Evidence map›Paper›PMID 42613604›Full record

ArticleBMC endocrine disorders2026

Differential analysis of gut microbiota and metabolites in patients with Graves' disease and combined Helicobacter pylori infection.

Suna Yang, Xinyue Chang, Baokun Peng, Yunhong Wei, Yipeng Wang

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Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Suna Yang *Department of Endocrinology, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, 650051, China.
Xinyue Chang *Department of Endocrinology, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, 650051, China.
Baokun PengDepartment of Endocrinology, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, 650051, China.
Yunhong WeiDepartment of General Practice, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, 650051, China. 66560309@qq.com.
Yipeng WangDepartment of Endocrinology, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, 650051, China. wypwyp2008@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGraves' disease (GD) is one of the most common organ-specific autoimmune disorders. Current evidence indicates that GD pathogenesis results from complex gene-environment interactions, although the precise mechanisms remain incompletely elucidated. This study aims to investigate effects of environmental factors such as gut microbiota and Helicobacter pylori (H. pylori) infection on the pathogenesis of GD.

methodsThis study enrolled 88 treatment-naïve GD patients and 33 healthy controls. Plasma H.pylori-IgG levels were measured using enzyme-linked immunosorbent assay (ELISA). Varieties of gut microbiota in fecal specimens were examined using 16S rDNA sequencing. Gut metabolites were subjected to untargeted metabolomic analysis using liquid chromatography-mass spectrometry (LC-MS). Differences in gut microbiota composition and metabolites were analyzed between the GD group and the control group, as well as between the H. pylori-positive[H. pylori (+)] subgroup and the H. pylori-negative[H. pylori (-)] subgroup within the GD group.

resultsBacteroidota, f-Lactobacillaceae, and Prevotella-9 demonstrated significantly higher prevalence in the GD group compared to the control group. Clostridium_sensu_stricto_1 and Limosilactobacillus exhibited significantly greater abundance in the GD + H. pylori (+) subgroup compared to the GD + H. pylori (-) subgroup. Compared to the control group, in the GD group pregnanetriol, kynurenic acid, and several metabolites in the tryptophan metabolism pathway (serotonin, kynurenate, xanthurenate, and 3-Methyldioxyindole) increased significantly, while mulberrofuran T and fragransol B decreased. Significantly reduced levels of N-methyltyramine, N-isovalerylglycine, and cafestol were observed in the GD + H. pylori (+) subgroup relative to the GD + H. pylori (-) subgroup.

conclusionSignificant differences were identified in both gut microbiota composition and metabolites between the GD group and the control group. Alterations in the gut microbiota are potentially linked to GD pathogenesis via modulation of tryptophan metabolic pathway. Significant differences in both gut microbiota composition and metabolites were identified between the H. pylori (+) subgroup and the H. pylori (-) subgroup within the GD group.

Indexed as

Gastrointestinal MicrobiomeGraves DiseaseHelicobacter InfectionsHelicobacter pyloriAdultBiomarkersCase-Control StudiesFecesFemaleFollow-Up StudiesHumansMaleMetabolomicsMiddle AgedPrognosisRNA, Ribosomal, 16SBiomarkersRNA, Ribosomal, 16S16S rDNA gene sequencingGraves’ diseaseGut microbiotaHelicobacter pyloriMetabolomics

Identifiers

PMID42613604
PMCPMC13483712

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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.