Abstract
Although the genetic basis of Duchenne muscular dystrophy has been known for almost thirty years, the cellular and molecular mechanisms characterizing the disease are not completely understood and an efficacious treatment remains to be developed. In this study we analyzed proteomics data obtained with the SomaLogic technology from blood serum of a cohort of patients and matched healthy subjects. We developed a workflow based on biomarker identification and network-based pathway analysis that allowed us to describe different deregulated pathways. In addition to muscle-related functions, we identified other biological processes such as apoptosis, signaling in the immune system and neurotrophin signaling as significantly modulated in patients compared with controls. Moreover, our network-based analysis identified the involvement of FoxO transcription factors as putative regulators of different pathways. On the whole, this study provided a global view of the molecular processes involved in Duchenne muscular dystrophy that are decipherable from serum proteome.
Highlights
Proteomics, the large scale analysis of proteins, is feasible thanks to the availability of different technologies, such as mass spectrometry, gel-based techniques, antibody-based arrays and recently developed aptamer-based technologies [1,2,3]
We applied the algorithm for biomarker identification to point out the essential features of the biological system, i.e. the minimum set of proteins able to fully separate healthy from affected subjects, and we applied the network analysis to unravel the complex interactions among the proteins
Findings from a more recent study suggest that sarcopenia is not due to FoxO activation [39], highlighting the need for further studies to better understand the role of FoxO proteins in physiological and pathological muscle conditions
Summary
Proteomics, the large scale analysis of proteins, is feasible thanks to the availability of different technologies, such as mass spectrometry, gel-based techniques, antibody-based arrays and recently developed aptamer-based technologies [1,2,3]. Despite these technological improvements, the extraction of knowledge from the data produced is still challenging and the development of data analysis workflows capable of providing additional insight compared to traditional methods would be highly advantageous. Protein biomarkers and network analysis in DMD
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