Human genetics · 2026
The Russian FSHD registry: a first look at the cohort.
СтатьяНазвание и аннотация: Перевод в очереди
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Kuchina Anna, Sherstyukova Darya, Borovikov Artem, Soloshenko Margarita, Zernov Nikolay, Subbotin Dmitrii, Dadali Elena, Sharkova Inna, Rudenskaya Galina, Kutsev Sergey, Skoblov Mikhail, Murtazina Aysylu
Аннотация
Facioscapulohumeral muscular dystrophy (FSHD) is a common hereditary neuromuscular disorder. The Russian FSHD Patient Registry was established in 2019 following the development of a PCR-based method for genetic confirmation of the diagnosis. The registry included 491 participants, of whom 51% were male. The mean age was 38.2 years (range 0-97 years), indicating a younger cohort compared to international data. Genetic confirmation of FSHD type 1 or type 2 was achieved for 76% of participants (n = 373). The remaining participants had not yet undergone genetic testing and were included based on clinical and anamnestic data. D4Z4 repeat units (RUs) ranged from 1 to 10, with equally predominant 3, 5, and 6 RUs, making our cohort more similar to Asian cohorts published earlier. Clinical assessment forms and patient-reported questionnaires were analyzed for 279 and 134 patients with genetically confirmed diagnoses, respectively. A moderate inverse correlation was found between RU number and clinical severity scales. Shoulder girdle weakness was the most common onset manifestation (45.2%), followed by facial weakness (34.4%). A delta-adjusted cluster analysis (n = 187) identified three distinct disease progression trajectories based on the temporal pattern of muscle involvement. The smallest cluster comprised patients with very slow progression, in whom facial muscle involvement occurred at late stages. The Russian FSHD registry provides a comprehensive characterization of a large national cohort, revealing a D4Z4 repeat unit distribution similar to Asian countries and a younger demographic profile than reported in international data. Cluster analysis identified three distinct disease progression trajectories, offering a valuable framework for improved patient stratification.