Exploring Biomarkers for Huntington’s Disease

Abstract

Huntington’s disease (HD) is a progressive, non-curative, autosomal dominant neurodegenerative disease characterized by prominent psychiatric problems, as well as progressive deterioration in both cognitive function and motor control. The success of therapeutic interventions in HD patients cannot be easily examined without reliable and practical measurements by using effective biomarkers. Many clinical trials have been held to evaluate biomarkers efficacies in disease-modifying treatment before the manifestation of the disease or its severity. Biofluid (wet) biomarkers have potential advantages of direct quantification of biological processes at the molecular level, imaging biomarkers, on the other hand, can quantify related changes at a structural level in the brain. The most robust biofluid and imaging biomarkers are being investigated for their clinical use and development of future treatment and can offer complementary information, providing a more comprehensive evaluation of disease stage and progression.

1. Introduction

Huntington’s disease (HD) is an inherited disease that causes breakdown of nerve cells in the brain. HD, resulting from gene mutation, affects different parts of the brain impacting movement, behavior, emotion regulation, and psychiatric disturbance. Eventually, the person will need full-time care, and death of the disease is inescapable. HD is caused by an expanded trinucleotide cytosine-adenine-guanine (CAG) repeat in the huntingtin gene. HD is one of the rare neurodegenerative conditions for which predictive genetic testing is available for individuals with a known family history [1]. The identification of HD gene mutation carriers, while they are still healthy before manifestation (premanifest) of clinical signs of the disease has several benefits as this may help prevent the development or slowdown of the progression of the disease, hence, improved quality of life of the patient.

HD symptoms can develop at any time, but they often start at 30–50 years of age. If the condition develops earlier, before the age of 20, the symptoms start with behavioral disturbances and learning difficulties. Because of this, there is an urgent need to diagnose the disease as early as possible using biomarkers and assess the development of the disease. This can be achieved by identifying a number of biomarkers that are altered either premanifest or during the disease progression.

The unified Huntington’s Rating Scale (UHDRS) has been used as a clinical rating scale to assess four domains (motor function, cognitive function, behavioral abnormalities, and functional capacity) of clinical performance and capacity in HD patients. However, one of the main challenges in using this rating scale is the slow progression of HD, rendering the scale imperfect as a standalone tool [2] leading, in some cases, to limitations of clinical trials that aiming to assess the benefits of therapeutic agents in HD. In addition, there are several factors that could influence the clinical measures including the placebo effect and the clinical rater variability. This results in reduced ability indistinguishing between symptom relief and amelioration of the underlying disease process [3].

Finding biomarkers that change with clinical progression quickly and predictably with the use of a therapeutic agent could greatly facilitate future HD clinical trials by reducing the duration and number of patient volunteer required for such studies. This is especially important in premanifest HD mutation carriers, who may remain free from all clinical manifestations for decades. In addition, pharmacodynamic biomarkers can be utilized in preclinical trials and early phase clinical trials to predict if the therapeutic agent will have its intended effect and to assist in the decision-making process on whether to continue such trials or not.

Up to date biomarker research has included both focused small-scale and large studies. For instance, TRACK-HD (a prospective observational study of HD that examines disease progression in premanifest individuals carrying the mutant HTT gene and those with early-stage disease and those who have had it for 12 months or less) [4], and PREDICT-HD (a multicenter observational research study aimed to examine measures that may be associated with disease in the largest cohort ever recruited of pre-diagnosed individuals carrying the gene expansion for HD) [5], have afforded scientists in the field the opportunity to study many potential biomarkers for HD.

2. Biomarkers

The term biomarker is defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [6]. Therefore, a biomarker can be related to the disease itself or to the response to treatment. Hence, biomarkers can serve many different functions, such as diagnostic, prognostic, monitoring, response/pharmacodynamic, susceptibility/Risk Biomarker [7, 8]. In addition, most therapeutic clinical trials that aim to evaluate the efficacy of potential disease-modifying treatments during pre-manifest HD require biomarkers to serve as outcome measures. Some efficacy biomarkers may also function as ‘state biomarkers’ or ‘biomarkers of progression’, which are used as indicators of disease severity. These state biomarkers could very well reflect the underlying disease pathobiology and linearly track clinical progression of the disease (including during the pre-manifest stage) [1].

The biomarkers that have been used, hitherto, in HD are of types including, clinical biomarkers, wet biomarkers, and imaging biomarkers. Detailed discussion of these biomarkers and their subtypes is presented below.

2.1 Clinical biomarkers

Rather than relying on United Huntington’s Disease Rating Scale (UHDRS’s) dichotomous notion of ‘disease onset’, some researchers have proposed the use of continuous measures, such as clinical symptoms of the disease. Some UHDRS motor abnormalities can be objectively quantified, thereby improving accuracy and reducing inter-rater and intra-rater variability [1].

Tabrizi et al. have supported the hypothesis that neuronal dysfunction occurs many years before the development of motor signs that are diagnostic of HD. The motor alterations that have been described are most likely secondary to progressive neuronal loss or dysfunction. This could help define quantifiable endpoints for future therapeutic interventions [9]. Motor signs are amenable to quantitative assessment and may provide objective measures for disease onset and progression. Several quantitative motor tasks, including force-transducer-based assessments, detect deficits in premanifest gene carriers [10], for example, finger tapping precision and a problem task is evident even in pre-manifest HD and worsen with time. Another longitudinal study identified numerous cognitive task impairments in more than one variable, one of these variables is the Symbol Digit Modalities test which assesses visual attention and psychomotor speed [1, 10, 11] suggesting the limited use of clinical markers in preventive clinical trials.

2.2 Wet biomarkers

Wet biomarkers also called biofluids, (those obtained from bodily fluids, such as blood, urine, saliva, and cerebrospinal fluids (CSF)) are another potential source of useful outcome measures if they reflect the pathophysiology of a disease and show the response for a therapeutic agent.

In HD, various pathologic mechanisms have been implicated and numerous potential molecular markers have been detected. Progression of the disease have been reported to be associated with detectable changes in inflammatory signals in peripheral blood which matched changes in peripheral and central processes such as immune activation, neuroinflammation, and metabolic markers [12, 13]. In some cases, substances that are released from dying neurons that can penetrate the blood-brain barrier can be detected in peripheral blood and could be used as a biomarker. Unfortunately, however, if these substances have peripheral sources, conflict in interpretation may occur [14]. Cerebrospinal fluid, which is enriched with brain-derived substances is of particular interest, however, other biofluids have the potential to yield relevant biomarkers if their composition reflects that of the CNS. Consequently, all biofluids, including CSF, may reflect peripheral as well as central disease-related changes [3].

2.2.1 Mutant huntingtin protein

Huntington’s disease (HD) is caused by a cytosine-adenine-guanine (CAG) trinucleotide repeat expansion in the huntingtin gene (HTT), which leads to the production of the mutant huntingtin (mHTT) protein. The degree of symptom severity, disease stage, and markers of neuronal damage have been shown to correlate with levels of mHTT protein in the CSF in patients with HD. This toxic mHTT protein production is believed to result in neurotoxicity, as normal cellular processes important for cellular survival are disrupted. Furthermore, decreased level of mHTT is an important measure of the response to the therapeutic agents. mHTT quantification has been achieved for the first time in 2015 using a `femtomolar` single molecule counting (SMC) immunoassay, and a combination of mHTT N-terminal-detecting 2B7 antibody and polyglutamine-binding MW1 antibody. mHTT was significantly higher in manifest HD and premanifest HD compared to controls with a roughly threefold difference seen between premanifest HD and manifest [3, 14].

mHTT detection is associated with disease onset and cognitive and motor function disability. mHTT quantification in CSF could potentially serve as a biomarker for the development and testing of experimental mHTT-lowering therapies for HD [15]. mHTT levels also correlate with clinical manifestations as well as with two indicators of neuronal damage (CSF tau and neurofilament light chain) [14] suggesting that mHTT is released from damaged or dying neurons.

2.2.2 Neurofilament light and tau protein

Neurofilament light protein (NfL, also known as NFL) is the smallest of three subunits that make up neurofilaments, which are major components of the neuronal cytoskeleton. NfL is released from damaged neurons. Its concentrations in CSF are elevated in people with neurodegenerative diseases.

Detection of NfL in the CSF using enzyme-linked immunosorbent assay (ELISA) reflects that NfL concentration is elevated in both premanifest and manifest HD. This elevation is associated with mHTT elevation in CSF, disease stage, motor and cognitive impairment, functional impairment and brain atrophy, as well as reduction in all brain volume measures [14, 16, 17, 18].

Also, NfL is detectable in blood plasma or serum using a single-molecule ‘Simoa’ assay. It has been shown to increase in blood of people with neurodegenerative diseases including HD [14, 16]. Quantification of NfL in plasma provides an accessible biomarker that has close links to diagnosis, progression of HD and the response to disease-modifying treatments. Also, NfL in both plasma and CSF is considered a better biomarker to differentiate between premanifest and manifest HD than CSF mHTT [3, 17, 18, 19].

Tau protein (a microtubule-associated protein, which aggregates abnormally under certain pathologic conditions) is another protein that is hypothesized to be associated withHD. It has been found that CSF tau concentration in HD gene mutation carriers is increased compared with that of healthy controls. It has also been reported that CSF tau concentrations are associated with phenotypic variability in HD. This report strengthens the case for CSF tau as a biomarker in HD [20].

2.2.3 Inflammatory markers

Activation of glial cells has been reported in several neurodegenerative diseases including HD. Biomarkers reflecting these peripheral and/or central neuroinflammation could be useful to identify the disease onset, progression, and the therapeutic response. Proteomics screen of HD plasma identified immune proteins that are elevated in HD compared to healthy controls, including pro-inflammatory cytokine IL-6, acute-phase protein alpha-2-macroglobulin, complement factors, and a complement inhibitor clusterin. Additionally, it has been found that IL-6 levels were significantly increased in premanifest subjects with an estimated mean of 16 years before motor signs onset [8, 12, 16, 21].

Another marker that has also been studied as a CSF inflammatory marker in HD is YKL-40 (chitinase 3-like protein 1 (CHI3L1)), a member of the glycosyl hydrolase family 18 and a marker of microglial activation. The results about this marker are mixed [3, 14, 16].

2.2.4 Metabolic markers

Weight loss and muscle wasting are examples of some disorders that appear in patients with HD reflecting metabolic alterations in those patients. Several metabolites were tested as potential biomarkers for HD. In addition, several amino acids were tested as potential biomarkers. It has been reported that plasma levels of asparagine (Asn) and Serine (Ser) were significantly decreased suggesting a potential biomarker role for these two amino acids [22].

Studies conducted on the association of total cholesterol, HDL-cholesterol and LDL-cholesterol with HD revealed mixed, and in some cases, contradictory results. Whereas most studies showed that changes in cholesterol levels were insignificant, one study showed that reductions in cholesterol levels were significant in premanifest and manifest patients [23]. In another study, 24(S) hydroxycholesterol (24OHC), the brain-specific elimination product of cholesterol long considered a marker of brain cholesterol turnover, was significantly reduced in HD patients at all disease stages. This reduction was paralleled with a reduction of the caudate volume suggesting that the reduction of 24OHC may reflect progressive neuronal loss in HD patients. In addition, a decrease in the plasma concentration of cholesterol precursors` lanosterol and lathosterol was observed [8, 24, 25]. These results suggest the potential usefulness of these two cholesterol precursors as metabolic biomarkers in HD diagnosis and progression.

2.2.5 Neuroendocrine markers

Patients with manifest HD display circadian rhythm abnormalities with disturbances in rest-activity profiles and abnormal day-night ratios associated with alterations in sleep-wake timing and melatonin and cortisol profiles [26].

Melatonin is a light-sensitive hormone secreted predominantly by the pineal gland and displays a circadian rhythm with maximum levels peaking at night. It has a key role in the sleep-wake cycle which is disrupted in the early stages of HD. A significant decrease in mean melatonin levels has been reported in manifest HD, with trends towards decreased melatonin levels in premanifest HD and temporal shift in melatonin release in mHTT carriers. Altered melatonin patterns may provide an explanation for disrupted sleep and circadian behavior of HD patients acting as a biomarker for this disease state [3, 26, 27, 28, 29]. While there were no differences in melatonin release when it was measured at a single time point in advanced HD, differences in melatonin release were detected when measured at multiple time points. This suggests the need to measure melatonin levels at points representing the whole circadian rhythmicity [8].

Cortisol is another substance that plays a role in circadian rhythm as it has been observed that increased cortisol levels lead to sleep disturbances, which are likely to potentiate neurodegeneration and associated changes in cognitive, motor deficits and mood disturbances in HD [27, 30].

With markers that have specific circadian rhythms, 24-hour sample collections could be the means to using these markers as pharmacodynamic markers to assess the response to the treatment rather than the progression of the disease [3].

2.2.6 Oxidative stress markers

Both human and animal studies have suggested the involvement of energy metabolism dysfunction and oxidative stress in HD pathogenesis as it has been shown that levels of oxidative damage products, free radical production are elevated in areas of degeneration in HD brain [31]. It is thought that impairment in the electron transport chain and mitochondrial dysfunction are behind the increased production of reactive oxygen species in HD [32, 33, 34]. Markers of oxidative stress have been investigated in HD blood plasma and brain tissue in the animal model, but few have been quantified in CSF.

Several studies have reported enhanced lipid peroxidation in individuals with HD with a correlation between lipid peroxidation products in plasma and the degree of severity in patients with HD. It has been reported that F2-isoprostanes are a marker for lipid peroxidation found to be elevated in HD [3, 8, 14].

2.2.7 Endogenous opioid peptides

The endogenous opioid peptides have been found to be implicated in the regulation of motor function as well as in the pathophysiology of abnormal movement disorders. Degeneration of opioid peptide-containing neurons in the basal ganglia has been demonstrated in some neurodegenerative diseases such as HD [35]. Recently, it has been found that CSF proenkephalin (PENK) levels were significantly decreased in manifest HD patients compared to premanifest. The decrease in PENK CSF levels in premanifest patients was insignificant when compared to controls. Moreover, levels of PENK in the CSF is inversely proportional to the progression of HD symptoms. This decrease in PENK levels reflects the degeneration or dysfunction of neurons that produce PENK, consequently, PENK levels may serve as marker for the state of medium spiny neurons (MSNs) in HD patients [36].

Prodynorphin (PDYN) is another endogenous opioid that has been studied in HD. It has been found that PDYN-derived peptide levels were significantly decreased in CSF of patients with HD. This decrease is unique to HD as a comparable decrease was not observed in the other neurodegenerative disorders studied. These results suggest that PDYN-derived peptides in CSF could be considered as strong biomarker candidates for HD [37].

2.2.8 MicroRNAs

The microRNAs (miRNAs) are involved in different biological processes including development, proliferation, inflammation and apoptosis. miRNA is an intracellular component but also can be detected in the peripheral circulation. The level, structure, type and sequence of miRNAs detected in blood will reflect the physiological status, the type and stage of the disease [38]. The detection of abnormal expression of different miRNAs in the HD mouse model provides further support regarding the importance of miRNA in HD pathogenesis and therapeutics [39], and the potential usefulness of miRNAs as biomarkers for diagnosis, prognosis, and therapeutic response [38].

2.2.9 Exosomes

In the central nervous system (CNS), exosomes play essential physiological roles in the cell-to-cell communication and homeostasis maintenance required for normal brain function [40]. Exosomes contain a variety of key bioactive substances reflecting the status of the intracellular environment. As exosomes can penetrate the blood-brain barrier they can be found in peripheral body fluids, and their contents will change with diseases [41]. Most cell types in the brain release extracellular vesicles (EVs) and these have been shown to contain neurodegenerative proteins. In HD, by using a model culture system with overexpression of HTT-exon 1 polyQ-GFP constructs in human 293 T cells, it has been found that the EVs did incorporate both the polyQ-GFP protein as well as the expanded repeat RNA. These findings support the role of EVs as delivery vehicles of toxic expanded trinucleotide repeat RNAs from one cell to another [42]. Exosomes have a huge potential as non-invasive diagnostic biomarkers of HD for their content of mHTT, its fragments, or other proteins reflect the conditions of exosomes producing CNS cells [40].

2.3 Imaging biomarkers

In HD, neuroimaging techniques have been extensively investigated and have aided in our understanding of the disease’s natural history. Imaging is attractive as a source of biomarkers because it is generally non-invasive; data collecting, processing, and quality control can be standardized, and data can be easily sent over great distances, which is advantageous for multi-site investigations. The ideal imaging biomarker would be widely available, reasonably priced, and repeatable across multiple sites using different scanner manufacturers and field strengths and have a reasonable acquisition time - especially since HD patients may not tolerate longer scanning protocols and movement that degrades image quality.

Structural MRI, diffusion imaging, functional MRI, and PET are just a few of the imaging modalities available. There are a variety of image processing algorithms for each modality, and the approach chosen can have a big impact on the output metrics that are used as biomarkers. Some automated procedures, for example, can generate mistake and systemic bias, especially in atrophic brains [43]. To avoid difficulties, extensive validation of the acquisition and processing technique is essential before such measures may be used as a biomarker, which has been absent in many imaging investigations to date.

2.3.1 Structural volumetric MRI

Structural MRI (sMRI) is a non-invasive technique that provides information to describe the shape, size, and integrity of gray and white matter structures in the brain. MRI results emphasized that there are strong correlations between many gray and white matter regions and clinical tests, including recognition of negative emotions, metronome tapping precision, and measures of tongue force. The latest findings point of sMRI data enables to collect information from across the brain during the premanifest to manifest period in HD. The data show that no uniform atrophy occurs throughout the brain (Figure 1), where the largest changes (~18–22%) occurring in the striatum (caudate, pallidum, and putamen) and gradual changes (~7–16%) occurring across the four main brain regions (parietal, temporal, frontal, and occipital) over a period of ~11 years [44]. This timeframe is similar to prior studies of the timing of sMRI alterations in HD [45], according to which the rate of putamen and caudate atrophy becomes substantial roughly 9 and 11 years after estimated onset, respectively [44].

Figure 1.

RACK-HD cohort. Average magnitude of change of ten regional volumes from genotype-positive trajectories in TRACK-HD [44].

When used as a clinical trial endpoint, the rate of change of a proposed biomarker can influence the length of the study and the number of participants required to identify a meaningful change. There is no agreement on whether the pace of striatal atrophy progression differs with disease stage. TRACK-HD found stepwise accelerated rates of change from the earliest premanifest stage to early-stage disease, with limited evidence that the acceleration diminishes after symptoms appear [4, 46]. After controlling for age, TRACK-HD found highly significant relationships between the rate of change and disease burden ratings in both the caudate and putamen. The PREDICT-HD study, on the other hand, did not discover that rates accelerated across its premanifest group, but this could be due to differences in longitudinal change assessment methodology [47].

Studies for regional Cortical found in HD patients reported a heterogeneous volume loss [4, 9, 46, 48, 49, 50], where the cortical thinning occurs early during the clinical stage of disease and seems to increase with disease progression. The reported thinning of the cortical gray was clear in posterior cortical regions, with increasing duration of symptoms, more anterior cortical regions were affected. The reported data suggest that the cortex undergoes degeneration, much of which occurs in the striatum particularly in the early premanifest stage of the disease [46, 48, 51]. Cortical thinning was distributed in many areas, even within gray regions. In some areas the thinning was as much as 0.4 mm which corresponds to approximately a 20% loss of thickness whereas in other areas, thinning was around 1 mm, corresponding to 30% loss of thickness (Figure 2) [49, 53, 54, 55, 56, 57].

Figure 2.

(A) Mean thickness maps. The surface reconstruction demonstrates mean thickness differences of three different subjects with Huntington’s disease (HD) in differing stages of the disease. Darker gray areas correspond to sulci; lighter gray areas correspond to gyri [52].

The Cross-sectional studies have reported volume reductions in the corpus callosum [5] and frontal white matter (Figure 3) [9, 52, 59]. In premanifest HD, both TRACK-HD and PREDICT-HD showed progressive white matter atrophy, even in the groups farthest from anticipated onset [9, 46, 60]. In manifest disease, a similar picture has been observed, with cross-sectional reductions in white matter volume compared to controls [4, 9, 61, 62, 63], and elevated atrophy rates in longitudinal studies [52, 64]. White matter atrophy has been shown to correlate with motor function [47, 59, 65, 66], cognitive function [59, 65, 67] and total functional capacity (TFC) [47, 68]. White matter volume loss’ prognostic value for manifest HD conversion is less evident, with inconsistent findings in two large observational investigations [48, 69]. White matter atrophy, on the other hand, does track disease progression and is present from the earliest premanifest stage through established disease.

Figure 3.

Tracts showing lower fractional anisotropy in Huntington’s disease gene carriers when compared with controls. Results (red-yellow [lower to higher statistical values]) are projected on a white matter skeleton (green), overlaid on a customized mean fractional anisotropy image [58].

2.3.2 Functional MRI

There is mounting evidence that the severity of clinical manifestations in HD is influenced not just by neuronal loss but also by neuronal dysfunction and circuitry rearrangement, and that these processes can occur early in the disease, possibly even before neurodegeneration. By monitoring the hemodynamic response (blood flow) of neural activation, functional neuroimaging methods such as functional MRI (fMRI) produce dynamic images of the brain that aid in elucidating neural activity. Data from manifest HD patients revealed decreased task-activation in multiple subcortical and cortical regions, as well as increased task-activation in various cortical areas, which was interpreted as a compensatory mechanism for task performance [70, 71, 72, 73, 74, 75]. Interestingly, premanifest HD gene carriers who were further away from illness onset showed increased activation in multiple brain regions, whereas premanifest HD gene carriers who were closer to disease onset showed lower activation in the striatum [76, 77, 78, 79].

Both premanifest and manifest HD gene carriers have exhibited intrinsic deficits in functional connectivity in resting-state fMRI data [80, 81, 82]. Reduced blood-oxygen-level-dependent (BOLD) synchronization between the caudate and premotor cortex was reported in premanifest HD gene carriers [80]. A study found several abnormal networks in both premanifest and manifest HD subjects using a method that measures changes in synchrony in BOLD signal amplitude and across space. For example, it has been found that premanifest HD gene carriers had lower resting-state synchronization in the sensory-motor network and that this level of synchrony was related to motor performance as determined by speeded self-paced tapping [83]. Overall, these data demonstrate aberrant functional network connection in both premanifest and manifest HD, implying that resting state fMRI could be valuable for detecting early neural dysfunction and tracking disease progression.

Premanifest HD gene carriers have also been discovered to have neurovascular changes. Cortical arteriolar cerebral blood volume (CBVa) was significantly elevated in premanifest HD gene carriers compared to normal controls, which was connected with genetic parameters including the CAG-age product score and estimated years to onset [84].

2.3.3 Diffusion MRI

Diffusion MRI assesses the microstructural integrity of white matter filaments, providing additional information to volumetric MRI. The diffusion of water in different directions within the brain is measured using this technique. Water diffusion in healthy white matter fibers is usually only in one direction, making them anisotropic. When white matter breaks down, for example, due to axonal injury or demyelination, diffusion increases in directions other than the axons. Diffusion MRI might, in theory, reveal neuronal injury or dysfunction that occurs before volumetric loss.

The most widely-studied diffusion technique in HD is diffusion tensor imaging (DTI). Across various neurodegenerative diseases, reductions in fractional anisotropy (FA) and increases in mean diffusivity (MD) are commonly observed [85, 86, 87] indicating their sensitivity but lack of specificity to the underlying neurodegenerative process. Axonal loss, demyelination, and less cohesive white matter tracts are thought to be the cause of these abnormalities, which would be expected to occur before volume loss.

A Diffusion metric change has been observed in premanifest HD in cross-sectional investigations, particularly in the corpus callosum, internal capsule, and thalamic radiations [88, 89, 90, 91]. These alterations in the white matter, particularly the frontal, parietal, and occipital white matter, become increasingly pronounced and extensive in manifest HD [92, 93, 94]. The results of longitudinal studies using diffusion metrics have proved inconclusive. Two studies in premanifest HD failed to find 12–30 month changes [89, 95], whereas two larger studies found progressive changes over 1–5 years in premanifest HD cohorts including those up to 10 years away from onset [90, 96]. In manifest-HD, longitudinal alterations in DTI measures have also been demonstrated [51].

Changes in regional DTI measurements have been linked to total motor score (TMS), timed finger tapping, executive function [80], apathy [97], and depression [98]. However, no research has looked into the effectiveness of DTI measurements in predicting clinical development. Furthermore, DTI measurements had smaller impact sizes than volumetric measures in a comparative investigation across periods of 6–15 months [99] limiting the use of DTI as a biomarker of HD progression.

Recent advances in diffusion acquisition and modeling techniques, such as the use of neurite orientation dispersion and density imaging (NODDI) methods (Figure 4), have the potential to improve the sensitivity of diffusion MRI measures in HD [100, 101, 102]. However, there is currently a lack of agreement on diffusion imaging acquisition parameters, processing, and analysis procedures, which accounts for some of the variance in findings to date.

Figure 4.

White matter abnormalities: Neurite orientation dispersion and density imaging (NODDI) analysis [100].

2.3.4 Positron emission tomography (PET)

The use of PET in the diagnosis and understanding of neurological pathologies is crucial. It is a non-invasive molecular imaging technology that uses radiopharmaceuticals to attach to a specific molecular target, such as a transporter or receptor, after crossing the blood–brain barrier, allowing accurate tracking of changes in their function. PET now has a wide range of radiolabeled biomarkers for neuroimaging in psychiatry and neurodegenerative diseases like Parkinson’s disease (PD), Alzheimer’s disease (AD), and Huntington’s disease (HD).

PET has been used in HD to investigate metabolic markers of hypo-metabolism, dopaminergic function, microglial activation, and the expression of the PDE10A enzyme [103]. However, similar research have been conducted in small numbers, with mixed results. PET scanning is also more expensive than volumetric or diffusion MRI, generally is less available for large multicenter studies, and is more invasive because it uses ionizing radiation. PET, on the other hand, has the advantage of being able to provide more detailed information about pathological processes, and a future use of PET as a biomarker for target engagement in smaller proof-of-concept or phase 1 trials is in the horizon. PET was recently used to demonstrate effective target engagement of a new PDE10A inhibitor after a single dosage, paving the way for continued clinical development into a phase 2 trial [104]. Amyloid PET has shown promise in both experimental and clinical studies of Alzheimer’s disease [105] and a ligand capable of binding a pathogenic form of mutant huntingtin protein could be a useful PET biomarker for relevant pathology and regional brain tissue target engagement in huntingtin lowering studies [106].

3. Artificial intelligence and machine-learning techniques

Computational methods such as machine learning techniques are very useful tools in helping and improving the diagnosis as well as the disease monitoring process. A recent review study [107] concentrated on artificial intelligence in neurodegenerative diseases such as Huntington’s disease and others in which the authors reviewed the available tools with focus on machine learning techniques. Many authors have concentrated on Huntington’s disease alone using artificial intelligence and machine learning techniques [108, 109, 110]. More details on using artificial intelligence and machine learning techniques in the diagnosis and monitoring of Huntington’s disease will be reviewed alone later in a future publication.

4. Conclusion

As Huntington’s disease is not a preventable or curative disease, the availability of a diagnostic, prognostic, or response biomarker will have significant importance either in premanifest or manifest stage. Reliable biomarkers are needed either to delay/prevent the appearance of symptoms, slow the progression of the disease, and/or to monitor response to the therapy.

The identification of imaging and other measurements that have the ability to monitor and predict disease progression and therapy response has recently progressed in HD biomarker research. The most promising of them appear to be suitable for providing target engagement and efficacy readouts in premanifest HD or at short intervals. Such biomarkers may be verified as surrogate endpoints or even in the clinical context to guide prognostic discussions and treatment decisions in HD in the future as viable medicines become available. This promise will be realized through ongoing efforts to standardize methodology and reproduce findings in large-scale cohorts.

Conflict of interest

The authors declare no conflict of interest.