Evidence map›Paper›PMID 35711412›Full record

ReviewFrontiers in immunology2022

Immunopsychiatry - Innovative Technology to Characterize Disease Activity in Autoantibody-Associated Psychiatric Diseases.

Niels Hansen

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. 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
0.1field-weighted citation impact, top 66% of its field
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, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

1 author at 1 institution in 1 country.

Niels HansenDepartment of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany.
Universitätsmedizin Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Anti-neural autoantibody-associated psychiatric disease is a novel field in immunopsychiatry that has been attracting attention thanks to its potentially positive therapeutic outcome and distinct prognosis compared with non-organic psychiatric disease. This review aims to describe recent novel technological developments for improving diagnostics in the field of autoantibody-related psychiatric disease. Methods: We screened for relevant articles in PubMed for this narrative article. We focused on research methods such as neuroimaging, immune cells and inflammation markers, and molecular biomarkers in human biofluids like serum and cerebrospinal fluid and plasma proteomics. Results: We introduce several novel methods for investigating autoinflammation with the aim of optimizing therapies for autoantibody-associated psychiatric disease. We describe measuring the translocator protein 18kDa in activated microglia via positron emission tomography imaging, brain volumetric assessment, flow cell cytometry of cerebrospinal fluid and blood, and blood biological probes as well as psychopathological cues to help us gain insights into diagnosing inflammation and brain damage better in psychiatric patients presenting a suspected autoimmune etiology. Conclusion: Our short methodological review provides an overview of recent developments in the field of autoantibody-related immunopsychiatry. More research is needed to prove their usefulness in diagnosing and treating autoantibody-associated psychiatric disease and its subtypes.

Indexed as

AutoantibodiesMental DisordersBiomarkersHumansInflammationTechnologyAutoantibodiesBiomarkersanti-neural autoantibodyautoimmunityimmunopsychiatryinnovative technologymethods

Identifiers

PMID35711412
PMCPMC9197207
OpenAlexW4281288365

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.