ArticleScientific reports2020
Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Machine learning and individual variability in electric field characteristics predict tDCS treatment response.Brain stimulationTrial
- Large scale functional and effective connectivity alterations cross the Huntington's disease integrated staging system.NeuroImage. Clinical · 2026Article
- Data analysis strategies for the Accelerating Medicines Partnership® Schizophrenia Program.Schizophrenia (Heidelberg, Germany) · 2025Article
- Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.Schizophrenia bulletin · 2024Article
- Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group.Journal of Huntington's disease · 2024Review
- Fusion of biomedical imaging studies for increased sample size and diversity: a case study of brain MRI.Frontiers in radiology · 2024Article
- Microglia and complement mediate early corticostriatal synapse loss and cognitive dysfunction in Huntington's disease.Nature medicine · 2023Article
- Neurophysiological hallmarks of Huntington's disease progression: an EEG and fMRI connectivity study.Frontiers in aging neuroscience · 2023Article
- Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes.Brain : a journal of neurology · 2022Article
- Forecasting individual progression trajectories in Huntington disease enables more powered clinical trials.Scientific reports · 2022Article
- Classification of Huntington's Disease Stage with Features Derived from Structural and Diffusion-Weighted Imaging.Journal of personalized medicine · 2022Article
- Cell therapy in Huntington's disease: Taking stock of past studies to move the field forward.Stem cells (Dayton, Ohio) · 2021Review
- Baseline Neuroimaging Predicts Decline to Dementia From Amnestic Mild Cognitive Impairment.Frontiers in aging neuroscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patient stratification is critical for the sensitivity of clinical trials at early stages of neurodegenerative disorders. In Huntington's disease (HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manifestation (pre-HD). We evaluated pre-HD stratification models based on single visit resting-state functional MRI (rs-fMRI) data that assess observed longitudinal motor and cognitive change rates from the multisite Track-On HD cohort (74 pre-HD, 79 control participants). We computed longitudinal performance change on 10 tasks (including visits from the preceding TRACK-HD study when available), as well as functional connectivity density (FCD) maps in single rs-fMRI visits, which showed high test-retest reliability. We assigned pre-HD subjects to subgroups of fast, intermediate, and slow change along single tasks or combinations of them, correcting for expectations based on aging; and trained FCD-based classifiers to distinguish fast- from slow-progressing individuals. For robustness, models were validated across imaging sites. Stratification models distinguished fast- from slow-changing participants and provided continuous assessments of decline applicable to the whole pre-HD population, relying on previously-neglected white matter functional signals. These results suggest novel correlates of early deterioration and a robust stratification strategy where a single MRI measurement provides an estimate of multiple ongoing longitudinal changes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.