Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study.
Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study.
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DOI：
10.1016/s2213-2600(17)30349-1
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发表时间：
2017-11
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影响因子：
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通讯作者：
Kaminski N
中科院分区：
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作者：
Herazo-Maya JD;Sun J;Molyneaux PL;Li Q;Villalba JA;Tzouvelekis A;Lynn H;Juan-Guardela BM;Risquez C;Osorio JC;Yan X;Michel G;Aurelien N;Lindell KO;Klesen MJ;Moffatt MF;Cookson WO;Zhang Y;Garcia JGN;Noth I;Prasse A;Bar-Joseph Z;Gibson KF;Zhao H;Herzog EL;Rosas IO;Maher TM;Kaminski N
特发性肺纤维化（IPF）的临床过程是不可预测的。临床预测工具不足以准确预测疾病结果。所有诊断为特发性肺纤维化的患者均入组一项6队列研究。在基线时从425名参与者和随访期间从98名患者收集外周血单核细胞或全血。通过nCounter®分析系统在四个组群中测量52个基因标签，并从另外两个组群的微阵列数据中提取。使用分子亚表型评分算法（SAMS）根据52个基因标签将患者分为低风险组或高风险组。死亡率和无移植存活率分别采用竞争风险模型和考克斯比例风险模型进行研究。使用线性混合效应模型分析时程数据和对抗纤维化药物的反应。将SAMS应用于52个基因签名，确定了两组IPF患者（低风险和高风险），在6个队列中的每一个队列中，死亡率或无移植生存率均存在显著差异（HR 2.03 - 4.37）。合并数据显示死亡率（HR：2.18，95%CI：1.53 - 3.09，P<0.0001）或无移植存活率（HR：2.04，95%CI：1.52 - 2.74，P<0.0001）结果相似。在性别、年龄和生理学（GAP）指数中添加52个基因风险特征显著提高了其死亡率预测准确性。在两个队列中，SAMS评分的时间变化与用力肺活量（FVC）的变化相关。未接受治疗的患者的风险状况并未随时间推移而改变。在匹兹堡队列中，向上评分的增加和向下评分的减少同时出现可预测无移植存活率（HR：3.18.95%CI 1.16，8.76，P= 0.025）。在耶鲁队列中，开始抗纤维化药物治疗后向上评分的降低和向下评分的增加与FVC的显著改善相关（P= 0.005）。外周血52基因表达特征可预测IPF患者的结局。应在前瞻性研究中确定52个基因特征在预测治疗反应方面的潜在价值。
The clinical course of Idiopathic Pulmonary Fibrosis (IPF) is unpredictable. Clinical prediction tools are not accurate enough to predict disease outcomes. All-comers with Idiopathic Pulmonary Fibrosis diagnosis were enrolled in a six-cohort study. Peripheral blood mononuclear cells or whole blood was collected at baseline from 425 participants and during follow up from 98 patients. The 52-gene signature was measured by the nCounter® analysis system in four cohorts and extracted from microarray data in two others. The Scoring Algorithm for Molecular Subphenotypes (SAMS) was used to classify patients into low or high risk groups based on a 52-gene signature. Mortality and transplant-free survival were studied using Competing risk and Cox proportional-hazard models, respectively. Time course data and response to anti-fibrotic drugs were analyzed using linear mixed-effect models. The application of SAMS to the 52-gene signature identified two groups of IPF patients (low and high risk) with significant differences in mortality or transplant-free survival in each of the six cohorts (HR 2·03–4·37). Pooled data revealed similar results for mortality (HR:2·18, 95%CI:1·53–3·09, P<0·0001) or transplant-free survival (HR:2·04, 95%CI: 1·52–2·74, P<0·0001). Adding 52-gene risk profiles to the Gender, Age and Physiology (GAP) index significantly improved its mortality predictive accuracy. Temporal changes in SAMS scores were associated with changes in forced vital capacity (FVC) in two cohorts. Untreated patients did not shift their risk profile over time. A simultaneous increase in up score and decrease in down score was predictive of transplant-free survival (HR:3·18· 95%CI 1·16, 8·76, P=0·025) in the Pittsburgh cohort. A simultaneous decrease in up score and increase in down score after initiation of anti-fibrotic drugs was associated with a significant (P=0·005) improvement in FVC in the Yale cohort. The peripheral blood 52-gene expression signature is predictive of outcome in patients with IPF. The potential value of the 52-gene signature in predicting response to therapy should be determined in prospective studies.