Evidence map›Paper›PMID 39295986›Full record

ArticleHeliyon2024

Peptidomic profiling of endogenous peptides in the spleens of mouse models of Graves' disease.

Zhengrong Jiang, Lijun Chen, Huibin Huang

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

3 authors.

Zhengrong JiangDepartment of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
Lijun ChenDepartment of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
Huibin HuangDepartment of Endocrinology, Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Graves' disease (GD) is a common autoimmune thyroid disorder. The pathogenesis of GD involves an autoimmune response to the A subunit of the human thyrotropin receptor (hTSHR), although the specific mechanisms are not fully elucidated. Methods: This study established a GD model by immunizing BALB/c mice with a recombinant adenovirus expressing the hTSHR A subunit. Spleen tissues were collected and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed peptides (DEPs). Gene Ontology (GO) analysis and KEGG pathway analysis were further utilized to annotate the functions of these DEPs. Additionally, peptide bioactivity prediction and molecular docking studies were conducted using Alphafold and Pymol software, respectively, to assess the binding affinity of specific peptides to the hTSHR A subunit. Results: The GD mouse model was successfully established, and 1,428 DEPs were identified in the spleen, with 368 upregulated and 1,060 downregulated. Functional analysis indicated that these DEPs are mainly involved in cellular endocytosis, regulation of gene expression, and nucleocytoplasmic transport. Notably, molecular docking studies revealed that the abnormally highly expressed peptide HG2A-24aa demonstrated potential bioactivity and strong binding affinity with hTSHR-289aa. Conclusion: The specific bioactive peptides may play key roles in the pathogenesis of GD, particularly HG2A-24aa, which may have a significant role in the MHC II antigen presentation pathway mediated by the hTSHR A subunit.

Indexed as

Antigen presentationGraves' diseaseHuman thyrotropin receptor A subunitMolecular dockingPeptidomics

Identifiers

PMID39295986
PMCPMC11408014

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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.