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Wang Y, Xiao Y, Xing Y, Yu M, Wang X, Ren J, Liu W, Zhong Y. Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures. CNS Neurosci Ther 2024; 30:e14680. [PMID: 38529533 DOI: 10.1111/cns.14680] [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: 10/30/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear. OBJECTIVE This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates. METHODS The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes. RESULTS Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development. CONCLUSIONS These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.
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Affiliation(s)
- Yajie Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Department of Neurology, The First People's Hospital of Yancheng, Yancheng, China
| | - Yiwen Xiao
- School of Psychology, Nanjing Normal University, Nanjing, China
| | - Yi Xing
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Wang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jingru Ren
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, China
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McColgan P, Gregory S, Zeun P, Zarkali A, Johnson EB, Parker C, Fayer K, Lowe J, Nair A, Estevez-Fraga C, Papoutsi M, Zhang H, Scahill RI, Tabrizi SJ, Rees G. Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes. Brain 2022; 145:3953-3967. [PMID: 35758263 PMCID: PMC9679168 DOI: 10.1093/brain/awac227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [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: 06/04/2021] [Revised: 05/27/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.
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Affiliation(s)
- Peter McColgan
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sarah Gregory
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Paul Zeun
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Angeliki Zarkali
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Eileanoir B Johnson
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Christopher Parker
- Department of Computer Science and Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Kate Fayer
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jessica Lowe
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Akshay Nair
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Carlos Estevez-Fraga
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Marina Papoutsi
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Hui Zhang
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Rachael I Scahill
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sarah J Tabrizi
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Geraint Rees
- University College London Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
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Abstract
PURPOSE OF REVIEW The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data. RECENT FINDINGS Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks. SUMMARY New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.
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Affiliation(s)
- Ibai Diez
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
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Zarkali A, Weil RS. Beyond dopamine: Further evidence of cholinergic dysfunction in Parkinson's disease (Commentary on Keo et al., 2021). Eur J Neurosci 2021; 53:3740-3742. [PMID: 33960522 DOI: 10.1111/ejn.15269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 04/13/2021] [Accepted: 04/29/2021] [Indexed: 11/30/2022]
Affiliation(s)
| | - Rimona S Weil
- Dementia Research Centre, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK.,Movement Disorders Consortium, National Hospital for Neurology and Neurosurgery, London, UK
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