Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging
Over the past decade, substantial progress has been made in understanding the pathophysiology of dystonia. The number of identified genes has surged—exceeding 400 by 2024—with approximately 76.6% linked to neurodevelopmental disorders. Despite this, the genetic diagnostic yield remains modest (12–36...
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MDPI AG
2025-07-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/15/7/767 |
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| author | Jamir Pitton Rissardo Andrew McGarry Yiwen Shi Ana Leticia Fornari Caprara Ian M. Walker |
| author_facet | Jamir Pitton Rissardo Andrew McGarry Yiwen Shi Ana Leticia Fornari Caprara Ian M. Walker |
| author_sort | Jamir Pitton Rissardo |
| collection | DOAJ |
| description | Over the past decade, substantial progress has been made in understanding the pathophysiology of dystonia. The number of identified genes has surged—exceeding 400 by 2024—with approximately 76.6% linked to neurodevelopmental disorders. Despite this, the genetic diagnostic yield remains modest (12–36%), and many newly discovered genes have yet to reveal novel mechanistic insights. The limited number of studies exploring dystonia-related pathways in animal models restricts the generalizability of findings to human disease, raising concerns about their external validity. Developing experimental models remains a challenge, particularly given the importance of critical developmental windows—periods during central nervous system maturation when disruptions can have lasting effects. Some models also exhibit delayed symptom onset, prompting a shift toward faster-developing organisms such as Drosophila. There is a pressing need for standardized, scalable protocols that enable precise evaluation of specific neural tissues. Advances in neuroimaging have improved our understanding of dystonia-related brain networks at both regional and whole-brain levels. The emerging concept of “network kernels” has provided new perspectives on brain connectivity. However, future imaging studies should incorporate effective connectivity analyses to distinguish between hemodynamic and neuronal contributions and to clarify neurobiological pathways. This review synthesizes current knowledge from genetics, animal models, and neuroimaging to present an integrated view of dystonia’s neurobiological underpinnings. |
| format | Article |
| id | doaj-art-606fc275eed54958a21d59732dcd33ef |
| institution | DOAJ |
| issn | 2076-3425 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj-art-606fc275eed54958a21d59732dcd33ef2025-08-20T03:07:57ZengMDPI AGBrain Sciences2076-34252025-07-0115776710.3390/brainsci15070767Neurobiology of Dystonia: Review of Genetics, Animal Models, and NeuroimagingJamir Pitton Rissardo0Andrew McGarry1Yiwen Shi2Ana Leticia Fornari Caprara3Ian M. Walker4Neurology Department, Cooper University Hospital, Camden, NJ 08103, USANeurology Department, Cooper University Hospital, Camden, NJ 08103, USANeurology Department, Cooper University Hospital, Camden, NJ 08103, USANeurology Department, Cooper University Hospital, Camden, NJ 08103, USANeurology Department, Cooper University Hospital, Camden, NJ 08103, USAOver the past decade, substantial progress has been made in understanding the pathophysiology of dystonia. The number of identified genes has surged—exceeding 400 by 2024—with approximately 76.6% linked to neurodevelopmental disorders. Despite this, the genetic diagnostic yield remains modest (12–36%), and many newly discovered genes have yet to reveal novel mechanistic insights. The limited number of studies exploring dystonia-related pathways in animal models restricts the generalizability of findings to human disease, raising concerns about their external validity. Developing experimental models remains a challenge, particularly given the importance of critical developmental windows—periods during central nervous system maturation when disruptions can have lasting effects. Some models also exhibit delayed symptom onset, prompting a shift toward faster-developing organisms such as Drosophila. There is a pressing need for standardized, scalable protocols that enable precise evaluation of specific neural tissues. Advances in neuroimaging have improved our understanding of dystonia-related brain networks at both regional and whole-brain levels. The emerging concept of “network kernels” has provided new perspectives on brain connectivity. However, future imaging studies should incorporate effective connectivity analyses to distinguish between hemodynamic and neuronal contributions and to clarify neurobiological pathways. This review synthesizes current knowledge from genetics, animal models, and neuroimaging to present an integrated view of dystonia’s neurobiological underpinnings.https://www.mdpi.com/2076-3425/15/7/767pathophysiologyneurobiologymechanismtorsionmuscle contractiondystonia |
| spellingShingle | Jamir Pitton Rissardo Andrew McGarry Yiwen Shi Ana Leticia Fornari Caprara Ian M. Walker Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging Brain Sciences pathophysiology neurobiology mechanism torsion muscle contraction dystonia |
| title | Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging |
| title_full | Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging |
| title_fullStr | Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging |
| title_full_unstemmed | Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging |
| title_short | Neurobiology of Dystonia: Review of Genetics, Animal Models, and Neuroimaging |
| title_sort | neurobiology of dystonia review of genetics animal models and neuroimaging |
| topic | pathophysiology neurobiology mechanism torsion muscle contraction dystonia |
| url | https://www.mdpi.com/2076-3425/15/7/767 |
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