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Matthew J, Uus A, Egloff Collado A, Luis A, Arulkumaran S, Fukami-Gartner A, Kyriakopoulou V, Cromb D, Wright R, Colford K, Deprez M, Hutter J, O’Muircheartaigh J, Malamateniou C, Razavi R, Story L, Hajnal JV, Rutherford MA. Automated craniofacial biometry with 3D T2w fetal MRI. PLOS DIGITAL HEALTH 2024; 3:e0000663. [PMID: 39774200 PMCID: PMC11684610 DOI: 10.1371/journal.pdig.0000663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 10/09/2024] [Indexed: 01/11/2025]
Abstract
OBJECTIVES Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated label propagation pipeline using 3D motion- corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements. METHODS A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers. RESULTS Automated labels were produced for all 132 subjects with a 0.3% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research. CONCLUSION This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.
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Affiliation(s)
- Jacqueline Matthew
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Alena Uus
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Alexia Egloff Collado
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Aysha Luis
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Sophie Arulkumaran
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Abi Fukami-Gartner
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Vanessa Kyriakopoulou
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Daniel Cromb
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Robert Wright
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Kathleen Colford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Maria Deprez
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Jana Hutter
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
| | - Jonathan O’Muircheartaigh
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Christina Malamateniou
- Division of Midwifery and Radiography, City University of London, London, United Kingdom
| | - Reza Razavi
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Lisa Story
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Joseph V. Hajnal
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Mary A. Rutherford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
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Lee SE, Baxter LL, Duran MI, Morris SD, Mosley IA, Fuentes KA, Pennings JLA, Guedj F, Bianchi DW. Analysis of genotype effects and inter-individual variability in iPSC-derived trisomy 21 neural progenitor cells. Hum Mol Genet 2024:ddae160. [PMID: 39533854 DOI: 10.1093/hmg/ddae160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 10/09/2024] [Accepted: 11/01/2024] [Indexed: 11/16/2024] Open
Abstract
Trisomy of human chromosome 21 (T21) gives rise to Down syndrome (DS), the most frequent live-born autosomal aneuploidy. T21 triggers genome-wide transcriptomic alterations that result in multiple atypical phenotypes with highly variable penetrance and expressivity in individuals with DS. Many of these phenotypes, including atypical neurodevelopment, emerge prenatally. To enable in vitro analyses of the cellular and molecular mechanisms leading to the neurological alterations associated with T21, we created and characterized a panel of genomically diverse T21 and euploid induced pluripotent stem cells (iPSCs). We subsequently differentiated these iPSCs to generate a panel of neural progenitor cells (NPCs). Alongside characterizing genotype effects from T21, we found that T21 NPCs showed inter-individual variability in growth rates, oxidative stress, senescence characteristics, and gene and protein expression. Pathway enrichment analyses of T21 NPCs identified vesicular transport, DNA repair, and cellular response to stress pathways. These results demonstrate T21-associated variability at the cellular level and suggest that cell lines from individuals with DS should not solely be analyzed as a homogenous population. Examining large cohorts of genetically diverse samples may more fully reveal the effects of aneuploidy on transcriptomic and phenotypic characteristics in T21 cell types. A panel of genomically diverse T21 and euploid induced pluripotent stem cells (iPSCs) were created and subsequently differentiated into neural progenitor cells (NPCs). T21 NPCs showed reduced growth, increased oxidative stress, and inter-individual variability in gene and protein expression. This inter-individual variability suggests that studies with large cohorts of genetically diverse T21 samples may more fully reveal the effects of aneuploidy.
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Affiliation(s)
- Sarah E Lee
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Laura L Baxter
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Monica I Duran
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Samuel D Morris
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Iman A Mosley
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Kevin A Fuentes
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Jeroen L A Pennings
- Center for Health Protection, National Institute for Public Health and the Environment, P.O. Box 1, Bilthoven, BA 3720, the Netherlands
| | - Faycal Guedj
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
| | - Diana W Bianchi
- Prenatal Genomics and Therapy Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, 35A Convent Drive Bethesda, MD 20892, United States
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, United States
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Russo ML, Sousa AMM, Bhattacharyya A. Consequences of trisomy 21 for brain development in Down syndrome. Nat Rev Neurosci 2024; 25:740-755. [PMID: 39379691 DOI: 10.1038/s41583-024-00866-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2024] [Indexed: 10/10/2024]
Abstract
The appearance of cognitive deficits and altered brain morphology in newborns with Down syndrome (DS) suggests that these features are driven by disruptions at the earliest stages of brain development. Despite its high prevalence and extensively characterized cognitive phenotypes, relatively little is known about the cellular and molecular mechanisms that drive the changes seen in DS. Recent technical advances, such as single-cell omics and the development of induced pluripotent stem cell (iPSC) models of DS, now enable in-depth analyses of the biochemical and molecular drivers of altered brain development in DS. Here, we review the current state of knowledge on brain development in DS, focusing primarily on data from human post-mortem brain tissue. We explore the biological mechanisms that have been proposed to lead to intellectual disability in DS, assess the extent to which data from studies using iPSC models supports these hypotheses, and identify current gaps in the field.
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Affiliation(s)
- Matthew L Russo
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - André M M Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Anita Bhattacharyya
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
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Lautarescu A, Bonthrone AF, Bos B, Barratt B, Counsell SJ. Advances in fetal and neonatal neuroimaging and everyday exposures. Pediatr Res 2024; 96:1404-1416. [PMID: 38877283 PMCID: PMC11624138 DOI: 10.1038/s41390-024-03294-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 06/16/2024]
Abstract
The complex, tightly regulated process of prenatal brain development may be adversely affected by "everyday exposures" such as stress and environmental pollutants. Researchers are only just beginning to understand the neural sequelae of such exposures, with advances in fetal and neonatal neuroimaging elucidating structural, microstructural, and functional correlates in the developing brain. This narrative review discusses the wide-ranging literature investigating the influence of parental stress on fetal and neonatal brain development as well as emerging literature assessing the impact of exposure to environmental toxicants such as lead and air pollution. These 'everyday exposures' can co-occur with other stressors such as social and financial deprivation, and therefore we include a brief discussion of neuroimaging studies assessing the effect of social disadvantage. Increased exposure to prenatal stressors is associated with alterations in the brain structure, microstructure and function, with some evidence these associations are moderated by factors such as infant sex. However, most studies examine only single exposures and the literature on the relationship between in utero exposure to pollutants and fetal or neonatal brain development is sparse. Large cohort studies are required that include evaluation of multiple co-occurring exposures in order to fully characterize their impact on early brain development. IMPACT: Increased prenatal exposure to parental stress and is associated with altered functional, macro and microstructural fetal and neonatal brain development. Exposure to air pollution and lead may also alter brain development in the fetal and neonatal period. Further research is needed to investigate the effect of multiple co-occurring exposures, including stress, environmental toxicants, and socioeconomic deprivation on early brain development.
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Affiliation(s)
- Alexandra Lautarescu
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alexandra F Bonthrone
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Brendan Bos
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Ben Barratt
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Serena J Counsell
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
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Emili M, Stagni F, Bonasoni MP, Guidi S, Bartesaghi R. Cellularity Defects Are Not Ubiquitous in the Brains of Fetuses With Down Syndrome. Dev Neurobiol 2024; 84:264-273. [PMID: 39344402 DOI: 10.1002/dneu.22953] [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: 07/09/2024] [Revised: 08/29/2024] [Accepted: 09/03/2024] [Indexed: 10/01/2024]
Abstract
Down syndrome (DS) is a genetic pathology characterized by various developmental defects. Unlike other clinical problems, intellectual disability is an invariant clinical trait of DS. Impairment of neurogenesis accompanied by brain hypotrophy is a typical neurodevelopmental phenotype of DS, suggesting that a reduction in the number of cells forming the brain may be a key determinant of intellectual disability. Previous evidence showed that fetuses with DS exhibit widespread hypocellularity in brain regions belonging to the temporal lobe memory systems, which may account for the typical explicit memory impairment that characterizes DS. In the current study, we have examined the basal ganglia, the insular cortex (INS), and the cingulate cortex (CCX) of fetuses with DS and age-matched controls (18-22 weeks of gestation), to establish whether cellularity defects involve regions that are not primarily involved in explicit memory. We found that fetuses with DS exhibit a notable hypocellularity in the putamen (-30%) and globus pallidus (-35%). In contrast, no cellularity differences were found in the INS and CCX, indicating that hypocellularity is not ubiquitous in the DS brain. The hypocellularity found in the basal ganglia, which are critically implicated in the control of movement, suggests that such alterations may contribute to the motor abnormalities of DS. The normal cytoarchitecture of the INS and CCX suggests that the alterations exhibited by people with DS in functions in which these regions are involved are not attributable to neuron paucity.
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Affiliation(s)
- Marco Emili
- Department for Life Quality Studies, University of Bologna, Rimini, Italy
| | - Fiorenza Stagni
- Department for Life Quality Studies, University of Bologna, Rimini, Italy
| | | | - Sandra Guidi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Renata Bartesaghi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
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6
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Matthew J, Uus A, Collado AE, Luis A, Arulkumaran S, Fukami-Gartner A, Kyriakopoulou V, Cromb D, Wright R, Colford K, Deprez M, Hutter J, O’Muircheartaigh J, Malamateniou C, Razavi R, Story L, Hajnal J, Rutherford MA. Automated Craniofacial Biometry with 3D T2w Fetal MRI. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.13.24311408. [PMID: 39185514 PMCID: PMC11343257 DOI: 10.1101/2024.08.13.24311408] [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
Objectives Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated landmark propagation pipeline using 3D motion-corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements. Methods A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers. Results Automated labels were produced for all 132 subjects with a 0.03% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research. Conclusion This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.
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Affiliation(s)
- Jacqueline Matthew
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Alena Uus
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Alexia Egloff Collado
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Aysha Luis
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Sophie Arulkumaran
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Abi Fukami-Gartner
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Vanessa Kyriakopoulou
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Daniel Cromb
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Robert Wright
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Kathleen Colford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Maria Deprez
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Jana Hutter
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
| | - Jonathan O’Muircheartaigh
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | | | - Reza Razavi
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Lisa Story
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Jo Hajnal
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Mary A. Rutherford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
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Canonica T, Kidd EJ, Gibbins D, Lana-Elola E, Fisher EMC, Tybulewicz VLJ, Good M. Dissecting the contribution of human chromosome 21 syntenic regions to recognition memory processes in adult and aged mouse models of Down syndrome. Front Behav Neurosci 2024; 18:1428146. [PMID: 39050700 PMCID: PMC11266108 DOI: 10.3389/fnbeh.2024.1428146] [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: 05/05/2024] [Accepted: 06/24/2024] [Indexed: 07/27/2024] Open
Abstract
Background Trisomy of human chromosome 21 (Hsa21) results in a constellation of features known as Down syndrome (DS), the most common genetic form of intellectual disability. Hsa21 is orthologous to three regions in the mouse genome on mouse chromosome 16 (Mmu16), Mmu17 and Mmu10. We investigated genotype-phenotype relationships by assessing the contribution of these three regions to memory function and age-dependent cognitive decline, using three mouse models of DS, Dp1Tyb, Dp(17)3Yey, Dp(10)2Yey, that carry an extra copy of the Hsa21-orthologues on Mmu16, Mmu17 and Mmu10, respectively. Hypothesis Prior research on cognitive function in DS mouse models has largely focused on models with an extra copy of the Mmu16 region and relatively little is known about the effects of increased copy number on Mmu17 and Mmu10 on cognition and how this interacts with the effects of aging. As aging is is a critical contributor to cognitive and psychiatric changes in DS, we hypothesised that ageing would differentially impact memory function in Dp1Tyb, Dp(17)3Yey, and Dp(10)2Yey, models of DS. Methods Young (12-13 months and old (18-20 months mice Dp1Tyb, Dp(17)3Yey and Dp(10)2Yey mice were tested on a battery of object recognition memory test that assessed object novelty detection, novel location detection and associative object-in place memory. Following behavioral testing, hippocampal and frontal cortical tissue was analysed for expression of glutamatergic receptor proteins using standard immunoblot techniques. Results Young (12-13 months and old (18-20 months mice Dp1Tyb, Dp(17)3Yey and Dp(10)2Yey mice were tested on a battery of object recognition memory test that assessed object novelty detection, novel location detection and associative object-in place memory. Following behavioral testing, hippocampal and frontal cortical tissue was analysed for expression of glutamatergic receptor proteins using standard immunoblot techniques. Conclusion Our results show that distinct Hsa21-orthologous regions contribute differentially to cognitive dysfunction in DS mouse models and that aging interacts with triplication of Hsa21-orthologous genes on Mmu10.
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Affiliation(s)
- Tara Canonica
- School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Emma J. Kidd
- School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, United Kingdom
| | | | | | - Elizabeth M. C. Fisher
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | | | - Mark Good
- School of Psychology, Cardiff University, Cardiff, United Kingdom
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Serrano ME, Kim E, Siow B, Ma D, Rojo L, Simmons C, Hayward D, Gibbins D, Singh N, Strydom A, Fisher EM, Tybulewicz VL, Cash D. Investigating brain alterations in the Dp1Tyb mouse model of Down syndrome. Neurobiol Dis 2023; 188:106336. [PMID: 38317803 PMCID: PMC7615598 DOI: 10.1016/j.nbd.2023.106336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024] Open
Abstract
Down syndrome (DS) is one of the most common birth defects and the most prevalent genetic form of intellectual disability. DS arises from trisomy of chromosome 21, but its molecular and pathological consequences are not fully understood. In this study, we compared Dp1Tyb mice, a DS model, against their wild-type (WT) littermates of both sexes to investigate the impact of DS-related genetic abnormalities on the brain phenotype. We performed in vivo whole brain magnetic resonance imaging (MRI) and hippocampal 1H magnetic resonance spectroscopy (MRS) on the animals at 3 months of age. Subsequently, ex vivo MRI scans and histological analyses were conducted post-mortem. Our findings unveiled the following neuroanatomical and biochemical alterations in the Dp1Tyb brains: a smaller surface area and a rounder shape compared to WT brains, with DS males also presenting smaller global brain volume compared with the counterpart WT. Regional volumetric analysis revealed significant changes in 26 out of 72 examined brain regions, including the medial prefrontal cortex and dorsal hippocampus. These alterations were consistently observed in both in vivo and ex vivo imaging data. Additionally, high-resolution ex vivo imaging enabled us to investigate cerebellar layers and hippocampal sub-regions, revealing selective areas of decrease and remodelling in these structures. An analysis of hippocampal metabolites revealed an elevation in glutamine and the glutamine/glutamate ratio in the Dp1Tyb mice compared to controls, suggesting a possible imbalance in the excitation/inhibition ratio. This was accompanied by the decreased levels of taurine. Histological analysis revealed fewer neurons in the hippocampal CA3 and DG layers, along with an increase in astrocytes and microglia. These findings recapitulate multiple neuroanatomical and biochemical features associated with DS, enriching our understanding of the potential connection between chromosome 21 trisomy and the resultant phenotype.
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Affiliation(s)
- Maria Elisa Serrano
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Eugene Kim
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Bernard Siow
- The Francis Crick Institute, London, United Kingdom
| | - Da Ma
- Department of Internal Medicine Section of Gerontology and Geriatric Science, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Loreto Rojo
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Camilla Simmons
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | | | | | - Nisha Singh
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Andre Strydom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Elizabeth M.C. Fisher
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | | | - Diana Cash
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
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