Evidence map›Paper›PMID 42812380›Full record

ArticleFrontiers in immunology2026

Discovery of plasma metabolomic biomarkers and a predictive model for immune checkpoint inhibitor-associated myocarditis: a pilot case-control study.

Zhuoling Zheng, Qingling Gu, Yiting Wang, Lihong Huang, Jingwen Xie, Chunmei Dai, Jiali Li, Xiaoyan Li

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Article in Frontiers in immunology, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Zhuoling Zheng *Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Qingling Gu *School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
Yiting Wang *Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Lihong HuangDepartment of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Jingwen XieDepartment of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Chunmei DaiDepartment of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Jiali LiSchool of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
Xiaoyan LiDepartment of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune checkpoint inhibitor (ICI)-associated myocarditis is a rare but potentially fatal immune-related adverse event lacking reliable biomarkers for risk stratification. This exploratory pilot case-control study aimed to characterize baseline plasma metabolomic profiles in patients who developed ICI-associated myocarditis and to evaluate a metabolite-based predictive model. Methods: Baseline plasma samples from 15 patients with ICI-associated myocarditis and 15 matched controls were analyzed by untargeted metabolomics using UHPLC-Q/Orbitrap HRMS. Differential metabolites were identified by OPLS-DA and univariate analysis. A metabolite-derived PC1 was used in logistic regression models (clinical-only, metabolite-only, combined), with performance assessed by AUC. Results: Ten differential metabolites were identified, implicating glutathione metabolism, phenylalanine metabolism, and histidine metabolism pathways. Key alterations included elevated phenylpyruvic acid, 1-methylpseudouridine, cinnamoylglycine, pyroglutamic acid and spermine, with decreased ceramide, cyclo-prolylglycine, propionic acid, glycolic acid, and histamine. A clinical model incorporating three baseline laboratory variables (lymphocyte ratio, monocyte ratio, and eosinophil ratio) achieved an AUC of 0.618. The metabolite PC1 model alone attained an AUC of 0.964, outperforming the clinical model. The combined clinical-metabolite model reached a fitted AUC of 0.973 (cross-validated AUC 0.925). Decision curve analysis indicated that the combined model provided potential net benefit within the 20%-40% threshold range, marginally exceeding the metabolite-only model. Conclusion: This exploratory study identified baseline plasma metabolites potentially associated with ICI-associated myocarditis risk, implicating oxidative stress, immune modulation, and gut microbiota-host interactions. The metabolite-based model showed preliminary discriminative ability, but prospective validation in independent cohorts is required.

Indexed as

BiomarkersImmune Checkpoint InhibitorsMetabolomeMetabolomicsMyocarditisAgedCase-Control StudiesFemaleHumansMaleMiddle AgedPilot ProjectsBiomarkersImmune Checkpoint Inhibitorsbiomarkersgut microbiotaimmune checkpoint inhibitorsmetabolomicsmyocarditisoxidative stress

Identifiers

PMID42812380
PMCPMC13619531

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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.