Genetic diagnosis of facioscapulohumeral muscular dystrophy (FSHD) remains a challenge in clinical practice as it cannot be detected by standard sequencing methods despite being the third most common muscular dystrophy. The conventional diagnostic strategy addresses the known genetic parameters of FSHD: the required presence of a permissive haplotype, a size reduction of the D4Z4 repeat of chromosome 4q35 (defining FSHD1) or a pathogenic variant in an epigenetic suppressor gene (consistent with FSHD2). Incomplete penetrance and epistatic effects of the underlying genetic parameters as well as epigenetic parameters (D4Z4 methylation) pose challenges to diagnostic accuracy and hinder prediction of clinical severity. In order to circumvent the known limitations of conventional diagnostics and to complement genetic parameters with epigenetic ones, we developed and validated a multistage diagnostic workflow that consists of a haplotype analysis and a high-throughput methylation profile analysis (FSHD-MPA). FSHD-MPA determines the average global methylation level of the D4Z4 repeat array as well as the regional methylation of the most distal repeat unit by combining bisulphite conversion with next-generation sequencing and a bioinformatics pipeline and uses these as diagnostic parameters. We applied the diagnostic workflow to a cohort of 148 patients and compared the epigenetic parameters based on FSHD-MPA to genetic parameters of conventional genetic testing. In addition, we studied the correlation of repeat length and methylation level within the most distal repeat unit with age-corrected clinical severity and age at disease onset in FSHD patients. The results of our study show that FSHD-MPA is a powerful tool to accurately determine the epigenetic parameters of FSHD, allowing discrimination between FSHD patients and healthy individuals, while simultaneously distinguishing FSHD1 and FSHD2. The strong correlation between methylation level and clinical severity indicates that the methylation level determined by FSHD-MPA accounts for differences in disease severity among individuals with similar genetic parameters. Thus, our findings further confirm that epigenetic parameters rather than genetic parameters represent FSHD disease status and may serve as a valuable biomarker for disease status.
Keywords: FSHD; bisulphite sequencing; epigenetics; methylation.
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