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. 2018 Apr 2;5(5):570-582.
doi: 10.1002/acn3.558. eCollection 2018 May.

An image-based model of brain volume biomarker changes in Huntington's disease

Peter A Wijeratne  1 , Alexandra L Young  1 , Neil P Oxtoby  1 , Razvan V Marinescu  1 , Nicholas C Firth  1 , Eileanoir B Johnson  2 , Amrita Mohan  3 , Cristina Sampaio  3 , Rachael I Scahill  2 , Sarah J Tabrizi  2 , Daniel C Alexander  1
Affiliations

An image-based model of brain volume biomarker changes in Huntington's disease

Peter A Wijeratne et al. Ann Clin Transl Neurol. .

Abstract

Objective: Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages.

Methods: We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides.

Results: The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers.

Interpretation: We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease.

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Figures

Figure 1
Figure 1
(A) Regional volume biomarker positional variance diagram. Dark diagonal components indicate strong event ordering, and lighter indicate possible event permutations with strength proportional to the off‐diagonal components. (B) Re‐estimation of the positional variance for 100 bootstrap samples of the data. (C) Graphic representation of the event sequence showing the corresponding subcortical regions transitioning from an initially healthy (grey) state to an unhealthy (red) state. To aid in visualization, the newly added region at each stage is colored in orange.
Figure 2
Figure 2
Distribution of subject stages: healthy controls (HC), premanifest A (pre‐HD A), premanifest B (pre‐HD B), and manifest (HD). The proportion is with respect to the total of each group: HC, pre‐HD A + pre‐HD B, and HD.
Figure 3
Figure 3
Predicted stage at baseline versus predicted stage at 1 year (A), 2 years (B), and 3 years (C) for the manifest cohort in TRACK‐HD. Predicted stages are shown as red circles (area scaled by the number of entries at each point). The uncertainty in the event ordering – equal to that of the bootstrapped EBM positional variance – is shown as a two‐dimensional heatmap.
Figure 4
Figure 4
(A) Total motor score (TMS) versus event‐based model (EBM) stage plus linear model fit to both pre‐HD and HD subjects; (B) Symbol Digit Modalities Test (SDMT) versus EBM stage plus linear model fit to both pre‐HD and HD subjects; (C) Stroop word reading test versus EBM stage plus linear model fit to both pre‐HD and HD subjects; (D) scaled CAP score versus EBM stage plus linear model fit to both pre‐HD and HD subjects; (E) TMS versus EBM stage brackets; (F) SDMT versus EBM stage brackets; (G) Stroop versus EBM stage brackets; (H) scaled CAP score versus EBM stage brackets. All plots show data from the premanifest (pre‐HD) and manifest (HD) groups. The mosaic plots (E–H) show the lower y‐axis bracket in solid color and the higher y‐axis bracket in thatch, and the number of subjects in each bracket is proportional to its area.
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