Article A new blood-based RNA signature (R9), for monitoring effectiveness of tuberculosis treatment in a South Indian longitudinal cohort

被引:2
|
作者
Thakur, Chandrani [1 ]
Tripathi, Ashutosh [2 ,3 ]
Ravichandran, Sathyabaarathi [4 ]
Shivananjaiah, Akshatha [5 ,6 ]
Chakraborty, Anushree [5 ,6 ]
Varadappa, Sreekala [5 ,6 ]
Chikkavenkatappa, Nagaraj [5 ,6 ]
Nagarajan, Deepesh [1 ]
Lakshminarasimhaiah, Sharada [7 ]
Singh, Amit [2 ,3 ]
Chandra, Nagasuma [1 ,4 ,8 ]
机构
[1] Indian Inst Sci, Dept Biochem, Bangalore, Karnataka, India
[2] Indian Inst Sci, Dept Microbiol & Cell Biol, Bangalore, Karnataka, India
[3] Indian Inst Sci, Ctr Infect Dis Res, Bangalore, Karnataka, India
[4] Indian Inst Sci, Natl Math Initiat, Bangalore, Karnataka, India
[5] SDS TB Res Ctr, Bangalore, Karnataka, India
[6] Rajiv Gandhi Inst Chest Dis, Bangalore, Karnataka, India
[7] Indian Inst Sci, Hlth Ctr, Bangalore, Karnataka, India
[8] Indian Inst Sci, Ctr Biosyst Sci & Engn, Bangalore, Karnataka, India
基金
英国惠康基金;
关键词
DRUG-RESISTANT TUBERCULOSIS; MYCOBACTERIUM-TUBERCULOSIS; PULMONARY TUBERCULOSIS; EXPRESSION; MULTICENTER; RELIABILITY; BIOMARKERS; EMERGENCE; DIAGNOSIS; PREDICT;
D O I
10.1016/j.isci.2022.103745
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Tuberculosis (TB) treatment involves a multidrug regimen for six months, and until two months, it is unclear if treatment is effective. This delay can lead to the evolution of drug resistance, lung damage, disease spread, and transmission. We identify a blood-based 9-gene signature using a computational pipeline that constructs and interrogates a genome-wide transcriptome-integrated protein-interaction network. The identified signature is able to determine treatment response at week 1-2 in three independent public datasets. Signature-based R-9-score correctly detected treatment response at individual timepoints (204 samples) from a newly developed South Indian longitudinal cohort involving 32 patients with pulmonary TB. These results are consistent with conventional clinical metrics and can discriminate good from poor treatment responders at week 2 (AUC 0.93(0.81-1.00)). In this work, we provide proof of concept that the R-9-score can determine treatment effectiveness, making a case for designing a larger clinical study.
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页数:23
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