Evidence map›Paper›PMID 39363385›Full record

ArticleClinical epigenetics2024

Epigenomic biomarkers insights in PBMCs for prognostic assessment of ECMO-treated cardiogenic shock patients.

Yi-Jing Hsiao, Su-Chien Chiang, Chih-Hsien Wang, Nai-Hsin Chi, Hsi-Yu Yu, Tsai-Hsia Hong, Hsuan-Yu Chen, Chien-Yu Lin, Shuenn-Wen Kuo, Kang-Yi Su and 7 more

Abstract read
In one paragraph

Article in Clinical epigenetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

17 authors.

Yi-Jing HsiaoDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Su-Chien ChiangCenter for Institutional Research and Data Analytics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Chih-Hsien Wang *Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Nai-Hsin ChiDepartment of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Hsi-Yu YuDepartment of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Tsai-Hsia HongCenters of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
Hsuan-Yu ChenInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Chien-Yu LinInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Shuenn-Wen KuoDepartment of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Kang-Yi SuDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Wen-Je KoDepartment of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Li-Ming HsuDepartment of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Chih-An LinDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Chiou-Ling ChengDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Yan-Ming ChenDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Yih-Sharng Chen *Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Sung-Liang YuDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan. slyu@ntu.edu.tw.

Funding

Ministry of Science and Technology, Taiwan MOST 102-2325-B-002-078Ministry of Science and Technology, Taiwan MOST 109-2314-B-002-218Ministry of Science and Technology, Taiwan, MOST 103-2325-B-002-026National Science and Technology Council NSC 100-2314-B-002-018-MY2National Science and Technology Council (NSTC), Taiwan. NSC 102-2325-B-002-009
6 · The paper itself

Abstract

objectiveAs the global use of extracorporeal membrane oxygenation (ECMO) treatment increases, survival rates have not correspondingly improved, emphasizing the need for refined patient selection to optimize resource allocation. Currently, prognostic markers at the molecular level are limited.

methodsThirty-four cardiogenic shock (CS) patients were prospectively enrolled, and peripheral blood mononuclear cells (PBMCs) were collected at the initiation of ECMO (t0), two-hour post-installation (t2), and upon removal of ECMO (tr). The PBMCs were analyzed by comprehensive epigenomic assays. Using the Wilcoxon signed-rank test and least absolute shrinkage and selection operator (LASSO) regression, 485,577 DNA methylation features were analyzed and selected from the t0 and tr datasets. A random forest classifier was developed using the t0 dataset and evaluated on the t2 dataset. Two models based on DNA methylation features were constructed and assessed using receiver operating characteristic (ROC) curves and Kaplan-Meier survival analyses.

resultsThe ten-feature and four-feature models for predicting in-hospital mortality attained area under the curve (AUC) values of 0.78 and 0.72, respectively, with LASSO alpha values of 0.2 and 0.25. In contrast, clinical evaluation systems, including ICU scoring systems and the survival after venoarterial ECMO (SAVE) score, did not achieve statistical significance. Moreover, our models showed significant associations with in-hospital survival (p < 0.05, log-rank test).

conclusionsThis study identifies DNA methylation features in PBMCs as potent prognostic markers for ECMO-treated CS patients. Demonstrating significant predictive accuracy for in-hospital mortality, these markers offer a substantial advancement in patient stratification and might improve treatment outcomes.

Indexed as

DNA MethylationExtracorporeal Membrane OxygenationLeukocytes, MononuclearShock, CardiogenicAdultAgedBiomarkersEpigenesis, GeneticEpigenomicsFemaleHospital MortalityHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisBiomarkersECMOEpigenomePrognostic biomarker

Identifiers

PMID39363385
PMCPMC11451087

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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.