학술논문

LGMDD1 natural history and phenotypic spectrum: Implications for clinical trials.
Document Type
Article
Source
Annals of Clinical & Translational Neurology. Feb2023, Vol. 10 Issue 2, p181-194. 14p.
Subject
*NATURAL history
*CLINICAL trials
*MUSCULAR dystrophy
*PHENOTYPES
*AGE of onset
Language
ISSN
2328-9503
Abstract
Objective: To delineate the full phenotypic spectrum and characterize the natural history of limb girdle muscular dystrophy type D1 (LGMDD1). Methods: We extracted age at clinical events of interest contributing to LGMDD1 disease burden via a systematic literature and chart review. Manual muscle testing and quantitative dynamometry data were used to estimate annualized rates of change. We also conducted a cross‐sectional observational study using previously validated patient‐reported outcome assessments (ACTIVLIM, PROMIS‐57) and a new LGMDD1 questionnaire. Some individuals underwent repeat ACTIVLIM and LGMDD1 questionnaire assessments at 1.5 and 2.5 years. Results: A total of 122 LGMDD1 patients were included from 14 different countries. We identified two new variants (p.E54K, p.V99A). In vitro assays and segregation support their pathogenicity. The mean onset age was 29.7 years. Genotype appears to impact onset age, weakness pattern, and median time to loss of ambulation (34 years). Dysphagia was the most frequent abnormality (51.4%). Deltoids, biceps, grip, iliopsoas, and hamstrings strength decreased by (0.5‐1 lb/year). Cross‐sectional ACTIVLIM and LGMDD1 questionnaire scores correlated with years from disease onset. Longitudinally, only the LGMDD1 questionnaire detected significant progression at both 1.5 and 2.5 years. Treatment trials would require 62 (1.5 years) or 30 (2.5 years) patients to detect a 70% reduction in the progression of the LGMDD1 questionnaire. Interpretation: This study is the largest description of LGMDD1 patients to date and highlights potential genotype‐dependent differences that need to be verified prospectively. Future clinical trials will need to account for variability in these key phenotypic features when selecting outcome measures and enrolling patients. [ABSTRACT FROM AUTHOR]