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利用多组学见解变革心脏移植护理。

Transforming heart transplantation care with multi-omics insights.

作者信息

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

机构信息

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.

出版信息

J Transl Med. 2025 Jul 1;23(1):710. doi: 10.1186/s12967-025-06772-0.

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.

摘要

心脏移植(HTx)仍然是终末期心脏病患者的确定性治疗方法。尽管全球每年进行的心脏移植数量持续增加,但心脏移植的并发症仍然影响生活质量和长期预后,包括排斥反应、感染和移植物功能障碍。心内膜心肌活检仍然是监测心脏移植后心脏移植物排斥反应的金标准,但其侵入性以及组织学分级中观察者间的误差使得开发新型非侵入性生物标志物以阐明排斥反应机制和进展成为必要。心脏移植物血管病变是长期预后的关键决定因素,通过血管内超声早期检测具有挑战性,这凸显了血浆生物标志物用于疾病监测的潜力。组学技术通常是指应用多种高通量筛选技术,能够在分子水平上对生物系统进行全面分析。多组学技术,包括基因组学(供体来源的游离DNA)、转录组学(微小RNA面板、基因表达谱)、蛋白质组学(细胞信号分子)和代谢组学(离体心脏灌注),在移植后监测中已显示出巨大的前景。这些方法为心脏移植物排斥反应、原发性移植物功能障碍和心脏移植物血管病变提供了个性化的风险分层和机制性见解。单细胞组学技术和机器学习算法进一步解决了细胞异质性问题并改进了预测模型,从而提高了多组学数据的临床可转化性。这篇综述综合了这些进展,并强调了将多组学与先进分析方法相结合以实现心脏移植精准监测和治疗的变革潜力,最终改善患者的长期预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d620/12211886/c23521744ace/12967_2025_6772_Fig1_HTML.jpg

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