Objective: The identification of sensitive biomarkers is essential to validate therapeutics for Huntington disease (HD).
We directly compare structural imaging markers across the largest collective imaging HD dataset to identify a set of
imaging markers robust to multicenter variation and to derive upper estimates on sample sizes for clinical trials in HD.
Methods: We used 1 postprocessing pipeline to retrospectively analyze T1-weighted magnetic resonance imaging
(MRI) scans from 624 participants at 3 time points, from the PREDICT-HD, TRACK-HD, and IMAGE-HD studies. We
used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible
treatment effects in disease-affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers.
Results: We identified a set of common anatomical regions that have similarly large standardized effect sizes (>0.5)
between healthy control and premanifest HD (PreHD) groups. These included subcortical, white matter, and cortical
regions and nonventricular cerebrospinal fluid (CSF). We also observed a consistent spatial distribution of effect size by
region across the whole brain. We found that multicenter studies were necessary to capture treatment effect variance;
for a 20% treatment effect, power of >80% was achieved for the caudate (n = 661), pallidum (n = 687), and nonventricular CSF (n = 939), and, crucially, these imaging markers provided greater power than standard clinical markers.
Interpretation: Our findings provide the first cross-study validation of structural imaging markers in HD, supporting the
use of these measurements as endpoints for both observational studies and clinical trial
