Evidence map›Paper›PMID 41085620›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Identification of Antibody-Cognate Antigens via a High-Throughput, Affinity Chromatography-Based, Shotgun Immunoproteomics Pipeline.

Nicholas A Shortreed, Kiran K Mangalaparthi, Benjamin J Madden, Akhilesh Pandey, Leigh G Griffiths

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Nicholas A ShortreedMayo Clinic Graduate School of Biomedical Sciences & Department of Immunology, Mayo Clinic, Rochester, MN, USA.
Kiran K MangalaparthiDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Benjamin J MaddenOCSS Proteomics Core, Mayo Clinic, Rochester, MN, USA.
Akhilesh PandeyDepartment of Laboratory Medicine and Pathology & Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Leigh G GriffithsDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA. griffiths.leigh@mayo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since they were first described in the late nineteenth century, antibodies have become widely recognized as being able to serve mechanistic functions in both "protective," as well as "pathogenic" adaptive immune responses. Due to their critical roles in a wide range of disease states, there has been significant interest in the fields of immunology and medicine in identifying individual antibody-cognate antigens. However, numerous technical and logistical challenges associated with older cognate antigen identification strategies limited their widespread utilization in these fields. To meet this critical need, we recently developed an optimized, high-throughput, affinity chromatography-based, shotgun immunoproteomics pipeline which we have previously demonstrated resolves many of the identified weaknesses of past methodologies. This chapter provides a comprehensive protocol for each step of this shotgun immunoproteomics pipeline, from input protein sample preparation through data analysis and antigen identification. This high-throughput methodology for antibody-cognate antigen identification is both a user-friendly and cost-effective procedure which could potentially facilitate novel discoveries in basic, translational, and clinical research settings.

Indexed as

AntibodiesAntigensChromatography, AffinityHigh-Throughput Screening AssaysProteomicsAnimalsHumansAntibodiesAntigensAdaptive immune responseAffinity chromatographyAntibodiesAntigen identificationCognate antigensHumoralImmunoproteomics

Identifiers

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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.