Age at onset mediates genetic impact on disease severity in facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy type 1 (FSHD1) patients exhibit marked variability in both age at onset (AAO) and disease severity. Early onset FSHD1 patients are at an increased risk of severe weakness, and early onset has been tentatively linked to the length of D4Z4 repeat units (RUs) and methylation levels. The present study explored potential relationships among genetic characteristics, AAO and disease severity in FSHD1. This retrospective and observational cohort study was conducted at the Fujian Neuromedical Centre (FNMC) in China. Genetically confirmed participants with FSHD1 recruited from 2001 to 2023 underwent distal D4Z4 methylation assessment. Disease severity was assessed by FSHD clinical score, age-corrected clinical severity score (ACSS) and onset age of lower extremity involvement. Mediation analyses were used to explore relationships among genetic characteristics, AAO and disease severity. Finally, machine learning was employed to explore AAO prediction in FSHD1. A total of 874 participants (including 804 symptomatic patients and 70 asymptomatic carriers) were included. Multivariate Cox regression analyses indicated that male gender, low DUZ4 RUs, low CpG6 methylation levels, non-mosaic mutation and de novo mutation were independently associated with early onset in FSHD1. Early onset patients (AAO < 10 years) had both a significantly higher proportion and an earlier median onset age of lower extremity involvement compared to the typical adolescent onset (10 ≤ AAO < 20 years), typical adult onset (20 ≤ AAO < 30 years) and late onset (AAO ≥ 30 years) subgroups. AAO was negatively correlated with both clinical score and ACSS. We found that AAO exerted mediation effects, accounting for 12.2% of the total effect of D4Z4 RUs and CpG6 methylation levels on ACSS and 38.6% of the total effect of D4Z4 RUs and CpG6 methylation levels on onset age of lower extremity involvement. A random forest model that incorporated variables including gender, age at examination, inheritance pattern, mosaic mutation, D4Z4 RUs and D4Z4 methylation levels (at CpG3, CpG6 and CpG10 loci) performed well for AAO prediction. The predicted AAO (pAAO) was negatively correlated with ACSS (Spearman's ρ = -0.692). Our study revealed independent contributions from D4Z4 RUs, D4Z4 methylation levels, mosaic mutation and inheritance pattern on AAO variation in FSHD1. AAO mediates effects of D4Z4 RUs and methylation levels on disease severity. The pAAO values from our random forest model informatively reflect disease severity, offering insights that can support efficacious patient management.