Biomarker panel increases accuracy for identification of an MS relapse beyond sNfL.
Biomarkers
Multiple sclerosis
Proteomics
Relapses
Journal
Multiple sclerosis and related disorders
ISSN: 2211-0356
Titre abrégé: Mult Scler Relat Disord
Pays: Netherlands
ID NLM: 101580247
Informations de publication
Date de publication:
Jul 2022
Jul 2022
Historique:
received:
25
03
2022
revised:
04
05
2022
accepted:
26
05
2022
pubmed:
8
6
2022
medline:
29
6
2022
entrez:
7
6
2022
Statut:
ppublish
Résumé
For relapsing-remitting multiple sclerosis (RRMS), there is a need for biomarker development beyond clinical manifestations and MRI. Soluble neurofilament light chain (sNfL) has emerged as a biomarker for inflammatory activity in RRMS. However, there are limitations to the accuracy of sNfL in identifying relapses. Here, we sought to identify a panel of biomarkers that would increase the precision of distinguishing patients in relapse compared to sNfL alone. We used a multiplex approach to measure levels of 724 blood proteins in two distinct RRMS cohorts. Multiple t-tests with covariate correction determined biomarkers that were differentially regulated in relapse and remission. Logistic regression models determined the accuracy of biomarkers to distinguish relapses from remission. The discovery cohort identified 37 proteins differentially abundant in active RRMS relapse compared to remission. The verification cohort confirmed four proteins, including sNfL, were altered in active RRMS relapse compared to remission. Logistic regression showed that the 4-protein panel identified active relapse with higher accuracy (AUC = 0.87) than sNfL alone (AUC = 0.69). Our studies confirmed that sNfL is elevated during relapses in RRMS patients. Furthermore, we identified three other blood proteins, uPA, hK8 and DSG3 that were altered during relapse. Together, these four biomarkers could be used to monitor disease activity in RRMS patients.
Sections du résumé
BACKGROUND
BACKGROUND
For relapsing-remitting multiple sclerosis (RRMS), there is a need for biomarker development beyond clinical manifestations and MRI. Soluble neurofilament light chain (sNfL) has emerged as a biomarker for inflammatory activity in RRMS. However, there are limitations to the accuracy of sNfL in identifying relapses. Here, we sought to identify a panel of biomarkers that would increase the precision of distinguishing patients in relapse compared to sNfL alone.
METHODS
METHODS
We used a multiplex approach to measure levels of 724 blood proteins in two distinct RRMS cohorts. Multiple t-tests with covariate correction determined biomarkers that were differentially regulated in relapse and remission. Logistic regression models determined the accuracy of biomarkers to distinguish relapses from remission.
RESULTS
RESULTS
The discovery cohort identified 37 proteins differentially abundant in active RRMS relapse compared to remission. The verification cohort confirmed four proteins, including sNfL, were altered in active RRMS relapse compared to remission. Logistic regression showed that the 4-protein panel identified active relapse with higher accuracy (AUC = 0.87) than sNfL alone (AUC = 0.69).
CONCLUSION
CONCLUSIONS
Our studies confirmed that sNfL is elevated during relapses in RRMS patients. Furthermore, we identified three other blood proteins, uPA, hK8 and DSG3 that were altered during relapse. Together, these four biomarkers could be used to monitor disease activity in RRMS patients.
Identifiants
pubmed: 35671674
pii: S2211-0348(22)00433-3
doi: 10.1016/j.msard.2022.103922
pmc: PMC9351348
mid: NIHMS1815209
pii:
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
103922Subventions
Organisme : NIAID NIH HHS
ID : R01 AI137047
Pays : United States
Organisme : NEI NIH HHS
ID : R01 EY027346
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI110557
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI144298
Pays : United States
Informations de copyright
Copyright © 2022. Published by Elsevier B.V.
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