Silterra Jacob, Gillette Michael A, Lanaspa Miguel, Pellé Karell G, Valim Clarissa, Ahmad Rushdy, Acácio Sozinho, Almendinger Katherine D, Tan Yan, Madrid Lola, Alonso Pedro L, Carr Steven A, Wiegand Roger C, Bassat Quique, Mesirov Jill P, Milner Danny A, Wirth Dyann F
Broad Institute of MIT and Harvard, Cambridge.
Massachusetts General Hospital.
J Infect Dis. 2017 Jan 15;215(2):312-320. doi: 10.1093/infdis/jiw531.
Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality rates and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs other) infections would have great clinical utility.
We performed RNA (RNA-seq) sequencing and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models in an independent test set of 37 patients (80%-85% accuracy).
We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. Findings of this study demonstrate that human transcription signatures in infected patients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment.
热带地区小儿急性呼吸窘迫十分常见。细菌性肺炎是发病率和死亡率的主要促成因素,需要进行充分诊断以实现正确治疗。一种能够识别细菌(相对于其他)感染的快速检测方法将具有巨大的临床应用价值。
我们进行了RNA(RNA测序)测序,并分析了68例具有明确临床表型的儿科患者的转录组,以识别与每种疾病类别相关的转录特征。我们将这些特征提炼为预测模型(支持向量机、弹性网络),并在37例患者的独立测试集中对这些模型进行了验证(准确率为80%-85%)。
我们已经确定了在因不同感染而导致肺炎综合征且需要不同治疗干预的儿科患者中差异表达的基因集。本研究结果表明,感染患者的人类转录特征概括了潜在生物学特性,并为预测细菌诊断以指导治疗提供了模型。