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Shammas MK, Nie Y, Gilsrud A, Huang X, Narendra DP, Chinnery PF. CHCHD10 mutations induce tissue-specific mitochondrial DNA deletions with a distinct signature. Hum Mol Genet 2023; 33:91-101. [PMID: 37815936 PMCID: PMC10729859 DOI: 10.1093/hmg/ddad161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 09/11/2023] [Accepted: 09/19/2023] [Indexed: 10/12/2023] Open
Abstract
Mutations affecting the mitochondrial intermembrane space protein CHCHD10 cause human disease, but it is not known why different amino acid substitutions cause markedly different clinical phenotypes, including amyotrophic lateral sclerosis-frontotemporal dementia, spinal muscular atrophy Jokela-type, isolated autosomal dominant mitochondrial myopathy and cardiomyopathy. CHCHD10 mutations have been associated with deletions of mitochondrial DNA (mtDNA deletions), raising the possibility that these explain the clinical variability. Here, we sequenced mtDNA obtained from hearts, skeletal muscle, livers and spinal cords of WT and Chchd10 G58R or S59L knockin mice to characterise the mtDNA deletion signatures of the two mutant lines. We found that the deletion levels were higher in G58R and S59L mice than in WT mice in some tissues depending on the Chchd10 genotype, and the deletion burden increased with age. Furthermore, we observed that the spinal cord was less prone to the development of mtDNA deletions than the other tissues examined. Finally, in addition to accelerating the rate of naturally occurring deletions, Chchd10 mutations also led to the accumulation of a novel set of deletions characterised by shorter direct repeats flanking the deletion breakpoints. Our results indicate that Chchd10 mutations in mice induce tissue-specific deletions which may also contribute to the clinical phenotype associated with these mutations in humans.
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Affiliation(s)
- Mario K Shammas
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, United Kingdom
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0XY, United Kingdom
- Inherited Movement Disorders Unit, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892, United States
| | - Yu Nie
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, United Kingdom
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Alexandra Gilsrud
- Inherited Movement Disorders Unit, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892, United States
| | - Xiaoping Huang
- Inherited Movement Disorders Unit, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892, United States
| | - Derek P Narendra
- Inherited Movement Disorders Unit, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892, United States
| | - Patrick F Chinnery
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, United Kingdom
- Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0XY, United Kingdom
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Evangelisti S, Boessenkool S, Pflanz CP, Basting R, Betts JF, Jenkinson M, Clare S, Muhammed K, LeHeron C, Armstrong R, Klein JC, Husain M, Nemeth AH, Hu MT, Douaud G. Subthalamic nucleus shows opposite functional connectivity pattern in Huntington's and Parkinson's disease. Brain Commun 2023; 5:fcad282. [PMID: 38075949 PMCID: PMC10699743 DOI: 10.1093/braincomms/fcad282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/26/2023] [Accepted: 11/06/2023] [Indexed: 02/12/2024] Open
Abstract
Huntington's and Parkinson's disease are two movement disorders representing mainly opposite states of the basal ganglia inhibitory function. Despite being an integral part of the cortico-subcortico-cortical circuitry, the subthalamic nucleus function has been studied at the level of detail required to isolate its signal only through invasive studies in Huntington's and Parkinson's disease. Here, we tested whether the subthalamic nucleus exhibited opposite functional signatures in early Huntington's and Parkinson's disease. We included both movement disorders in the same whole-brain imaging study, and leveraged ultra-high-field 7T MRI to achieve the very fine resolution needed to investigate the smallest of the basal ganglia nuclei. Eleven of the 12 Huntington's disease carriers were recruited at a premanifest stage, while 16 of the 18 Parkinson's disease patients only exhibited unilateral motor symptoms (15 were at Stage I of Hoehn and Yahr off medication). Our group comparison interaction analyses, including 24 healthy controls, revealed a differential effect of Huntington's and Parkinson's disease on the functional connectivity at rest of the subthalamic nucleus within the sensorimotor network, i.e. an opposite effect compared with their respective age-matched healthy control groups. This differential impact in the subthalamic nucleus included an area precisely corresponding to the deep brain stimulation 'sweet spot'-the area with maximum overall efficacy-in Parkinson's disease. Importantly, the severity of deviation away from controls' resting-state values in the subthalamic nucleus was associated with the severity of motor and cognitive symptoms in both diseases, despite functional connectivity going in opposite directions in each disorder. We also observed an altered, opposite impact of Huntington's and Parkinson's disease on functional connectivity within the sensorimotor cortex, once again with relevant associations with clinical symptoms. The high resolution offered by the 7T scanner has thus made it possible to explore the complex interplay between the disease effects and their contribution on the subthalamic nucleus, and sensorimotor cortex. Taken altogether, these findings reveal for the first time non-invasively in humans a differential, clinically meaningful impact of the pathophysiological process of these two movement disorders on the overall sensorimotor functional connection of the subthalamic nucleus and sensorimotor cortex.
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Affiliation(s)
- Stefania Evangelisti
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40127 Bologna, Italy
| | - Sirius Boessenkool
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Chris Patrick Pflanz
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, CB2 0QQ Cambridge, UK
| | - Romina Basting
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Jill F Betts
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Mark Jenkinson
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- School of Computer Science, Faculty of Engineering, University of Adelaide, 5005 Adelaide, Australia
| | - Stuart Clare
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Kinan Muhammed
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Campbell LeHeron
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- New Zealand Brain Research Institute, 8011 Christchurch, New Zealand
| | - Richard Armstrong
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Johannes C Klein
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Masud Husain
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Andrea H Nemeth
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Gwenaëlle Douaud
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
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Estevez-Fraga C, Altmann A, Parker CS, Scahill RI, Costa B, Chen Z, Manzoni C, Zarkali A, Durr A, Roos RAC, Landwehrmeyer B, Leavitt BR, Rees G, Tabrizi SJ, McColgan P. Genetic topography and cortical cell loss in Huntington's disease link development and neurodegeneration. Brain 2023; 146:4532-4546. [PMID: 37587097 PMCID: PMC10629790 DOI: 10.1093/brain/awad275] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 07/12/2023] [Accepted: 07/28/2023] [Indexed: 08/18/2023] Open
Abstract
Cortical cell loss is a core feature of Huntington's disease (HD), beginning many years before clinical motor diagnosis, during the premanifest stage. However, it is unclear how genetic topography relates to cortical cell loss. Here, we explore the biological processes and cell types underlying this relationship and validate these using cell-specific post-mortem data. Eighty premanifest participants on average 15 years from disease onset and 71 controls were included. Using volumetric and diffusion MRI we extracted HD-specific whole brain maps where lower grey matter volume and higher grey matter mean diffusivity, relative to controls, were used as proxies of cortical cell loss. These maps were combined with gene expression data from the Allen Human Brain Atlas (AHBA) to investigate the biological processes relating genetic topography and cortical cell loss. Cortical cell loss was positively correlated with the expression of developmental genes (i.e. higher expression correlated with greater atrophy and increased diffusivity) and negatively correlated with the expression of synaptic and metabolic genes that have been implicated in neurodegeneration. These findings were consistent for diffusion MRI and volumetric HD-specific brain maps. As wild-type huntingtin is known to play a role in neurodevelopment, we explored the association between wild-type huntingtin (HTT) expression and developmental gene expression across the AHBA. Co-expression network analyses in 134 human brains free of neurodegenerative disorders were also performed. HTT expression was correlated with the expression of genes involved in neurodevelopment while co-expression network analyses also revealed that HTT expression was associated with developmental biological processes. Expression weighted cell-type enrichment (EWCE) analyses were used to explore which specific cell types were associated with HD cortical cell loss and these associations were validated using cell specific single nucleus RNAseq (snRNAseq) data from post-mortem HD brains. The developmental transcriptomic profile of cortical cell loss in preHD was enriched in astrocytes and endothelial cells, while the neurodegenerative transcriptomic profile was enriched for neuronal and microglial cells. Astrocyte-specific genes differentially expressed in HD post-mortem brains relative to controls using snRNAseq were enriched in the developmental transcriptomic profile, while neuronal and microglial-specific genes were enriched in the neurodegenerative transcriptomic profile. Our findings suggest that cortical cell loss in preHD may arise from dual pathological processes, emerging as a consequence of neurodevelopmental changes, at the beginning of life, followed by neurodegeneration in adulthood, targeting areas with reduced expression of synaptic and metabolic genes. These events result in age-related cell death across multiple brain cell types.
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Affiliation(s)
- Carlos Estevez-Fraga
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Christopher S Parker
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Rachael I Scahill
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Beatrice Costa
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Zhongbo Chen
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Claudia Manzoni
- School of Pharmacy, University College London, London WC1N 1AX, UK
| | - Angeliki Zarkali
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute (ICM), AP-HP, Inserm, CNRS, Paris 75013, France
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden 2333, The Netherlands
| | | | - Blair R Leavitt
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver BC V5Z 4H4Canada
- Division of Neurology, Department of Medicine, University of British Columbia Hospital, Vancouver BC V6T 2B5, Canada
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Sarah J Tabrizi
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Peter McColgan
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
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