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
(A) This spatial covariance pattern was characterized by areas of declining (blue) and increasing (red) metabolic activity over time. The pattern is displayed as a reliability map of voxel weights thresholded at z = 2.33, P < 0.01 (1-tailed), using a bootstrap resampling procedure (ICV range = –6.02, 5.63, P < 0.0001; 1,000 iterations). (B) All premanifest HD1 subjects exhibited a monotonic increase in pattern expression (P < 0.001; permutation test) across the first 3 time points. (C) In the HD1 longitudinal cohort, pattern expression increased linearly with disease progression (P < 0.0001; IGM) at an estimated progression rate of 0.21/year (95% CI = 0.15, 0.27). Values from the 5 early symptomatic members of the HD2 testing cohort (yellow triangles) are provided for reference. (D) In the HD3 longitudinal testing cohort, pattern expression exhibited a similar linear increase with advancing disease (P < 0.0001; IGM) at a nearly identical rate of 0.19/year (95% CI = 0.11, 0.26). The longitudinal data from each subject are connected by lines. Red lines denote the initially premanifest HD1 subjects who subsequently phenoconverted (i.e., were clinically diagnosed as HD); blue lines denote their counterparts who did not phenoconvert during the study. Values before and after phenoconversion are represented by open and filled symbols. The horizontal broken line represents the mean (equal to 0) of the HC1 healthy control group; the dotted lines represent 2 SD above and below the normal mean. In C and D, the solid lines represent the best model-fitted lines with a 95% CI (broken curves).