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Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis
Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cereb...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616092/ https://www.ncbi.nlm.nih.gov/pubmed/37903821 http://dx.doi.org/10.1038/s41467-023-42682-9 |
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author | Åkesson, Julia Hojjati, Sara Hellberg, Sandra Raffetseder, Johanna Khademi, Mohsen Rynkowski, Robert Kockum, Ingrid Altafini, Claudio Lubovac-Pilav, Zelmina Mellergård, Johan Jenmalm, Maria C. Piehl, Fredrik Olsson, Tomas Ernerudh, Jan Gustafsson, Mika |
author_facet | Åkesson, Julia Hojjati, Sara Hellberg, Sandra Raffetseder, Johanna Khademi, Mohsen Rynkowski, Robert Kockum, Ingrid Altafini, Claudio Lubovac-Pilav, Zelmina Mellergård, Johan Jenmalm, Maria C. Piehl, Fredrik Olsson, Tomas Ernerudh, Jan Gustafsson, Mika |
author_sort | Åkesson, Julia |
collection | PubMed |
description | Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS. |
format | Online Article Text |
id | pubmed-10616092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106160922023-11-01 Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis Åkesson, Julia Hojjati, Sara Hellberg, Sandra Raffetseder, Johanna Khademi, Mohsen Rynkowski, Robert Kockum, Ingrid Altafini, Claudio Lubovac-Pilav, Zelmina Mellergård, Johan Jenmalm, Maria C. Piehl, Fredrik Olsson, Tomas Ernerudh, Jan Gustafsson, Mika Nat Commun Article Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS. Nature Publishing Group UK 2023-10-30 /pmc/articles/PMC10616092/ /pubmed/37903821 http://dx.doi.org/10.1038/s41467-023-42682-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Åkesson, Julia Hojjati, Sara Hellberg, Sandra Raffetseder, Johanna Khademi, Mohsen Rynkowski, Robert Kockum, Ingrid Altafini, Claudio Lubovac-Pilav, Zelmina Mellergård, Johan Jenmalm, Maria C. Piehl, Fredrik Olsson, Tomas Ernerudh, Jan Gustafsson, Mika Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title | Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title_full | Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title_fullStr | Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title_full_unstemmed | Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title_short | Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
title_sort | proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616092/ https://www.ncbi.nlm.nih.gov/pubmed/37903821 http://dx.doi.org/10.1038/s41467-023-42682-9 |
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