Evidence map›Paper›PMID 40598485›Full record

ReviewJournal of translational medicine2025

Transforming heart transplantation care with multi-omics insights.

Zhengbang Zou, Jianing Han, Zhiyuan Zhu, Shanshan Zheng, Xinhe Xu, Sheng Liu

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Recent advances in biomarkers for cardiac fibrosis.Frontiers in cardiovascular medicine · 2026
    Review
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

6 authors.

Zhengbang Zou *National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Jianing Han *National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Zhiyuan Zhu *National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Shanshan ZhengNational Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Xinhe XuNational Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.
Sheng LiuNational Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China. liusheng@fuwai.com.ORCID 0000-0001-8929-7178

Funding

Medical Foundation of China zgyxjjh-wcwk-2023110801
6 · The paper itself

Abstract

Heart transplantation (HTx) remains the definitive treatment for patients with end-stage heart disease. Despite the number of HTx performed annually in worldwide continues to increase, complications of HTx still impact the quality of life and long-term prognosis, including rejection, infection, and allograft dysfunction. Endomyocardial biopsy remains the gold standard for monitoring cardiac allograft rejection post-heart transplantation, yet its invasiveness and interobserver error in histologic grading necessitate the development of novel noninvasive biomarkers to elucidate rejection mechanisms and progression. Cardiac allograft vasculopathy, a critical determinant of long-term outcomes, is challenging to detect early via intravascular ultrasound, underscoring the potential of plasma biomarkers for disease surveillance. Omic technologies usually refers to the application of multiple high-throughput screening technologies enabling comprehensive analysis of biological systems at a molecular level. Multi-omics technologies, including genomics(donor-derived cell-free DNA), transcriptomics(microRNAs panels, gene expression profiling), proteomics(cell signaling molecule), and metabolomics(ex situ heart perfusion), have demonstrated significant promise in post-transplant monitoring. These approaches provide personalized risk stratification and mechanical insights into cardiac allograft rejection, primary graft dysfunction, and cardiac allograft vasculopathy. Single-cell omics technologies and machine learning algorithms further resolve cellular heterogeneity and improve predictive modeling, thereby enhancing the clinical translatability of multi-omics data. This comprehensive review synthesizes these advances and highlights the transformative potential of integrating multi-omics with advanced analytics to achieve precision monitoring and therapy in HTx, ultimately improving long-term patient outcomes.

Indexed as

GenomicsHeart TransplantationMetabolomicsBiomarkersGraft RejectionHumansMultiomicsProteomicsBiomarkersBiomarkersCell-free DNAGene expression profilingHeart transplantationMachine learningMicroRNAsMulti-omics

Identifiers

PMID40598485
PMCPMC12211886

What OpenQuestion holds

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Registered trials

None linked

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.