Evidence map›Paper›PMID 42388799›Full record

ArticlebioRxiv : the preprint server for biology2026

Evaluation of potential serum biomarkers for individuals at risk of multiple sclerosis.

Kristin Mounts, YunDuo Liu, Masashi Fujita, Juliana Oyegunle, Tradite Neziraj, Susan V Pollak, Renu Nandakumar, Nyater Ngouth, Sonya U Steele, Irene Cortese and 4 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 · Who and what money

Authors and funding

14 authors.

Kristin MountsCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0009-0002-2775-5932
YunDuo LiuCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
Masashi FujitaCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0002-1457-6233
Juliana OyegunleCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
Tradite NezirajCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0001-8428-604X
Susan V PollakBiomarker Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY, United States.
Renu NandakumarBiomarker Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY, United States.ORCID 0009-0009-9273-504X
Nyater NgouthNeuroimmunology Branch, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0002-5994-3535
Sonya U SteeleNeuroimmunology Branch, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0002-6536-4513
Irene CorteseNeuroimmunology Branch, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0001-9631-7181
Charles C WhiteCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0001-9702-4516
Steven JacobsonNeuroimmunology Branch, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0003-3127-1287
Daniel S ReichNeuroimmunology Branch, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0002-2628-4334
Philip L De JagerCenter for Translational & Computational Neuroimmunology, Division of Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0002-8057-2505

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Medical Scientist Training ProgramT32GM145440 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STEVEN L REINER · 2022 to 2026
$7.3M
NCATS NIH HHS UL1 TR001873NIGMS NIH HHS T32 GM145440
6 · The paper itself

Abstract

Circulating proteins have been widely investigated as potential biomarkers in multiple sclerosis (MS), yet findings across studies are often inconsistent, likely reflecting differences in disease stage, treatment exposure, and cohort composition. Studying individuals at elevated risk of MS prior to disease onset offers a unique opportunity to identify immune alterations that precede clinical disease while minimizing confounders. Here, we investigated whether alterations in six previously MS-associated biomarkers are detectable and associate to underlying genetic susceptibility in two independent sample collections comprising people with MS (pwMS), healthy controls, and asymptomatic first-degree relatives of pwMS from the Genes & Environment in MS (GEMS) study cohort. The panel, representing complementary axes of MS immunopathology, included granzyme A (GZMA), MER tyrosine kinase (MERTK), interleukin-2 receptor alpha (IL2RA), osteopontin (SPP1), CD30 (TNFRSF8), and chitinase-3-like protein 1 (CHI3L1). None of the proteins demonstrated associations with MS. A composite score constructed from externally derived effect estimates was not associated with MS status in either collection or in meta-analysis. Among asymptomatic first-degree relatives, the composite score was not significantly associated with group status. In contrast, an inverse correlation between SPP1 and the MS genetic risk score among GEMS participants was found (β = -0.246, p = 0.001). Together, these findings suggest that several circulating proteins recently proposed as MS biomarkers are not robust tools to distinguish MS from healthy individuals. However, SPP1 levels are highlighted for further evaluation among at-risk individuals, and further work is needed to determine whether circulating immune signatures can capture the earliest stages of MS in at-risk individuals.

Identifiers

PMID42388799
PMCPMC13317616

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.