Resting-state connectivity stratifies premanifest Huntington’s disease by longitudinal cognitive decline rate

• Published in: Scientific reports Vol. 10; no. 1; p. 1252
• Main Authors: Polosecki, Pablo, Castro, Eduardo, Rish, Irina, Pustina, Dorian, Warner, John H., Wood, Andrew, Sampaio, Cristina, Cecchi, Guillermo A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.01.2020; Nature Publishing Group
• Subjects: 59/36; 631/114/1305; 631/378/1689/1558; Adult; Aging; Brain - pathology; Brain mapping; Brain Mapping - methods; Brain research; Case-Control Studies; Clinical trials; Cognition Disorders - physiopathology; Cognitive ability; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - physiopathology; Cohort Studies; Disease Progression; Early Diagnosis; Ethics; Female; Functional magnetic resonance imaging; Gene mapping; Genetic screening; Humanities and Social Sciences; Humans; Huntington Disease - classification; Huntington Disease - metabolism; Huntington Disease - physiopathology; Huntington's disease; Huntingtons disease; Image Processing, Computer-Assisted - methods; Machine Learning; Magnetic Resonance Imaging - methods; Male; Medical imaging; Middle Aged; multidisciplinary; Neural networks; Neurodegenerative diseases; Neuroimaging; Neurologic Examination - methods; Rest; Science; Science (multidisciplinary); Substantia alba
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-020-58074-8

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.