A Predictive Autoantibody Signature in Multiple Sclerosis Article Swipe
Colin R. Zamecnik
,
Gavin M. Sowa
,
Ahmed Abdelhak
,
Ravi Dandekar
,
Rebecca Bair
,
Kristen J. Wade
,
Christopher M. Bartley
,
Asritha Tubati
,
Refujia Gomez
,
Camille Fouassier
,
Chloe Gerungan
,
Jessica Alexander
,
Anne E. Wapniarski
,
Rita P. Loudermilk
,
Erica Eggers
,
Kelsey C. Zorn
,
Kirtana Ananth
,
Nora Jabassini
,
Sabrina A Mann
,
Nicholas R. Ragan
,
Adam Santaniello
,
Roland G. Henry
,
Sergio E. Baranzini
,
Scott S. Zamvil
,
Riley Bove
,
Chu‐Yueh Guo
,
Jeffrey M. Gelfand
,
Richard Cuneo
,
H.-Christian von Büdingen
,
Jorge R. Oksenberg
,
Bruce Cree
,
Jill A. Hollenbach
,
Ari Green
,
Stephen L. Hauser
,
Mitchell T. Wallin
,
Joseph L. DeRisi
,
Michael R. Wilson
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.05.01.23288943
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.05.01.23288943
Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. Here, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster of PwMS that share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active prodromal period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid (CSF) and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically- or radiologically-isolated neuroinflammatory syndromes.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.05.01.23288943
- https://www.medrxiv.org/content/medrxiv/early/2023/05/15/2023.05.01.23288943.full.pdf
- OA Status
- green
- Cited By
- 7
- References
- 66
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1101/2023.05.01.23288943Digital Object Identifier
- Title
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A Predictive Autoantibody Signature in Multiple SclerosisWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-02Full publication date if available
- Authors
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Colin R. Zamecnik, Gavin M. Sowa, Ahmed Abdelhak, Ravi Dandekar, Rebecca Bair, Kristen J. Wade, Christopher M. Bartley, Asritha Tubati, Refujia Gomez, Camille Fouassier, Chloe Gerungan, Jessica Alexander, Anne E. Wapniarski, Rita P. Loudermilk, Erica Eggers, Kelsey C. Zorn, Kirtana Ananth, Nora Jabassini, Sabrina A Mann, Nicholas R. Ragan, Adam Santaniello, Roland G. Henry, Sergio E. Baranzini, Scott S. Zamvil, Riley Bove, Chu‐Yueh Guo, Jeffrey M. Gelfand, Richard Cuneo, H.-Christian von Büdingen, Jorge R. Oksenberg, Bruce Cree, Jill A. Hollenbach, Ari Green, Stephen L. Hauser, Mitchell T. Wallin, Joseph L. DeRisi, Michael R. WilsonList of authors in order
- Landing page
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https://doi.org/10.1101/2023.05.01.23288943Publisher landing page
- PDF URL
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https://www.medrxiv.org/content/medrxiv/early/2023/05/15/2023.05.01.23288943.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2023/05/15/2023.05.01.23288943.full.pdfDirect OA link when available
- Concepts
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Autoantibody, Multiple sclerosis, Medicine, Cohort, Immunology, Biomarker, Antibody, Proteome, Cerebrospinal fluid, Internal medicine, Bioinformatics, Biology, BiochemistryTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2024: 4, 2023: 3Per-year citation counts (last 5 years)
- References (count)
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66Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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