Identification of immune-related features involved in Duchenne muscular dystrophy: A bidirectional transcriptome and proteome-driven analysis

Abstract

BackgroundWe aimed to investigate the biological mechanism and feature genes of Duchenne muscular dystrophy (DMD) by multi-omics and experimental verification strategy.MethodsWe integrated the transcriptomic and proteomic methods to find the differentially expressed mRNAs (DEMs) and proteins (DEPs) between DMD and Control groups. Weighted gene co-expression network analysis (WGCNA) was then used to identify modules of highly correlated genes and hub genes. In the following steps, the immune and stromal cells infiltrations were accomplished by xCELL algorithm. Furthermore, TF and miRNA prediction were performed with Networkanalyst. ELISA, western blot and external datasets were performed to verify the key proteins/mRNAs in DMD patient and mouse. Finally, a nomogram model was established based on the potential biomarkers.Results4515 DEMs and 56 DEPs were obtained from the transcriptomic and proteomic study respectively. 14 common genes were identified, which is enriched in muscle contraction and inflammation-related pathways. Meanwhile, we observed 33 significant differences in the infiltration of cells in DMD. Afterwards, a total of 22 miRNAs and 23 TF genes interacted with the common genes, including TFAP2C, MAX, MYC, NFKB1, RELA, hsa-miR-1255a, hsa-miR-130a, hsa-miR-130b, hsa-miR-152, and hsa-miR-17. In addition, three genes (ATP6AP2, CTSS, and VIM) showed excellent diagnostic performance on discriminating DMD in GSE1004, GSE3307, GSE6011 and GSE38417 datasets (all AUC > 0.8), which is validated in patients (10 DMD vs. 10 controls), DMD with exon 55 mutations, mdx mouse, and nomogram model.ConclusionTaken together, ATP6AP2, CTSS, and VIM play important roles in the inflammatory response in DMD, which may serve as diagnostic biomarkers and therapeutic targets.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

“…Multi-omics approaches have a great potential to improve our understanding of complex human disease mechanisms [ 473 ] and establish systems biological concepts [ 474 ], including the systems biology of skeletal muscles [ 475 ]. The application of multi-omics has already been used to study crucial aspects of skeletal muscle cell biology in health and disease [ 476 , 477 , 478 , 479 ] and been applied to certain aspects of the field of dystrophinopathy research, including the integrative screening of dystrophic animal models [ 277 , 480 , 481 , 482 ], the evaluation of immune responses in muscular dystrophy [ 483 ], myogenic remodeling by human pluripotent stem cells [ 484 ], astrocyte-related abnormalities [ 485 ] and dystrophinopathy-associated cardiomyopathy [ 324 , 331 ]. The main techniques used for proteomics-centric and multi-omics studies have been recently reviewed by Rajczewski et al [ 486 ].…”

Transcriptomic analysis of paired healthy human skeletal muscles to identify modulators of disease severity in DMD

“…To explore potential relationships between our differential gene expression and reported mechanisms of DMD pathology that can be mapped to individual genes, we analyzed the differential expression of previously reported human serum/blood DMD biomarkers (Hathout et al, 2014;Parolo et al, 2018;Spitali et al, 2018;Al-Khalili Szigyarto, 2020;Grounds et al, 2020;Alonso-Jiménez et al, 2021;Wagner et al, 2021;Lee-Gannon et al, 2022;Wu et al, 2022), and of genes modifying the phenotype of DMD in humans (Pegoraro et al, 2011;Flanigan et al, 2013;Bello et al, 2016;Hogarth et al, 2017;Li et al, 2018;Weiss et al, 2018;Spitali et al, 2020;Flanigan et al, 2023) or the mdx mouse (Deconinck et al, 1997;Wagner et al, 2002;Han et al, 2011;Morales et al, 2013;de Zélicourt et al, 2022), also known as genetic modifiers, across the VL and TA and identified the predominant cell type in which they were expressed.…”