Summary Background Huntington’s disease (HD) is an autosomal dominant, fully penetrant, neurodegenerative disease that most commonly affects adults in mid-life. Our aim was to identify sensitive and reliable biomarkers in premanifest carriers of mutated HTT and in individuals with early HD that could provide essential methodology for the assessment of therapeutic interventions. Methods This multicentre study uses an extensive battery of novel assessments, including multi-site 3T MRI, clinical, cognitive, quantitative motor, oculomotor, and neuropsychiatric measures. Blinded analyses were done on the baseline cross-sectional data from 366 individuals: 123 controls, 120 premanifest (pre-HD) individuals, and 123 patients with early HD. Findings The first participant was enrolled in January, 2008, and all assessments were completed by August, 2008. Cross-sectional analyses identified significant changes in whole-brain volume, regional grey and white matter differences, impairment in a range of voluntary neurophysiological motor, and oculomotor tasks, and cognitive and neuropsychiatric dysfunction in premanifest HD gene carriers with normal motor scores through to early clinical stage 2 disease. Interpretation We show the feasibility of rapid data acquisition and the use of multi-site 3T MRI and neurophysiological motor measures in a large multicentre study. Our results provide evidence for quantifiable biological and clinical alterations in HTT expansion carriers compared with age-matched controls. Many parameters differ from age-matched controls in a graded fashion and show changes of increasing magnitude across our cohort, who range from about 16 years from predicted disease diagnosis to early HD. These findings might help to define novel quantifiable endpoints and methods for rapid and reliable data acquisition, which could aid the design of therapeutic trials. Funding CHDI/High Q Foundation.

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Huntington disease (HD) can be seen as a model neurodegenerative disorder, in that it is caused by a single genetic mutation and is amenable to predictive genetic testing, with estimation of years to predicted onset, enabling the entire range of disease natural history to be studied. Structural neuroimaging biomarkers show that progressive regional brain atrophy begins many years before the emergence of diagnosable signs and symptoms of HD, and continues steadily during the symptomatic or 'manifest' period. The continued development of functional, neurochemical and other biomarkers raises hopes that these biomarkers might be useful for future trials of disease-modifying therapeutics to delay the onset and slow the progression of HD. Such advances could herald a new era of personalized preventive therapeutics. We describe the natural history of HD, including the timing of emergence of motor, cognitive and emotional impairments, and the techniques that are used to assess these features. Building on this information, we review recent progress in the development of biomarkers for HD, and potential future roles of these biomarkers in clinical trials.

Objective:The objective of the Predict-HD study is to use genetic, neurobiological and refined clinical markers to understand the early progression of Huntington’s disease (HD), prior to the point of traditional diagnosis, in persons with a known gene mutation. Here we estimate the approximate onset and initial course of various measurable aspects of HD relative to the time of eventual diagnosis.Methods:We studied 438 participants who were positive for the HD gene mutation, but did not yet meet the diagnostic criteria for HD and had no functional decline. Predictability of baseline cognitive, motor, psychiatric and imaging measures was modelled non-linearly using estimated time until diagnosis (based on CAG repeat length and current age) as the predictor.Results:Estimated time to diagnosis was related to most clinical and neuroimaging markers. The patterns of association suggested the commencement of detectable changes one to two decades prior to the predicted time of clinical diagnosis. The patterns were highly robust and consistent, despite the varied types of markers and diverse measurement methodologies.Conclusions:These findings from the Predict-HD study suggest the approximate time scale of measurable disease development, and suggest candidate disease markers for use in preventive HD trials.

Normal volunteers, aged 30 to 99 years, were studied with MRI. Age was related to estimated volumes of: gray matter, white matter, and CSF of the cerebrum and cerebellum; gray matter, white matter, white matter abnormality, and CSF within each cerebral lobe; and gray matter of eight subcortical structures. The results were: 1) Age-related losses in the hippocampus were significantly accelerated relative to gray matter losses elsewhere in the brain. 2) Among the cerebral lobes, the frontal lobes were disproportionately affected by cortical volume loss and increased white matter abnormality. 3) Loss of cerebral and cerebellar white matter occurred later than, but was ultimately greater than, loss of gray matter. It is estimated that between the ages of 30 and 90 volume loss averages 14% in the cerebral cortex, 35% in the hippocampus, and 26% in the cerebral white matter. Separate analyses were conducted in which genetic risk associated with the Apolipoprotein E ⑀4 allele was either overrepresented or underrepresented among elderly participants. Accelerated loss of hippocampal volume was observed with both analyses and thus does not appear to be due to the presence of at-risk subjects. MR signal alterations in the tissues of older individuals pose challenges to the validity of current methods of tissue segmentation, and should be considered in the interpretation of the results.

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The Bechara simulated gambling task is a popular method of examining decision-making deficits exhibited by people with brain damage, psychopathology, antisocial personality, or drug abuse problems. However, performance on this task is confounded by complex interdependencies between cognitive, motivational, and response processes, making it difficult to sort out and identify the specific processes responsible for the observed behavioral deficits. The authors compare 3 competing cognitive decision models of the Bechara task in terms of their ability to explain the performance deficits observed in Huntington's disease patients as compared with healthy populations and people with Parkinson's disease. The parameters of the best fitting model are used to decompose the observed performance deficit of the Huntington patients into cognitive, motivational, and response sources.The clinical neuroscience, psychopathology, and drug abuse literatures have experienced a surge of interest in the use of a laboratory-based simulated gambling paradigm developed by Bechara, Damasio, Tranel, and Anderson (1994). These tasks have been used to experimentally study the neuropsychological basis of deficits in decision making exhibited by populations with brain damage, psychopathology, antisocial personality, or drug abuse problems (Bartzokis et al.

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