Statistical disease modeling and clinimetrics to prepare for preventive trials in huntington disease

项目总结

Project Summary Huntington disease (HD) is a fatal, costly, autosomal dominant neurodegenerative disease with no available disease-modifying treatments. While genetic testing can identify the presence of the mutant HTT gene, there are no markers to document the initiation of pathological changes or demarcate when preventive interventions are optimal to maximize quality of life. While clinical trials to slow progression and delay or prevent onset are beginning, methods to assess their efficacy are lacking. The proposed research will fill these gaps in our ability to design preventive clinical trials for HD. First, we will use the legacy PREDICT data to develop statistical models of onset, progression rate and phenotypic heterogeneity and then we will recruit 250 participants to complete the field's best Clinical Outcome Assessments (COAs) for premanifest HD and subject them to clinimetric tests of reliability, validity and responsiveness so future preventive trialists can utilize the information to design well-powered and efficient trials to delay the onset or slow the progression of HD