Purpose:There is currently no measure to predict a treatability of long-acting β-2 agonist (LABA) or long-acting muscarinic antagonist (LAMA) in patients with chronic obstructive pulmonary disease (COPD). We aimed to build prediction models for the treatment response to these bronchodilators, in order to determine the most responsive medication for patients with COPD.
Methods:We performed a prospective open-label crossover study, in which each long-acting bronchodilator was given in a random order to 65 patients with stable COPD for 4 weeks, with a 4-week washout period in between. We analyzed 14 baseline clinical traits, expression profiles of 31,426 gene transcripts, and damaged-gene scores of 6,464 genes acquired from leukocytes. The gene expression profiles were measured by RNA microarray and the damaged-gene scores were obtained after DNA exome sequencing. Linear regression analyses were performed to build prediction models after using factor and correlation analyses.
Results:Using a prediction model for a LABA, traits found associated with the treatment response were post-bronchodilator forced expiratory volume in 1 second, bronchodilator reversibility (BDR) to salbutamol, expression of three genes (CLN8, PCSK5, and SKP2), and damage scores of four genes (EPG5, FNBP4, SCN10A, and SPTBN5) (R2=0.512, p<0.001). Traits associated with the treatment response to a LAMA were COPD assessment test score, BDR, expression of four genes (C1orf115, KIAA1618, PRKX, and RHOQ) and damage scores of three genes (FBN3, FDFT1, and ZBED6) (R2=0.575, p<0.001). The prediction models consisting only of clinical traits appeared too weak to predict the treatment response, with R2=0.231 for the LABA model and R2=0.121 for the LAMA model.
Conclusion:Adding the expressions of genes and damaged-gene scores to the clinical traits may improve the predictability of treatment response to long-acting bronchodilators.
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【Predicting treatable traits for long-acting bronchodilators in patients with stable COPD.].
【预测稳定COPD患者中长效支气管扩张剂的可治疗性状。】
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DOI：10.2147/COPD.S151909文章类型：杂志文章
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目的：目前尚无措施预测长效β-2激动剂（LABA）或长效毒蕈碱拮抗剂（LAMA）在慢性阻塞性肺疾病（COPD）患者中的可治疗性。我们旨在建立针对这些支气管扩张剂的治疗反应的预测模型，以确定对COPD患者最有效的药物。
方法：我们进行了一项前瞻性开放标签交叉研究，其中对65例COPD稳定的患者随机给予每种长效支气管扩张剂4周，其间有4周的清除期。我们分析了14种基线临床特征，31,426个基因转录物的表达谱以及从白细胞获得的6,464个基因的受损基因得分。通过RNA微阵列测量基因表达谱，并在DNA外显子组测序后获得受损基因得分。使用因子和相关性分析后，进行线性回归分析以建立预测模型。
结果：使用LABA的预测模型，发现与治疗反应相关的特征是1秒钟内的支气管扩张剂后呼气量，沙丁胺醇的可逆性（BDR），三种基因（CLN8，PCSK5和SKP2）的表达，以及四个基因（EPG5，FNBP4，SCN10A和SPTBN5）的损伤评分（R2 = 0.512，p <0.001）。与对LAMA的治疗反应相关的特征是COPD评估测试评分，BDR，四个基因（C1orf115，KIAA1618，PRKX和RHOQ）的表达以及三个基因（FBN3，FDFT1和ZBED6）的损害评分（R2 = 0.575， p ＜0.001）。仅由临床特征组成的预测模型显得太弱而无法预测治疗反应，LABA模型的R2 = 0.231，LAMA模型的R2 = 0.121。
结论：在临床特征中增加基因表达和受损基因评分可以提高对长效支气管扩张剂治疗反应的可预测性。
方法：我们进行了一项前瞻性开放标签交叉研究，其中对65例COPD稳定的患者随机给予每种长效支气管扩张剂4周，其间有4周的清除期。我们分析了14种基线临床特征，31,426个基因转录物的表达谱以及从白细胞获得的6,464个基因的受损基因得分。通过RNA微阵列测量基因表达谱，并在DNA外显子组测序后获得受损基因得分。使用因子和相关性分析后，进行线性回归分析以建立预测模型。
结果：使用LABA的预测模型，发现与治疗反应相关的特征是1秒钟内的支气管扩张剂后呼气量，沙丁胺醇的可逆性（BDR），三种基因（CLN8，PCSK5和SKP2）的表达，以及四个基因（EPG5，FNBP4，SCN10A和SPTBN5）的损伤评分（R2 = 0.512，p <0.001）。与对LAMA的治疗反应相关的特征是COPD评估测试评分，BDR，四个基因（C1orf115，KIAA1618，PRKX和RHOQ）的表达以及三个基因（FBN3，FDFT1和ZBED6）的损害评分（R2 = 0.575， p ＜0.001）。仅由临床特征组成的预测模型显得太弱而无法预测治疗反应，LABA模型的R2 = 0.231，LAMA模型的R2 = 0.121。
结论：在临床特征中增加基因表达和受损基因评分可以提高对长效支气管扩张剂治疗反应的可预测性。
