Evidence map›Paper›PMID 41080544›Full record

ArticleFrontiers in immunology2025

The study of the relationship between food additives and the childhood asthma based on metabolome analysis.

Mingcong Chen, Xinfeng Xu, Xinyao Jiang, Jinyan Hui, Xuna Tao, Yuling Bao, Shuyuan Cao, Qian Wu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Mingcong Chen *Department of Physical and Chemical Inspection and Nanjing Municipal Key Laboratory for Public Health Laboratory Technology, Nanjing Municipal Center for Disease Control and Prevention of Nanjing Medical University, Nanjing, Jiangsu, China.
Xinfeng Xu *China International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Xinyao JiangChina International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Jinyan HuiChina International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Xuna TaoChina International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Yuling BaoDepartment of Respiratory, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Shuyuan CaoChina International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Qian WuChina International Cooperation Center (CCC) for Environment and Human Health and Department of Health Inspection and Quarantine, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidemiological evidence suggests health risks arise from intake of food additives. This study aims to investigate the mechanisms linking food additives to childhood asthma through a metabolomics strategy. Methods: A total of 120 children with asthma and 120 control subjects were recruited. Serum concentrations of ten food additives - including cyclamate, neotame, aspartame, sodium saccharin, acesulfame, sucralose, benzoic acid, dehydroacetic acid, sunset yellow, and ponceau 4R - were quantified using UPLC-MS/MS. The associations between food additives and asthma were evaluated by logistic regression and chi-square tests. Serum metabolic profiling was performed by UPLC-MS. Identified asthma-associated metabolites were subsequently analyzed for pathway enrichment and mediation effects. In murine studies, acesulfame, sodium saccharin, sodium benzoate, or their mixtures were co-administered with OVA to C57BL/6 mice. Airway inflammation, IgE, IL-4, IL-17A, immune cell differentiation, and CD4 Results: The detection rates for dehydroacetic acid, benzoic acid and sodium cyclamate exceeded 60%. Benzoic acid, dehydroacetic acid and acesulfame were significantly associated with asthma. Mediation analysis identified fourteen metabolites as mediators in the relationship between benzoic acid and dehydroacetic acid, and childhood asthma, including PC(14:0/14:0), LysoPC(17:0), glycerophosphocholine, PC(18:1(9Z)e/2:0), PE(18:2(9Z,12Z)/14:0), glutamic acid, glutamine, GlcCer(d18:1/16:0), sphingosine, sphingosine-1-phosphate, spermine, spermidine, histidine, and acetylcholine. These metabolites were enriched in glycerophospholipid metabolism, β-alanine metabolism, glutathione metabolism, sphingolipid metabolism, arginine and proline metabolism, arginine biosynthesis, and histidine metabolism pathways. In murine models, food additives significantly exacerbated lung tissue inflammation and elevated levels of IgE, IL-4, and IL-17A in both BALF and serum, and also increased eosinophil percentages in BALF. Furthermore, flow cytometry showed significant alterations in Th1/Th2, Th17/Treg and allergic DC/tolerogenic DC balance within the mesenteric lymph node (MLN) and the lung tissue. Metabolomic profiling of CD4 Conclusion: Food additives may aggravate asthma by metabolically dysregulating the homeostasis of helper T-cells and antigen-presenting cells, thereby disrupting immune tolerance.

Indexed as

AsthmaFood AdditivesMetabolomeAnimalsBiomarkersChildChild, PreschoolDisease Models, AnimalFemaleHumansMaleMetabolomicsMiceMice, Inbred C57BLBiomarkersFood Additivesantigen-presenting cellschildhood asthmadendritic cellsfood additiveshelper T cellsmetabolism

Identifiers

PMID41080544
PMCPMC12510829

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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.