A biological classification of Huntington's disease: the Integrated Staging System

The current research paradigm for Huntington's disease is based on participants with overt clinical phenotypes and does not address its pathophysiology nor the biomarker changes that can precede by decades the functional decline. We have generated a new research framework to standardise clinical research and enable interventional studies earlier in the disease course. The Huntington's Disease Integrated Staging System (HD-ISS) comprises a biological research definition and evidence-based staging centred on biological, clinical, and functional assessments. We used a formal consensus method that involved representatives from academia, industry, and non-profit organisations. The HD-ISS characterises individuals for research purposes from birth, starting at Stage 0 (ie, individuals with the Huntington's disease genetic mutation without any detectable pathological change) by using a genetic definition of Huntington's disease. Huntington's disease progression is then marked by measurable indicators of underlying pathophysiology (Stage 1), a detectable clinical phenotype (Stage 2), and then decline in function (Stage 3). Individuals can be precisely classified into stages based on thresholds of stage-specific landmark assessments. We also demonstrated the internal validity of this system. The adoption of the HD-ISS could facilitate the design of clinical trials targeting populations before clinical motor diagnosis and enable data standardisation across ongoing and future studies.

T cells targeting a neuronal paraneoplastic antigen mediate tumor rejection and trigger CNS autoimmunity with humoral activation

Paraneoplastic neurologic diseases (PND) involving immune responses directed toward intracellular antigens are poorly understood. Here, we examine immunity to the PND antigen Nova2, which is expressed exclusively in central nervous system (CNS) neurons. We hypothesized that ectopic expression of neuronal antigen in the periphery could incite PND. In our C57BL/6 mouse model, CNS antigen expression limits antigen-specific CD4+ and CD8+ T-cell expansion. Chimera experiments demonstrate that this tolerance is mediated by antigen expression in nonhematopoietic cells. CNS antigen expression does not limit tumor rejection by adoptively transferred transgenic T cells but does limit the generation of a memory population that can be expanded upon secondary challenge in vivo. Despite mediating cancer rejection, adoptively transferred transgenic T cells do not lead to paraneoplastic neuronal targeting. Preliminary experiments suggest an additional requirement for humoral activation to induce CNS autoimmunity. This work provides evidence that the requirements for cancer immunity and neuronal autoimmunity are uncoupled. Since humoral immunity was not required for tumor rejection, B-cell targeting therapy, such as rituximab, may be a rational treatment option for PND that does not hamper tumor immunity.

Volumetric MRI-Based Biomarkers in Huntington's Disease: An Evidentiary Review

Huntington's disease (HD) is an autosomal-dominant inherited neurodegenerative disorder that is caused by expansion of a CAG-repeat tract in the huntingtin gene and characterized by motor impairment, cognitive decline, and neuropsychiatric disturbances. Neuropathological studies show that disease progression follows a characteristic pattern of brain atrophy, beginning in the basal ganglia structures. The HD Regulatory Science Consortium (HD-RSC) brings together diverse stakeholders in the HD community—biopharmaceutical industry, academia, nonprofit, and patient advocacy organizations—to define and address regulatory needs to accelerate HD therapeutic development. Here, the Biomarker Working Group of the HD-RSC summarizes the cross-sectional evidence indicating that regional brain volumes, as measured by volumetric magnetic resonance imaging, are reduced in HD and are correlated with disease characteristics. We also evaluate the relationship between imaging measures and clinical change, their longitudinal change characteristics, and within-individual longitudinal associations of imaging with disease progression. This analysis will be valuable in assessing pharmacodynamics in clinical trials and supporting clinical outcome assessments to evaluate treatment effects on neurodegeneration.

Applying the Huntington's Disease Integrated Staging System (HD-ISS) to Observational Studies

BACKGROUND

The Huntington's Disease Integrated Staging System (HD-ISS) has four stages that characterize disease progression. Classification is based on CAG length as a marker of Huntington's disease (Stage 0), striatum atrophy as a biomarker of pathogenesis (Stage 1), motor or cognitive deficits as HD signs and symptoms (Stage 2), and functional decline (Stage 3). One issue for implementation is the possibility that not all variables are measured in every study, and another issue is that the stages are broad and may benefit from progression subgrouping.

OBJECTIVE

Impute stages of the HD-ISS for observational studies in which missing data precludes direct stage classification, and then define progression subgroups within stages.

METHODS

A machine learning algorithm was used to impute stages. Agreement of the imputed stages with the observed stages was evaluated using graphical methods and propensity score matching. Subgroups were defined based on descriptive statistics and optimal cut-point analysis.

RESULTS

There was good overall agreement between the observed stages and the imputed stages, but the algorithm tended to over-assign Stage 0 and under-assign Stage 1 for individuals who were early in progression.

CONCLUSION

There is evidence that the imputed stages can be treated similarly to the observed stages for large-scale analyses. When imaging data are not available, imputation can be avoided by collapsing the first two stages using the categories of Stage≤1, Stage 2, and Stage 3. Progression subgroups defined within a stage can help to identify groups of more homogeneous individuals.

T cells presenting viral antigens or autoantigens induce cytotoxic T cell anergy

In the course of modeling the naturally occurring tumor immunity seen in patients with paraneoplastic cerebellar degeneration (PCD), we discovered an unexpectedly high threshold for breaking CD8+ cytotoxic T cell (CTL) tolerance to the PCD autoantigen, CDR2. While CDR2 expression was previously found to be strictly restricted to immune-privileged cells (cerebellum, testes, and tumors), unexpectedly we have found that T cells also express CDR2. This expression underlies inhibition of CTL activation; CTLs that respond to epithelial cells expressing CDR2 fail to respond to T cells expressing CDR2. This was a general phenomenon, as T cells presenting influenza (flu) antigen also fail to activate otherwise potent flu-specific CTLs either in vitro or in vivo. Moreover, transfer of flu peptide-pulsed T cells into flu-infected mice inhibits endogenous flu-specific CTLs. Our finding that T cells serve as a site of immune privilege, inhibiting effector CTL function, uncovers an autorepressive loop with general biologic and clinical relevance.

Recommendations to Optimize the Use of Volumetric MRI in Huntington's Disease Clinical Trials

Volumetric magnetic resonance imaging (vMRI) has been widely studied in Huntington's disease (HD) and is commonly used to assess treatment effects on brain atrophy in interventional trials. Global and regional trajectories of brain atrophy in HD, with early involvement of striatal regions, are becoming increasingly understood. However, there remains heterogeneity in the methods used and a lack of widely-accessible multisite, longitudinal, normative datasets in HD. Consensus for standardized practices for data acquisition, analysis, sharing, and reporting will strengthen the interpretation of vMRI results and facilitate their adoption as part of a pathobiological disease staging system. The Huntington's Disease Regulatory Science Consortium (HD-RSC) currently comprises 37 member organizations and is dedicated to building a regulatory science strategy to expedite the approval of HD therapeutics. Here, we propose four recommendations to address vMRI standardization in HD research: (1) a checklist of standardized practices for the use of vMRI in clinical research and for reporting results; (2) targeted research projects to evaluate advanced vMRI methodologies in HD; (3) the definition of standard MRI-based anatomical boundaries for key brain structures in HD, plus the creation of a standard reference dataset to benchmark vMRI data analysis methods; and (4) broad access to raw images and derived data from both observational studies and interventional trials, coded to protect participant identity. In concert, these recommendations will enable a better understanding of disease progression and increase confidence in the use of vMRI for drug development.

Huntington's Disease Regulatory Science Consortium: Accelerating Medical Product Development

Huntington's disease (HD) is a devastating neurodegenerative disorder that urgently needs disease-modifying therapeutics. To this end, collaboration to standardize clinical research practices in the field and drive progress in addressing drug development challenges is paramount. At a meeting in 2017 organized by CHDI Foundation and the Critical Path Institute, stakeholders across the pharmaceutical industry, academia, regulatory agencies, and patient advocacy groups discussed the need for and potential impact of a consortium dedicated to HD regulatory science. Consequently, the Huntington's Disease Regulatory Science Consortium (HD-RSC) was formed, a precompetitive consortium that is dedicated to building a regulatory strategy to expedite the approval of HD therapeutics.

Time to Functional Loss as an Endpoint in Huntington's Disease Trials: Enrichment and Sample Size

BACKGROUND

Clinical trial scenarios can be modeled using data from observational studies, providing critical information for design of real-world trials. The Huntington's Disease Integrated Staging System (HD-ISS) characterizes disease progression over an individual's lifespan and allows for flexibility in the design of trials with the goal of delaying progression. Enrichment methods can be applied to the HD-ISS to identify subgroups requiring smaller estimated sample sizes.

OBJECTIVE

Investigate time to the event of functional decline (HD-ISS Stage 3) as an endpoint for trials in HD and present sample size estimates after enrichment.

METHODS

We classified individuals from observational studies according to the HD-ISS. We assessed the ability of the prognostic index normed (PIN) and its components to predict time to HD-ISS Stage 3. For enrichment, we formed groups from deciles of the baseline PIN distribution for HD-ISS Stage 2 participants. We selected enrichment subgroups closer to Stage 3 transition and estimated sample sizes, using delay in the transition time as the effect size.

RESULTS

In predicting time to HD-ISS Stage 3, PIN outperforms its components. Survival curves for each PIN decile show that groups with PIN from 1.48 to 2.74 have median time to Stage 3 of approximately 2 years and these are combined to create enrichment subgroups. Sample size estimates are presented by enrichment subgroup.

CONCLUSIONS

PIN is predictive of functional decline. A delay of 9 months or more in the transition to Stage 3 for an enriched sample yields feasible sample size estimates, demonstrating that this approach can aid in planning future trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.