8,026 research outputs found

    Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning

    Get PDF
    To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy-Richardson and variant progressive supranuclear palsy syndromes). Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy-Richardson, 52 with a progressive supranuclear palsy-cortical variant (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech/language, or progressive supranuclear palsy-corticobasal), and 17 with a progressive supranuclear palsy-subcortical variant (progressive supranuclear palsy-parkinsonism or progressive supranuclear palsy-progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation. The data supported two subtypes, each with a distinct progression of atrophy: a 'subcortical' subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a 'cortical' subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage Inference subtype with 82% of progressive supranuclear palsy-subcortical cases and 81% of progressive supranuclear palsy-Richardson cases assigned to the subcortical subtype and 82% of progressive supranuclear palsy-cortical cases assigned to the cortical subtype. The increasing stage was associated with worsening clinical scores, whilst the 'subcortical' subtype was associated with worse clinical severity scores compared to the 'cortical subtype' (progressive supranuclear palsy rating scale and Unified Parkinson's Disease Rating Scale). Validation experiments showed that subtype assignment was longitudinally stable (95% of scans were assigned to the same subtype at follow-up) and individual staging was longitudinally consistent with 90% remaining at the same stage or progressing to a later stage at follow-up. In summary, we applied Subtype and Stage Inference to structural MRI data and empirically identified two distinct subtypes of spatiotemporal atrophy in progressive supranuclear palsy. These image-based subtypes were differentially enriched for progressive supranuclear palsy clinical syndromes and showed different clinical characteristics. Being able to accurately subtype and stage progressive supranuclear palsy patients at baseline has important implications for screening patients on entry to clinical trials, as well as tracking disease progression

    Clinical Conditions “Suggestive of Progressive Supranuclear Palsy”—Diagnostic Performance

    Get PDF
    Background: The Movement Disorder Society diagnostic criteria for progressive supranuclear palsy introduced the diagnostic certainty level “suggestive of progressive supranuclear palsy” for clinical conditions with subtle signs, suggestive of the disease. This category aims at the early identification of patients, in whom the diagnosis may be confirmed as the disease evolves. Objective: To assess the diagnostic performance of the defined clinical conditions suggestive of progressive supranuclear palsy in an autopsy-confirmed cohort. Methods: Diagnostic performance of the criteria was analyzed based on retrospective clinical data of 204 autopsy-confirmed patients with progressive supranuclear palsy and 216 patients with other neurological diseases. Results: The conditions suggestive of progressive supranuclear palsy strongly increased the sensitivity compared to the National Institute of Neurological Disorders and Stroke and Society for Progressive Supranuclear Palsy criteria. Within the first year after symptom onset, 40% of patients with definite progressive supranuclear palsy fulfilled criteria for suggestive of progressive supranuclear palsy. Two-thirds of patients suggestive of progressive supranuclear palsy evolved into probable progressive supranuclear palsy after an average of 3.6 years. Application of the criteria for suggestive of progressive supranuclear palsy reduced the average time to diagnosis from 3.8 to 2.2 years. Conclusions: Clinical conditions suggestive of progressive supranuclear palsy allow earlier identification of patients likely to evolve into clinically possible or probable progressive supranuclear and to have underlying progressive supranuclear palsy pathology. Further work needs to establish the specificity and positive predictive value of this category in real-life clinical settings, and to develop specific biomarkers that enhance their diagnostic accuracy in early disease stages

    Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials

    Get PDF
    The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based endpoint selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy, corticobasal syndrome, multiple system atrophy and related disorders, to compare candidate clinical trial endpoints. In this multicentre United Kingdom study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and magnetic resonance imaging assessments at baseline, six and twelve-months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, progressive supranuclear palsy-subcortical (progressive supranuclear palsy-parkinsonism and progressive gait freezing subtypes), progressive supranuclear palsy-cortical (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech-and-language, and progressive supranuclear palsy-corticobasal syndrome subtypes), multiple system atrophy-parkinsonism, multiple system atrophy-cerebellar, corticobasal syndrome with and without evidence of Alzheimer’s disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling, and sample sizes for clinical trials of disease modifying agents, according to group and assessment type. Two hundred forty-three people were recruited (117 progressive supranuclear palsy, 68 corticobasal syndrome, 42 multiple system atrophy and 16 indeterminate; 138 [56.8%] male; age at recruitment 68.7 ± 8.61 years). One hundred fifty-nine completed six-month assessment (82 progressive supranuclear palsy, 27 corticobasal syndrome, 40 multiple system atrophy and 10 indeterminate) and 153 completed twelve-month assessment (80 progressive supranuclear palsy, 29 corticobasal syndrome, 35 multiple system atrophy and 9 indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N < 100 required for one-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease specific. In conclusion, phenotypic variance within progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial endpoints, from potential functional, cognitive, clinical or neuroimaging measures of disease progression

    Progressive supranuclear palsy

    Get PDF

    Progressive supranuclear palsy

    Get PDF

    Sleep abnormalities in progressive supranuclear palsy

    Full text link
    We studied sleep patterns for three nights in 10 subjects with moderate to severe progressive supranuclear palsy and correlated the findings with disease severity using quantitative measures of motor, cognitive, and eye movement impairment. All subjects had severe insomnia, spending 2 to 6 hours awake per night; the mean time awake per night for the group was more than 4 hours. Sleep latency became shorter and the number of awakenings increased with greater motor impairment, and total sleep time declined as dementia worsened. These findings indicate that in progressive supranuclear palsy insomnia is related to disease severity. Insomnia associated with progressive supranuclear palsy appears to be worse than the insomnia of Parkinson's disease or Alzheimer's disease and may be due to degenerative changes in brain structures responsible for sleep maintenance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50331/1/410250609_ftp.pd
    • …
    corecore