Boyd C. P. Ghosh

Background Seed amplification assay (SAA) testing has been developed as a biomarker for the diagnosis of α-synuclein-related neurodegenerative disorders. Objective The objective of this study was to assess the rate of α-synuclein SAA positivity in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) and to analyze clinical and pathological features of SAA-positive and -negative cases. Methods A total of 96 cerebrospinal fluid samples from clinically diagnosed PSP (n = 59) and CBS (n = 37) cases were analyzed using α-synuclein SAA. Results Six of 59 (10.2%) PSP cases were α-synuclein SAA positive, including one case who was MSA-type positive. An exploratory analysis showed that PSP cases who were Parkinson's disease–type positive were older and had a shorter disease duration compared with SAA-negative cases. In contrast, 11 of 37 (29.7%) CBS cases were α-synuclein SAA positive, including two cases who were MSA-type positive. Conclusions Our results suggest that α-synuclein seeds can be detected in PSP and CBS using a cerebrospinal fluid α-synuclein SAA, and in PSP this may impact on clinical course. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Introduction Progressive supranuclear palsy (PSP) is a neurodegenerative disorder initially characterised by disturbances in gait, balance and posture, with death occurring after several years of progressive physical and cognitive decline. This, along with a low index of suspicion, a high degree of diagnostic uncertainty and no approved treatment options, greatly impacts the lives of patients and caregivers. This research was conducted to (i) gain insight into the clinical and emotional journey of patients with PSP, (ii) assess experiences and perspectives, (iii) understand disease impact and (iv) identify key challenges and unmet needs. Methods A literature search and qualitative interviews with six PSP experts were conducted to map the clinical pathway and identify breakpoints. The pathway was validated by key opinion leaders in seven countries. Qualitative research was conducted over 6 months in seven countries with PSP stakeholders (N = 112) to explore the emotional journey. The approach included self-ethnography, 60-min telephone interviews and the completion of 7-day smartphone diaries. Results The current PSP clinical journey can take many different pathways, with patients cycling through the healthcare system before a correct referral is made and a possible/probable diagnosis received. Breakpoints contribute to delays in accessing appropriate clinical care, a high degree of diagnostic divergence and suboptimal management of the disease. The emotional journey is dominated by negative feelings, although some moments of positivity were noted. The research highlighted a lack of disease understanding amongst all stakeholders and a lack of support for patients/caregivers. The authors make a number of recommendations for care improvements, including longer consultation times, closer collaboration among healthcare professionals and patient organisations, and more varied support and information for patients/caregivers. Conclusion This work represents a major collaborative effort to understand the lived experience of PSP. The research illustrates that a coordinated effort from all stakeholders is required to address ongoing needs and challenges within PSP.

The early and accurate differential diagnosis of parkinsonian disorders is still a significant challenge for clinicians. In recent years, a number of studies have used magnetic resonance imaging data combined with machine learning and statistical classifiers to successfully differentiate between different forms of Parkinsonism. However, several questions and methodological issues remain, to minimize bias and artefact-driven classification. In this study, we compared different approaches for feature selection, as well as different magnetic resonance imaging modalities, with well-matched patient groups and tightly controlling for data quality issues related to patient motion. Our sample was drawn from a cohort of 69 healthy controls, and patients with idiopathic Parkinson’s disease (n = 35), progressive supranuclear palsy Richardson’s syndrome (n = 52) and corticobasal syndrome (n = 36). Participants underwent standardized T1-weighted and diffusion-weighted magnetic resonance imaging. Strict data quality control and group matching reduced the control and patient numbers to 43, 32, 33 and 26, respectively. We compared two different methods for feature selection and dimensionality reduction: whole-brain principal components analysis, and an anatomical region-of-interest based approach. In both cases, support vector machines were used to construct a statistical model for pairwise classification of healthy controls and patients. The accuracy of each model was estimated using a leave-two-out cross-validation approach, as well as an independent validation using a different set of subjects. Our cross-validation results suggest that using principal components analysis for feature extraction provides higher classification accuracies when compared to a region-of-interest based approach. However, the differences between the two feature extraction methods were significantly reduced when an independent sample was used for validation, suggesting that the principal components analysis approach may be more vulnerable to overfitting with cross-validation. Both T1-weighted and diffusion magnetic resonance imaging data could be used to successfully differentiate between subject groups, with neither modality outperforming the other across all pairwise comparisons in the cross-validation analysis. However, features obtained from diffusion magnetic resonance imaging data resulted in significantly higher classification accuracies when an independent validation cohort was used. Overall, our results support the use of statistical classification approaches for differential diagnosis of parkinsonian disorders. However, classification accuracy can be affected by group size, age, sex and movement artefacts. With appropriate controls and out-of-sample cross validation, diagnostic biomarker evaluation including magnetic resonance imaging based classifiers may be an important adjunct to clinical evaluation.

Alien limb refers to movements that seem purposeful but are independent of patients’ reported intentions. Alien limb often co-occurs with apraxia in the corticobasal syndrome, and anatomical and phenomenological comparisons have led to the suggestion that alien limb and apraxia may be causally related as failures of goal-directed movements. Here, we characterised the nature of alien limb symptoms in patients with the corticobasal syndrome (n=30) and their relationship to limb apraxia. Twenty-five patients with progressive supranuclear palsy Richardson syndrome served as a disease-control group. Structured examinations of praxis, motor function, cognition and alien limb were undertaken in patients attending a regional specialist clinic. Twenty-eight patients with corticobasal syndrome (93%) demonstrated significant apraxia and this was often asymmetrical, with the left hand preferentially affected in 77% of patients. Moreover, 83% reported one or more symptoms consistent with alien limb. The range of these phenomena was broad, including changes in the sense of ownership and control as well as unwanted movements. Regression analyses showed no significant association between the severity of limb apraxia and both the occurrence of an alien limb and the number of alien limb phenomena reported. Bayesian estimation showed a low probability for a positive association between alien limb and apraxia, suggesting that alien limb phenomena are not likely to be related to severe apraxia. Our results shed light on the phenomenology of these disabling and as yet untreatable clinical features, with relevance to theoretical models of voluntary action.

The early and accurate differential diagnosis of parkinsonian disorders is still a significant challenge for clinicians. In recent years, a number of studies have used MRI data combined with machine learning and statistical classifiers to successfully differentiate between different forms of Parkinsonism. However, several questions and methodological issues remain, to minimise bias and artefact-driven classification. In this study we compared different approaches for feature selection, as well as different MRI modalities, with well matched patient groups and tightly controlling for data quality issues related to patient motion. Our sample was drawn from a cohort of 69 healthy controls, and patients with idiopathic Parkinson’s disease (n=35, PD), Progressive Supranuclear Palsy Richardson’s syndrome (n=52, PSP) and corticobasal syndrome (n=36, CBS). Participants underwent standardised T1-weighted MPRAGE and diffusion-weighted MRI. We compared two different methods for feature selection and dimensionality reduction: whole-brain principal components analysis, and an anatomical region-of-interest based approach. In both cases, support vector machines were used to construct a statistical model for pairwise classification of healthy controls and patients. The accuracy of each model was estimated using a leave-two-out cross-validation approach, as well as an independent validation using a different set of subjects. Our cross-validation results suggest that using principal components analysis (PCA) for feature extraction provides higher classification accuracies when compared to a region-of-interest based approach. However, the differences between the two feature extraction methods were significantly reduced when an independent sample was used for validation, suggesting that the principal components analysis approach may be more vulnerable to overfitting with cross-validation. Both T1-weighted and diffusion MRI data could be used to successfully differentiate between subject groups, with neither modality outperforming the other across all pairwise comparisons in the cross-validation analysis. However, features obtained from diffusion MRI data resulted in significantly higher classification accuracies when an independent validation cohort was used. Overall, our results support the use of statistical classification approaches for differential diagnosis of parkinsonian disorders. However, classification accuracy can be affected by group size, age, sex and movement artifacts. With appropriate controls and out-of-sample cross validation, diagnostic biomarker evaluation including MRI based classifiers can be an important adjunct to clinical evaluation.

Under binaural listening conditions, the detection of target signals within background masking noise is substantially improved when the interaural phase of the target differs from that of the masker. Neural correlates of this binaural masking level difference (BMLD) have been observed in the inferior colliculus and temporal cortex, but it is not known whether degeneration of the inferior colliculus would result in a reduction of the BMLD in humans. We used magnetoencephalography to examine the BMLD in 13 healthy adults and 13 patients with progressive supranuclear palsy (PSP). PSP is associated with severe atrophy of the upper brain stem, including the inferior colliculus, confirmed by voxel-based morphometry of structural MRI. Stimuli comprised in-phase sinusoidal tones presented to both ears at three levels (high, medium, and low) masked by in-phase noise, which rendered the low-level tone inaudible. Critically, the BMLD was measured using a low-level tone presented in opposite phase across ears, making it audible against the noise. The cortical waveforms from bilateral auditory sources revealed significantly larger N1m peaks for the out-of-phase low-level tone compared with the in-phase low-level tone, for both groups, indicating preservation of early cortical correlates of the BMLD in PSP. In PSP a significant delay was observed in the onset of the N1m deflection and the amplitude of the P2m was reduced, but these differences were not restricted to the BMLD condition. The results demonstrate that although PSP causes subtle auditory deficits, binaural processing can survive the presence of significant damage to the upper brain stem.

A 23-year-old woman with idiopathic intracranial hypertension (IIH) presented with a recurrence of headache and visual disturbance. She had presented with similar symptoms 5 years earlier, when the diagnosis of IIH had been made, after magnetic resonance venography (MRV) had excluded cerebral venous sinus thrombosis (VST) (figure 1A,B). She had been asymptomatic for 18 months and had stopped her acetazolamide 6 months earlier.