Evidence map›Paper›PMID 40982233›Full record

ArticleHepatology communications2025

Identification of anti-DOK2 antibodies in patients with autoimmune hepatitis via a human protein microarray.

Kazumichi Abe, Jun Wada, Manabu Hayashi, Tatsuro Sugaya, Naoto Abe, Yosuke Takahata, Masashi Fujita, Atsushi Takahashi, Yukiko Kanno, Masahito Kuroda and 5 more

Abstract read
In one paragraph

Article in Hepatology communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Autoantibodies in the follow-up of autoimmune hepatitis.Journal of translational autoimmunity · 2026
    Review
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

15 authors.

Kazumichi AbeDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.ORCID 0000-0001-5359-9465
Jun WadaDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Manabu HayashiDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Tatsuro SugayaDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Naoto AbeDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Yosuke TakahataDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Masashi FujitaDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Atsushi TakahashiDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.
Yukiko KannoDepartment of Gastroenterology, Fukushima Red Cross Hospital, Fukushima, Japan.
Masahito KurodaDepartment of Gastroenterology, Fukushima Red Cross Hospital, Fukushima, Japan.
Keietsu SaitoDepartment of Internal Medicine, Hanawa Kosei Hospital, Higashishirakawa, Japan.
Yoshihiro NozawaDepartment of Pathology, Shirakawa Kousei General Hospital, Shirakawa, Japan.
Kiyoshi MigitaDepartment of Hepatology, National Hospital Organization Nagasaki Medical Center, Nagasaki, Japan.
Hiroshi YatsuhashiDepartment of Hepatology, National Hospital Organization Nagasaki Medical Center, Nagasaki, Japan.
Hiromasa OhiraDepartment of Gastroenterology, Fukushima Medical University School of Medicine, Fukushima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutoantibodies such as antinuclear antibodies (ANAs) and anti-smooth muscle antibodies (ASMAs), which are detected in many cases of autoimmune hepatitis (AIH), are not disease-specific; thus, they have limited value in disease diagnosis. In this study, we aimed to identify disease-specific autoantibodies related to AIH diagnosis or pathogenesis.

methodsWe analyzed human protein microarrays (containing more than 16,000 human proteins, including membrane, cytoplasmic, and nuclear proteins, synthesized in a wheat germ cell-free system using cDNA). To identify AIH-specific autoantibodies, we performed a cross-sectional study of AIH patients (n=67) and matched healthy controls (HCs) (n=25) via ELISA. An independent cohort of 123 AIH patients and 75 HCs was analyzed for validation. All patient data were collected before corticosteroid therapy. We also evaluated the associations between candidate protein antigen expression and clinical findings in AIH patients. Candidate protein antigen expression in liver tissues was confirmed by immunohistochemistry.

resultsAccording to comprehensive human protein microarray analysis, docking protein 2 (DOK2) was selected from 6 antigens upregulated in AIH patients. The mean anti-DOK2 level was significantly greater in AIH patients (36.1-37.4 AU) than in those with other liver diseases (2.6-9.2) or HCs (1.0-4.5 AU) in the exploration and validation cohorts (p value/AUROC, vs. HCs, <0.0001/0.87-0.90). Serum anti-DOK2 levels were positively correlated with serum IgG levels and liver histological activity. The serum IgG level was an independent predictor of increased anti-DOK2 antibody levels in patients with AIH. Immunostaining revealed that DOK2-positive cells were present in the hepatic lobules and portal tracts of patients with AIH.

conclusionsWe provide the first evidence that serum anti-DOK2 antibody levels are associated with the diagnosis and disease activity of AIH patients.

Indexed as

Adaptor Proteins, Signal TransducingAutoantibodiesHepatitis, AutoimmuneAdultCase-Control StudiesCross-Sectional StudiesFemaleHumansLiverMaleMiddle AgedProtein Array AnalysisYoung AdultAdaptor Proteins, Signal TransducingAutoantibodiesautoantibodyautoimmune hepatitisdocking protein 2human protein microarraymacrophage

Identifiers

PMID40982233
PMCPMC12456515

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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.