Nature Communications (Oct 2023)

Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis

  • Julia Åkesson,
  • Sara Hojjati,
  • Sandra Hellberg,
  • Johanna Raffetseder,
  • Mohsen Khademi,
  • Robert Rynkowski,
  • Ingrid Kockum,
  • Claudio Altafini,
  • Zelmina Lubovac-Pilav,
  • Johan Mellergård,
  • Maria C. Jenmalm,
  • Fredrik Piehl,
  • Tomas Olsson,
  • Jan Ernerudh,
  • Mika Gustafsson

DOI
https://doi.org/10.1038/s41467-023-42682-9
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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Abstract 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.