Evidence map›Paper›PMID 42155846›Full record

ReviewJournal of immunological methods2026

Novel methods for neural IgG characterization and validation in autoimmune neurologic disorders.

Michael Gilligan, Andrew McKeon

Abstract readReview
In one paragraph

Review in Journal of immunological methods, 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

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

2 authors.

Michael GilliganDepartments of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Department of Neurology, St Vincent's University Hospital, Dublin, Ireland. Electronic address: gilligan.michael@mayo.edu.
Andrew McKeonDepartments of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA.

Funding

A Phase-2b, Double-Blind, Randomized Controlled Trial to Evaluate the Activity and Safety of Inebilizumab in Anti-N-methyl-D-aspartate receptor (NMDAR) Encephalitis and Assess Markers of DiseaseU01NS120901 · NINDS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Stacey Lynn Clardy · 2021 to 2026
$19.6M
Seronegative Autoimmune Encephalopathies: Biomarker Discovery, Validation & Deep PhenotypingR01NS126227 · NINDS · MAYO CLINIC ROCHESTER · PI Andrew McKeon · 2022 to 2026
$1.9M
NINDS NIH HHS R01 NS126227NINDS NIH HHS U01 NS120901Wellcome Trust
6 · The paper itself

Abstract

Neural autoantibody testing is standard for patients with suspected autoimmune neurologic disorders. The number of neural antibodies has increased dramatically in the past 40 years, with over 50 disease-specific neural antibodies defined to date. The advent of immune-profiling assays such as protein array and phage immunoprecipitation sequencing (PhIP-Seq) has further expedited the rate of antibody discovery, with many recent targets identified using these methods. In this review, we discuss traditional and novel methods of antibody discovery, with an emphasis on the incorporation of protein array and PhIP-Seq into our antibody discovery approach. Advantages, limitations, and potential future uses of these platforms within the field of autoimmune neurology are also considered.

Indexed as

AutoantibodiesAutoimmune DiseasesAutoimmune Diseases of the Nervous SystemImmunoglobulin GProtein Array AnalysisAnimalsHumansImmunoprecipitationAutoantibodiesImmunoglobulin GImmune-profiling assayNeural antibodySeronegativeUnclassified antibody

Identifiers

PMID42155846
PMCPMC13333153

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.