@article{discovery10172369,
         journal = {Neurobiology of Disease},
       publisher = {Elsevier BV},
           title = {Uncovering a neurological protein signature for severe COVID-19},
            year = {2023},
            note = {{\copyright} 2023 The Author(s). Published by Elsevier Inc. under a Creative Commons license (http://creativecommons.org/licenses/by/4.0/).},
          volume = {182},
             url = {https://doi.org/10.1016/j.nbd.2023.106147},
          author = {El-Agnaf, O and Bensmail, I and Al-Nesf, MAY and Flynn, J and Taylor, M and Majbour, NK and Abdi, IY and Vaikath, NN and Farooq, A and Vemulapalli, PB and Schmidt, F and Ouararhni, K and Al-Siddiqi, HH and Arredouani, A and Wijten, P and Al-Maadheed, M and Mohamed-Ali, V and Decock, J and Abdesselem, HB},
        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.},
        keywords = {Severe COVID-19, Neurological complications, Olink proteomics, Protein signature}
}