Serviço de Cardiologia e Cirurgia Cardiovascular e Centro de Telessaúde do Hospital das Clínicas da UFMG, Belo Horizonte, MG, Brazil; Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Serviço de Cardiologia e Cirurgia Cardiovascular e Centro de Telessaúde do Hospital das Clínicas da UFMG, Belo Horizonte, MG, Brazil; Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Cytokine. 2021 Feb;138:155370. doi: 10.1016/j.cyto.2020.155370. Epub 2020 Dec 19.
Inflammation associated with rheumatic heart disease (RHD) is influenced by gene polymorphisms and inflammatory cytokines. There are currently no immunologic and genetic markers to discriminate latent versus clinical patients, critical to predict disease evolution. Employing machine-learning, we searched for predictors that could discriminate latent versus clinical RHD, and eventually identify latent patients that may progress to clinical disease.
A total of 212 individuals were included, 77 with latent, 100 with clinical RHD, and 35 healthy controls. Circulating levels of 27 soluble factors were evaluated using Bio-Plex ProTM® Human Cytokine Standard 27-plex assay. Gene polymorphism analyses were performed using RT-PCR for the following genes: IL2, IL4, IL6, IL10, IL17A, TNF and IL23.
Serum levels of all cytokines were higher in clinical as compared to latent RHD patients, and in those groups than in controls. IL-4, IL-8, IL-1RA, IL-9, CCL5 and PDGF emerged in the final multivariate model as predictive factors for clinical, compared with latent RHD. IL-4, IL-8 and IL1RA had the greater power to predict clinical RHD. In univariate analysis, polymorphisms in IL2 and IL4 were associated with clinical RHD and in the logistic analysis, IL6 (GG + CG), IL10 (CT + TT), IL2 (CA + AA) and IL4 (CC) genotypes were associated with RHD.
Despite higher levels of all cytokines in clinical RHD patients, IL-4, IL-8 and IL-1RA were the best predictors of clinical disease. An association of polymorphisms in IL2, IL4, IL6 and IL10 genes and clinical RHD was observed. Gene polymorphism and phenotypic expression of IL-4 accurately discriminate latent versus clinical RHD, potentially instructing clinical management.
风湿性心脏病（RHD）相关炎症受基因多态性和炎症细胞因子的影响。目前尚无免疫和遗传标志物来区分潜伏性和临床患者，这对于预测疾病进展至关重要。我们采用机器学习方法，寻找能够区分潜伏性和临床 RHD 的预测因子，并最终确定可能发展为临床疾病的潜伏患者。
共纳入 212 名个体，其中 77 名潜伏性 RHD 患者，100 名临床 RHD 患者，35 名健康对照者。采用 Bio-Plex ProTM® Human Cytokine Standard 27-plex assay 评估 27 种可溶性因子的循环水平。采用 RT-PCR 对以下基因进行基因多态性分析：IL2、IL4、IL6、IL10、IL17A、TNF 和 IL23。
与潜伏性 RHD 患者相比，临床 RHD 患者的血清细胞因子水平均升高，且高于对照组。与潜伏性 RHD 相比，IL-4、IL-8、IL-1RA、IL-9、CCL5 和 PDGF 是预测临床 RHD 的最终多变量模型中的预测因子。IL-4、IL-8 和 IL1RA 对预测临床 RHD 具有更大的作用。在单变量分析中，IL2 和 IL4 的多态性与临床 RHD 相关，在逻辑分析中，IL6（GG+CG）、IL10（CT+TT）、IL2（CA+AA）和 IL4（CC）基因型与 RHD 相关。
尽管临床 RHD 患者的所有细胞因子水平均较高，但 IL-4、IL-8 和 IL-1RA 是临床疾病的最佳预测因子。观察到 IL2、IL4、IL6 和 IL10 基因的多态性与临床 RHD 相关。IL-4 基因多态性和表型表达可准确区分潜伏性和临床 RHD，可能为临床管理提供指导。
