QuantiFERON Supernatant-based Host Biomarkers Predicting Progression to Active Tuberculosis Disease Among Household Contacts of Tuberculosis Patients

Author:

Daniel Evangeline Ann12ORCID,Thiruvengadam Kannan1,Rajamanickam Anuradha3,Chandrasekaran Padmapriyadarsini1,Pattabiraman Sathyamurthi1,Bhanu Brindha1,Sivaprakasam Amsaveni1,Paradkar Mandar45,Kulkarni Vandana45,Karyakarte Rajesh6,Shivakumar Shri Vijay Bala Yogendra5,Mave Vidya457,Gupta Amita7,Babu Subash3,Hanna Luke Elizabeth1

Affiliation:

1. National Institute for Research in Tuberculosis, Indian Council of Medical Research (ICMR) , Chennai , India

2. University of Madras , Chennai , India

3. International Centre for Excellence in Research-National Institute for Research in Tuberculosis, Indian Council of Medical Research (ICMR) , Chennai , India

4. Byramjee Jeejeebhoy Government Medical College, Johns Hopkins Clinical Research Site , Pune , India

5. Johns Hopkins Center for Infectious Diseases in India , Pune , India

6. Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals , Pune , India

7. John Hopkins University School of Medicine , Baltimore, Maryland , USA

Abstract

Abstract Background The positive predictive value of tuberculin skin test and current generation interferon gamma release assays are very low leading to high numbers needed to treat. Therefore, it is critical to identify new biomarkers with high predictive accuracy to identify individuals bearing high risk of progression to active tuberculosis (TB). Methods We used stored QuantiFERON supernatants from 14 household contacts of index TB patients who developed incident active TB during a 2-year follow-up and 20 age and sex-matched non-progressors. The supernatants were tested for an expanded panel of 45 cytokines, chemokines, and growth factors using the Luminex Multiplex Array kit. Results We found significant differences in the levels of TB-antigen induced production of several analytes between progressors and non-progressors. Dominance analysis identified 15 key predictive biomarkers based on relative percentage importance. Principal component analysis revealed that these biomarkers could robustly distinguish between the 2 groups. Receiver operating characteristic analysis identified interferon-γ inducible protein (IP)-10, chemokine ligand (CCL)19, interferon (IFN)-γ, interleukin (IL)-1ra, CCL3, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as the most promising predictive markers, with area under the curve (AUC) ≥90. IP-10/CCL19 ratio exhibited maximum sensitivity and specificity (100%) for predicting progression. Through Classification and Regression Tree analysis, a cutoff of 0.24 for IP-10/CCL19 ratio was found to be ideal for predicting short-term risk of progression to TB disease with a positive predictive value of 100 (95% confidence interval [CI] 85.8–100). Conclusions The biomarkers identified in this study will pave way for the development of a more accurate test that can identify individuals at high risk for immediate progression to TB disease for targeted intervention.

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3