Modelling the natural history of Huntington's disease progression

Selective neurodegeneration generated by intravenous α-synuclein pre-formed fibril administration is not associated with endogenous α-synuclein levels in the rat brain

Selective loss of discrete neuronal populations is a prominent feature of many neurodegenerative conditions, but the molecular basis of this is poorly understood. A central role of α-synuclein in the selective neurodegeneration of Parkinson's disease has been speculated, as its level of expression critically determines the propensity of this protein to misfold. To investigate whether the propensity of neuronal cell loss is associated with the level of endogenous α-synuclein expression, non-transgenic rats were given a single intravenous administration of α-synuclein pre-formed fibrils (PFFs) reversibly complexed with the rabies virus glycoprotein peptide (RVG9R). The number of surviving cells in different neuronal populations was systematically quantified using unbiased stereology. Our data demonstrated that a non-selective, transvascular delivery of α-synuclein PFFs led to a time-dependent loss of specific populations of midbrain (but not olfactory) dopaminergic neurons, medullary (but not pontine) cholinergic neurons, and brainstem serotonergic neurons. Contrary to the central role of endogenous α-synuclein expression in determining the seeding and aggregation propensity of pathological α-synuclein, we did not observe an association between the levels of α-synuclein expression in different regions of the rodent brain (although did not ascertain this at the individual cell level) and neurodegenerative propensity. The results from our study highlight the complexity of the neurodegenerative process generated by α-synuclein seeding. Further investigations are therefore required to elucidate the molecular basis of neurodegeneration driven by exogenous pathogenic α-synuclein spread.

Applications of Induced Pluripotent Stem Cell-Derived Glia in Brain Disease Research and Treatment

Glia are integral components of neural networks and are crucial in both physiological functions and pathological processes of the brain. Many brain diseases involve glial abnormalities, including inflammatory changes, mitochondrial damage, calcium signaling disturbance, hemichannel opening, and loss of glutamate transporters. Induced pluripotent stem cell (iPSC)-derived glia provide opportunities to study the contributions of glia in human brain diseases. These cells have been used for human disease modeling as well as generating new therapies. This chapter introduces glial involvement in brain diseases, then summarizes different methods of generating iPSC-derived glia disease models of these cells. Finally, strategies for treating disease using iPSC-derived glia are discussed. The goal of this chapter is to provide an overview and shed light on the applications of iPSC-derived glia in brain disease research and treatment.

Natural History and Real‐World Data in Rare Diseases: Applications, Limitations, and Future Perspectives

Rare diseases represent a highly heterogeneous group of disorders with high phenotypic and genotypic diversity within individual conditions. Due to the small numbers of people affected, there are unique challenges in understanding rare diseases and drug development for these conditions, including patient identification and recruitment, trial design, and costs. Natural history data and real-world data (RWD) play significant roles in defining and characterizing disease progression, final patient populations, novel biomarkers, genetic relationships, and treatment effects. This review provides an introduction to rare diseases, natural history data, RWD, and real-world evidence, the respective sources and applications of these data in several rare diseases. Considerations for data quality and limitations when using natural history and RWD are also elaborated. Opportunities are highlighted for cross-sector collaboration, standardized and high-quality data collection using new technologies, and more comprehensive evidence generation using quantitative approaches such as disease progression modeling, artificial intelligence, and machine learning. Advanced statistical approaches to integrate natural history data and RWD to further disease understanding and guide more efficient clinical study design and data analysis in drug development in rare diseases are also discussed.

A hierarchical Bayesian entry time realignment method to study the long-term natural history of diseases

A major question in clinical science is how to study the natural course of a chronic disease from inception to end, which is challenging because it is impractical to follow patients over decades. Here, we developed BETR (Bayesian entry time realignment), a hierarchical Bayesian method for investigating the long-term natural history of diseases using data from patients followed over short durations. A simulation study shows that BETR outperforms an existing method that ignores patient-level variation in progression rates. BETR, when combined with a common Bayesian model comparison tool, can identify the correct disease progression function nearly 100% of the time, with high accuracy in estimating the individual disease durations and progression rates. Application of BETR in patients with geographic atrophy, a disease with a known natural history model, shows that it can identify the correct disease progression model. Applying BETR in patients with Huntington’s disease demonstrates that the progression of motor symptoms follows a second order function over approximately 20 years.

Therapeutic Potential of Astrocyte Transplantation

Cell transplantation is an attractive treatment strategy for a variety of brain disorders, as it promises to replenish lost functions and rejuvenate the brain. In particular, transplantation of astrocytes has come into light recently as a therapy for amyotrophic lateral sclerosis (ALS); moreover, grafting of astrocytes also showed positive results in models of other conditions ranging from neurodegenerative diseases of older age to traumatic injury and stroke. Despite clear differences in etiology, disorders such as ALS, Parkinson's, Alzheimer's, and Huntington's diseases, as well as traumatic injury and stroke, converge on a number of underlying astrocytic abnormalities, which include inflammatory changes, mitochondrial damage, calcium signaling disturbance, hemichannel opening, and loss of glutamate transporters. In this review, we examine these convergent pathways leading to astrocyte dysfunction, and explore the existing evidence for a therapeutic potential of transplantation of healthy astrocytes in various models. Existing literature presents a wide variety of methods to generate astrocytes, or relevant precursor cells, for subsequent transplantation, while described outcomes of this type of treatment also differ between studies. We take technical differences between methodologies into account to understand the variability of therapeutic benefits, or lack thereof, at a deeper level. We conclude by discussing some key requirements of an astrocyte graft that would be most suitable for clinical applications.

Cell therapy in Huntington's disease: Taking stock of past studies to move the field forward

Huntington's disease (HD) is a rare inherited neurodegenerative disease that manifests mostly in adulthood with progressive cognitive, behavioral, and motor dysfunction. Neuronal loss occurs predominantly in the striatum but also extends to other brain regions, notably the cortex. Most patients die around 20 years after motor onset, although there is variability in the rate of progression and some phenotypic heterogeneity. The most advanced experimental therapies currently are huntingtin-lowering strategies, some of which are in stage 3 clinical trials. However, even if these approaches are successful, it is unlikely that they will be applicable to all patients or will completely halt continued loss of neural cells in all cases. On the other hand, cellular therapies have the potential to restore atrophied tissues and may therefore provide an important complementary therapeutic avenue. Pilot studies of fetal cell grafts in the 2000s reported the most dramatic clinical improvements yet achieved for this disease, but subsequent studies have so far failed to identify methodology to reliably reproduce these results. Moving forward, a major challenge will be to generate suitable donor cells from (nonfetal) cell sources, but in parallel there are a host of procedural and trial design issues that will be important for improving reliability of transplants and so urgently need attention. Here, we consider findings that have emerged from clinical transplant studies in HD to date, in particular new findings emerging from the recent multicenter intracerebral transplant HD study, and consider how these data may be used to inform future cell therapy trials.

The effects of multidisciplinary rehabilitation on neuroimaging, biological, cognitive and motor outcomes in individuals with premanifest Huntington's disease

BACKGROUND

Huntington's disease (HD) is a chronic, progressive neurodegenerative condition for which there are currently no proven disease-modifying therapies. Lifestyle factors have been shown to impact on the age of disease onset and progression of disease features. We therefore investigated the effects of a nine-month multidisciplinary rehabilitation intervention on neuroimaging, biological and clinical disease outcomes in individuals with premanifest HD.

METHODS

31 individuals with premanifest HD participated in the study. Eighteen participants underwent a nine-month multidisciplinary rehabilitation intervention comprising aerobic and resistance exercise, computerised cognitive training, dual-task training and sleep hygiene and nutritional guidance. The remaining 13 participants were allocated to a standard care control group. Neuroimaging, biological, cognitive, motor and cardiorespiratory fitness data was collected.

RESULTS

Participants displayed good adherence (87%) and compliance (85%) to the intervention. Maintenance of the shape of the right putamen was observed in the intervention group when compared to the control group. The intervention group displayed significant improvements in verbal learning and memory, attention, cognitive flexibility and processing speed following the intervention when compared to the control group. Performance on the mini-social cognition and emotional assessment (mini-SEA) was maintained in the intervention group, but decreased in the control group. No changes were observed in serum neurofilament light protein levels, postural stability outcomes or cardiorespiratory fitness.

CONCLUSION

This study adds to the accumulating body of literature to suggest that multidisciplinary rehabilitation is of clinical benefit for individuals with HD. Large randomised controlled trials are necessary to determine the extent to which benefits occur across the spectrum of the disease.

Antidopaminergic treatment is associated with reduced chorea and irritability but impaired cognition in Huntington's disease (Enroll-HD)

OBJECTIVES

Alterations in dopamine neurotransmission underlie some of the clinical features of Huntington's disease (HD) and as such are a target for therapeutic intervention, especially for the treatment of chorea and some behavioural problems. However, justification for such an intervention is mainly based on case reports and small open label studies and the effects these drugs have on cognition in HD remain unclear.

METHODS

In this study, we used the Enroll-HD observational database to assess the effects of antidopaminergic medication on motor, psychiatric and cognitive decline, over a 3-year period. We first looked at the annual rate of decline of a group of HD patients taking antidopaminergic medication (n=466) compared with an untreated matched group (n=466). The groups were matched on specified clinical variables using propensity score matching. Next, we studied a separate group of HD patients who were prescribed such medications part way through the study (n=90) and compared their rate of change before and after the drugs were introduced and compared this to a matched control group.

RESULTS

We found that HD patients taking antidopaminergic medication had a slower progression in chorea and irritability compared with those not taking such medications. However, this same group of patients also displayed significantly greater rate of decline in a range of cognitive tasks.

CONCLUSION

In conclusion we found that antidopaminergic treatment is associated with improvements in the choreic movements and irritability of HD but worsens cognition. However, further research is required to prospectively investigate this and whether these are causally linked, ideally in a double-blind placebo-controlled trial.

Association Between Toll-Like Receptor 4 (TLR4) and Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) Genetic Variants and Clinical Progression of Huntington's Disease

BACKGROUND

Although Huntington's disease (HD) is caused by a single dominant gene, it is clear that there are genetic modifiers that may influence the age of onset and disease progression.

OBJECTIVES

We sought to investigate whether new inflammation-related genetic variants may contribute to the onset and progression of HD.

METHODS

We first used postmortem brain material from patients at different stages of HD to look at the protein expression of toll-like receptor 4 (TLR4) and triggering receptor expressed on myeloid cells 2 (TREM2). We then genotyped the TREM2 R47H gene variant and 3 TLR4 single nucleotide polymorphisms in a large cohort of HD patients from the European Huntington's Disease Network REGISTRY.

RESULTS

We found an increase in the number of cells expressing TREM2 and TLR4 in postmortem brain samples from patients dying with HD. We also found that the TREM2 R47H gene variant was associated with changes in cognitive decline in the large cohort of HD patients, whereas 2 of 3 TLR4 single nucleotide polymorphisms assessed were associated with changes in motor progression in this same group.

CONCLUSIONS

These findings identify TREM2 and TLR4 as potential genetic modifiers for HD and suggest that inflammation influences disease progression in this condition. © 2019 International Parkinson and Movement Disorder Society.

Serum Raman spectroscopy as a diagnostic tool in patients with Huntington's disease

Huntington's disease is an inherited fatal progressive neurodegenerative disorder. A possible new Raman ‘spectral’ biomarker was identified that uses a tiny drop of patients' blood serum; thus can have immense diagnostic and therapeutic implications.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an abnormal CAG expansion in exon 1 of the huntingtin (HTT) gene. Given its genetic basis it is possible to study patients both in the pre-manifest and manifest stages of the condition. While disease onset can be modelled using CAG repeat size, there are no easily accessible biomarkers that can objectively track disease progression. Here, we employed a holistic approach using spectral profiles generated using both surface-enhanced Raman spectroscopy (SERS) and Raman Spectroscopy (RS), on the serum of healthy participants and HD patients covering a wide spectrum of disease stages. We found that there was both genotype- and gender-specific segregation on using the full range in the fingerprint region with both SERS and RS. On a more detailed interrogation using specific spectral intervals, SERS revealed significant correlations with disease progression, in particular progression from pre-manifest through to advanced HD was associated with serum molecules related to protein misfolding and nucleotide catabolism. Thus, this study shows the potential of Raman spectroscopy-based techniques for stratification of patients and, of SERS, in particular, to track disease status through provision of ‘spectral’ biomarkers in HD, with clinical applications for other diseases and trials looking at disease modifying therapies.

Disease-Modification in Huntington's Disease: Moving Away from a Single-Target Approach

To date, no candidate intervention has demonstrated a disease-modifying effect in Huntington's disease, despite promising results in preclinical studies. In this commentary we discuss disease-modifying therapies that have been trialled in Huntington's disease and speculate that these failures may be attributed, in part, to the assumption that a single drug selectively targeting one aspect of disease pathology will be universally effective, regardless of disease stage or "subtype". We therefore propose an alternative approach for effective disease-modification that uses 1) a combination approach rather than monotherapy, and 2) targets the disease process early on - before it is clinically manifest. Finally, we will consider whether this change in approach that we propose will be relevant in the future given the recent shift to targeting more proximal disease processes-e.g., huntingtin gene expression; a timely question given Roche's recent decision to take on the clinical development of a promising new drug candidate in Huntington's disease, IONIS-HTTRx.

Assessing Decline: Visualising Progression in Huntington's Disease using a Clinical Dashboard with Enroll-HD Data

BACKGROUND

In Huntington's disease (HD), it remains unclear how symptom severity and rate of symptomatic change relates to age and CAG repeat number (CAGn). It is often difficult for clinicians to assess whether an affected individual's symptoms are progressing at a similar rate to their affected peers, limiting their ability to intervene at the most appropriate time.

OBJECTIVE

To develop a clinical dashboard that compares an individual's total motor score (TMS), total functional capacity (TFC) and symbol digit modality test (SDMT) scores against a global cohort, controlling for age and CAGn. The dashboard could then be used by clinicians to identify individuals progressing at a disproportionate rate to his or her peers.

METHODS

Annualised longitudinal clinical assessment scores from the Enroll-HD dataset were used to generate decline trajectories of the global cohort, allowing cross-sectional (TMS n = 734; TFC n = 734; SDMT n = 694) and longitudinal (TMS n = 270; TFC n = 270; SDMT n = 247) comparison with individual clinical symptom rating scores, to assess decline relative to affected peers.

RESULTS

An electronic dashboard with a dynamic output display was created that rapidly compares clinical symptom rating scores of a specific individual against affected peers from a global cohort of comparable CAGn.

CONCLUSIONS

This study shows the potential for use of multi-centre trial data in allowing comparison of the individual to a larger group to facilitate improved decision-making for individual patients. Visualisation of these metrics via a clinical dashboard demonstrates how it may aid identification of those with disproportionate decline, offering potential for intervention at specific critical points in the disease course.

Clinical and genetic investigation of a Brazilian family with Huntington's disease

The aim of this study was to investigate a Brazilian family carrying full penetrance alleles for Huntington's disease (HD) in order to correlate each member's genetic and clinical features. To this end, the following scales were administered in each patient: the Beck Depression Inventory, the Mini-Mental State Examination (MMSE) and the Unified Huntington's Disease Rating Scale (UHDRS). The patterns of CAG and CCG polymorphic regions in the HTT gene were determined, the disease burden score was calculated, and genotypes were correlated with phenotypes within this family. We suggest that HD duration, the number of years of formal education, and UHDRS status variables can explain 96.6% of the MMSE variability in HD patients. A strong significant correlation was found between the disease burden score and the UHDRS (r = 0.76; p-value = 0.049) and the MMSE (r = -0.90; p-value = 0.006). The correlations between CAG allele size and the three clinical evaluations performed in the HD patients were not statistically significant.

Disease Progression Modeling: Key Concepts and Recent Developments

Disease modeling involves the use of mathematical functions to describe quantitatively the time course of disease progression. In order to characterize the natural progression of disease, these models generally incorporate longitudinal data for some biomarker(s) of disease severity or can incorporate more direct measures of disease severity. Disease models are also often linked to pharmacokinetic-pharmacodynamic models so that the influence of drug treatment on disease progression can be quantified and evaluated. Regulatory agencies have embraced disease progression models as powerful tools that can be used to improve drug development productivity. This article provides a brief overview of key concepts in disease progression modeling followed by illustrative examples from models for Alzheimer's disease. Finally, recent novel applications in which disease progression models have been linked to cost-effectiveness analysis and genomic analysis are described.