Background. The evaluation of effective disease-modifying therapies for neurodegenerative disorders relies on objective and accurate measures of progression in at-risk individuals. Here we used a computational approach to identify a functional brain network associated with the progression of preclinical Huntington’s disease (HD).
Methods. Twelve premanifest HD mutation carriers were scanned with [18F]-fluorodeoxyglucose PET to measure cerebral metabolic activity at baseline and again at 1.5, 4, and 7 years. At each time point, the subjects were also scanned with [11C]-raclopride PET and structural MRI to measure concurrent declines in caudate/putamen D2 neuroreceptor binding and tissue volume. The rate of metabolic network progression in this cohort was compared with the corresponding estimate obtained in a separate group of 21 premanifest HD carriers who were scanned twice over a 2-year period.
Results. In the original premanifest cohort, network analysis disclosed a significant spatial covariance pattern characterized by progressive changes in striato-thalamic and cortical metabolic activity. In these subjects, network activity increased linearly over 7 years and was not influenced by intercurrent phenoconversion. The rate of network progression was nearly identical when measured in the validation sample. Network activity progressed at approximately twice the rate of single region measurements from the same subjects.
Conclusion. Metabolic network measurements provide a sensitive means of quantitatively evaluating disease progression in premanifest individuals. This approach may be incorporated into clinical trials to assess disease-modifying agents.
Trial registration. Registration is not required for observational studies.
Funding. NIH (National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering) and CHDI Foundation Inc.
Chris C. Tang, Andrew Feigin, Yilong Ma, Christian Habeck, Jane S. Paulsen, Klaus L. Leenders, Laura K. Teune, Joost C.H. van Oostrom, Mark Guttman, Vijay Dhawan, David Eidelberg
Linear trajectories (solid lines) of the network and regional imaging measures for the premanifest HD1 longitudinal cohort according to the best-fitting models. The rate of increase in the HD metabolic pattern expression (red) was greater than that for the volume-loss progression pattern (orange; P < 0.05, IGM) and the rates of decline measured for caudate D2 receptor binding (light blue; P < 0.0001) and tissue volume (dark blue; P < 0.0005) (Table 2). To allow for direct comparison of network progression (increasing time course) with corresponding changes in regional measures (decreasing time course), the values for caudate D2 receptor binding and tissue volume were flipped and analyzed as increasing mirror lines (dotted lines). The y axis represents the standard z scale. The horizontal dotted line represents the normal mean (equal to 0) for each parameter. The vertical dotted line represents the time of phenoconversion (i.e., YTO was zero). The estimated value for the metabolic progression pattern at phenoconversion (i.e., the y axis intercept) is signified by a red arrow. The estimated “start time” for the decline of caudate D2 receptor binding (i.e., the x axis intercept) is signified by a light blue arrow. Inset: Bubble plots depicting the estimated rates of disease progression and values at phenoconversion (see Methods) for the HD metabolic and volume-loss patterns (red and orange discs) and for caudate D2 receptor binding and tissue volume (light and blue discs).The diameter of each disc is proportional to the SE for each parameter estimate.