Aix Marseille Univ, TAGC Theories and Approaches of Genomic Complexity, Institut MarMaRa, Marseille, France.
Laboratory of Immunology, Heart Institute Instituto do Coração(InCor), School of Medicine, University of São Paulo, São Paulo, Brazil.
Front Immunol. 2022 Sep 29;13:1020572. doi: 10.3389/fimmu.2022.1020572. eCollection 2022.
Chagas disease is a parasitic disease from South America, affecting around 7 million people worldwide. Decades after the infection, 30% of people develop chronic forms, including Chronic Chagas Cardiomyopathy (CCC), for which no treatment exists. Two stages characterized this form: the moderate form, characterized by a heart ejection fraction (EF) ≥ 0.4, and the severe form, associated to an EF < 0.4. We propose two sets of DNA methylation biomarkers which can predict in blood CCC occurrence, and CCC stage. This analysis, based on machine learning algorithms, makes predictions with more than 95% accuracy in a test cohort. Beyond their predictive capacity, these CpGs are located near genes involved in the immune response, the nervous system, ion transport or ATP synthesis, pathways known to be deregulated in CCCs. Among these genes, some are also differentially expressed in heart tissues. Interestingly, the CpGs of interest are tagged to genes mainly involved in nervous and ionic processes. Given the close link between methylation and gene expression, these lists of CpGs promise to be not only good biomarkers, but also good indicators of key elements in the development of this pathology.
克氏锥虫病是一种来自南美洲的寄生虫病,影响着全球约 700 万人。在感染几十年后,30%的人会发展出慢性形式,包括慢性克氏锥虫心肌病(CCC),目前尚无治疗方法。这种疾病有两个阶段:中度形式,特征为心脏射血分数(EF)≥0.4;严重形式,与 EF<0.4 相关。我们提出了两组 DNA 甲基化生物标志物,可预测血液中 CCC 的发生和 CCC 阶段。该分析基于机器学习算法,在测试队列中进行预测的准确率超过 95%。除了具有预测能力外,这些 CpG 位于涉及免疫反应、神经系统、离子转运或 ATP 合成的基因附近,这些途径在 CCC 中已知被失调。在这些基因中,一些在心脏组织中也有差异表达。有趣的是,感兴趣的 CpG 被标记为主要涉及神经和离子过程的基因。鉴于甲基化与基因表达之间的密切联系,这些 CpG 列表不仅有望成为良好的生物标志物,而且有望成为该病理学发展的关键因素的良好指标。