Institute of Integrative Biology, University of Liverpool and Institute of Ageing and Chronic Disease, University Hospital Aintree, Liverpool, Merseyside, UK.
Rheumatology (Oxford). 2015 Jan;54(1):188-93. doi: 10.1093/rheumatology/keu299. Epub 2014 Aug 13.
The aim of this study was to use whole transcriptome sequencing (RNA-Seq) of RA neutrophils to identify pre-therapy gene expression signatures that correlate with disease activity or response to TNF inhibitor (TNFi) therapy.
Neutrophils were isolated from the venous blood of RA patients (n = 20) pre-TNFi therapy and from healthy controls (n = 6). RNA was poly(A) selected and sequenced on the Illumina HiSeq 2000 platform. Reads were mapped to the human genome (hg19) using TopHat and differential expression analysis was carried out using edgeR (5% false discovery rate). Signalling pathway analysis was carried out using Ingenuity Pathway Analysis (IPA) software. IFN signalling was confirmed by western blotting for phosphorylated signal transducer and activator of transcription (STAT) proteins. Response to TNFi was measured at 12 weeks using change in the 28-item DAS (DAS28).
Pathway analysis with IPA predicted activation of IFN signalling in RA neutrophils, identifying 178 IFN-response genes regulated by IFN-α, IFN-β or IFN-γ (P < 0.01). IPA also predicted activation of STAT1, STAT2 and STAT3 transcription factors in RA neutrophils (P < 0.01), which was confirmed by western blotting. Expression of IFN-response genes was heterogeneous and patients could be categorized as IFN-high or IFN-low. Patients in the IFN-high group achieved a better response to TNFi therapy [ΔDAS28, P = 0.05, odds ratio (OR) 1.4 (95% CI 1.005, 1.950)] than patients in the IFN-low group. The level of expression of IFN-response genes (IFN score) predicted a good response [European League Against Rheumatism (EULAR) criteria] to TNFi using receiver operating characteristic curve analysis (area under the curve 0.76).
IFN-response genes are significantly up-regulated in RA neutrophils compared with healthy controls. Higher IFN-response gene expression in RA neutrophils correlates with a good response to TNFi therapy.
本研究旨在通过 RA 中性粒细胞的全转录组测序(RNA-Seq),鉴定与疾病活动或对 TNF 抑制剂(TNFi)治疗反应相关的治疗前基因表达特征。
RA 患者(n=20)在 TNFi 治疗前和健康对照者(n=6)的静脉血中分离中性粒细胞。使用 Poly(A) 选择 RNA,并在 Illumina HiSeq 2000 平台上进行测序。使用 TopHat 将读取映射到人类基因组(hg19),并使用 edgeR(5%错误发现率)进行差异表达分析。使用 IPA 软件进行信号通路分析。通过 Western 印迹法检测磷酸化信号转导和转录激活因子(STAT)蛋白来确认 IFN 信号。在 12 周时使用 28 项 DAS(DAS28)的变化来衡量 TNFi 的反应。
IPA 的通路分析预测 RA 中性粒细胞中 IFN 信号的激活,确定了 178 个受 IFN-α、IFN-β 或 IFN-γ调节的 IFN 反应基因(P<0.01)。IPA 还预测了 RA 中性粒细胞中 STAT1、STAT2 和 STAT3 转录因子的激活(P<0.01),这通过 Western 印迹法得到了证实。IFN 反应基因的表达具有异质性,患者可分为 IFN-高或 IFN-低。IFN-高组患者对 TNFi 治疗的反应更好[ΔDAS28,P=0.05,优势比(OR)1.4(95%CI 1.005,1.950)],而 IFN-低组患者则较差。使用受试者工作特征曲线分析(曲线下面积 0.76),IFN 反应基因的表达水平(IFN 评分)预测了对 TNFi 的良好反应[欧洲抗风湿病联盟(EULAR)标准]。
与健康对照者相比,RA 中性粒细胞中 IFN 反应基因显著上调。RA 中性粒细胞中更高的 IFN 反应基因表达与对 TNFi 治疗的良好反应相关。