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Lancet Neurol
Published

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

Authors

Sarah J Tabrizi, Scott Schobel, Emily C Gantman, Alexandra Mansbach, Beth Borowsky, Pavlina Konstantinova, Tiago A Mestre, Jennifer Panagoulias, Christopher A Ross, Maurice Zauderer, Ariana P Mullin, Klaus Romero, Sudhir Sivakumaran, Emily C Turner, Jeffrey D Long, Cristina Sampaio,

Abstract

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.

PMID:35716693 | DOI:S1474-4422(22)00120-X

UK DRI Authors

Paul Matthews

Prof Paul Matthews

Group Leader

Exploring neuronal vulnerability and genetic risk variants in Alzheimer’s progression

Prof Paul Matthews