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Adamo M, Gayer M, Jacobs A, Raynaud Q, Sebbah R, di Domenicantonio G, Latypova A, Vionnet N, Kherif F, Lutti A, Pitteloud N, Draganski B. Enduring differential patterns of neuronal loss and myelination along 6-month pulsatile gonadotropin-releasing hormone therapy in individuals with Down syndrome. Brain Commun 2025; 7:fcaf117. [PMID: 40190351 PMCID: PMC11969670 DOI: 10.1093/braincomms/fcaf117] [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: 07/19/2024] [Revised: 01/08/2025] [Accepted: 03/21/2025] [Indexed: 04/09/2025] Open
Abstract
Despite major progress in understanding the impact of the triplicated chromosome 21 on the brain and behaviour in Down syndrome, our knowledge of the underlying neurobiology in humans is still limited. We sought to address some of the pertinent questions about the drivers of brain structure differences and their associations with cognitive function in Down syndrome. To this aim, in a pilot magnetic resonance imaging (MRI) study, we monitored brain anatomy in individuals with Down syndrome receiving pulsatile gonadotropin-releasing hormone (GnRH) therapy over 6 months in comparison with typically developed age- and sex-matched healthy controls. We analysed cross-sectional (Down syndrome/healthy controls n = 11/27; Down syndrome-2 females/9 males, age 26.7 ± 5.0 years old; healthy controls-8 females/19 males, age 24.1 ± 2.5 years old) and longitudinal (Down syndrome/healthy controls n = 8/13; Down syndrome-1 female/7 males, age 26.4 ± 5.3 years old; healthy controls-4 females/9 males, 24.7 ± 2.2 years old) relaxometry and diffusion-weighted MRI data alongside standard cognitive assessment. The statistical tests looked for cross-sectional baseline differences and for differential changes over time between Down syndrome and healthy controls. The post hoc analysis confined to the Down syndrome group, tested for potential time-dependent interactions between individuals' overall cognitive performance and associated brain anatomy changes. The brain MRI statistical analyses covered both grey and white matter regions across the whole brain allowing for investigation of regional volume, macromolecular/myelin and iron content, additionally to diffusion tensor and neurite orientation and dispersion density characterization across major white matter tracts. The cross-sectional analysis showed reduced frontal, temporal and cerebellar volumes in Down syndrome with only the cerebellar differences remaining significant after adjustment for the presence of microcephaly (P family-wise-corrected < 0.05). The volume reductions were paralleled by decreased cortical and subcortical macromolecular/myelin content confined to the cortical motor system, thalamus and basal ganglia (P family-wise-corrected < 0.05). All major white matter tracts showed a ubiquitous mean diffusivity and intracellular volume fraction reduction contrasted with no differences in magnetization transfer saturation metrics (P family-wise-corrected < 0.05). Compared with healthy controls over the same period, Down syndrome individuals under GnRH therapy showed cognitive improvement (Montreal Cognitive Assessment from 11.4 ± 5.5 to 15.1 ± 5.6; P < 0.01) on the background of stability of the observed differential neuroanatomical patterns. Despite the lack of adequate Down syndrome control group, we interpret the obtained cross-sectional and longitudinal findings in young adults as evidence for predominant neurodevelopmental neuronal loss due to dysfunctional neurogenesis without signs for short-term myelin loss.
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Affiliation(s)
- Michela Adamo
- Department of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Mihaly Gayer
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - An Jacobs
- Department of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Quentin Raynaud
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Raphael Sebbah
- Department of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Giulia di Domenicantonio
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Nathalie Vionnet
- Department of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Nelly Pitteloud
- Department of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, CH-1011 Lausanne, Switzerland
- Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
- Department of Neurology, Inselspital, University of Bern, CH-3010 Bern, Switzerland
- University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, CH-3010 Bern, Switzerland
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Sánchez‐Moreno B, Zhang L, Mateo G, Moldenhauer F, Brudfors M, Ashburner J, Nachev P, de Asúa DR, Strange BA. Voxel-based dysconnectomic brain morphometry with computed tomography in Down syndrome. Ann Clin Transl Neurol 2024; 11:143-155. [PMID: 38158639 PMCID: PMC10791030 DOI: 10.1002/acn3.51940] [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: 06/06/2023] [Revised: 09/23/2023] [Accepted: 10/20/2023] [Indexed: 01/03/2024] Open
Abstract
OBJECTIVE Alzheimer's disease (AD) is a major health concern for aging adults with Down syndrome (DS), but conventional diagnostic techniques are less reliable in those with severe baseline disability. Likewise, acquisition of magnetic resonance imaging to evaluate cerebral atrophy is not straightforward, as prolonged scanning times are less tolerated in this population. Computed tomography (CT) scans can be obtained faster, but poor contrast resolution limits its function for morphometric analysis. We implemented an automated analysis of CT scans to characterize differences across dementia stages in a cross-sectional study of an adult DS cohort. METHODS CT scans of 98 individuals were analyzed using an automatic algorithm. Voxel-based correlations with clinical dementia stages and AD plasma biomarkers (phosphorylated tau-181 and neurofilament light chain) were identified, and their dysconnectomic patterns delineated. RESULTS Dementia severity was negatively correlated with gray (GM) and white matter (WM) volumes in temporal lobe regions, including parahippocampal gyri. Dysconnectome analysis revealed an association between WM loss and temporal lobe GM volume reduction. AD biomarkers were negatively associated with GM volume in hippocampal and cingulate gyri. INTERPRETATION Our automated algorithm and novel dysconnectomic analysis of CT scans successfully described brain morphometric differences related to AD in adults with DS, providing a new avenue for neuroimaging analysis in populations for whom magnetic resonance imaging is difficult to obtain.
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Affiliation(s)
- Beatriz Sánchez‐Moreno
- Adult Down Syndrome Unit, Department of Internal MedicineHospital Universitario de La PrincesaMadridSpain
| | - Linda Zhang
- Alzheimer Disease Research UnitCIEN Foundation, Queen Sofia Foundation Alzheimer CentreMadridSpain
| | - Gloria Mateo
- Adult Down Syndrome Unit, Department of Internal MedicineHospital Universitario de La PrincesaMadridSpain
| | - Fernando Moldenhauer
- Adult Down Syndrome Unit, Department of Internal MedicineHospital Universitario de La PrincesaMadridSpain
| | - Mikael Brudfors
- Wellcome Centre for Human NeuroimagingUniversity College LondonLondonUK
| | - John Ashburner
- Wellcome Centre for Human NeuroimagingUniversity College LondonLondonUK
| | - Parashkev Nachev
- High‐Dimensional Neurology GroupUniversity College London Queen Square Institute of NeurologyLondonUK
| | - Diego Real de Asúa
- Adult Down Syndrome Unit, Department of Internal MedicineHospital Universitario de La PrincesaMadridSpain
| | - Bryan A. Strange
- Alzheimer Disease Research UnitCIEN Foundation, Queen Sofia Foundation Alzheimer CentreMadridSpain
- Laboratory for Clinical NeuroscienceCTB, Universidad Politécnica de MadridMadridSpain
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