Evidence map›Paper›PMID 42493655›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2026

Broad-coverage targeted lipidomics reveals stage-specific lipid metabolic profiles and diagnostic and prognostic marker panels in ischemic stroke.

Haoran Huang, Liu Liu, Can Zhao, Shuying Cheng, Wenxuan Li, Anbao Xu, Xiaoqin Yin, Xin Xu

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Article in Metabolomics : Official journal of the Metabolomic Society, 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Haoran Huang *Department of Pharmacy, Affiliated Hospital of Nantong University, Pharmacy School of Nantong University, Nantong, China.
Liu Liu *Department of Oncology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
Can Zhao *Department of Oncology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
Shuying ChengDepartment of Oncology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
Wenxuan LiDepartment of Oncology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
Anbao XuDepartment of Pharmacy, Affiliated Hospital of Nantong University, Pharmacy School of Nantong University, Nantong, China. jsntxab@163.com.
Xiaoqin YinDepartment of Pharmacy, Affiliated Hospital of Nantong University, Pharmacy School of Nantong University, Nantong, China. 2013783884@qq.com.
Xin XuDepartment of Pharmacy, Affiliated Hospital of Nantong University, Pharmacy School of Nantong University, Nantong, China. xiner_nt@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIschemic stroke (IS) is a major cause of mortality and disability globally, with challenges in early diagnosis and prognosis prediction. Dysregulated lipid metabolism is key to IS pathophysiology, but comprehensive profiling of lipid changes during disease progression remains limited.

methodsThis study enrolled 223 IS patients and 57 healthy controls. Plasma lipid profiles were analyzed using broad-coverage targeted lipidomics by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Differential lipids were identified through orthogonal partial least squares discriminant analysis (OPLS-DA) with univariate analysis, and their changes across acute, subacute, convalescent, and chronic phases were examined by clustering analysis. Machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) regression and support vector machine (SVM), were used to screen diagnostic and prognostic biomarkers, followed by logistic regression models and receiver operating characteristic (ROC) curve evaluation.

resultsFrom 607 identified lipids, 54 showed differential abundance between IS patients and healthy controls, grouped into four clusters. For diagnosis, six lipids-LPG(18:0), PE(O-16:0/18:2), TG(52:2/FA16:0), PE(O-16:0/22:6), PE(O-16:0/20:3), and PE(O-18:0/18:2)- achieved an area under the curve (AUC) of 0.984. For prognosis, six lipids-PE(O-16:0/22:5), PE(O-18:0/22:5), SM(d18:1/14:0), PG(18:0/18:1), PE(O-16:0/20:3), and LPI(16:0)-achieved an AUC of 0.925.

conclusionThis study characterizes lipid metabolism changes across IS stages reconstructed from cross-sectional data of different patient groups and establishes two six-lipid panels for diagnosis and prognosis. These findings provide insights into lipid metabolism evolution following stroke and offer candidate biomarker panels for IS management.

Indexed as

Ischemic StrokeLipidomicsLipidsAgedBiomarkersBrain IschemiaFemaleHumansLipid MetabolismLiquid Chromatography-Mass SpectrometryMaleMiddle AgedPrognosisROC CurveTandem Mass SpectrometryBiomarkersLipidsBiomarkersDiagnosisIschemic strokeLipidomicsMachine learningPrognosis

Identifiers

PMID42493655
PMCPMC13395834

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.