Plasma proteomic profiles of UK Biobank participants with multiple sclerosis

Author:

Jacobs Benjamin M.12ORCID,Vickaryous Nicola1,Giovannoni Gavin12,Proitsi Petroula1,Waters Sheena1,Dobson Ruth12ORCID

Affiliation:

1. Centre for Preventive Neurology, Wolfson Institute of Population Health Queen Mary University of London London UK

2. Department of Neurology Royal London Hospital London UK

Abstract

AbstractObjectiveWe aimed to describe plasma protein biomarkers of multiple sclerosis risk and to explore protein biomarkers of disease severity using radiological outcome measures.MethodsMultiple sclerosis cases and controls were identified in UK Biobank, a longitudinal cohort study of ~500,000 British adults. Plasma proteins were assayed in ~50,000 UK Biobank participants using the Olink proximity extension assay. We performed case–control association testing to examine the association between 2911 proteins and multiple sclerosis, using linear models adjusted for confounding covariates. Associations with radiological lesion burden and brain volume were determined in a subset of the cohort with available magnetic resonance imaging, using normalized T2‐hyperintensity volume or whole brain volume as the outcome measure.ResultsIn total, 407 prevalent multiple sclerosis cases and 39,979 healthy controls were included. We discovered 72 proteins associated with multiple sclerosis at a Bonferroni‐adjusted p value of 0.05, including established markers such as neurofilament light chain and glial fibrillary acidic protein. We observed a decrease in plasma Granzyme A, a marker of T cell and NK cell degranulation, which was specific to multiple sclerosis. Higher levels of plasma proteins involved in coagulation were associated with lower T2 lesion burden and preserved brain volume.InterpretationWe report the largest plasma proteomic screen of multiple sclerosis, replicating important known associations and suggesting novel markers, such as the reduction in granzyme A. While these findings require external validation, they demonstrate the power of biobank‐scale datasets for discovering new biomarkers for multiple sclerosis.

Funder

Medical Research Council

Publisher

Wiley

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