Plasma Biomarkers to Detect Prevalent or Predict Progressive Tuberculosis Associated With Human Immunodeficiency Virus–1

Author:

Lesosky Maia12,Rangaka Molebogeng X234,Pienaar Cara1,Coussens Anna K25,Goliath Rene2,Mathee Shaheed6,Mwansa-Kambafwile Judith2,Maartens Gary3ORCID,Wilkinson Robert J2378,Wilkinson Katalin Andrea238ORCID

Affiliation:

1. Division of Epidemiology & Biostatistics, School of Public Health and Family Medicine

2. Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, Observatory, South Africa

3. Department of Medicine, Faculty of Health Sciences, University of Cape Town, Observatory, South Africa

4. Institute for Global Health, Faculty of Population Health Sciences, University College London, United Kingdom

5. Department of Pathology, Faculty of Health Sciences, University of Cape Town, Observatory

6. Site B Khayelitsha Community Health Centre, Western Cape Department of Health, South Africa

7. Department of Medicine, Imperial College London, London, United Kingdom

8. The Francis Crick Institute, London, United Kingdom

Abstract

Abstract Background The risk of individuals infected with human immunodeficiency virus (HIV)-1 developing tuberculosis (TB) is high, while both prognostic and diagnostic tools remain insensitive. The potential for plasma biomarkers to predict which HIV-1–infected individuals are likely to progress to active disease is unknown. Methods Thirteen analytes were measured from QuantiFERON Gold in-tube (QFT) plasma samples in 421 HIV-1–infected persons recruited within the screening and enrollment phases of a randomized, controlled trial of isoniazid preventive therapy. Blood for QFT was obtained pre-randomization. Individuals were classified into prevalent TB, incident TB, and control groups. Comparisons between groups, supervised learning methods, and weighted correlation network analyses were applied utilizing the unstimulated and background-corrected plasma analyte concentrations. Results Unstimulated samples showed higher analyte concentrations in the prevalent and incident TB groups compared to the control group. The largest differences were seen for C-X-C motif chemokine 10 (CXCL10), interleukin-2 (IL-2), IL-1α, transforming growth factor-α (TGF-α). A predictive model analysis using unstimulated analytes discriminated best between the control and prevalent TB groups (area under the curve [AUC] = 0.9), reasonably well between the incident and prevalent TB groups (AUC > 0.8), and poorly between the control and incident TB groups. Unstimulated IL-2 and IFN-γ were ranked at or near the top for all comparisons, except the comparison between the control vs incident TB groups. Models using background-adjusted values performed poorly. Conclusions Single plasma biomarkers are unlikely to distinguish between disease states in HIV-1 co-infected individuals, and combinations of biomarkers are required. The ability to detect prevalent TB is potentially important, as no blood test hitherto has been suggested as having the utility to detect prevalent TB amongst HIV-1 co-infected persons.

Funder

Department of Health of South Africa

Cancer Research UK

UK Medical Research Council

European Union Horizon 2020 research

Wellcome Trust

National Research Foundation of South Africa

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