Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults.
Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults.
复制标题
DOI：
10.1093/infdis/jiv047
复制
发表时间：
2015-07-15
期刊：
影响因子：
--
通讯作者：
Ramilo O
中科院分区：
文献类型：
--
作者：
Suarez NM;Bunsow E;Falsey AR;Walsh EE;Mejias A;Ramilo O
背景：区分细菌性和病毒性下呼吸道感染（LRTI）仍然是一个挑战. 转录谱分析是一个很有前途的工具，提高诊断LRTI。 方法：我们对118例因下呼吸道感染住院的患者（中位年龄[四分位距]，61 [50-76]岁）和40例年龄匹配的健康对照（中位年龄，60 [46-70]岁）进行了全血转录分析。 我们应用类比较，模块化分析和类预测算法来识别和验证细菌和病毒LRTI的诊断生物特征。 结果：根据全面的微生物学检测，患者分为细菌性（n = 22）、病毒性（n = 71）或细菌-病毒性LRTI（n = 25）。 与健康对照组相比，统计组比较（P <0.01;多重检验校正）在细菌性LRTI患者中鉴定出3376个差异表达基因，在病毒性LRTI患者中鉴定出2391个差异表达基因，在细菌-病毒性LRTI患者中鉴定出2628个差异表达基因。细菌性LRTI患者表现出显著的炎症和中性粒细胞基因过表达（细菌>细菌-病毒>病毒），而病毒性LRTI患者表现出显著更高的干扰素基因过表达（病毒>细菌-病毒>细菌）。K-最近邻算法识别了10个分类器基因，其以95%的灵敏度（95%置信区间，77%-100%）和92%的特异性（77%-98%）区分细菌和病毒LRTI，而降钙素原的灵敏度为38%（18%-62%），特异性为91%（76%-98%）。 结论：转录谱是诊断下呼吸道感染的有用工具。
Background. Distinguishing between bacterial and viral lower respiratory tract infection (LRTI) remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods. We performed whole blood transcriptional analysis in 118 patients (median age [interquartile range], 61 [50–76] years) hospitalized with LRTI and 40 age-matched healthy controls (median age, 60 [46–70] years). We applied class comparisons, modular analysis, and class prediction algorithms to identify and validate diagnostic biosignatures for bacterial and viral LRTI. Results. Patients were classified as having bacterial (n = 22), viral (n = 71), or bacterial-viral LRTI (n = 25) based on comprehensive microbiologic testing. Compared with healthy controls, statistical group comparisons (P < .01; multiple-test corrections) identified 3376 differentially expressed genes in patients with bacterial LRTI, 2391 in viral LRTI, and 2628 in bacterial-viral LRTI. Patients with bacterial LRTI showed significant overexpression of inflammation and neutrophil genes (bacterial > bacterial-viral > viral), and those with viral LRTI displayed significantly greater overexpression of interferon genes (viral > bacterial-viral > bacterial). The K–nearest neighbors algorithm identified 10 classifier genes that discriminated between bacterial and viral LRTI with a 95% sensitivity (95% confidence interval, 77%–100%) and 92% specificity (77%–98%), compared with a sensitivity of 38% (18%–62%) and a specificity of 91% (76%–98%) for procalcitonin. Conclusions. Transcriptional profiling is a helpful tool for diagnosis of LRTI.