MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1093/brain/awaf389

Медицинская библиотека · Brain : a journal of neurology · 2026

Muscle transcriptomics of alpha-sarcoglycanopathy highlights inflammatory pathways driving disease.

Amaro Adriana, Reggiani Francesco, Panicucci Chiara, Petito Mariangela, Baratto Serena, Pintus Sara, Principi Elisa, Antonini Francesca, Del Zotto Genny, Vellone Valerio Gaetano, D'Amico Adele, Lopergolo Diego, Tonin Paola, Malfatti Edoardo, Mongini Tiziana, Pegoraro Elena, Previtali Stefano C, Rodolico Carmelo, Tasca Giorgio, Fiorillo Chiara, Gazzerro Elisabetta, Pfeffer Ulrich, Bruno Claudio, Raffaghello Lizzia

СтатьяПеревод в очереди

Аннотация

Muscular dystrophies are a heterogeneous group of genetic disorders associated with an aberrant inflammatory response, that contributes to disease progression impairing regeneration and inducing fibrosis. Sarcoglycanopathies are recessively inherited limb-girdle muscular dystrophies (LGMDRs), in which the role of inflammation and its association with disease severity remains poorly understood, particularly in alpha-sarcoglycanopathy (LGMDR3). This study characterizes skeletal muscle and peripheral inflammatory signatures in 16 LGMDR3 patients and 8 unaffected individuals through bulk RNA sequencing with additional validation in Sgca-null mice. Patients were classified into mild and severe groups based on alpha sarcoglycan (SGCA) expression in muscle biopsy. Peripheral immunophenotype was assessed via flow cytometry analysis of peripheral blood mononuclear cells (PBMC). Principal component analysis showed a clear separation of severe LGMDR3 from mild LGMDR3 and unaffected individuals, with the latter two groups overlapping. Unsupervised hierarchical clustering analysis of the most variable genes identified distinct gene expression profiles between severe and mild LGMDR3 samples. Severe LGMD3 showed overexpression of innate immune system and T-cell activation pathways, with higher abundance of inflammatory infiltrate, mainly monocytes, cytotoxic T cells and dendritic cells. Notably, severe LGMDR3 were characterized by enrichment of M1-polarized macrophages and pro-inflammatory chemokines, whereas M2-polarized monocytes predominated in mild cases. Similar inflammatory profiles were observed in Sgca-null mice. PBMC analysis revealed significantly increased CD8+, TH1 CD4+ lymphocytes and activated monocytes in LGMDR3 patients compared with controls. Severe LGMDR3 patients additionally showed overexpression of genes governing fibrosis and muscle tissue regeneration and exhibited a clustering pattern similar to Duchenne muscular dystrophy patients. In conclusion, this study represents the first comprehensive characterization of LGMDR3 immunological profiles and demonstrated that inflammation plays a significant role in severe disease pathogenesis. The distinct immune signatures separating severe from mild cases provide a foundation for developing targeted anti-inflammatory therapies that may benefit severe LGMDR3 patients with severe phenotype.

Для цитирования: Amaro Adriana, Reggiani Francesco, Panicucci Chiara, Petito Mariangela, Baratto Serena, Pintus Sara, Principi Elisa, Antonini Francesca, Del Zotto Genny, Vellone Valerio Gaetano, D'Amico Adele, Lopergolo Diego, Tonin Paola, Malfatti Edoardo, Mongini Tiziana, Pegoraro Elena, Previtali Stefano C, Rodolico Carmelo, Tasca Giorgio, Fiorillo Chiara, Gazzerro Elisabetta, Pfeffer Ulrich, Bruno Claudio, Raffaghello Lizzia. Muscle transcriptomics of alpha-sarcoglycanopathy highlights inflammatory pathways driving disease.. Brain : a journal of neurology. 2026. DOI: 10.1093/brain/awaf389.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.