Transcriptomic differences in MSA clinical variants

Abstract

Background: Multiple system atrophy (MSA) is a rare oligodendroglial synucleinopathy of unknown etiopathogenesis including two major clinical variants with predominant parkinsonism (MSA-P) or cerebellar dysfunction (MSA-C). Objective: To identify novel disease mechanisms we performed a blood transcriptomic study investigating differential gene expression changes and biological process alterations in MSA and its clinical subtypes. Methods: We compared the transcriptome from rigorously gender and age-balanced groups of 10 probable MSA-P, 10 probable MSA-C cases, 10 controls from the Catalan MSA Registry (CMSAR), and 10 Parkinson Disease (PD) patients. Results: Gene set enrichment analyses showed prominent positive enrichment in processes related to immunity and inflammation in all groups, and a negative enrichment in cell differentiation and development of the nervous system in both MSA-P and PD, in contrast to protein translation and processing in MSA-C. Gene set enrichment analysis using expression patterns in different brain regions as a reference also showed distinct results between the different synucleinopathies. Conclusions: In line with the two major phenotypes described in the clinic, our data suggest that gene expression and biological processes might be differentially affected in MSA-P and MSA-C. Future studies using larger sample sizes are warranted to confirm these results.We would like to thank all the patients for their always willing and generous collaboration. This project has been possible thanks to the funding from the Fundació Marató TV3 and CERCA Programme from Generalitat de Catalunya. We also thank the European Research Council RIBOMYLOME_309545 and Spanish Ministry of Economy and Competitiveness (BFU2017-86970-P). A.P.-S. was funded by a PHD4MD grant, which is a collaborative research training program for medical doctors. R.F.-S. was supported by a Jóvenes Investigadores (JIN) grant of the Spanish Ministry of Economy and Competitiveness (MINECO) and the Agencia Estatal de Investigación (AEI) (AEI/FEDER/UE) (grant # SAF2015-73508-JIN), and a Miguel Servet grant from the Instituto de Salud Carlos III (grant # CP19/00048). M.F. was funded by María de Maeztu programme (grant # MDM-2017-0729). Thanks to Lara Nonell, head of the Human Computational Biology group in IMIM, for offering the computational resources in the institution and the help with data management