Unraveling the spatial landscape of dystrophinopathies
a transcriptomic approach to Becker and Duchenne muscular dystrophies
Laura G.M. Heezen (Leiden University Medical Center)
Qirong Mao (Leiden University Medical Center)
Stefan Nicolau (The Abigail Wexner Research Institute at Nationwide Children's Hospital)
Claudio Novella Rausell (Leiden University Medical Center)
Julia van der Weerd (Leiden University Medical Center)
Jan Kueckelhaus (Erlangen University, University of Freiburg)
Rasya Gokul Nath (Newcastle University Translational and Clinical Research Institute)
Jordi Diaz Manera (Centro de Investigación Biomédica en red de enfermedades raras (CIBERER), Institu de recerca Hospital Sant Pau, Newcastle University Translational and Clinical Research Institute)
Hermien E. Kan (Leiden University Medical Center, Duchenne Center)
Erik H. Niks (Duchenne Center, Leiden University Medical Center)
Maaike van Putten (Duchenne Center, Leiden University Medical Center)
Annemieke Aartsma-Rus (Leiden University Medical Center, Duchenne Center)
Kevin M. Flanigan (The Abigail Wexner Research Institute at Nationwide Children's Hospital, The Ohio State University)
Ahmed Mahfouz (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
Pietro Spitali (Leiden University Medical Center, Duchenne Center)
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Abstract
Dystrophinopathies are caused by pathogenic variants in the DMD gene, resulting in partial (Becker) or complete loss (Duchenne) of dystrophin. Becker (BMD) and Duchenne muscular dystrophy (DMD) are characterized by progressive muscle wasting, fatty replacement, fibrosis, and loss of function. To study histopathological changes, we used Visium spatial transcriptomics to profile skeletal muscle biopsies of patients affected by dystrophinopathy (n = 8) and healthy controls (n = 4). We estimated the proportion of cell types and their spatial localization across samples applying a deconvolution strategy using previously published single-nucleus RNA-sequencing data. We identified genes enriched in fat patches and cell types such as fibroadipogenic progenitors (FAPs) in areas of active pathology. Using expression data of ligand–receptor pairs, we highlight cell–cell communications leading to fibrotic and adipogenic lesions. Finally, analysis of gene expression gradients in areas of adjacent muscle and fat, allowed the identification of genes associated with muscle areas committed to becoming fat.
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