Laboratorio di Patologia Vascolare, Istituto Dermopatico dell'Immacolata IRCCS, Rome.
Physiol Genomics. 2009 Aug 7;38(3):233-40. doi: 10.1152/physiolgenomics.90364.2008. Epub 2009 Mar 31.
The present study was aimed at identifying chronic heart failure (CHF) biomarkers from peripheral blood mononuclear cells (PBMCs) in patients with ischemic (ICM) and nonischemic dilated (NIDCM) cardiomyopathy. PBMC gene expression profiling was performed by Affymetrix in two patient groups, 1) ICM (n = 12) and 2) NIDCM (n = 12) New York Heart Association (NYHA) III/IV CHF patients, vs. 3) age- and sex-matched control subjects (n = 12). Extracted RNAs were then pooled and hybridized to a total of 11 microarrays. Gene ontology (GO) analysis separated gene profiling into functional classes. Prediction analysis of microarrays (PAM) and significance analysis of microarrays (SAM) were utilized in order to identify a molecular signature. Candidate markers were validated by quantitative real-time polymerase chain reaction. We identified a gene expression profiling that distinguished between CHF patients and control subjects. Interestingly, among the set of genes constituting the signature, chemokine receptor (CCR2, CX(3)CR1) and early growth response (EGR1, 2, 3) family members were found to be upregulated in CHF patients vs. control subjects and to be part of a gene network. Such findings were strengthened by the analysis of an additional 26 CHF patients (n = 14 ICM and n = 12 NIDCM), which yielded similar results. The present study represents the first large-scale gene expression analysis of CHF patient PBMCs that identified a molecular signature of CHF and putative biomarkers of CHF, i.e., chemokine receptor and EGR family members. Furthermore, EGR1 expression levels can discriminate between ICM and NIDCM CHF patients.
本研究旨在从缺血性(ICM)和非缺血性扩张型(NIDCM)心肌病患者的外周血单核细胞(PBMC)中鉴定慢性心力衰竭(CHF)的生物标志物。通过 Affymetrix 在两个患者组中进行 PBMC 基因表达谱分析,1)ICM(n = 12)和 2)NYHA III/IV CHF 患者的 NIDCM(n = 12),与 3)年龄和性别匹配的对照组(n = 12)。然后提取 RNA 并混合到总共 11 个微阵列中。基因本体论(GO)分析将基因谱分为功能类别。预测微阵列分析(PAM)和微阵列显著性分析(SAM)用于识别分子特征。通过定量实时聚合酶链反应验证候选标志物。我们确定了一种可以区分 CHF 患者和对照组的基因表达谱。有趣的是,在构成特征的一组基因中,趋化因子受体(CCR2、CX(3)CR1)和早期生长反应(EGR1、2、3)家族成员在 CHF 患者中上调与对照组相比,并且是基因网络的一部分。对另外 26 名 CHF 患者(n = 14 ICM 和 n = 12 NIDCM)的分析加强了这些发现,结果相似。本研究代表了对 CHF 患者 PBMC 进行的首次大规模基因表达分析,该分析确定了 CHF 的分子特征和 CHF 的潜在生物标志物,即趋化因子受体和 EGR 家族成员。此外,EGR1 表达水平可区分 ICM 和 NIDCM CHF 患者。