Back to Search Start Over

Uncovering a neurological protein signature for severe COVID-19

Authors :
Omar El-Agnaf
Ilham Bensmail
Maryam A.Y. Al-Nesf
James Flynn
Mark Taylor
Nour K. Majbour
Ilham Y. Abdi
Nishant N. Vaikath
Abdulaziz Farooq
Praveen B. Vemulapalli
Frank Schmidt
Khalid Ouararhni
Heba H. Al-Siddiqi
Abdelilah Arredouani
Patrick Wijten
Mohammed Al-Maadheed
Vidya Mohamed-Ali
Julie Decock
Houari B. Abdesselem
Source :
Neurobiology of Disease, Vol 182, Iss , Pp 106147- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has sparked a global pandemic with severe complications and high morbidity rate. Neurological symptoms in COVID-19 patients, and neurological sequelae post COVID-19 recovery have been extensively reported. Yet, neurological molecular signature and signaling pathways that are affected in the central nervous system (CNS) of COVID-19 severe patients remain still unknown and need to be identified. Plasma samples from 49 severe COVID-19 patients, 50 mild COVID-19 patients, and 40 healthy controls were subjected to Olink proteomics analysis of 184 CNS-enriched proteins. By using a multi-approach bioinformatics analysis, we identified a 34-neurological protein signature for COVID-19 severity and unveiled dysregulated neurological pathways in severe cases. Here, we identified a new neurological protein signature for severe COVID-19 that was validated in different independent cohorts using blood and postmortem brain samples and shown to correlate with neurological diseases and pharmacological drugs. This protein signature could potentially aid the development of prognostic and diagnostic tools for neurological complications in post-COVID-19 convalescent patients with long term neurological sequelae.

Details

Language :
English
ISSN :
1095953X
Volume :
182
Issue :
106147-
Database :
Directory of Open Access Journals
Journal :
Neurobiology of Disease
Publication Type :
Academic Journal
Accession number :
edsdoj.fd669ebb74b0473c81aeb3ab6179a51c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.nbd.2023.106147