However, genetic studies on alcohol consumption primarily focuses on common variants, while insights from rare coding variants are lacking. Here we leverage whole exome sequencing data across 304,119 white British individuals from UK Biobank to identify protein-coding variants associated with alcohol consumption. Twenty-five variants are associated with alcohol consumption through single variant analysis and thirteen genes through gene-based analysis, ten of which have not been reported previously. Notably, the two unreported alcohol consumption-related genes GIGYF1 and ANKRD12 show enrichment in brain function-related pathways including glial cell differentiation and are strongly expressed in the cerebellum. Phenome-wide association analyses reveal that alcohol consumption-related genes are associated with brain white matter integrity and risk of digestive and neuropsychiatric diseases. In summary, this study enhances the comprehension of the genetic architecture of alcohol consumption and implies biological mechanisms underlying alcohol-related adverse outcomes.
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Affiliation(s)
- Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Xiaohong Gong
- School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- School of Psychology, University of Southampton, Southampton, UK
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China.
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China.
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China.
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
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76
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Morales-Vicente DA, Tahira AC, Woellner-Santos D, Amaral MS, Berzoti-Coelho MG, Verjovski-Almeida S. The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons. Mol Biol Evol 2024; 41:msae123. [PMID: 38913688 PMCID: PMC11221658 DOI: 10.1093/molbev/msae123] [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: 11/23/2023] [Revised: 06/12/2024] [Accepted: 06/14/2024] [Indexed: 06/26/2024] Open
Abstract
The outstanding human cognitive capacities are computed in the cerebral cortex, a mammalian-specific brain region and the place of massive biological innovation. Long noncoding RNAs have emerged as gene regulatory elements with higher evolutionary turnover than mRNAs. The many long noncoding RNAs identified in neural tissues make them candidates for molecular sources of cerebral cortex evolution and disease. Here, we characterized the genomic and cellular shifts that occurred during the evolution of the long noncoding RNA repertoire expressed in the developing cerebral cortex and explored putative roles for these long noncoding RNAs in the evolution of the human brain. Using transcriptomics and comparative genomics, we comprehensively annotated the cortical transcriptomes of humans, rhesus macaques, mice, and chickens and classified human cortical long noncoding RNAs into evolutionary groups as a function of their predicted minimal ages. Long noncoding RNA evolutionary groups showed differences in expression levels, splicing efficiencies, transposable element contents, genomic distributions, and transcription factor binding to their promoters. Furthermore, older long noncoding RNAs showed preferential expression in germinative zones, outer radial glial cells, and cortical inhibitory (GABAergic) neurons. In comparison, younger long noncoding RNAs showed preferential expression in cortical excitatory (glutamatergic) neurons, were enriched in primate and human-specific gene co-expression modules, and were dysregulated in neurodevelopmental disorders. These results suggest different evolutionary routes for older and younger cortical long noncoding RNAs, highlighting old long noncoding RNAs as a possible source of molecular evolution of conserved developmental programs; conversely, we propose that the de novo expression of primate- and human-specific young long noncoding RNAs is a putative source of molecular evolution and dysfunction of cortical excitatory neurons, warranting further investigation.
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Affiliation(s)
- David A Morales-Vicente
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Ana C Tahira
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
| | - Daisy Woellner-Santos
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Murilo S Amaral
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
| | - Maria G Berzoti-Coelho
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Sergio Verjovski-Almeida
- Laboratório de Ciclo Celular, Instituto Butantan, São Paulo, Brazil
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
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77
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Zheng J, Zong X, Tang L, Guo H, Zhao P, Womer FY, Zhang X, Tang Y, Wang F. Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders. Psychol Med 2024; 54:2774-2784. [PMID: 38804091 DOI: 10.1017/s0033291724000886] [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: 05/29/2024]
Abstract
BACKGROUND Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine. METHODS We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort. RESULTS Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable. CONCLUSIONS Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.
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Affiliation(s)
- Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China
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78
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Kissel LT, Pochareddy S, An JY, Sestan N, Sanders SJ, Wang X, Werling DM. Sex-Differential Gene Expression in Developing Human Cortex and Its Intersection With Autism Risk Pathways. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100321. [PMID: 38957312 PMCID: PMC11217612 DOI: 10.1016/j.bpsgos.2024.100321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 04/09/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024] Open
Abstract
Background Sex-differential biology may contribute to the consistently male-biased prevalence of autism spectrum disorder (ASD). Gene expression differences between males and females in the brain can indicate possible molecular and cellular mechanisms involved, although transcriptomic sex differences during human prenatal cortical development have been incompletely characterized, primarily due to small sample sizes. Methods We performed a meta-analysis of sex-differential expression and co-expression network analysis in 2 independent bulk RNA sequencing datasets generated from cortex of 273 prenatal donors without known neuropsychiatric disorders. To assess the intersection between neurotypical sex differences and neuropsychiatric disorder biology, we tested for enrichment of ASD-associated risk genes and expression changes, neuropsychiatric disorder risk genes, and cell type markers within identified sex-differentially expressed genes (sex-DEGs) and sex-differential co-expression modules. Results We identified 101 significant sex-DEGs, including Y-chromosome genes, genes impacted by X-chromosome inactivation, and autosomal genes. Known ASD risk genes, implicated by either common or rare variants, did not preferentially overlap with sex-DEGs. We identified 1 male-specific co-expression module enriched for immune signaling that is unique to 1 input dataset. Conclusions Sex-differential gene expression is limited in prenatal human cortex tissue, although meta-analysis of large datasets allows for the identification of sex-DEGs, including autosomal genes that encode proteins involved in neural development. Lack of sex-DEG overlap with ASD risk genes in the prenatal cortex suggests that sex-differential modulation of ASD symptoms may occur in other brain regions, at other developmental stages, or in specific cell types, or may involve mechanisms that act downstream from mutation-carrying genes.
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Affiliation(s)
- Lee T. Kissel
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, Wisconsin
| | - Sirisha Pochareddy
- Department of Neuroscience and Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, Connecticut
| | - Joon-Yong An
- Department of Integrated Biomedical and Life Science, Korea University, Seoul, Republic of Korea
- Transdisciplinary Major in Learning Health Systems, Department of Healthcare Sciences, Graduate School, Korea University, Seoul, Republic of Korea
- BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, Republic of Korea
| | - Nenad Sestan
- Department of Neuroscience and Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, Connecticut
| | - Stephan J. Sanders
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Xuran Wang
- Seaver Autism Center for Research and Treatment, New York, New York
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Donna M. Werling
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, Wisconsin
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79
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Fazel Darbandi S, An JY, Lim K, Page NF, Liang L, Young DM, Ypsilanti AR, State MW, Nord AS, Sanders SJ, Rubenstein JLR. Five autism-associated transcriptional regulators target shared loci proximal to brain-expressed genes. Cell Rep 2024; 43:114329. [PMID: 38850535 PMCID: PMC11235582 DOI: 10.1016/j.celrep.2024.114329] [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: 05/29/2023] [Revised: 09/15/2023] [Accepted: 05/22/2024] [Indexed: 06/10/2024] Open
Abstract
Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). Chromatin immunoprecipitation sequencing (ChIP-seq) was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000 bp upstream of the transcription start site, was highly predictive of brain-expressed genes. This signature was observed in 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After 8 days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest that functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.
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Affiliation(s)
- Siavash Fazel Darbandi
- Nina Ireland Laboratory of Developmental Neurobiology, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Joon-Yong An
- School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, South Korea; BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, South Korea
| | - Kenneth Lim
- Nina Ireland Laboratory of Developmental Neurobiology, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Nicholas F Page
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Lindsay Liang
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - David M Young
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Athena R Ypsilanti
- Nina Ireland Laboratory of Developmental Neurobiology, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Matthew W State
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alex S Nord
- Department of Neurobiology, Physiology, and Behavior and Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA
| | - Stephan J Sanders
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA; Institute for Developmental and Regenerative Medicine, Old Road Campus, Roosevelt Dr., Headington, Oxford OX3 7TY, UK.
| | - John L R Rubenstein
- Nina Ireland Laboratory of Developmental Neurobiology, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA.
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80
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Feng G, Wang Y, Huang W, Chen H, Cheng J, Shu N. Spatial and temporal pattern of structure-function coupling of human brain connectome with development. eLife 2024; 13:RP93325. [PMID: 38900563 PMCID: PMC11189631 DOI: 10.7554/elife.93325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024] Open
Abstract
Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7-21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.
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Affiliation(s)
- Guozheng Feng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Yiwen Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Haojie Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Jian Cheng
- School of Computer Science and Engineering, Beihang UniversityBeijingChina
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- BABRI Centre, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
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81
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Vogel JW, Alexander-Bloch AF, Wagstyl K, Bertolero MA, Markello RD, Pines A, Sydnor VJ, Diaz-Papkovich A, Hansen JY, Evans AC, Bernhardt B, Misic B, Satterthwaite TD, Seidlitz J. Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain. Proc Natl Acad Sci U S A 2024; 121:e2219137121. [PMID: 38861593 PMCID: PMC11194492 DOI: 10.1073/pnas.2219137121] [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: 11/08/2022] [Accepted: 04/27/2024] [Indexed: 06/13/2024] Open
Abstract
Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.
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Affiliation(s)
- Jacob W. Vogel
- Department of Clinical Sciences Malmö, SciLifeLab, Lund University, Lund, Sweden202 13
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
| | - Aaron F. Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA19104
- Penn-Children’s Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA19104
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, LondonWC1N 3AR, United Kingdom
| | - Maxwell A. Bertolero
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
| | - Ross D. Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QCH3A 2B4, Canada
| | - Adam Pines
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Valerie J. Sydnor
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
| | - Alex Diaz-Papkovich
- Quantitative Life Sciences, McGill University, Montreal, QCH3A 1E3, Canada
- McGill Genome Centre, McGill University, Montreal, QCH3A 0G1, Canada
| | - Justine Y. Hansen
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QCH3A 2B4, Canada
| | - Alan C. Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QCH3A 2B4, Canada
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QCH3A 2B4, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QCH3A 2B4, Canada
| | - Theodore D. Satterthwaite
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
- Penn-Children’s Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA19104
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA19104
- Penn-Children’s Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA19104
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Ganglberger F, Kargl D, Töpfer M, Hernandez-Lallement J, Lawless N, Fernandez-Albert F, Haubensak W, Bühler K. BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource. Commun Biol 2024; 7:730. [PMID: 38877144 PMCID: PMC11178817 DOI: 10.1038/s42003-024-06355-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/20/2024] [Indexed: 06/16/2024] Open
Abstract
Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.
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Affiliation(s)
- Florian Ganglberger
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Dominic Kargl
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
| | - Markus Töpfer
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
| | - Julien Hernandez-Lallement
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Nathan Lawless
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Francesc Fernandez-Albert
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Wulf Haubensak
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
| | - Katja Bühler
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria.
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83
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Mato-Blanco X, Kim SK, Jourdon A, Ma S, Tebbenkamp AT, Liu F, Duque A, Vaccarino FM, Sestan N, Colantuoni C, Rakic P, Santpere G, Micali N. Early Developmental Origins of Cortical Disorders Modeled in Human Neural Stem Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.14.598925. [PMID: 38915580 PMCID: PMC11195173 DOI: 10.1101/2024.06.14.598925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The implications of the early phases of human telencephalic development, involving neural stem cells (NSCs), in the etiology of cortical disorders remain elusive. Here, we explored the expression dynamics of cortical and neuropsychiatric disorder-associated genes in datasets generated from human NSCs across telencephalic fate transitions in vitro and in vivo. We identified risk genes expressed in brain organizers and sequential gene regulatory networks across corticogenesis revealing disease-specific critical phases, when NSCs are more vulnerable to gene dysfunctions, and converging signaling across multiple diseases. Moreover, we simulated the impact of risk transcription factor (TF) depletions on different neural cell types spanning the developing human neocortex and observed a spatiotemporal-dependent effect for each perturbation. Finally, single-cell transcriptomics of newly generated autism-affected patient-derived NSCs in vitro revealed recurrent alterations of TFs orchestrating brain patterning and NSC lineage commitment. This work opens new perspectives to explore human brain dysfunctions at the early phases of development.
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Affiliation(s)
- Xoel Mato-Blanco
- Hospital del Mar Research Institute, Parc de Recerca Biomèdica de Barcelona (PRBB), 08003 Barcelona, Catalonia, Spain
| | - Suel-Kee Kim
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Alexandre Jourdon
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Fuchen Liu
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Alvaro Duque
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Flora M. Vaccarino
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Departments of Psychiatry, Genetics and Comparative Medicine, Wu Tsai Institute, Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale School of Medicine, New Haven, CT 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Carlo Colantuoni
- Depts. of Neurology, Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Pasko Rakic
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Gabriel Santpere
- Hospital del Mar Research Institute, Parc de Recerca Biomèdica de Barcelona (PRBB), 08003 Barcelona, Catalonia, Spain
| | - Nicola Micali
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
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84
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Kul E, Okoroafor U, Dougherty A, Palkovic L, Li H, Valiño-Ramos P, Aberman L, Young SM. Development of adenoviral vectors that transduce Purkinje cells and other cerebellar cell-types in the cerebellum of a humanized mouse model. Mol Ther Methods Clin Dev 2024; 32:101243. [PMID: 38605812 PMCID: PMC11007541 DOI: 10.1016/j.omtm.2024.101243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/22/2024] [Indexed: 04/13/2024]
Abstract
Viral vector gene therapy has immense promise for treating central nervous system (CNS) disorders. Although adeno-associated virus vectors (AAVs) have had success, their small packaging capacity limits their utility to treat the root cause of many CNS disorders. Adenoviral vectors (Ad) have tremendous potential for CNS gene therapy approaches. Currently, the most common vectors utilize the Group C Ad5 serotype capsid proteins, which rely on the Coxsackievirus-Adenovirus receptor (CAR) to infect cells. However, these Ad5 vectors are unable to transduce many neuronal cell types that are dysfunctional in many CNS disorders. The human CD46 (hCD46) receptor is widely expressed throughout the human CNS and is the primary attachment receptor for many Ad serotypes. Therefore, to overcome the current limitations of Ad vectors to treat CNS disorders, we created chimeric first generation Ad vectors that utilize the hCD46 receptor. Using a "humanized" hCD46 mouse model, we demonstrate these Ad vectors transduce cerebellar cell types, including Purkinje cells, that are refractory to Ad5 transduction. Since Ad vector transduction properties are dependent on their capsid proteins, these chimeric first generation Ad vectors open new avenues for high-capacity helper-dependent adenovirus (HdAd) gene therapy approaches for cerebellar disorders and multiple neurological disorders.
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Affiliation(s)
- Emre Kul
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Uchechi Okoroafor
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
- Cell Developmental Biology Graduate Program, University of Iowa, Iowa City, IA 52242, USA
| | - Amanda Dougherty
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Lauren Palkovic
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Hao Li
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Paula Valiño-Ramos
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Leah Aberman
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
| | - Samuel M. Young
- Department of Anatomy and Cell Biology, University of Iowa, Iowa City, IA 52242, USA
- Cell Developmental Biology Graduate Program, University of Iowa, Iowa City, IA 52242, USA
- Department of Otolaryngology, University of Iowa, Iowa City, IA 52242, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA 52242, USA
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85
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Recinos Y, Bao S, Wang X, Phillips BL, Yeh YT, Weyn-Vanhentenryck SM, Swanson MS, Zhang C. Lineage-specific splicing regulation of MAPT gene in the primate brain. CELL GENOMICS 2024; 4:100563. [PMID: 38772368 PMCID: PMC11228892 DOI: 10.1016/j.xgen.2024.100563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 01/22/2024] [Accepted: 04/23/2024] [Indexed: 05/23/2024]
Abstract
Divergence of precursor messenger RNA (pre-mRNA) alternative splicing (AS) is widespread in mammals, including primates, but the underlying mechanisms and functional impact are poorly understood. Here, we modeled cassette exon inclusion in primate brains as a quantitative trait and identified 1,170 (∼3%) exons with lineage-specific splicing shifts under stabilizing selection. Among them, microtubule-associated protein tau (MAPT) exons 2 and 10 underwent anticorrelated, two-step evolutionary shifts in the catarrhine and hominoid lineages, leading to their present inclusion levels in humans. The developmental-stage-specific divergence of exon 10 splicing, whose dysregulation can cause frontotemporal lobar degeneration (FTLD), is mediated by divergent distal intronic MBNL-binding sites. Competitive binding of these sites by CRISPR-dCas13d/gRNAs effectively reduces exon 10 inclusion, potentially providing a therapeutically compatible approach to modulate tau isoform expression. Our data suggest adaptation of MAPT function and, more generally, a role for AS in the evolutionary expansion of the primate brain.
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Affiliation(s)
- Yocelyn Recinos
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Suying Bao
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Xiaojian Wang
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Brittany L Phillips
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Yow-Tyng Yeh
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Sebastien M Weyn-Vanhentenryck
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Maurice S Swanson
- Department of Molecular Genetics and Microbiology, University of Florida, College of Medicine, Gainesville, FL 32610, USA; Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL 32610, USA
| | - Chaolin Zhang
- Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.
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86
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Prince GS, Reynolds M, Martina V, Sun H. Gene-environmental regulation of the postnatal post-mitotic neuronal maturation. Trends Genet 2024; 40:480-494. [PMID: 38658255 PMCID: PMC11153025 DOI: 10.1016/j.tig.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/20/2024] [Accepted: 03/21/2024] [Indexed: 04/26/2024]
Abstract
Embryonic neurodevelopment, particularly neural progenitor differentiation into post-mitotic neurons, has been extensively studied. While the number and composition of post-mitotic neurons remain relatively constant from birth to adulthood, the brain undergoes significant postnatal maturation marked by major property changes frequently disrupted in neural diseases. This review first summarizes recent characterizations of the functional and molecular maturation of the postnatal nervous system. We then review regulatory mechanisms controlling the precise gene expression changes crucial for the intricate sequence of maturation events, highlighting experience-dependent versus cell-intrinsic genetic timer mechanisms. Despite significant advances in understanding of the gene-environmental regulation of postnatal neuronal maturation, many aspects remain unknown. The review concludes with our perspective on exciting future research directions in the next decade.
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Affiliation(s)
- Gabrielle S Prince
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Molly Reynolds
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Verdion Martina
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - HaoSheng Sun
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA; Freeman Hrabowski Scholar, Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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87
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Kaizuka T, Takumi T. Alteration of synaptic protein composition during developmental synapse maturation. Eur J Neurosci 2024; 59:2894-2914. [PMID: 38571321 DOI: 10.1111/ejn.16304] [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: 05/01/2023] [Revised: 01/02/2024] [Accepted: 02/07/2024] [Indexed: 04/05/2024]
Abstract
The postsynaptic density (PSD) is a collection of specialized proteins assembled beneath the postsynaptic membrane of dendritic spines. The PSD proteome comprises ~1000 proteins, including neurotransmitter receptors, scaffolding proteins and signalling enzymes. Many of these proteins have essential roles in synaptic function and plasticity. During brain development, changes are observed in synapse density and in the stability and shape of spines, reflecting the underlying molecular maturation of synapses. Synaptic protein composition changes in terms of protein abundance and the assembly of protein complexes, supercomplexes and the physical organization of the PSD. Here, we summarize the developmental alterations of postsynaptic protein composition during synapse maturation. We describe major PSD proteins involved in postsynaptic signalling that regulates synaptic plasticity and discuss the effect of altered expression of these proteins during development. We consider the abnormality of synaptic profiles and synaptic protein composition in the brain in neurodevelopmental disorders such as autism spectrum disorders. We also explain differences in synapse development between rodents and primates in terms of synaptic profiles and protein composition. Finally, we introduce recent findings related to synaptic diversity and nanoarchitecture and discuss their impact on future research. Synaptic protein composition can be considered a major determinant and marker of synapse maturation in normality and disease.
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Affiliation(s)
- Takeshi Kaizuka
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Kobe, Japan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Toru Takumi
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Kobe, Japan
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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88
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Dear R, Wagstyl K, Seidlitz J, Markello RD, Arnatkevičiūtė A, Anderson KM, Bethlehem RAI, Raznahan A, Bullmore ET, Vértes PE. Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia. Nat Neurosci 2024; 27:1075-1086. [PMID: 38649755 PMCID: PMC11156586 DOI: 10.1038/s41593-024-01624-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 03/18/2024] [Indexed: 04/25/2024]
Abstract
Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.
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Affiliation(s)
- Richard Dear
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | | | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Aurina Arnatkevičiūtė
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | | | | | - Armin Raznahan
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, USA
| | | | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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89
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Li J, Zhang C, Meng Y, Yang S, Xia J, Chen H, Liao W. Morphometric brain organization across the human lifespan reveals increased dispersion linked to cognitive performance. PLoS Biol 2024; 22:e3002647. [PMID: 38900742 PMCID: PMC11189252 DOI: 10.1371/journal.pbio.3002647] [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: 09/25/2023] [Accepted: 04/26/2024] [Indexed: 06/22/2024] Open
Abstract
The human brain is organized as segregation and integration units and follows complex developmental trajectories throughout life. The cortical manifold provides a new means of studying the brain's organization in a multidimensional connectivity gradient space. However, how the brain's morphometric organization changes across the human lifespan remains unclear. Here, leveraging structural magnetic resonance imaging scans from 1,790 healthy individuals aged 8 to 89 years, we investigated age-related global, within- and between-network dispersions to reveal the segregation and integration of brain networks from 3D manifolds based on morphometric similarity network (MSN), combining multiple features conceptualized as a "fingerprint" of an individual's brain. Developmental trajectories of global dispersion unfolded along patterns of molecular brain organization, such as acetylcholine receptor. Communities were increasingly dispersed with age, reflecting more disassortative morphometric similarity profiles within a community. Increasing within-network dispersion of primary motor and association cortices mediated the influence of age on the cognitive flexibility of executive functions. We also found that the secondary sensory cortices were decreasingly dispersed with the rest of the cortices during aging, possibly indicating a shift of secondary sensory cortices across the human lifespan from an extreme to a more central position in 3D manifolds. Together, our results reveal the age-related segregation and integration of MSN from the perspective of a multidimensional gradient space, providing new insights into lifespan changes in multiple morphometric features of the brain, as well as the influence of such changes on cognitive performance.
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Affiliation(s)
- Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Chao Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Siqi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Jie Xia
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
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90
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Liu J, Supekar K, El-Said D, de los Angeles C, Zhang Y, Chang H, Menon V. Neuroanatomical, transcriptomic, and molecular correlates of math ability and their prognostic value for predicting learning outcomes. SCIENCE ADVANCES 2024; 10:eadk7220. [PMID: 38820151 PMCID: PMC11141625 DOI: 10.1126/sciadv.adk7220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 04/29/2024] [Indexed: 06/02/2024]
Abstract
Foundational mathematical abilities, acquired in early childhood, are essential for success in our technology-driven society. Yet, the neurobiological mechanisms underlying individual differences in children's mathematical abilities and learning outcomes remain largely unexplored. Leveraging one of the largest multicohort datasets from children at a pivotal stage of knowledge acquisition, we first establish a replicable mathematical ability-related imaging phenotype (MAIP). We then show that brain gene expression profiles enriched for candidate math ability-related genes, neuronal signaling, synaptic transmission, and voltage-gated potassium channel activity contributed to the MAIP. Furthermore, the similarity between MAIP gene expression signatures and brain structure, acquired before intervention, predicted learning outcomes in two independent math tutoring cohorts. These findings advance our knowledge of the interplay between neuroanatomical, transcriptomic, and molecular mechanisms underlying mathematical ability and reveal predictive biomarkers of learning. Our findings have implications for the development of personalized education and interventions.
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Affiliation(s)
- Jin Liu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kaustubh Supekar
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Dawlat El-Said
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlo de los Angeles
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yuan Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Hyesang Chang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
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91
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Li Q, Xia M, Zeng D, Xu Y, Sun L, Liang X, Xu Z, Zhao T, Liao X, Yuan H, Liu Y, Huo R, Li S, He Y. Development of segregation and integration of functional connectomes during the first 1,000 days. Cell Rep 2024; 43:114168. [PMID: 38700981 DOI: 10.1016/j.celrep.2024.114168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/26/2024] [Accepted: 04/15/2024] [Indexed: 05/05/2024] Open
Abstract
The first 1,000 days of human life lay the foundation for brain development and later cognitive growth. However, the developmental rules of the functional connectome during this critical period remain unclear. Using high-resolution, longitudinal, task-free functional magnetic resonance imaging data from 930 scans of 665 infants aged 28 postmenstrual weeks to 3 years, we report the early maturational process of connectome segregation and integration. We show the dominant development of local connections alongside a few global connections, the shift of brain hubs from primary regions to high-order association cortices, the developmental divergence of network segregation and integration along the anterior-posterior axis, the prediction of neurocognitive outcomes, and their associations with gene expression signatures of microstructural development and neuronal metabolic pathways. These findings advance our understanding of the principles of connectome remodeling during early life and its neurobiological underpinnings and have implications for studying typical and atypical development.
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Affiliation(s)
- Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Debin Zeng
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing 100191, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing 100191, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing 100191, China
| | - Shuyu Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China.
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92
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Morys F, Tremblay C, Rahayel S, Hansen JY, Dai A, Misic B, Dagher A. Neural correlates of obesity across the lifespan. Commun Biol 2024; 7:656. [PMID: 38806652 PMCID: PMC11133431 DOI: 10.1038/s42003-024-06361-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 05/20/2024] [Indexed: 05/30/2024] Open
Abstract
Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.
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Affiliation(s)
- Filip Morys
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada.
| | - Christina Tremblay
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Shady Rahayel
- Department of Medicine and Medical Specialties, University of Montreal, Montreal, QC, Canada
- Center for Advanced Research in Sleep Medicine, Hopital du Sacre-Coeur de Montreal, Montreal, QC, Canada
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Alyssa Dai
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, QC, Canada
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93
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Courchesne E, Taluja V, Nazari S, Aamodt CM, Pierce K, Duan K, Stophaeros S, Lopez L, Barnes CC, Troxel J, Campbell K, Wang T, Hoekzema K, Eichler EE, Nani JV, Pontes W, Sanchez SS, Lombardo MV, de Souza JS, Hayashi MAF, Muotri AR. Embryonic origin of two ASD subtypes of social symptom severity: the larger the brain cortical organoid size, the more severe the social symptoms. Mol Autism 2024; 15:22. [PMID: 38790065 PMCID: PMC11127428 DOI: 10.1186/s13229-024-00602-8] [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: 12/05/2023] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Social affective and communication symptoms are central to autism spectrum disorder (ASD), yet their severity differs across toddlers: Some toddlers with ASD display improving abilities across early ages and develop good social and language skills, while others with "profound" autism have persistently low social, language and cognitive skills and require lifelong care. The biological origins of these opposite ASD social severity subtypes and developmental trajectories are not known. METHODS Because ASD involves early brain overgrowth and excess neurons, we measured size and growth in 4910 embryonic-stage brain cortical organoids (BCOs) from a total of 10 toddlers with ASD and 6 controls (averaging 196 individual BCOs measured/subject). In a 2021 batch, we measured BCOs from 10 ASD and 5 controls. In a 2022 batch, we tested replicability of BCO size and growth effects by generating and measuring an independent batch of BCOs from 6 ASD and 4 control subjects. BCO size was analyzed within the context of our large, one-of-a-kind social symptom, social attention, social brain and social and language psychometric normative datasets ranging from N = 266 to N = 1902 toddlers. BCO growth rates were examined by measuring size changes between 1- and 2-months of organoid development. Neurogenesis markers at 2-months were examined at the cellular level. At the molecular level, we measured activity and expression of Ndel1; Ndel1 is a prime target for cell cycle-activated kinases; known to regulate cell cycle, proliferation, neurogenesis, and growth; and known to be involved in neuropsychiatric conditions. RESULTS At the BCO level, analyses showed BCO size was significantly enlarged by 39% and 41% in ASD in the 2021 and 2022 batches. The larger the embryonic BCO size, the more severe the ASD social symptoms. Correlations between BCO size and social symptoms were r = 0.719 in the 2021 batch and r = 0. 873 in the replication 2022 batch. ASD BCOs grew at an accelerated rate nearly 3 times faster than controls. At the cell level, the two largest ASD BCOs had accelerated neurogenesis. At the molecular level, Ndel1 activity was highly correlated with the growth rate and size of BCOs. Two BCO subtypes were found in ASD toddlers: Those in one subtype had very enlarged BCO size with accelerated rate of growth and neurogenesis; a profound autism clinical phenotype displaying severe social symptoms, reduced social attention, reduced cognitive, very low language and social IQ; and substantially altered growth in specific cortical social, language and sensory regions. Those in a second subtype had milder BCO enlargement and milder social, attention, cognitive, language and cortical differences. LIMITATIONS Larger samples of ASD toddler-derived BCO and clinical phenotypes may reveal additional ASD embryonic subtypes. CONCLUSIONS By embryogenesis, the biological bases of two subtypes of ASD social and brain development-profound autism and mild autism-are already present and measurable and involve dysregulated cell proliferation and accelerated neurogenesis and growth. The larger the embryonic BCO size in ASD, the more severe the toddler's social symptoms and the more reduced the social attention, language ability, and IQ, and the more atypical the growth of social and language brain regions.
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Affiliation(s)
- Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA.
| | - Vani Taluja
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Sanaz Nazari
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Caitlin M Aamodt
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Kuaikuai Duan
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Sunny Stophaeros
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Cynthia Carter Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Jaden Troxel
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Kathleen Campbell
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, 8110 La Jolla Shores Dr., La Jolla, CA, 92037, USA
| | - Tianyun Wang
- Department of Medical Genetics, Center for Medical Genetics, Peking University Health Science Center, Beijing, 100191, China
- Neuroscience Research Institute, Peking University, Key Laboratory for Neuroscience, Ministry of Education of China and National Health Commission of China, Beijing, 100191, China
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA
| | - Joao V Nani
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Wirla Pontes
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA
| | - Sandra Sanchez Sanchez
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Janaina S de Souza
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA
| | - Mirian A F Hayashi
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Alysson R Muotri
- Department of Pediatrics and Department of Molecular and Cellular Medicine, University of California, San Diego, Gilman Drive, La Jolla, CA, 92093, USA.
- Rady Children's Hospital, Center for Academic Research and Training in Anthropogeny (CARTA), Archealization Center (ArchC), Kavli Institute for Brain and Mind, La Jolla, CA, USA.
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94
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Ruzicka WB, Mohammadi S, Fullard JF, Davila-Velderrain J, Subburaju S, Tso DR, Hourihan M, Jiang S, Lee HC, Bendl J, Voloudakis G, Haroutunian V, Hoffman GE, Roussos P, Kellis M. Single-cell multi-cohort dissection of the schizophrenia transcriptome. Science 2024; 384:eadg5136. [PMID: 38781388 DOI: 10.1126/science.adg5136] [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: 02/02/2023] [Accepted: 07/21/2023] [Indexed: 05/25/2024]
Abstract
The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.
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Affiliation(s)
- W Brad Ruzicka
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02478, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shahin Mohammadi
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jose Davila-Velderrain
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Neurogenomics Research Center, Human Technopole, 20157 Milan, Italy
| | - Sivan Subburaju
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02478, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel Reed Tso
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02478, USA
| | - Makayla Hourihan
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02478, USA
| | - Shan Jiang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hao-Chih Lee
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Neurogenomics Research Center, Human Technopole, 20157 Milan, Italy
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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95
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Pratt HE, Andrews G, Shedd N, Phalke N, Li T, Pampari A, Jensen M, Wen C, Consortium P, Gandal MJ, Geschwind DH, Gerstein M, Moore J, Kundaje A, Colubri A, Weng Z. Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements. SCIENCE ADVANCES 2024; 10:eadj4452. [PMID: 38781344 PMCID: PMC11114231 DOI: 10.1126/sciadv.adj4452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/25/2024] [Indexed: 05/25/2024]
Abstract
Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements' sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type-specific gene regulation in various types of glia and neurons. The elements' evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.
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Affiliation(s)
- Henry E. Pratt
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Gregory Andrews
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Tongxin Li
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA
| | - Anusri Pampari
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matthew Jensen
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | | | - Michael J. Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Daniel H. Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Andrés Colubri
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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96
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. Science 2024; 384:eadi5199. [PMID: 38781369 PMCID: PMC11365579 DOI: 10.1126/science.adi5199] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Chicago, IL 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597 Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, USA
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97
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Wen C, Margolis M, Dai R, Zhang P, Przytycki PF, Vo DD, Bhattacharya A, Matoba N, Tang M, Jiao C, Kim M, Tsai E, Hoh C, Aygün N, Walker RL, Chatzinakos C, Clarke D, Pratt H, Peters MA, Gerstein M, Daskalakis NP, Weng Z, Jaffe AE, Kleinman JE, Hyde TM, Weinberger DR, Bray NJ, Sestan N, Geschwind DH, Roeder K, Gusev A, Pasaniuc B, Stein JL, Love MI, Pollard KS, Liu C, Gandal MJ. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain. Science 2024; 384:eadh0829. [PMID: 38781368 DOI: 10.1126/science.adh0829] [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: 02/14/2023] [Accepted: 03/07/2024] [Indexed: 05/25/2024]
Abstract
Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.
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Affiliation(s)
- Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Michael Margolis
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Rujia Dai
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Pan Zhang
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Pawel F Przytycki
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
| | - Daniel D Vo
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nana Matoba
- 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
| | - Miao Tang
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Chuan Jiao
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team Krebs, 75014 Paris, France
| | - Minsoo Kim
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Ellen Tsai
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Celine Hoh
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nil Aygün
- 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
| | - Rebecca L Walker
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Christos Chatzinakos
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Declan Clarke
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Henry Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Mette A Peters
- CNS Data Coordination Group, Sage Bionetworks, Seattle, WA 98109, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nikolaos P Daskalakis
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Neumora Therapeutics, Watertown, MA 02472, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nicholas J Bray
- MRC Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University School of Medicine, Cardiff CF24 4HQ, UK
| | - Nenad Sestan
- Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT 06520, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kathryn Roeder
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Alexander Gusev
- Department of Medical Oncology, Division of Population Sciences, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02215, USA
- Division of Genetics, Brigham and Women's Hospital, Boston, MA 02215, USA
| | - Bogdan Pasaniuc
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, 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
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
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98
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Wamsley B, Bicks L, Cheng Y, Kawaguchi R, Quintero D, Margolis M, Grundman J, Liu J, Xiao S, Hawken N, Mazariegos S, Geschwind DH. Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics. Science 2024; 384:eadh2602. [PMID: 38781372 DOI: 10.1126/science.adh2602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 02/28/2024] [Indexed: 05/25/2024]
Abstract
Genomic profiling in postmortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition are not well understood. We performed deep single-nucleus RNA sequencing (snRNA-seq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism spectrum disorder (ASD), which we corroborated using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) and spatial transcriptomics. Transcriptomic changes were primarily cell type specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain.
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Affiliation(s)
- Brie Wamsley
- Program in Neurobehavioral Genetics and Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Michael Margolis
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer Grundman
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Daniel H Geschwind
- Program in Neurobehavioral Genetics and Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
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99
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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 pivotal role of the X-chromosome in the genetic architecture of the human brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294848. [PMID: 37693466 PMCID: PMC10491353 DOI: 10.1101/2023.08.30.23294848] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
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 network. We examined 1,045 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 (DC) 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 discovered 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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100
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Cai W, Song W, Yu S, Zhao M, Lin GN. Human lineage mutations regulate RNA-protein binding of conserved genes NTRK2 and ITPR1 involved in human evolution. Gen Psychiatr 2024; 37:e101425. [PMID: 38770356 PMCID: PMC11103204 DOI: 10.1136/gpsych-2023-101425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 04/14/2024] [Indexed: 05/22/2024] Open
Abstract
Background The role of human lineage mutations (HLMs) in human evolution through post-transcriptional modification is unclear. Aims To investigate the contribution of HLMs to human evolution through post-transcriptional modification. Methods We applied a deep learning model Seqweaver to predict how HLMs impact RNA-binding protein affinity. Results We found that only 0.27% of HLMs had significant impacts on RNA-binding proteins at the threshold of the top 1% of human common variations. These HLMs enriched in a set of conserved genes highly expressed in adult excitatory neurons and prenatal Purkinje neurons, and were involved in synapse organisation and the GTPase pathway. These genes also carried excess damaging coding mutations that caused neurodevelopmental disorders, ataxia and schizophrenia. Among these genes, NTRK2 and ITPR1 had the most aggregated evidence of functional importance, suggesting their essential roles in cognition and bipedalism. Conclusions Our findings suggest that a small subset of human-specific mutations have contributed to human speciation through impacts on post-transcriptional modification of critical brain-related genes.
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Affiliation(s)
- Wenxiang Cai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Shunying Yu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| |
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