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Biomarker development for Huntington's disease
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Biomarker development for Huntington’s disease Ralph Andre, Rachael I. Scahill, Salman Haider and Sarah J. Tabrizi UCL Institute of Neurology, Department of Neurodegenerative Disease, Queen Square, London WC1N 3BG, UK
Huntington’s disease (HD) is a fatal inherited neurodegenerative disorder, treatment to slow the progression of which has not yet been found. Human clinical trials to test a number of therapeutic strategies are underway or imminent, facilitated in part by the recent development of biomarkers that might be used as surrogate endpoints in such trials. However, although much progress in developing HD biomarkers has been made, ongoing work seeks to improve the sensitivity and reliability of current measures, and to demonstrate that they correspond to clear meaningful benefit to patients. Of particular importance is the identification of state biomarkers that can be used in pre-manifest HD gene carriers to test therapies hoped to delay symptom onset in these individuals. Functional, neuroimaging and biochemical biomarkers continue to be investigated for use in the development of disease-modifying treatments of HD.
Introduction
Biomarkers and HD
Huntington’s disease (HD) is a fatal autosomal-dominant neurodegenerative disorder caused by an expanded trinucleotide CAG tract in the gene encoding the huntingtin protein (HTT). There are currently no disease-modifying treatments for HD, but several new therapeutic strategies are showing promise, for which clinical trials are ongoing or imminent [1]. Findings from TRACK-HD and PREDICT-HD, longitudinal observational studies aimed at identifying early HD clinical biomarkers, have provided important insights into disease progression [2,3], and a battery of potential outcome measures that are realistic for future therapeutic trials involving HD patients in the early stages of manifest disease has been identified [4,5]. Research is now focused on the pre-manifest stages of HD (preHD), when therapeutic intervention might preserve neural function in individuals who have not yet developed overt signs or symptoms of disease. However, current outcome measures are relatively insensitive in preHD patients and there is a particular need for biomarkers in this cohort. Here we focus on the current state of biomarker development in HD and its implications for future clinical research.
Well-designed clinical trials are required to bring safe and effective treatments to patients. Such trials require the appropriate tools, including biomarkers that are reliable and objective. A biomarker is a measureable characteristic of a biological or pathogenic process. In the context of disease, a biomarker reflects the presence or severity of disease, or its response to treatment. There are three different areas where biomarkers could have an important role: trait, state and pharmacological. A marker of disease trait is a stable measure that predicts the likelihood of developing a disease; such markers are required for the selection of individuals for a clinical trial. In HD, predictive gene testing is the sole trait biomarker required to identify individuals who will develop the disease during their lifetime. Because it does so with absolute certainty, this allows the identification of HD gene carriers many years before symptom onset. A marker of disease state is one that determines the severity of disease and would be expected to change as the disease progresses or in response to treatment. Such biomarkers are important because they provide an early indication as to whether a potential therapeutic intervention is beneficial or not. If such a state biomarker predicts a clinically meaningful benefit it might be possible to use it as a surrogate endpoint in a clinical trial. This type of
Corresponding author: Tabrizi, S.J. ([email protected])
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biomarker has been the focus of considerable research in HD, but the development of state biomarkers that are sensitive to change in preHD patients remains an important challenge. A marker of pharmacological activity, or a pharmacodynamic marker, is important to confirm that the therapeutic agent is engaging its intended target to have a biological effect. This type of biomarker could be specific for a particular mechanism of action and different biomarkers might be required depending on the type of therapeutic intervention. For example, a particular challenge in the development of HTT-gene-lowering therapies is the search for markers of mutant (m)HTT-lowering in the brain. However, a pharmacodynamic biomarker is not always a reliable marker of
disease progression or an effective measure of therapeutic efficacy, and other biomarkers are often required. For every biomarker to be useful it needs to be readily quantifiable, robust and reproducible. If used as an outcome measure in a clinical trial, it should show a measureable clinically meaningful response to the intended intervention. The modality of a particular biomarker will be associated with specific methodological considerations and will determine the kind of information that it yields (Table 1). For example, clinical assessments are more likely to measure impairments in function that are relevant to the everyday living of the patient, whereas biochemical measures provide potentially important information about underlying
TABLE 1
Different biomarker modalities in HD: their advantages and disadvantages Assessment
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Disadvantages
Longitudinal change?a
UHDRS
Widely used and inexpensive Easy to administer Well standardised and robust Relatively rapid
Floor and ceiling effects Inter-rater variability Influenced by physiological factors Mostly insensitive in preHD
TFC shows decline in early HD over 12 months TMS shows decline in early HD and preHD over 12 months
Other clinical measures (including quantitative motor, cognitive and neuropsychiatric tests)
Measures that are important to the patient Widely available and inexpensive Easy to administer and standardise Relatively rapid Noninvasive
Mostly insensitive in preHD or longitudinal change over short periods of time, have not been fully established Inter-rater variability Potential for practice effects Some tests are susceptible to floor and ceiling effects Some tests are susceptible to day-today fluctuations or are influenced by physiological factors
Speeded tapping shows decline in early HD over 12 months and preHD over 36 months Tongue force variability shows decline in early HD over 12 months and preHD controls over 24 months Negative emotion recognition shows decline in early HD and close-to-onset preHD over 24 months Circle tracing shows decline in early HD and closeto-onset preHD over 12 months Symbol Digit Modality test shows decline in early HD over 12 months, conflicting evidence about period required to detect change in preHD PBA apathy measures show decline in early HD over 36 months Combined Stroop and set-shifting task with electrophysical measures has shown decline in preHD over 6 months
Neuroimaging measures (including structural MRI, diffusion MRI, PET and TMS)
Measures are proximal to underlying pathological processes Have shown longitudinal change over short periods of time and sensitivity in preHD, with large effect sizes Robust and reproducible Most methods are noninvasive Functional and metabolic measures can show reversal in response to intervention and/ or be sensitive to the very earliest change
Relatively expensive and timeconsuming Unsuitable for some subjects owing to, for example, chorea, claustrophobia or metal implants PET is invasive Some technologies are not widely available
Volumetric MRI measures of caudate atrophy in early HD and preHD over 12 months Volumetric MRI measures of whole-brain atrophy in early HD and close-to-onset preHD over 12 months Fractional anisotropy has had conflicting results regarding longitudinal sensitivity FDG-PET has shown increased thalamic metabolism in preHD over 18 months RAC-PET has shown increased loss of dopamine receptors in early HD over 29 months
Biochemical measures
Measures are proximal to underlying pathological processes Most biofluids are readily accessible and rapidly obtained High-throughput and relatively inexpensive Measures can show reversal in response to intervention
Sampling CSF is invasive Potential for variability between sites as a result of differences in sample handling, processing and storage Measures can be affected by physiological and environmental factors Not all measures are sufficiently robust
No validated measures of longitudinal change
Abbreviations: CSF, cerebrospinal fluid; FDG, fluorodeoxyglucose; HD, Huntington’s disease; MRI, magnetic resonance imaging; PBA, Problem Behaviours Assessment; PET, positron emission tomography; RAC, raclopride; TFC, total functional capacity; TMS, total motor score; UHDRS, Unified Huntington’s Disease Rating Scale. a Change relative to control subjects.
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Clinical biomarkers
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Measures of patient function have been used widely in HD clinical trials conducted to date and undoubtedly provide assessments that are most directly relevant to patients themselves. Current clinical rating scales such as the Unified Huntington’s Disease Rating Scale (UHDRS) are well-established and easy to administer. One of the most commonly used components of the UHDRS, the total functional capacity (TFC) scale, does show reasonably good effect sizes in measuring change in early-HD patients, but is insensitive in preHD individuals [4–6]. The UHDRS total motor score (TMS) is likewise sensitive in early HD, but there is some inconsistency in
Symbol digit modality test (number correct)
measures of change over time before symptom onset [6], possibly as a result of the high inter- and intra-rater variability associated with this scale [7]. The TRACK-HD and PREDICT-HD studies have aimed to develop more-objective markers of patient function using specific measures of motor performance, cognition and neuropsychiatric behaviour. Indeed, the quantitative motor battery employed in the TRACK-HD study has enabled rigorous standardisation of such measures across multiple sites. Measures such as speeded tapping and tongue force variability tests have proved sensitive to cross-sectional differences in those far from disease onset [3,8], and have shown good sensitivity to longitudinal change over 12 months in early-stage HD [4] (Fig. 1). However, these measures require much longer periods of time to show change in the pre-HD phase [4–6] and might be unfeasible as primary outcome measures in such a cohort. Subtle impairment of cognitive functions such as recognition of negative emotions and visuomotor integration [2,3,5,9,10], and altered neuropsychiatric characteristics such as apathy and irritability [3,11,12], are evident from the preHD stage onwards. The majority of cognitive measures show change over short periods of time in early-stage HD [4,5,13] but, despite evidence that cognitive
PBA apathy (sqrt of points on PBA scale)
pathogenic processes. In HD, various functional, neuroimaging and biochemical measures have been used to observe differences between HD and control subjects, and between mutation gene carriers at different stages of disease. Such cross-sectional studies could be considered a useful first step in identifying potential biomarkers, but longitudinal data are required to understand fully the kinetics of a candidate biomarker over time (Table 1). This type of data has been yielded by the TRACK-HD and PREDICT-HD studies, significantly furthering biomarker development in HD.
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FIGURE 1
Longitudinal changes in quantitative motor, cognitive and neuropsychiatric measures over 36 months. (a) Grip force variability, heavy, nondominant, (b) speeded tapping inter-tap interval, nondominant, (c) symbol digit modality test, (d) Stroop word reading, (e) indirect circle tracing, (f) Problem Behaviours Assessment (PBA) apathy, (g) PBA composite behaviour; and mean-adjusted values for (h) Unified Huntington’s Disease Rating Scale (UHDRS) total motor score (TMS) and (i) UHDRS total functional capacity (TFC). Significant differences compared with controls over 36 months are represented by *P < 0.05, **P < 0.01 and ***P < 0.001. Reproduced, with permission, from [6]. Abbreviations: HD, Huntington’s disease; sqrt, square root. www.drugdiscoverytoday.com Please cite this article in press as: R. Andre, et al., Biomarker development for Huntington’s disease, Drug Discov Today (2014), http://dx.doi.org/10.1016/j.drudis.2014.03.002
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assessment such as the symbol digit modality task shows sensitivity to change in pre-HD over 12 months [14], larger studies indicate that longer periods of observation are required to observe decline in this cohort [4–6]. Moreover, many cognitive tasks such as circle tracing suffer from practice effects [5], which need to be considered when recruiting subjects with differing levels of prior experience of a particular task. Neuropsychiatric measures are highly variable over time, limiting their utility as a primary outcome measure [4–6], but their relevance to assessing patient function clinically in terms of safe response to a treatment remains. An interesting new approach could be the coupling of cognitive and electrophysiological measures. Use of a joint Stroop test and set-shifting task paradigm with electrophysiological measurement of event-related potential (ERP) measurements has shown sensitivity in separating HD and control subjects and gene carriers at differing disease stages, and in detecting significant decline with a large effect size over 6 months [15]. This novel cognitive–neurophysiological biomarker shows promise as a biomarker in pre-HD, where 6-month interval change had not been shown previously. Demonstrating the reproducibility of this single-centre study will be important in determining the utility of using these cognitive and electrophysiological measures together as an HD biomarker.
Neuroimaging biomarkers Neuroimaging has shown perhaps the most significant recent developments as a tool to detect disease-related change in HD. The most widely used modality in HD biomarker research has been structural magnetic resonance imaging (MRI). For example, crosssectional studies using volumetric MRI have shown disease-related atrophy of the striatum and white matter of HD gene carriers as compared with control subjects, including those who are several years away from expected symptom onset [2,3,16]. Analysis of the whole brain using automated techniques such as voxel-based morphometry and FreeSurfer measurements of cortical thickness have also shown reduced volumes in HD gene carriers before symptom onset [3]. More importantly, longitudinal studies that detect change in individuals over time have shown progressive loss in the striatum [4–6,17–20], other subcortical structures [18] and global measures of grey and white matter [4–6,17,18,21] in early and preHD cohorts (Fig. 2). Progressive cortical thinning has been demonstrated in early-HD [22], but as yet has not been shown in preHD patients. The effect sizes of some of these volumetric measures, such as caudate atrophy, range from 0.9 in far-fromonset preHD subjects to 2.2 in early-stage patients [5], suggesting sample sizes that are feasible for use in clinical trials. The robustness of these measures across multiple sites has also been established [2,3]. More recently, other imaging modalities have been proposed as potential biomarkers in HD and work is ongoing to establish their validity. Diffusion MRI provides measures of microstructure, such as tissue integrity and myelination, which are indicative of underlying pathological processes that can precede macrostructural loss of tissue volume. Such measures have shown differences between HD and control subjects [23–25], but a direct comparison of diffusion and volume metrics has found that to date the former are less sensitive and more variable [26]. Moreover, diffusion MRI has shown conflicting evidence with regards to its utility to measure longitudinal change [27,28]. This reduced sensitivity 4
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might be caused by current technical limitations such as lower spatial resolution and increased scan dropout, and further refinement of the acquisition and analysis techniques might increase its utility in the future. Functional (f)MRI, which measures blood oxygen consumption as a proxy for metabolic activity, can be used to determine alterations in neuronal network structure that likewise might be expected to precede macrostructural tissue loss. Task-based measurements have highlighted differences in neuronal networks in preHD, even when these subjects have similar functional performance to healthy controls [29,30]. However, task-based fMRI has limited utility in the manifest stages of HD when functional impairment confounds the signal and atrophy is increasingly widespread. Resting-state fMRI avoids the problem of functional impairment and has demonstrated differences between gene carriers and controls [31,32]. Longitudinal change using fMRI has not been shown to date [33] and standardisation of these measures between individuals has proven problematic, but work to validate task-based and resting-state longitudinal fMRI across multiple sites is ongoing. Fluorodeoxyglucose positron emission tomography (FDG-PET) can be used to measure metabolic activity within the brain and has identified brain hypometabolism prior to disease onset [34–36]. Disease-related reductions in glucose metabolism over time have also been demonstrated [37]. The development of a range of ligands for specific receptors in the brain has allowed assessment of disease-related depletion of, for example, dopamine receptors using raclopride (RAC)-PET [38,39]; this loss of dopamine receptors appears to be progressive over time [37,38]. 11C-(R)-PK11195PET has also highlighted elevated microglial activation [40,41]. PET is used extensively as a research tool but is invasive, expensive and currently less widely available than MRI. Nevertheless, it is likely that PET will show a more rapid response to therapeutic intervention than volumetric MRI measures and could have particular utility in proof-of-concept trials where only small sample numbers are required. Magnetic resonance spectroscopy (MRS) provides measures of metabolites that are indicative of tissue health in either the brain or muscle, and disease-associated reductions in neuronal health have been detected using MRS in early-stage and preHD [42,43]. Such measures have potential utility in a clinical trial where, for example, a therapeutic intervention might be expected to restore neuronal health. Increasingly, imaging modalities are being used to measure different aspects of the disease process. For example, MRI has been used to identify elevated iron concentrations in the striatum and the cortex [44–46], with associated reductions in white matter [46]. Magnetisation transfer ratio imaging appears sensitive to microstructural grey and white matter disruption, but only once symptoms are manifest [47], and this technique is insensitive to longitudinal change over two years [48]. Novel techniques such as these will undoubtedly show further promise, but demonstrations of longitudinal sensitivity and robustness across different sites and between different scanner types will be required.
Biochemical biomarkers Biochemical analysis of biofluids has the potential to be rapid, high-throughput and inexpensive compared with the technical
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FIGURE 2
Longitudinal volumetric magnetic resonance imaging (MRI) changes over 36 months. Parametric maps showing regions with statistically significant atrophy in (a) white matter and (b) grey matter over 36 months, relative to controls. Mean-adjusted values for (c) whole-brain volume, (d) caudate volume, (e) putamen volume, (f) grey-matter volume and (g) white-matter volume. Significant differences compared with controls over 36 months are represented by *P < 0.05, **P < 0.01 and ***P < 0.001. Panels c–g are reproduced, with permission, from [6]. Abbreviation: HD, Huntington’s disease.
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demonstrated no significant longitudinal changes in 8OHdG levels at any disease stage [52]. Accurate measurement in biosamples of levels of mutant and wild-type HTT offers a new avenue for biomarker development in HD, and is a prerequisite for mHTT-lowering therapies that are expected to enter clinical trials in the near future. A novel time¨ rster resonance energy transfer assay that utilises fluorresolved Fo escently labelled anti-HTT antibodies has been used to measure soluble HTT levels in circulating immune cells, showing that mean mHTT levels in monocytes, T cells and B cells differ significantly between HD gene carriers and controls, and between pre-HD subjects and those with clinical onset [53] (Fig. 3). These findings indicate that quantification of mHTT in peripheral immune cells holds promise as a noninvasive HD biomarker; whether measures of the disease-associated protein accurately reflect the changing the state of the disease remains unknown.
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FIGURE 3
Measures of huntingtin protein (HTT) levels in peripheral immune cells. Total and mutant (m)HTT protein levels were quantified by time-resolved fluorescence resonance energy transfer (TR-FRET) in monocytes. (a) Total HTT levels in monocytes showed no significant differences between Huntington’s disease (HD) patients and control subjects, or between HD gene carriers at different disease stages. (b) mHTT protein was detected in samples from HD patients and pre-manifest HD mutation carriers, as compared with controls. Differences in mean mHTT levels in monocytes were observed between pre-manifest and manifest HD patients (P < 0.01), and between premanifest and early-stage HD subjects (P = 0.051). Coloured circles indicate multiple samples from a single subject. Reproduced, with permission, from [53].
complexities of neuroimaging, and such biomarkers are likely to evaluate changes that are proximal to the underlying pathology and perhaps have the greatest potential to show reversal in response to therapeutic intervention. Indeed, many biomarkers spanning a wide range of biological pathways have been identified in HD. These include molecules involved in endocrine function, metabolism, immune responses and oxidative stress, as well as antioxidants, neurotransmitters and other neurochemicals [49]. Most of these measures have been made in blood components such as serum, plasma and buffy coats; despite the ease with which urine and saliva can be obtained, limited results have been obtained from these materials. In comparison with functional and neuroimaging measures however, relatively few measures of biochemical biomarkers identified in cross-sectional studies have either been subject to or stood up to longitudinal analysis. For example, 8-hydroxy-2-deoxyguanisine (8OHdG), a major product of DNA oxidation, has been reported as being increased in blood samples of HD gene carriers [50,51], but subsequent work 6
Much recent progress has been made to identify HD biomarkers that show promise within the setting of a clinical trial. In particular, the identification by international, multisite studies such as TRACK-HD and PREDICT-HD of state biomarkers as potential outcome measures has been invaluable. These studies have validated the most robust and reproducible measures to date, yielding a battery comprising structural MRI, quantitative motor, cognitive and neuropsychiatric measures for use in clinical trials in earlystage HD [5]. However, these measures are insensitive to change in pre-HD over timescales realistic for clinical trials [6] and more sensitive measures are required to capture subtle changes that might be taking place before symptom onset. To that end, a new study, TrackOn-HD (http://hdresearch.ucl.ac.uk/currentstudies/trackon-hd/), aims to refine existing assessments further in pre-HD subjects, as well as investigating novel imaging modalities such as task and resting-state fMRI and transcranial magnetic stimulation that might be able to monitor compensatory mechanisms in the brains of this cohort. It is likely that existing state biomarkers will be superseded as current and novel methodologies are further developed, with technical advances resulting in enhanced sensitivity and reliability. For example, structural MRI has already benefitted from the increased tissue contrast provided by 3 Tesla (T) as compared with 1.5 T imaging and, although its use in a clinical setting is not yet widespread, research is now being undertaken using 7 T scanners. Similarly, although diffusion MRI has not yet shown the sensitivity of volumetric imaging despite its theoretical advantages, novel image analysis methods such as neurite orientation and dispersion diffusion imaging (NODDI) could allow much improved interrogation of the brain microstructure [54]. Furthermore, much work is ongoing to establish new PET ligands that can be used in HD to detect change in various aspects of the underlying disease processes. Such developments in neuroimaging-based measures clearly hold much promise, but existing studies have made clear the need for robust validation to demonstrate reproducibility between different test sites and scanner types. Particularly promising among current therapeutic strategies in HD is the reduction of mHTT levels in the brain by gene lowering. However, developments in this area are reliant on finding measures that accurately reflect mHTT levels in the brain. In the
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Finally, the selection of particular biomarkers in a clinical trial setting will depend upon the nature of the study cohort, as well as the proposed mechanism of action and probable timeframe of a given therapy. However, we are now in a position to embark on clinical trials of potentially disease-modifying compounds in HD with a number of validated state biomarkers, with the prospect of new measures arising for preHD cohorts in the near future.
Conflicts of interest The authors have no conflicts of interest to declare.
Acknowledgements We are grateful to Dr Edward Wild for review of the manuscript and to Ray Young for help with the graphics. S.J.T.’s work is funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n261358 (PADDINGTON), MRC, BBSRC, the CHDI Foundation, the UCL/ UCLH NIHR Biomedical Research Centre, the Huntington’s Disease Association, the European HD Network and the UK Dementia and Neurodegenerative Diseases Network.
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18 Majid, D.S. et al. (2011) Basal ganglia atrophy in prodromal Huntington’s disease is detectable over one year using automated segmentation. Mov. Disord. 26, 2544– 2551 19 Aylward, E.H. et al. (2004) Onset and rate of striatal atrophy in preclinical Huntington disease. Neurology 63, 66–72 20 Hobbs, N.Z. et al. (2009) Automated quantification of caudate atrophy by local registration of serial MRI: evaluation and application in Huntington’s disease. Neuroimage 47, 1659–1665 21 Squitieri, F. et al. (2009) Distinct brain volume changes correlating with clinical stage, disease progression rate, mutation size, and age at onset prediction as early biomarkers of brain atrophy in Huntington’s disease. CNS Neurosci. Ther. 15, 1–11 22 Rosas, H.D. et al. (2011) A tale of two factors: what determines the rate of progression in Huntington’s disease? A longitudinal MRI study. Mov. Disord. 26, 1691–1697 23 Rosas, H.D. et al. (2006) Diffusion tensor imaging in presymptomatic and early Huntington’s disease: selective white matter pathology and its relationship to clinical measures. Mov. Disord. 21, 1317–1325 24 Stoffers, D. et al. (2010) Contrasting gray and white matter changes in preclinical Huntington disease: an MRI study. Neurology 74, 1208–1216 25 Bohanna, I. et al. (2011) Diffusion tensor imaging in Huntington’s disease reveals distinct patterns of white matter degeneration associated with motor and cognitive deficits. Brain Imaging Behav. 5, 171–180 26 Hobbs, N.Z. et al. (2012) Evaluation of multi-modal, multi-site neuroimaging measures in Huntington’s disease: Baseline results from the PADDINGTON study. Neuroimage Clin. 2, 204–211 27 Weaver, K.E. et al. (2009) Longitudinal diffusion tensor imaging in Huntington’s disease. Exp. Neurol. 216, 525–529 28 Sritharan, A. et al. (2010) A longitudinal diffusion tensor imaging study in symptomatic Huntington’s disease. J. Neurol. Neurosurg. Psychiatry 81, 257–262 ¨ ppel, S. et al. (2009) Functional compensation of motor function in pre29 Klo symptomatic Huntington’s disease. Brain 132, 1624–1632 30 Novak, M.J. et al. (2012) Altered brain mechanisms of emotion processing in premanifest Huntington’s disease. Brain 135, 1165–1179 31 Wolf, R.C. et al. (2011) Magnetic resonance perfusion imaging of resting-state cerebral blood flow in preclinical Huntington’s disease. J. Cereb. Blood Flow Metab. 31, 1908–1918 32 Unschuld, P.G. et al. (2012) Impaired cortico-striatal functional connectivity in prodromal Huntington’s disease. Neurosci. Lett. 514, 204–209 33 Wolf, R.C. et al. (2011) Longitudinal functional magnetic resonance imaging of cognition in preclinical Huntington’s disease. Exp. Neurol. 231, 214–222 34 Ciarmiello, A. et al. (2006) Brain white-matter volume loss and glucose hypometabolism precede the clinical symptoms of Huntington’s disease. J. Nucl. Med. 47, 215–222
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absence of direct measures within the brain, improved assays sensitive enough to detect mHTT in easily accessible biofluids and optimised for high-throughput use are required. Measures of mHTT in this manner could be crucial in monitoring the pharmacological activity of gene-lowering interventions, but it remains to be determined whether their levels accurately reflect the underlying state of the disease such that they can also be used as an outcome measure. For this and other candidate biomarkers in biofluids, longitudinal analyses of large numbers samples are required, for which the blood sample collections such as those from TRACK-HD will be invaluable. Despite the invasiveness of the procedure, cerebrospinal fluid (CSF) collection is well-tolerated and routinely undertaken in other neurodegenerative diseases, and could reasonably be considered the optimal biofluid in which to identify biomarkers. However, highly sensitive assays and standardised longitudinal studies are needed to identify CSF biomarkers in HD. More generally, where peripheral measures are made, an understanding of how they relate to HD pathogenesis is required to interpret their measurement best in the context of a clinical trial.
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35 Feigin, A. et al. (2001) Metabolic network abnormalities in early Huntington’s disease: an [(18)F]FDG PET study. J. Nucl. Med. 42, 1591–1595 36 Kuhl, D.E. et al. (1982) Cerebral metabolism and atrophy in Huntington’s disease determined by 18FDG and computed tomographic scan. Ann. Neurol. 12, 425–434 37 Feigin, A. et al. (2007) Thalamic metabolism and symptom onset in preclinical Huntington’s disease. Brain 130, 2858–2867 38 Pavese, N. et al. (2003) Progressive striatal and cortical dopamine receptor dysfunction in Huntington’s disease: a PET study. Brain 126, 1127–1135 39 Pavese, N. et al. (2010) Cortical dopamine dysfunction in symptomatic and premanifest Huntington’s disease gene carriers. Neurobiol. Dis. 37, 356–361 40 Pavese, N. et al. (2006) Microglial activation correlates with severity in Huntington disease: a clinical and PET study. Neurology 66, 1638–1643 41 Politis, M. et al. (2011) Microglial activation in regions related to cognitive function predicts disease onset in Huntington’s disease: a multimodal imaging study. Hum. Brain Mapp. 32, 258–270 42 Sturrock, A. et al. (2010) Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease. Neurology 75, 1702–1710 43 van den Bogaard, S.J. et al. (2011) Exploratory 7-Tesla magnetic resonance spectroscopy in Huntington’s disease provides in vivo evidence for impaired energy metabolism. J. Neurol. 258, 2230–2239 44 Rosas, H.D. et al. (2012) Alterations in brain transition metals in Huntington disease: an evolving and intricate story. Arch. Neurol. 69, 887–893
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45 Dumas, E.M. et al. (2012) Elevated brain iron is independent from atrophy in Huntington’s disease. Neuroimage 61, 558–564 46 Bartzokis, G. et al. (2007) Myelin breakdown and iron changes in Huntington’s disease: pathogenesis and treatment implications. Neurochem. Res. 32, 1655–1664 47 van den Bogaard, S.J. et al. (2012) Magnetization transfer imaging in premanifest and manifest Huntington disease. Am. J. Neuroradiol. 33, 884–889 48 van den Bogaard, S.J. et al. (2013) Magnetization transfer imaging in premanifest and manifest Huntington disease: a 2-year follow-up. Am. J. Neuroradiol. 34, 317–322 49 Weir, D.W. et al. (2011) Development of biomarkers for Huntington’s disease. Lancet Neurol. 10, 573–590 50 Chen, C.M. et al. (2007) Increased oxidative damage and mitochondrial abnormalities in the peripheral blood of Huntington’s disease patients. Biochem. Biophys. Res. Commun. 359, 335–340 51 Hersch, S.M. et al. (2006) Creatine in Huntington disease is safe, tolerable, bioavailable in brain and reduces serum 8OH2’dG. Neurology 66, 250–252 52 Borowsky, B. et al. (2013) 8OHdG is not a biomarker for Huntington disease state or progression. Neurology 80, 1934–1941 53 Weiss, A. et al. (2012) Mutant huntingtin fragmentation in immune cells tracks Huntington’s disease progression. J. Clin. Invest. 122, 3731–3736 54 Zhang, H. et al. (2012) NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 61, 1000–1016
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Biomarker development for Huntington’s disease Ralph Andre, Rachael I. Scahill, Salman Haider and Sarah J. Tabrizi UCL Institute of Neurology, Department of Neurodegenerative Disease, Queen Square, London WC1N 3BG, UK
Huntington’s disease (HD) is a fatal inherited neurodegenerative disorder, treatment to slow the progression of which has not yet been found. Human clinical trials to test a number of therapeutic strategies are underway or imminent, facilitated in part by the recent development of biomarkers that might be used as surrogate endpoints in such trials. However, although much progress in developing HD biomarkers has been made, ongoing work seeks to improve the sensitivity and reliability of current measures, and to demonstrate that they correspond to clear meaningful benefit to patients. Of particular importance is the identification of state biomarkers that can be used in pre-manifest HD gene carriers to test therapies hoped to delay symptom onset in these individuals. Functional, neuroimaging and biochemical biomarkers continue to be investigated for use in the development of disease-modifying treatments of HD.
Introduction
Biomarkers and HD
Huntington’s disease (HD) is a fatal autosomal-dominant neurodegenerative disorder caused by an expanded trinucleotide CAG tract in the gene encoding the huntingtin protein (HTT). There are currently no disease-modifying treatments for HD, but several new therapeutic strategies are showing promise, for which clinical trials are ongoing or imminent [1]. Findings from TRACK-HD and PREDICT-HD, longitudinal observational studies aimed at identifying early HD clinical biomarkers, have provided important insights into disease progression [2,3], and a battery of potential outcome measures that are realistic for future therapeutic trials involving HD patients in the early stages of manifest disease has been identified [4,5]. Research is now focused on the pre-manifest stages of HD (preHD), when therapeutic intervention might preserve neural function in individuals who have not yet developed overt signs or symptoms of disease. However, current outcome measures are relatively insensitive in preHD patients and there is a particular need for biomarkers in this cohort. Here we focus on the current state of biomarker development in HD and its implications for future clinical research.
Well-designed clinical trials are required to bring safe and effective treatments to patients. Such trials require the appropriate tools, including biomarkers that are reliable and objective. A biomarker is a measureable characteristic of a biological or pathogenic process. In the context of disease, a biomarker reflects the presence or severity of disease, or its response to treatment. There are three different areas where biomarkers could have an important role: trait, state and pharmacological. A marker of disease trait is a stable measure that predicts the likelihood of developing a disease; such markers are required for the selection of individuals for a clinical trial. In HD, predictive gene testing is the sole trait biomarker required to identify individuals who will develop the disease during their lifetime. Because it does so with absolute certainty, this allows the identification of HD gene carriers many years before symptom onset. A marker of disease state is one that determines the severity of disease and would be expected to change as the disease progresses or in response to treatment. Such biomarkers are important because they provide an early indication as to whether a potential therapeutic intervention is beneficial or not. If such a state biomarker predicts a clinically meaningful benefit it might be possible to use it as a surrogate endpoint in a clinical trial. This type of
Corresponding author: Tabrizi, S.J. ([email protected])
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biomarker has been the focus of considerable research in HD, but the development of state biomarkers that are sensitive to change in preHD patients remains an important challenge. A marker of pharmacological activity, or a pharmacodynamic marker, is important to confirm that the therapeutic agent is engaging its intended target to have a biological effect. This type of biomarker could be specific for a particular mechanism of action and different biomarkers might be required depending on the type of therapeutic intervention. For example, a particular challenge in the development of HTT-gene-lowering therapies is the search for markers of mutant (m)HTT-lowering in the brain. However, a pharmacodynamic biomarker is not always a reliable marker of
disease progression or an effective measure of therapeutic efficacy, and other biomarkers are often required. For every biomarker to be useful it needs to be readily quantifiable, robust and reproducible. If used as an outcome measure in a clinical trial, it should show a measureable clinically meaningful response to the intended intervention. The modality of a particular biomarker will be associated with specific methodological considerations and will determine the kind of information that it yields (Table 1). For example, clinical assessments are more likely to measure impairments in function that are relevant to the everyday living of the patient, whereas biochemical measures provide potentially important information about underlying
TABLE 1
Different biomarker modalities in HD: their advantages and disadvantages Assessment
Advantages
Disadvantages
Longitudinal change?a
UHDRS
Widely used and inexpensive Easy to administer Well standardised and robust Relatively rapid
Floor and ceiling effects Inter-rater variability Influenced by physiological factors Mostly insensitive in preHD
TFC shows decline in early HD over 12 months TMS shows decline in early HD and preHD over 12 months
Other clinical measures (including quantitative motor, cognitive and neuropsychiatric tests)
Measures that are important to the patient Widely available and inexpensive Easy to administer and standardise Relatively rapid Noninvasive
Mostly insensitive in preHD or longitudinal change over short periods of time, have not been fully established Inter-rater variability Potential for practice effects Some tests are susceptible to floor and ceiling effects Some tests are susceptible to day-today fluctuations or are influenced by physiological factors
Speeded tapping shows decline in early HD over 12 months and preHD over 36 months Tongue force variability shows decline in early HD over 12 months and preHD controls over 24 months Negative emotion recognition shows decline in early HD and close-to-onset preHD over 24 months Circle tracing shows decline in early HD and closeto-onset preHD over 12 months Symbol Digit Modality test shows decline in early HD over 12 months, conflicting evidence about period required to detect change in preHD PBA apathy measures show decline in early HD over 36 months Combined Stroop and set-shifting task with electrophysical measures has shown decline in preHD over 6 months
Neuroimaging measures (including structural MRI, diffusion MRI, PET and TMS)
Measures are proximal to underlying pathological processes Have shown longitudinal change over short periods of time and sensitivity in preHD, with large effect sizes Robust and reproducible Most methods are noninvasive Functional and metabolic measures can show reversal in response to intervention and/ or be sensitive to the very earliest change
Relatively expensive and timeconsuming Unsuitable for some subjects owing to, for example, chorea, claustrophobia or metal implants PET is invasive Some technologies are not widely available
Volumetric MRI measures of caudate atrophy in early HD and preHD over 12 months Volumetric MRI measures of whole-brain atrophy in early HD and close-to-onset preHD over 12 months Fractional anisotropy has had conflicting results regarding longitudinal sensitivity FDG-PET has shown increased thalamic metabolism in preHD over 18 months RAC-PET has shown increased loss of dopamine receptors in early HD over 29 months
Biochemical measures
Measures are proximal to underlying pathological processes Most biofluids are readily accessible and rapidly obtained High-throughput and relatively inexpensive Measures can show reversal in response to intervention
Sampling CSF is invasive Potential for variability between sites as a result of differences in sample handling, processing and storage Measures can be affected by physiological and environmental factors Not all measures are sufficiently robust
No validated measures of longitudinal change
Abbreviations: CSF, cerebrospinal fluid; FDG, fluorodeoxyglucose; HD, Huntington’s disease; MRI, magnetic resonance imaging; PBA, Problem Behaviours Assessment; PET, positron emission tomography; RAC, raclopride; TFC, total functional capacity; TMS, total motor score; UHDRS, Unified Huntington’s Disease Rating Scale. a Change relative to control subjects.
2
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Measures of patient function have been used widely in HD clinical trials conducted to date and undoubtedly provide assessments that are most directly relevant to patients themselves. Current clinical rating scales such as the Unified Huntington’s Disease Rating Scale (UHDRS) are well-established and easy to administer. One of the most commonly used components of the UHDRS, the total functional capacity (TFC) scale, does show reasonably good effect sizes in measuring change in early-HD patients, but is insensitive in preHD individuals [4–6]. The UHDRS total motor score (TMS) is likewise sensitive in early HD, but there is some inconsistency in
Symbol digit modality test (number correct)
measures of change over time before symptom onset [6], possibly as a result of the high inter- and intra-rater variability associated with this scale [7]. The TRACK-HD and PREDICT-HD studies have aimed to develop more-objective markers of patient function using specific measures of motor performance, cognition and neuropsychiatric behaviour. Indeed, the quantitative motor battery employed in the TRACK-HD study has enabled rigorous standardisation of such measures across multiple sites. Measures such as speeded tapping and tongue force variability tests have proved sensitive to cross-sectional differences in those far from disease onset [3,8], and have shown good sensitivity to longitudinal change over 12 months in early-stage HD [4] (Fig. 1). However, these measures require much longer periods of time to show change in the pre-HD phase [4–6] and might be unfeasible as primary outcome measures in such a cohort. Subtle impairment of cognitive functions such as recognition of negative emotions and visuomotor integration [2,3,5,9,10], and altered neuropsychiatric characteristics such as apathy and irritability [3,11,12], are evident from the preHD stage onwards. The majority of cognitive measures show change over short periods of time in early-stage HD [4,5,13] but, despite evidence that cognitive
PBA apathy (sqrt of points on PBA scale)
pathogenic processes. In HD, various functional, neuroimaging and biochemical measures have been used to observe differences between HD and control subjects, and between mutation gene carriers at different stages of disease. Such cross-sectional studies could be considered a useful first step in identifying potential biomarkers, but longitudinal data are required to understand fully the kinetics of a candidate biomarker over time (Table 1). This type of data has been yielded by the TRACK-HD and PREDICT-HD studies, significantly furthering biomarker development in HD.
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FIGURE 1
Longitudinal changes in quantitative motor, cognitive and neuropsychiatric measures over 36 months. (a) Grip force variability, heavy, nondominant, (b) speeded tapping inter-tap interval, nondominant, (c) symbol digit modality test, (d) Stroop word reading, (e) indirect circle tracing, (f) Problem Behaviours Assessment (PBA) apathy, (g) PBA composite behaviour; and mean-adjusted values for (h) Unified Huntington’s Disease Rating Scale (UHDRS) total motor score (TMS) and (i) UHDRS total functional capacity (TFC). Significant differences compared with controls over 36 months are represented by *P < 0.05, **P < 0.01 and ***P < 0.001. Reproduced, with permission, from [6]. Abbreviations: HD, Huntington’s disease; sqrt, square root. www.drugdiscoverytoday.com Please cite this article in press as: R. Andre, et al., Biomarker development for Huntington’s disease, Drug Discov Today (2014), http://dx.doi.org/10.1016/j.drudis.2014.03.002
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assessment such as the symbol digit modality task shows sensitivity to change in pre-HD over 12 months [14], larger studies indicate that longer periods of observation are required to observe decline in this cohort [4–6]. Moreover, many cognitive tasks such as circle tracing suffer from practice effects [5], which need to be considered when recruiting subjects with differing levels of prior experience of a particular task. Neuropsychiatric measures are highly variable over time, limiting their utility as a primary outcome measure [4–6], but their relevance to assessing patient function clinically in terms of safe response to a treatment remains. An interesting new approach could be the coupling of cognitive and electrophysiological measures. Use of a joint Stroop test and set-shifting task paradigm with electrophysiological measurement of event-related potential (ERP) measurements has shown sensitivity in separating HD and control subjects and gene carriers at differing disease stages, and in detecting significant decline with a large effect size over 6 months [15]. This novel cognitive–neurophysiological biomarker shows promise as a biomarker in pre-HD, where 6-month interval change had not been shown previously. Demonstrating the reproducibility of this single-centre study will be important in determining the utility of using these cognitive and electrophysiological measures together as an HD biomarker.
Neuroimaging biomarkers Neuroimaging has shown perhaps the most significant recent developments as a tool to detect disease-related change in HD. The most widely used modality in HD biomarker research has been structural magnetic resonance imaging (MRI). For example, crosssectional studies using volumetric MRI have shown disease-related atrophy of the striatum and white matter of HD gene carriers as compared with control subjects, including those who are several years away from expected symptom onset [2,3,16]. Analysis of the whole brain using automated techniques such as voxel-based morphometry and FreeSurfer measurements of cortical thickness have also shown reduced volumes in HD gene carriers before symptom onset [3]. More importantly, longitudinal studies that detect change in individuals over time have shown progressive loss in the striatum [4–6,17–20], other subcortical structures [18] and global measures of grey and white matter [4–6,17,18,21] in early and preHD cohorts (Fig. 2). Progressive cortical thinning has been demonstrated in early-HD [22], but as yet has not been shown in preHD patients. The effect sizes of some of these volumetric measures, such as caudate atrophy, range from 0.9 in far-fromonset preHD subjects to 2.2 in early-stage patients [5], suggesting sample sizes that are feasible for use in clinical trials. The robustness of these measures across multiple sites has also been established [2,3]. More recently, other imaging modalities have been proposed as potential biomarkers in HD and work is ongoing to establish their validity. Diffusion MRI provides measures of microstructure, such as tissue integrity and myelination, which are indicative of underlying pathological processes that can precede macrostructural loss of tissue volume. Such measures have shown differences between HD and control subjects [23–25], but a direct comparison of diffusion and volume metrics has found that to date the former are less sensitive and more variable [26]. Moreover, diffusion MRI has shown conflicting evidence with regards to its utility to measure longitudinal change [27,28]. This reduced sensitivity 4
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might be caused by current technical limitations such as lower spatial resolution and increased scan dropout, and further refinement of the acquisition and analysis techniques might increase its utility in the future. Functional (f)MRI, which measures blood oxygen consumption as a proxy for metabolic activity, can be used to determine alterations in neuronal network structure that likewise might be expected to precede macrostructural tissue loss. Task-based measurements have highlighted differences in neuronal networks in preHD, even when these subjects have similar functional performance to healthy controls [29,30]. However, task-based fMRI has limited utility in the manifest stages of HD when functional impairment confounds the signal and atrophy is increasingly widespread. Resting-state fMRI avoids the problem of functional impairment and has demonstrated differences between gene carriers and controls [31,32]. Longitudinal change using fMRI has not been shown to date [33] and standardisation of these measures between individuals has proven problematic, but work to validate task-based and resting-state longitudinal fMRI across multiple sites is ongoing. Fluorodeoxyglucose positron emission tomography (FDG-PET) can be used to measure metabolic activity within the brain and has identified brain hypometabolism prior to disease onset [34–36]. Disease-related reductions in glucose metabolism over time have also been demonstrated [37]. The development of a range of ligands for specific receptors in the brain has allowed assessment of disease-related depletion of, for example, dopamine receptors using raclopride (RAC)-PET [38,39]; this loss of dopamine receptors appears to be progressive over time [37,38]. 11C-(R)-PK11195PET has also highlighted elevated microglial activation [40,41]. PET is used extensively as a research tool but is invasive, expensive and currently less widely available than MRI. Nevertheless, it is likely that PET will show a more rapid response to therapeutic intervention than volumetric MRI measures and could have particular utility in proof-of-concept trials where only small sample numbers are required. Magnetic resonance spectroscopy (MRS) provides measures of metabolites that are indicative of tissue health in either the brain or muscle, and disease-associated reductions in neuronal health have been detected using MRS in early-stage and preHD [42,43]. Such measures have potential utility in a clinical trial where, for example, a therapeutic intervention might be expected to restore neuronal health. Increasingly, imaging modalities are being used to measure different aspects of the disease process. For example, MRI has been used to identify elevated iron concentrations in the striatum and the cortex [44–46], with associated reductions in white matter [46]. Magnetisation transfer ratio imaging appears sensitive to microstructural grey and white matter disruption, but only once symptoms are manifest [47], and this technique is insensitive to longitudinal change over two years [48]. Novel techniques such as these will undoubtedly show further promise, but demonstrations of longitudinal sensitivity and robustness across different sites and between different scanner types will be required.
Biochemical biomarkers Biochemical analysis of biofluids has the potential to be rapid, high-throughput and inexpensive compared with the technical
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Longitudinal volumetric magnetic resonance imaging (MRI) changes over 36 months. Parametric maps showing regions with statistically significant atrophy in (a) white matter and (b) grey matter over 36 months, relative to controls. Mean-adjusted values for (c) whole-brain volume, (d) caudate volume, (e) putamen volume, (f) grey-matter volume and (g) white-matter volume. Significant differences compared with controls over 36 months are represented by *P < 0.05, **P < 0.01 and ***P < 0.001. Panels c–g are reproduced, with permission, from [6]. Abbreviation: HD, Huntington’s disease.
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demonstrated no significant longitudinal changes in 8OHdG levels at any disease stage [52]. Accurate measurement in biosamples of levels of mutant and wild-type HTT offers a new avenue for biomarker development in HD, and is a prerequisite for mHTT-lowering therapies that are expected to enter clinical trials in the near future. A novel time¨ rster resonance energy transfer assay that utilises fluorresolved Fo escently labelled anti-HTT antibodies has been used to measure soluble HTT levels in circulating immune cells, showing that mean mHTT levels in monocytes, T cells and B cells differ significantly between HD gene carriers and controls, and between pre-HD subjects and those with clinical onset [53] (Fig. 3). These findings indicate that quantification of mHTT in peripheral immune cells holds promise as a noninvasive HD biomarker; whether measures of the disease-associated protein accurately reflect the changing the state of the disease remains unknown.
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FIGURE 3
Measures of huntingtin protein (HTT) levels in peripheral immune cells. Total and mutant (m)HTT protein levels were quantified by time-resolved fluorescence resonance energy transfer (TR-FRET) in monocytes. (a) Total HTT levels in monocytes showed no significant differences between Huntington’s disease (HD) patients and control subjects, or between HD gene carriers at different disease stages. (b) mHTT protein was detected in samples from HD patients and pre-manifest HD mutation carriers, as compared with controls. Differences in mean mHTT levels in monocytes were observed between pre-manifest and manifest HD patients (P < 0.01), and between premanifest and early-stage HD subjects (P = 0.051). Coloured circles indicate multiple samples from a single subject. Reproduced, with permission, from [53].
complexities of neuroimaging, and such biomarkers are likely to evaluate changes that are proximal to the underlying pathology and perhaps have the greatest potential to show reversal in response to therapeutic intervention. Indeed, many biomarkers spanning a wide range of biological pathways have been identified in HD. These include molecules involved in endocrine function, metabolism, immune responses and oxidative stress, as well as antioxidants, neurotransmitters and other neurochemicals [49]. Most of these measures have been made in blood components such as serum, plasma and buffy coats; despite the ease with which urine and saliva can be obtained, limited results have been obtained from these materials. In comparison with functional and neuroimaging measures however, relatively few measures of biochemical biomarkers identified in cross-sectional studies have either been subject to or stood up to longitudinal analysis. For example, 8-hydroxy-2-deoxyguanisine (8OHdG), a major product of DNA oxidation, has been reported as being increased in blood samples of HD gene carriers [50,51], but subsequent work 6
Much recent progress has been made to identify HD biomarkers that show promise within the setting of a clinical trial. In particular, the identification by international, multisite studies such as TRACK-HD and PREDICT-HD of state biomarkers as potential outcome measures has been invaluable. These studies have validated the most robust and reproducible measures to date, yielding a battery comprising structural MRI, quantitative motor, cognitive and neuropsychiatric measures for use in clinical trials in earlystage HD [5]. However, these measures are insensitive to change in pre-HD over timescales realistic for clinical trials [6] and more sensitive measures are required to capture subtle changes that might be taking place before symptom onset. To that end, a new study, TrackOn-HD (http://hdresearch.ucl.ac.uk/currentstudies/trackon-hd/), aims to refine existing assessments further in pre-HD subjects, as well as investigating novel imaging modalities such as task and resting-state fMRI and transcranial magnetic stimulation that might be able to monitor compensatory mechanisms in the brains of this cohort. It is likely that existing state biomarkers will be superseded as current and novel methodologies are further developed, with technical advances resulting in enhanced sensitivity and reliability. For example, structural MRI has already benefitted from the increased tissue contrast provided by 3 Tesla (T) as compared with 1.5 T imaging and, although its use in a clinical setting is not yet widespread, research is now being undertaken using 7 T scanners. Similarly, although diffusion MRI has not yet shown the sensitivity of volumetric imaging despite its theoretical advantages, novel image analysis methods such as neurite orientation and dispersion diffusion imaging (NODDI) could allow much improved interrogation of the brain microstructure [54]. Furthermore, much work is ongoing to establish new PET ligands that can be used in HD to detect change in various aspects of the underlying disease processes. Such developments in neuroimaging-based measures clearly hold much promise, but existing studies have made clear the need for robust validation to demonstrate reproducibility between different test sites and scanner types. Particularly promising among current therapeutic strategies in HD is the reduction of mHTT levels in the brain by gene lowering. However, developments in this area are reliant on finding measures that accurately reflect mHTT levels in the brain. In the
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Finally, the selection of particular biomarkers in a clinical trial setting will depend upon the nature of the study cohort, as well as the proposed mechanism of action and probable timeframe of a given therapy. However, we are now in a position to embark on clinical trials of potentially disease-modifying compounds in HD with a number of validated state biomarkers, with the prospect of new measures arising for preHD cohorts in the near future.
Conflicts of interest The authors have no conflicts of interest to declare.
Acknowledgements We are grateful to Dr Edward Wild for review of the manuscript and to Ray Young for help with the graphics. S.J.T.’s work is funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n261358 (PADDINGTON), MRC, BBSRC, the CHDI Foundation, the UCL/ UCLH NIHR Biomedical Research Centre, the Huntington’s Disease Association, the European HD Network and the UK Dementia and Neurodegenerative Diseases Network.
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absence of direct measures within the brain, improved assays sensitive enough to detect mHTT in easily accessible biofluids and optimised for high-throughput use are required. Measures of mHTT in this manner could be crucial in monitoring the pharmacological activity of gene-lowering interventions, but it remains to be determined whether their levels accurately reflect the underlying state of the disease such that they can also be used as an outcome measure. For this and other candidate biomarkers in biofluids, longitudinal analyses of large numbers samples are required, for which the blood sample collections such as those from TRACK-HD will be invaluable. Despite the invasiveness of the procedure, cerebrospinal fluid (CSF) collection is well-tolerated and routinely undertaken in other neurodegenerative diseases, and could reasonably be considered the optimal biofluid in which to identify biomarkers. However, highly sensitive assays and standardised longitudinal studies are needed to identify CSF biomarkers in HD. More generally, where peripheral measures are made, an understanding of how they relate to HD pathogenesis is required to interpret their measurement best in the context of a clinical trial.
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