Although the genetic basis of autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) has been uncovered, our poor understanding of disease mechanisms requires new light on functional pathways and modifying factors to improve early diagnostic strategies and offer alternative treatment options in a rare condition with no cure. Investigation of the pathologic state combining disease models and quantitative omic approach might improve biomarkers discovery with possible implications in patients' diagnoses. In this study, we analyzed proteomics data obtained using the SomaLogic technology, comparing cell lysates from ARSACS patients and from a SACS KO SH-SY5Y neuroblastoma cell model. Single-stranded deoxyoligonucleotides, selected in vitro from large random libraries, bound and quantified molecular targets related to the neuroinflammation signaling pathway and to neuronal development. Changes in protein levels were further analyzed by bioinformatics and network approaches to identify biomarkers of ARSACS and functional pathways impaired in the disease. We identified novel significantly dysregulated biological processes related to neuroinflammation, synaptogenesis, and engulfment of cells in patients and in KO cells compared with controls. Among the differential expressed proteins found in this work, we identified several proteins encoded by genes already known to be mutated in other forms of neurodegeneration. This finding suggests that common dysfunctional networks could be therapeutic targets for future investigations.

Functional Network Profiles in ARSACS Disclosed by Aptamer-Based Proteomic Technology

Morani, Federica
Primo
;
Doccini, Stefano;Gemignani, Federica;
2021-01-01

Abstract

Although the genetic basis of autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) has been uncovered, our poor understanding of disease mechanisms requires new light on functional pathways and modifying factors to improve early diagnostic strategies and offer alternative treatment options in a rare condition with no cure. Investigation of the pathologic state combining disease models and quantitative omic approach might improve biomarkers discovery with possible implications in patients' diagnoses. In this study, we analyzed proteomics data obtained using the SomaLogic technology, comparing cell lysates from ARSACS patients and from a SACS KO SH-SY5Y neuroblastoma cell model. Single-stranded deoxyoligonucleotides, selected in vitro from large random libraries, bound and quantified molecular targets related to the neuroinflammation signaling pathway and to neuronal development. Changes in protein levels were further analyzed by bioinformatics and network approaches to identify biomarkers of ARSACS and functional pathways impaired in the disease. We identified novel significantly dysregulated biological processes related to neuroinflammation, synaptogenesis, and engulfment of cells in patients and in KO cells compared with controls. Among the differential expressed proteins found in this work, we identified several proteins encoded by genes already known to be mutated in other forms of neurodegeneration. This finding suggests that common dysfunctional networks could be therapeutic targets for future investigations.
2021
Morani, Federica; Doccini, Stefano; Chiorino, Giovanna; Fattori, Fabiana; Galatolo, Daniele; Sciarrillo, Elisa; Gemignani, Federica; Züchner, Stephan; Bertini, Enrico Silvio; Santorelli, Filippo Maria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1105274
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