Evidence map›Paper›PMID 40693926›Full record

ReviewPsychiatry and clinical neurosciences2025

Autoantibodies and Inflammation in Schizophrenia.

Hiroki Shiwaku

Abstract readReview
In one paragraph

Review in Psychiatry and clinical neurosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  7. Review
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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

1 author.

Hiroki ShiwakuDepartment of Psychiatry and Behavioral Sciences, Institute of Science Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-7503-8044

Funding

Fusion Oriented REsearch for disruptive Science and Technology JPMJFR231UJapan Agency for Medical Research and Development JP22wm0525036Japan Agency for Medical Research and Development JP24wm0625312
6 · The paper itself

Abstract

The potential role of autoantibodies in the etiology of schizophrenia is a key research focus because growing evidence suggests an association between immune dysfunction and psychotic disorders. This hypothesis is supported by findings indicating immune-related abnormalities in patients with schizophrenia, including chronic inflammation and genetic alterations associated with immune system dysregulation. Epidemiological studies have reinforced this perspective by demonstrating a significant correlation between autoimmune diseases and schizophrenia, suggesting shared pathological mechanisms including autoantibodies. A particularly compelling line of evidence comes from the identification of autoantibodies targeting synaptic molecules in patients with schizophrenia. Autoantibodies against N-methyl-D-aspartate (NMDA) receptors, gamma-aminobutyric acid (GABA) receptors, neural cell adhesion molecule 1 (NCAM1), and neurexin 1 (NRXN1) have been detected in patients, raising the possibility that immune-mediated synaptic dysfunction contributes to the disorder's pathophysiology. Experimental studies support this notion because the administration of these autoantibodies in mice induces molecular, cellular, and behavioral abnormalities that mirror aspects of schizophrenia. This review summarizes the relationships among schizophrenia, inflammation, immune-related genetic factors, autoimmune diseases, and autoantibodies. Furthermore, this review discusses future research directions for further elucidating the role of autoantibodies in schizophrenia.

Indexed as

AutoantibodiesInflammationSchizophreniaAnimalsAutoimmune DiseasesHumansReceptors, N-Methyl-D-AspartateAutoantibodiesReceptors, N-Methyl-D-Aspartateautoantibodiesautoimmunityinflammationschizophrenia

Identifiers

PMID40693926
PMCPMC12498127

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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.