The progressive supranuclear palsy (PSP) syndrome encompasses different entities. PSP disease of sporadic origin is the most frequent presentation, but different genetic mutations can lead either to monogenic variants of PSP disease, or to other conditions with a different pathophysiology that eventually may result in PSP phenotype. PSP syndrome of monogenic origin is poorly understood due to the low prevalence and variable expressivity of some mutations. Through this review, we describe how early age of onset, family history of early dementia, parkinsonism, dystonia, or motor neuron disease among other clinical features, as well as some neuroimaging signatures, may be the important clues to suspect PSP syndrome of monogenic origin. In addition, a diagnostic algorithm is proposed that may be useful to guide the genetic diagnosis once there is clinical suspicion of a monogenic PSP syndrome.
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http://dx.doi.org/10.3389/fneur.2022.861585 | DOI Listing |
Brain Sci
January 2025
Department of Neurology, NHO Higashinagoya National Hospital, Nagoya 465-8620, Japan.
: Progressive supranuclear palsy (PSP) is characterized by early postural instability and gait dysfunction, with frequent falls. Rehabilitation is an important therapeutic approach for motor dysfunction in patients with PSP. However, no conclusions have yet been drawn regarding the beneficial effects of rehabilitation in PSP, including the optimal duration of rehabilitation and differences in treatment effects among PSP subtypes.
View Article and Find Full Text PDFBMJ Neurol Open
January 2025
Department of Neurology, National Hospital Organization Higashinagoya National Hospital, Nagoya, Japan.
Background: Longitudinal studies investigating cognitive function changes in patients with progressive supranuclear palsy (PSP) are limited. The variability of cognitive impairment across clinical subtypes of PSP remains unclear.
Objective: This study aimed to compare the longitudinal changes in cognitive function between patients with PSP and Parkinson's disease (PD) and to assess differences in cognitive impairment among PSP subtypes.
Parkinsonism Relat Disord
January 2025
Department of Neurology, Gifu University Graduate School of Medicine, Gifu, Japan. Electronic address:
Serum anti-IgLON5 antibodies, which were tested in 223 patients meeting the diagnostic criteria for progressive supranuclear palsy/corticobasal syndrome (PSP/CBS), were negative in all patients. Our study suggests that the frequency of anti-IgLON5 disease is extremely rare in patients with typical presentation of PSP/CBS.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
January 2025
From the Department of Neurology, the First Hospital of Jilin University, Changchun, Jilin Province, China.
Background And Purpose: Differentiating Parkinson's Disease (PD) from Atypical Parkinsonism Syndrome (APS), including Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP), is challenging, and there is no gold standard. Integrating quantitative susceptibility mapping (QSM) and morphometry can help differentiate PD from APS and improve the internal diagnosis of APS.
Materials And Methods: In this retrospective study, we enrolled 55 patients with PD, 17 with MSA-parkinsonian type (MSA-P), 15 with MSA-cerebellar type (MSA-C), and 14 with PSP.
Brain Behav
January 2025
Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Background: While automated methods for differential diagnosis of parkinsonian syndromes based on MRI imaging have been introduced, their implementation in clinical practice still underlies considerable challenges.
Objective: To assess whether the performance of classifiers based on imaging derived biomarkers is improved with the addition of basic clinical information and to provide a practical solution to address the insecurity of classification results due to the uncertain clinical diagnosis they are based on.
Methods: Retro- and prospectively collected data from multimodal MRI and standardized clinical datasets of 229 patients with PD (n = 167), PSP (n = 44), or MSA (n = 18) underwent multinomial classification in a benchmark study comparing the performance of nine machine learning methods.
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