Prediction of manifest Huntington's disease with clinical and imaging measures: a prospective observational study

Abstract

BACKGROUND Although correlation between cytosine-adenine-guanine (CAG) repeat length and age of Huntington disease (HD) onset is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counseling. We compared genetic, demographic, motor, cognitive, psychiatric, functional and imaging measures for tracking progression and predicting conversion to manifest HD. METHODS N=1078 research participants with the gene mutation for HD, but without a rating of 4 on the Diagnostic Confidence Level (DCL) following administration of the 15-item motor assessment of the Unified Huntington’s Disease Rating Scale. Participants were from 33 world wide sites and followed for up to 12 years (mean=5, SD=3·3) over the period 2001–2013. A subset of 225 participants prospectively converted to manifest HD according to the DCL (“meets the operational definition of the unequivocal presence of an otherwise unexplained extrapyramidal movement disorder in a subject at risk for HD” with ≥99% confidence). Joint modeling of longitudinal and survival data was used to examine the extent to which baseline and change of 40 variables analyzed separately was predictive of CAG-adjusted age at motor diagnosis. FINDINGS Cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors in the top three phenotypic domains were total motor score (motor), putamen volume (imaging), and Stroop word test (cognitive). A one standard deviation (SD) difference in total motor score increased the risk of a motor diagnosis by 3·1 times (95% CI=[2·3,4·2]), one SD loss in putamen volume increased risk by 3·3 times ([2·4,4·7]) and one SD cognitive decline increased risk by 2·3 ([1·9,2·9]). INTERPRETATION Prediction of HD diagnosis can be considerably improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest HD should inform discussions about revisions to guidelines for diagnosis, and prognosis, and counselling, and might be useful in guiding selection of participants and outcome measures for clinical trials. FUNDING National Institutes of Health, National Institute of Neurological Disorders and Stroke, and CHDI Foundation, Inc.

Allosteric activation of M 4 muscarinic receptors improve behavioral and physiological alterations in early symptomatic YAC128 mice

“…The risk of developing HD can be clearly determined via early genetic testing, and recent research is aimed at determining objective biomarkers to improve the diagnosis of HD (7,15,16,56,57). HD patients could represent an ideal target for a therapeutic strategy involving chronic exposure to M 4 PAMs beginning in the prodromal stages of the disease.…”

“…At later stages of disease progression, patients experience dystonia, rigidity, and bradykinesia, and ultimately death (3)(4)(5)(6)(7). The cortex and striatum are the most severely affected brain regions in HD and, interestingly, an increasing number of reports suggest that alterations in cortical and striatal physiology are present in prediagnostic individuals and in young HD mice (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16).…”

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

“…The expression of that biological trait could, however, influence the vulnerability to the effects of a mutated gene. TRACK‐HD and PREDICT‐HD, for example, reported changes in brain structure that were independent of HTT CAG repeat length and age (Paulsen et al, 2014; Tabrizi et al, 2013). The identification of biological traits could help reveal an interaction between the underlying biology and pathogenesis, or the timing of clinical manifestations of HD.…”

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

“…Researchers have postulated that neuroimaging markers of structural, functional, and connectivity changes in the premanifest brain have a more predictable relationship with the onset of clinically diagnosable HD 9, 10, 11. Over the past 5 years, the number of different imaging techniques has rapidly increased.…”