Evidence map›Paper›PMID 42171268›Full record

ArticleAnnals of neurology2026

Genetic-Proteomic Integration Identifies Predictive Plasma Proteins for Multiple Sclerosis.

Yuan Ding, Dylan Hamitouche, Simon Thebault, Patrick Kearns, Ahmed Abdelhak, Adil Harroud

Abstract read
In one paragraph

Article in Annals of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuan DingThe Neuro (Montreal Neurological Institute-Hospital), Montréal, Canada.ORCID https://orcid.org/0009-0002-6261-772X
Dylan HamitoucheThe Neuro (Montreal Neurological Institute-Hospital), Montréal, Canada.
Simon ThebaultThe Neuro (Montreal Neurological Institute-Hospital), Montréal, Canada.
Patrick KearnsAnne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK.
Ahmed AbdelhakDepartment of Neurology, University of California, San Francisco, San Francisco, CA.ORCID https://orcid.org/0000-0001-9731-4169
Adil HarroudThe Neuro (Montreal Neurological Institute-Hospital), Montréal, Canada.ORCID https://orcid.org/0000-0003-2616-7274

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMultiple sclerosis (MS) develops after a prolonged preclinical phase. Identifying circulating biomarkers that capture this early biology can improve risk stratification and guide intervention. We aimed to identify plasma proteins driving MS susceptibility using large-scale proteogenomic integration and to evaluate their prediagnostic predictive value and effects on severity.

methodsWe used cis-acting protein quantitative trait loci (pQTL) for 2,545 plasma proteins (n = 80,824). Predicted protein levels were tested for association with MS risk in 14,802 cases and 26,703 controls using Mendelian randomization and colocalization. Splicing annotations were integrated to interpret platform-specific discrepancies. We validated candidates as predictors of incident MS in prediagnostic United Kingdom Biobank samples (124 cases, 52,515 controls; median 5.9 years prediagnosis) and assessed associations with disease severity (n = 12,584).

resultsWe identified 39 proteins associated with MS risk. Most formed a densely connected network enriched in immune regulatory pathways, B- and T-cell costimulation, cytokine signaling, and Epstein-Barr virus-related pathways. Transcriptomic enrichment was strongest in B-cell subsets. Splicing data suggested that discordances between proteomic platforms reflect distinct proteoforms. Among 28 genetically implicated proteins measured in prediagnostic samples, 8 were associated with time to MS diagnosis, demonstrating enrichment beyond chance expectation (p

interpretationThis integrated genetic-proteomic framework identifies causal proteins, refines risk loci, and supports the development of early predictive biomarkers with translational potential. These findings support genetically anchored biomarkers for preclinical disease detection and intervention. ANN NEUROL 2026;100:268-281.

Indexed as

Blood ProteinsMultiple SclerosisProteomicsBiomarkersFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMalePredictive Value of TestsQuantitative Trait LociBiomarkersBlood Proteins

Identifiers

PMID42171268
PMCPMC13387974

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.