Leong Samantha, Zhao Yue, Joseph Noyal M, Hochberg Natasha S, Sarkar Sonali, Pleskunas Jane, Hom David, Lakshminarayanan Subitha, Horsburgh C Robert, Roy Gautam, Ellner Jerrold J, Johnson W Evan, Salgame Padmini
Centre for Emerging Pathogens, Department of Medicine, Rutgers-New Jersey Medical School, Newark, NJ, USA.
Division of Computational Biomedicine, Boston University School of Medicine and Bioinformatics Program, Boston University, Boston, MA, USA.
Tuberculosis (Edinb). 2018 Mar;109:41-51. doi: 10.1016/j.tube.2018.01.002. Epub 2018 Jan 31.
Several studies have identified blood transcriptomic signatures that can distinguish active from latent Tuberculosis (TB). The purpose of this study was to assess how well these existing gene profiles classify TB disease in a South Indian population. RNA sequencing was performed on whole blood PAXgene samples collected from 28 TB patients and 16 latently TB infected (LTBI) subjects enrolled as part of an ongoing household contact study. Differential gene expression and clustering analyses were performed and compared with explicit predictive testing of TB and LTBI individuals based on established gene signatures. We observed strong predictive performance of TB disease states based on expression of known gene sets (ROC AUC 0.9007-0.9879). Together, our findings indicate that previously reported classifiers generated from different ethnic populations can accurately discriminate active TB from LTBI in South Indian patients. Future work should focus on converting existing gene signatures into a universal TB gene signature for diagnosis, monitoring TB treatment, and evaluating new drug regimens.
多项研究已确定了可区分活动性肺结核(TB)与潜伏性肺结核的血液转录组特征。本研究的目的是评估这些现有的基因谱在印度南部人群中对结核病的分类效果如何。对作为正在进行的家庭接触者研究一部分而招募的28例结核病患者和16例潜伏性结核感染(LTBI)受试者采集的全血PAXgene样本进行了RNA测序。进行了差异基因表达和聚类分析,并与基于既定基因特征对结核病和LTBI个体进行的明确预测测试进行了比较。我们观察到基于已知基因集表达的结核病状态具有很强的预测性能(ROC AUC为0.9007 - 0.9879)。总之,我们的研究结果表明,先前报道的来自不同种族人群的分类器能够准确区分印度南部患者的活动性肺结核与LTBI。未来的工作应集中于将现有的基因特征转化为用于诊断、监测结核病治疗和评估新药物方案的通用结核病基因特征。