Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease.

Depression is common in premanifest Huntington's disease (preHD) and results in significant morbidity. We sought to examine how variations in structural and functional brain networks relate to depressive symptoms in premanifest HD and healthy controls. Brain networks were constructed using diffusion tractography (70 preHD and 81 controls) and resting state fMRI (92 preHD and 94 controls) data. A sub-network associated with depression was identified in a data-driven fashion and network-based statistics was used to investigate which specific connections correlated with depression scores. A replication analysis was then performed using data from a separate study. Correlations between depressive symptoms with increased functional connectivity and decreased structural connectivity were seen for connections in the default mode network (DMN) and basal ganglia in preHD. This study reveals specific connections in the DMN and basal ganglia that are associated with depressive symptoms in preHD. Hum Brain Mapp 38:2819-2829, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Medication Use in Early-HD Participants in Track-HD: an Investigation of its Effects on Clinical Performance.

 Insufficient evidence exists to guide the long-term pharmacological management of Huntington's disease (HD) although most current interventions rely on symptomatic management. The effect of many frontline treatments on potential endpoints for HD clinical trials remains unknown. Our objective was to investigate how therapies widely used to manage HD affect the symptom for which they are prescribed and other endpoints using data from TRACK-HD. We used longitudinal models to estimate effects of medication use on performance on tests of motor, cognitive and neuropsychiatric function using data from 123 TRACK-HD stage 1/2 participants across four study visits. Adjustment for confounding by prior medication use, prior clinical performance, concomitant use of other medications, and baseline variables (sex, disease group, age, CAG, study site, education) enabled a closer-to-causal interpretation of the associations. Adjusting for baseline variables only, medication use was typically associated with worse clinical performance, reflecting greater medication use in more advanced patients. After additional adjustment for longitudinal confounders such "inverse" associations were generally eliminated and in the expected directions: participants taking neuroleptics tended to have better motor performance, improved affect and poorer cognitive performance, and those taking SSRI/SNRIs had less apathy, less affect and better total behaviour scores. However, we uncovered few statistically significant associations. Limitations include sample size and unmeasured confounding. In conclusion, adjustment for confounding by prior measurements largely eliminated associations between medication use and poorer clinical performance from simple analyses. However, there was little convincing evidence of causal effects of medication on clinical performance and larger cohorts or trials are needed.

The potential of composite cognitive scores for tracking progression in Huntington's disease.

BACKGROUND: Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. OBJECTIVE: We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. METHODS: Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. RESULTS: In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. CONCLUSIONS: Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.

Evaluation of longitudinal 12 and 24 month cognitive outcomes in premanifest and early Huntington's disease.

BACKGROUND: Deterioration of cognitive functioning is a debilitating symptom in many neurodegenerative diseases, such as Huntington's disease (HD). To date, there are no effective treatments for the cognitive problems associated with HD. Cognitive assessment outcomes will have a central role in the efforts to develop treatments to delay onset or slow the progression of the disease. The TRACK-HD study was designed to build a rational basis for the selection of cognitive outcomes for HD clinical trials. METHODS: There were a total of 349 participants, including controls (n=116), premanifest HD (n=117) and early HD (n=116). A standardised cognitive assessment battery (including nine cognitive tests comprising 12 outcome measures) was administered at baseline, and at 12 and 24 months, and consisted of a combination of paper and pencil and computerised tasks selected to be sensitive to cortical-striatal damage or HD. Each cognitive outcome was analysed separately using a generalised least squares regression model. Results are expressed as effect sizes to permit comparisons between tasks. RESULTS: 10 of the 12 cognitive outcomes showed evidence of deterioration in the early HD group, relative to controls, over 24 months, with greatest sensitivity in Symbol Digit, Circle Tracing direct and indirect, and Stroop word reading. In contrast, there was very little evidence of deterioration in the premanifest HD group relative to controls. CONCLUSIONS: The findings describe tests that are sensitive to longitudinal cognitive change in HD and elucidate important considerations for selecting cognitive outcomes for clinical trials of compounds aimed at ameliorating cognitive decline in HD.

Diffusion Tensor Imaging in Preclinical Huntington's Disease.

Diffusion tensor imaging was used to study brain related changes in white matter that may be associated with Huntington's Disease progression. Thirty-one preclinical gene-mutation carriers were imaged cross-sectionally using diffusion tensor and anatomical brain imaging. Subjects were individuals who had a known gene mutation for HD but did not manifest motor diagnostic criteria for HD. Fractional anisotropy scalar maps showed a positive correlation with five year probability of diagnosis (based upon gene repeat length and current age) in the putamen and a negative correlation in the external capsule. This study shows that scalar maps generated from diffusion tensor imaging may be directly related to the earliest stages of disease progression within HD, even before a diagnosis is given. Findings suggest that DTI measures, therefore, may have the ability to act as a biomarker for disease progression in clinical trials of pre-manifest subjects.

Co-morbid health conditions at mid-life in the Iowa adoptees.

Adverse health effects due to alcohol and illicit drug abuse and dependence have been well documented. This study examines the effect of substance misuse on five major groups of health conditions using a sample of well characterized adoptees. The sample consisted of 742 adoptees interviewed in the last wave of the Iowa Adoption Studies. Death rate analyses included an additional 34 participants who had died prior to the last follow-up. Substance use patterns and medical history were assessed using the SSAGA-II (Bucholz, K. K., Cadoret, R. J., Cloninger, C. R., Dinwiddie, S. H., Hesselbrock, V. M., Nurnberger, J. L., Jr., et al. (1994). A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. Journal of Studies on Alcohol, 55 (2), 149-158). Subjects were divided into three groups according to DSM-IV diagnostic criteria, controls, alcohol abuse or dependence only (alcohol only), and the Alcohol-Drug group (abuse or dependence diagnosis on at least one illicit substance with or without alcohol diagnosis). Incidence rates of various diseases were measured using logistic regression. Survival analyses were used to examine whether substance abusers developed cardiovascular or metabolic disease at an earlier age than control subjects. Diagnostic grouping made no difference in the incidence rates or age of onset of health conditions. The amount of alcohol consumed by males significantly predicted higher number of overall health complaints as well as higher incidence rates of cardiovascular disease. The amount of illicit drug exposure did not predict an earlier age of diagnosis for cardiovascular or metabolic disease. Individuals in the Alcohol-Drug group had an increased incidence of deaths than either the alconly or the control groups.