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Arya R, Shakya H, Chaurasia R, Kumar S, Vinetz JM, Kim JJ. Computational reassessment of RNA-seq data reveals key genes in active tuberculosis. PLoS One 2024; 19:e0305582. [PMID: 38935691 PMCID: PMC11210783 DOI: 10.1371/journal.pone.0305582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/31/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Tuberculosis is a serious life-threatening disease among the top global health challenges and rapid and effective diagnostic biomarkers are vital for early diagnosis especially given the increasing prevalence of multidrug resistance. METHODS Two human whole blood microarray datasets, GSE42826 and GSE42830 were retrieved from publicly available gene expression omnibus (GEO) database. Deregulated genes (DEGs) were identified using GEO2R online tool and Gene Ontology (GO), protein-protein interaction (PPI) network analysis was performed using Metascape and STRING databases. Significant genes (n = 8) were identified using T-test/ANOVA and Molecular Complex Detection (MCODE) score ≥10, which was validated in GSE34608 dataset. The diagnostic potential of three biomarkers was assessed using Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) plot. The transcriptional levels of these genes were also examined in a separate dataset GSE31348, to monitor the patterns of variation during tuberculosis treatment. RESULTS A total of 62 common DEGs (57 upregulated, 7 downregulated genes) were identified in two discovery datasets. GO functions and pathway enrichment analysis shed light on the functional roles of these DEGs in immune response and type-II interferon signaling. The genes in Module-1 (n = 18) were linked to innate immune response, interferon-gamma signaling. The common genes (n = 8) were validated in GSE34608 dataset, that corroborates the results obtained from discovery sets. The gene expression levels demonstrated responsiveness to Mtb infection during anti-TB therapy in GSE31348 dataset. In GSE34608 dataset, the expression levels of three specific genes, GBP5, IFITM3, and EPSTI1, emerged as potential diagnostic makers. In combination, these genes scored remarkable diagnostic performance with 100% sensitivity and 89% specificity, resulting in an impressive Area Under Curve (AUC) of 0.958. However, GBP5 alone showed the highest AUC of 0.986 with 100% sensitivity and 89% specificity. CONCLUSIONS The study presents valuable insights into the critical gene network perturbed during tuberculosis. These genes are determinants for assessing the effectiveness of an anti-TB response and distinguishing between active TB and healthy individuals. GBP5, IFITM3 and EPSTI1 emerged as candidate core genes in TB and holds potential as novel molecular targets for the development of interventions in the treatment of TB.
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Affiliation(s)
- Rakesh Arya
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, South Korea
| | - Hemlata Shakya
- Department of Biomedical Engineering, Shri G. S. Institute of Technology and Science, Indore, Madhya Pradesh, India
| | - Reetika Chaurasia
- Department of Internal Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, United States of America
| | - Surendra Kumar
- Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Joseph M. Vinetz
- Department of Internal Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, United States of America
| | - Jong Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, South Korea
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Wang X, VanValkenberg A, Odom AR, Ellner JJ, Hochberg NS, Salgame P, Patil P, Johnson WE. Comparison of gene set scoring methods for reproducible evaluation of tuberculosis gene signatures. BMC Infect Dis 2024; 24:610. [PMID: 38902649 PMCID: PMC11191245 DOI: 10.1186/s12879-024-09457-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 05/31/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed. METHODS We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models. RESULTS For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies. CONCLUSION Gene set enrichment scoring of existing gene sets can distinguish patients with active TB disease from other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.
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Affiliation(s)
- Xutao Wang
- Department of Biostatistics, Boston University, Boston, MA, USA
- Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Arthur VanValkenberg
- Division of Infectious Disease, Center for Data Science, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Aubrey R Odom
- Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Jerrold J Ellner
- Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Natasha S Hochberg
- Boston Medical Center, Boston, MA, USA
- Section of Infectious Diseases, Boston University School of Medicine, Boston, MA, USA
| | - Padmini Salgame
- Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Prasad Patil
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - W Evan Johnson
- Division of Infectious Disease, Center for Data Science, Rutgers New Jersey Medical School, Newark, NJ, USA.
- Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School, Newark, NJ, USA.
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Davies LRL, Wang C, Steigler P, Bowman KA, Fischinger S, Hatherill M, Fisher M, Mbandi SK, Rodo M, Ottenhoff THM, Dockrell HM, Sutherland JS, Mayanja-Kizza H, Boom WH, Walzl G, Kaufmann SHE, Nemes E, Scriba TJ, Lauffenburger D, Alter G, Fortune SM. Age and sex influence antibody profiles associated with tuberculosis progression. Nat Microbiol 2024; 9:1513-1525. [PMID: 38658786 PMCID: PMC11153143 DOI: 10.1038/s41564-024-01678-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/20/2024] [Indexed: 04/26/2024]
Abstract
Antibody features vary with tuberculosis (TB) disease state. Whether clinical variables, such as age or sex, influence associations between Mycobacterium tuberculosis-specific antibody responses and disease state is not well explored. Here we profiled Mycobacterium tuberculosis-specific antibody responses in 140 TB-exposed South African individuals from the Adolescent Cohort Study. We identified distinct response features in individuals progressing to active TB from non-progressing, matched controls. A multivariate antibody score differentially associated with progression (SeroScore) identified progressors up to 2 years before TB diagnosis, earlier than that achieved with the RISK6 transcriptional signature of progression. We validated these antibody response features in the Grand Challenges 6-74 cohort. Both the SeroScore and RISK6 correlated better with risk of TB progression in adolescents compared with adults, and in males compared with females. This suggests that age and sex are important, underappreciated modifiers of antibody responses associated with TB progression.
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Affiliation(s)
- Leela R L Davies
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Chuangqi Wang
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Pia Steigler
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
- Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Kathryn A Bowman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | | | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Michelle Fisher
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Stanley Kimbung Mbandi
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Miguel Rodo
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Hazel M Dockrell
- Vaccines and Immunity Theme, Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | - Jayne S Sutherland
- Vaccines and Immunity Theme, Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | - Harriet Mayanja-Kizza
- Department of Medicine and Department of Microbiology, Makerere University, Kampala, Uganda
| | - W Henry Boom
- Tuberculosis Research Unit, Case Western Reserve University, Cleveland, OH, USA
| | - Gerhard Walzl
- Department of Science and Technology National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Stefan H E Kaufmann
- Max Planck Institute for Infection Biology, Berlin, Germany
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Hagler Institute for Advanced Study, Texas A&M University, College Station, TX, USA
| | - Elisa Nemes
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative and Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | | | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA.
- Moderna Therapeutics, Cambridge, MA, USA.
| | - Sarah M Fortune
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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Li LS, Yang L, Zhuang L, Ye ZY, Zhao WG, Gong WP. From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning. Mil Med Res 2023; 10:58. [PMID: 38017571 PMCID: PMC10685516 DOI: 10.1186/s40779-023-00490-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/06/2023] [Indexed: 11/30/2023] Open
Abstract
Latent tuberculosis infection (LTBI) has become a major source of active tuberculosis (ATB). Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI, these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB. Thus, the diagnosis of LTBI faces many challenges, such as the lack of effective biomarkers from Mycobacterium tuberculosis (MTB) for distinguishing LTBI, the low diagnostic efficacy of biomarkers derived from the human host, and the absence of a gold standard to differentiate between LTBI and ATB. Sputum culture, as the gold standard for diagnosing tuberculosis, is time-consuming and cannot distinguish between ATB and LTBI. In this article, we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI, including the innate and adaptive immune responses, multiple immune evasion mechanisms of MTB, and epigenetic regulation. Based on this knowledge, we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning (ML) in LTBI diagnosis, as well as the advantages and limitations of ML in this context. Finally, we discuss the future development directions of ML applied to LTBI diagnosis.
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Affiliation(s)
- Lin-Sheng Li
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China
- Hebei North University, Zhangjiakou, 075000, Hebei, China
- Senior Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China
| | - Ling Yang
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Li Zhuang
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Zhao-Yang Ye
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Wei-Guo Zhao
- Senior Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China.
| | - Wen-Ping Gong
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China.
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5
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Zhuang L, Ye Z, Li L, Yang L, Gong W. Next-Generation TB Vaccines: Progress, Challenges, and Prospects. Vaccines (Basel) 2023; 11:1304. [PMID: 37631874 PMCID: PMC10457792 DOI: 10.3390/vaccines11081304] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 07/28/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023] Open
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is a prevalent global infectious disease and a leading cause of mortality worldwide. Currently, the only available vaccine for TB prevention is Bacillus Calmette-Guérin (BCG). However, BCG demonstrates limited efficacy, particularly in adults. Efforts to develop effective TB vaccines have been ongoing for nearly a century. In this review, we have examined the current obstacles in TB vaccine research and emphasized the significance of understanding the interaction mechanism between MTB and hosts in order to provide new avenues for research and establish a solid foundation for the development of novel vaccines. We have also assessed various TB vaccine candidates, including inactivated vaccines, attenuated live vaccines, subunit vaccines, viral vector vaccines, DNA vaccines, and the emerging mRNA vaccines as well as virus-like particle (VLP)-based vaccines, which are currently in preclinical stages or clinical trials. Furthermore, we have discussed the challenges and opportunities associated with developing different types of TB vaccines and outlined future directions for TB vaccine research, aiming to expedite the development of effective vaccines. This comprehensive review offers a summary of the progress made in the field of novel TB vaccines.
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Affiliation(s)
- Li Zhuang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
- Hebei North University, Zhangjiakou 075000, China
| | - Zhaoyang Ye
- Hebei North University, Zhangjiakou 075000, China
| | - Linsheng Li
- Hebei North University, Zhangjiakou 075000, China
| | - Ling Yang
- Hebei North University, Zhangjiakou 075000, China
| | - Wenping Gong
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
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6
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Vargas R, Abbott L, Bower D, Frahm N, Shaffer M, Yu WH. Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment. PLoS Comput Biol 2023; 19:e1010770. [PMID: 37471455 PMCID: PMC10393163 DOI: 10.1371/journal.pcbi.1010770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023] Open
Abstract
While blood gene signatures have shown promise in tuberculosis (TB) diagnosis and treatment monitoring, most signatures derived from a single cohort may be insufficient to capture TB heterogeneity in populations and individuals. Here we report a new generalized approach combining a network-based meta-analysis with machine-learning modeling to leverage the power of heterogeneity among studies. The transcriptome datasets from 57 studies (37 TB and 20 viral infections) across demographics and TB disease states were used for gene signature discovery and model training and validation. The network-based meta-analysis identified a common 45-gene signature specific to active TB disease across studies. Two optimized random forest regression models, using the full or partial 45-gene signature, were then established to model the continuum from Mycobacterium tuberculosis infection to disease and treatment response. In model validation, using pooled multi-cohort datasets to mimic the real-world setting, the model provides robust predictive performance for incipient to active TB risk over a 2.5-year period with an AUROC of 0.85, 74.2% sensitivity, and 78.3% specificity, which approximates the minimum criteria (>75% sensitivity and >75% specificity) within the WHO target product profile for prediction of progression to TB. Moreover, the model strongly discriminates active TB from viral infection (AUROC 0.93, 95% CI 0.91-0.94). For treatment monitoring, the TB scores generated by the model statistically correlate with treatment responses over time and were predictive, even before treatment initiation, of standard treatment clinical outcomes. We demonstrate an end-to-end gene signature model development scheme that considers heterogeneity for TB risk estimation and treatment monitoring.
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Affiliation(s)
- Roger Vargas
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
- Harvard University, Cambridge, Massachusetts, United States of America
| | - Liam Abbott
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
| | - Daniel Bower
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
| | - Nicole Frahm
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
| | - Mike Shaffer
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
| | - Wen-Han Yu
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, United States of America
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Buijze H, Brinkmann V, Hurwitz R, Dorhoi A, Kaufmann SHE, Pei G. Human GBP1 Is Involved in the Repair of Damaged Phagosomes/Endolysosomes. Int J Mol Sci 2023; 24:ijms24119701. [PMID: 37298652 DOI: 10.3390/ijms24119701] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 05/25/2023] [Accepted: 05/27/2023] [Indexed: 06/12/2023] Open
Abstract
Mouse guanylate-binding proteins (mGBPs) are recruited to various invasive pathogens, thereby conferring cell-autonomous immunity against these pathogens. However, whether and how human GBPs (hGBPs) target M. tuberculosis (Mtb) and L. monocytogenes (Lm) remains unclear. Here, we describe hGBPs association with intracellular Mtb and Lm, which was dependent on the ability of bacteria to induce disruption of phagosomal membranes. hGBP1 formed puncta structures which were recruited to ruptured endolysosomes. Furthermore, both GTP-binding and isoprenylation of hGBP1 were required for its puncta formation. hGBP1 was required for the recovery of endolysosomal integrity. In vitro lipid-binding assays demonstrated direct binding of hGBP1 to PI4P. Upon endolysosomal damage, hGBP1 was targeted to PI4P and PI(3,4)P2-positive endolysosomes in cells. Finally, live-cell imaging demonstrated that hGBP1 was recruited to damaged endolysosomes, and consequently mediated endolysosomal repair. In summary, we uncover a novel interferon-inducible mechanism in which hGBP1 contributes to the repair of damaged phagosomes/endolysosomes.
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Affiliation(s)
- Hellen Buijze
- Department of Immunology, Max Planck Institute for Infection Biology, Charitéplatz 1, 10117 Berlin, Germany
| | - Volker Brinkmann
- Microscopy Core Facility, Max Planck Institute for Infection Biology, Charitéplatz 1, 10117 Berlin, Germany
| | - Robert Hurwitz
- Protein Purification Facility, Max Planck Institute for Infection Biology, Charitéplatz 1, 10117 Berlin, Germany
| | - Anca Dorhoi
- Institute of Immunology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, 17493 Greifswald, Germany
- Faculty of Mathematics and Natural Sciences, University of Greifswald, 17489 Greifswald, Germany
| | - Stefan H E Kaufmann
- Department of Immunology, Max Planck Institute for Infection Biology, Charitéplatz 1, 10117 Berlin, Germany
- Emeritus Group of Systems Immunology, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, 37077 Göttingen, Germany
- Hagler Institute for Advanced Study, Texas A&M University, College Station, TX 77843, USA
| | - Gang Pei
- Institute of Immunology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, 17493 Greifswald, Germany
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de Olazarra AS, Wang SX. Advances in point-of-care genetic testing for personalized medicine applications. BIOMICROFLUIDICS 2023; 17:031501. [PMID: 37159750 PMCID: PMC10163839 DOI: 10.1063/5.0143311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 04/12/2023] [Indexed: 05/11/2023]
Abstract
Breakthroughs within the fields of genomics and bioinformatics have enabled the identification of numerous genetic biomarkers that reflect an individual's disease susceptibility, disease progression, and therapy responsiveness. The personalized medicine paradigm capitalizes on these breakthroughs by utilizing an individual's genetic profile to guide treatment selection, dosing, and preventative care. However, integration of personalized medicine into routine clinical practice has been limited-in part-by a dearth of widely deployable, timely, and cost-effective genetic analysis tools. Fortunately, the last several decades have been characterized by tremendous progress with respect to the development of molecular point-of-care tests (POCTs). Advances in microfluidic technologies, accompanied by improvements and innovations in amplification methods, have opened new doors to health monitoring at the point-of-care. While many of these technologies were developed with rapid infectious disease diagnostics in mind, they are well-suited for deployment as genetic testing platforms for personalized medicine applications. In the coming years, we expect that these innovations in molecular POCT technology will play a critical role in enabling widespread adoption of personalized medicine methods. In this work, we review the current and emerging generations of point-of-care molecular testing platforms and assess their applicability toward accelerating the personalized medicine paradigm.
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Affiliation(s)
- A. S. de Olazarra
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - S. X. Wang
- Author to whom correspondence should be addressed:
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Sarmah DT, Parveen R, Kundu J, Chatterjee S. Latent tuberculosis and computational biology: A less-talked affair. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 178:17-31. [PMID: 36781150 DOI: 10.1016/j.pbiomolbio.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/13/2023]
Abstract
Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.
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Affiliation(s)
- Dipanka Tanu Sarmah
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Rubi Parveen
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Jayendrajyoti Kundu
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Samrat Chatterjee
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India.
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10
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Mendelsohn SC, Verhage S, Mulenga H, Scriba TJ, Hatherill M. Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV. Gates Open Res 2023; 7:27. [PMID: 37123047 PMCID: PMC10133453 DOI: 10.12688/gatesopenres.14327.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2023] [Indexed: 02/05/2023] Open
Abstract
Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.
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Affiliation(s)
- Simon C Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Savannah Verhage
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Humphrey Mulenga
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
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Wang X, VanValkenberg A, Odom-Mabey AR, Ellner JJ, Hochberg NS, Salgame P, Patil P, Johnson WE. Comparison of gene set scoring methods for reproducible evaluation of multiple tuberculosis gene signatures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.19.520627. [PMID: 36711818 PMCID: PMC9882404 DOI: 10.1101/2023.01.19.520627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Rationale Many blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures' replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed. Objectives We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use. Methods We considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature's performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models. Measurement and Main Results For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies. Conclusion Gene set enrichment scoring of existing blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.
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Affiliation(s)
- Xutao Wang
- Department of Biostatistics, Boston University, Boston, MA, USA
- Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Arthur VanValkenberg
- Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Aubrey R. Odom-Mabey
- Division of Computational Biomedicine and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Jerrold J. Ellner
- Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Natasha S. Hochberg
- Boston Medical Center, Boston, MA, USA
- Section of Infectious Diseases, Boston University School of Medicine, Boston, MA, USA
| | - Padmini Salgame
- Department of Medicine, Center for Emerging Pathogens, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Prasad Patil
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - W. Evan Johnson
- Division of Infectious Disease, Center for Data Science, Rutgers New Jersey Medical School, Newark, NJ, USA
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12
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Mendelsohn SC, Verhage S, Mulenga H, Scriba TJ, Hatherill M. Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV. Gates Open Res 2023; 7:27. [PMID: 37123047 PMCID: PMC10133453.2 DOI: 10.12688/gatesopenres.14327.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/02/2023] [Indexed: 05/09/2023] Open
Abstract
Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.
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Affiliation(s)
- Simon C Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Savannah Verhage
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Humphrey Mulenga
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, Western Cape, 7935, South Africa
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13
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Chendi BH, Jooste T, Scriba TJ, Kidd M, Mendelsohn S, Tonby K, Walzl G, Dyrhol-Riise AM, Chegou NN. Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting. Infect Dis (Lond) 2023; 55:44-54. [PMID: 36214761 DOI: 10.1080/23744235.2022.2129779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country. METHOD Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves. RESULTS A significant difference (p < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%). CONCLUSION The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.
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Affiliation(s)
- Bih Hycenta Chendi
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tracey Jooste
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Thomas Jens Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Martin Kidd
- Department of Statistics and Actuarial Sciences, Centre for Statistical Consultation, Stellenbosch University, Cape Town, South Africa
| | - Simon Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Kristian Tonby
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.,Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Gerhard Walzl
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Anne M Dyrhol-Riise
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.,Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Novel Njweipi Chegou
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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14
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Wang J, Li Y, Wang N, Wu J, Ye X, Jiang Y, Tang L. Functions of exosomal non-coding RNAs to the infection with Mycobacterium tuberculosis. Front Immunol 2023; 14:1127214. [PMID: 37033928 PMCID: PMC10073540 DOI: 10.3389/fimmu.2023.1127214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
Tuberculosis (TB) is a major infectious disease induced by Mycobacterium tuberculosis (M. tb) which causes the world's dominant fatal bacterial contagious disease. Increasing studies have indicated that exosomes may be a novel option for the diagnosis and treatment of TB. Exosomes are nanovesicles (30-150 nm) containing lipids, proteins and non-coding RNAs (ncRNAs) released from various cells, and can transfer their cargos and communicate between cells. Furthermore, exosomal ncRNAs exhibit diagnosis potential in bacterial infections, including TB. Additionally, differential exosomal ncRNAs regulate the physiological and pathological functions of M. tb-infected cells and act as diagnostic markers for TB. This current review explored the potential biological roles and the diagnostic application prospects of exosomal ncRNAs, and included recent information on their pathogenic and therapeutic functions in TB.
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Affiliation(s)
- Jianjun Wang
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
- *Correspondence: Lijun Tang, ; Jianjun Wang,
| | - Yujie Li
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
| | - Nan Wang
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
| | - Jianhong Wu
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
| | - Xiaojian Ye
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
| | - Yibiao Jiang
- Department of Clinical Laboratory, The First People’s Hospital of Kunshan, Suzhou, China
| | - Lijun Tang
- Department of Biochemistry and Molecular Biology, School of Life Sciences, Central South University, Changsha, China
- *Correspondence: Lijun Tang, ; Jianjun Wang,
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15
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Mousavian Z, Folkesson E, Fröberg G, Foroogh F, Correia-Neves M, Bruchfeld J, Källenius G, Sundling C. A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis. iScience 2022; 25:105652. [PMID: 36561889 PMCID: PMC9763869 DOI: 10.1016/j.isci.2022.105652] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/19/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022] Open
Abstract
Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.
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Affiliation(s)
- Zaynab Mousavian
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
| | - Elin Folkesson
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gabrielle Fröberg
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Microbiology, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Fariba Foroogh
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Margarida Correia-Neves
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal
| | - Judith Bruchfeld
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gunilla Källenius
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Christopher Sundling
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
- Corresponding author
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16
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Valinetz ED, Matemo D, Gersh JK, Joudeh LL, Mendelsohn SC, Scriba TJ, Hatherill M, Kinuthia J, Wald A, Cangelosi GA, Barnabas RV, Hawn TR, Horne DJ. Isoniazid preventive therapy and tuberculosis transcriptional signatures in people with HIV. AIDS 2022; 36:1363-1371. [PMID: 35608118 PMCID: PMC9329226 DOI: 10.1097/qad.0000000000003262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES To examine the association between isoniazid preventive therapy (IPT) or nontuberculous mycobacteria (NTM) sputum culture positivity and tuberculosis (TB) transcriptional signatures in people with HIV. DESIGN Cross-sectional study. METHODS We enrolled adults living with HIV who were IPT-naive or had completed IPT more than 6 months prior at HIV care clinics in western Kenya. We calculated TB signatures using gene expression data from qRT-PCR. We used multivariable linear regression to analyze the association between prior receipt of IPT or NTM sputum culture positivity with a transcriptional TB risk score, RISK6 (range 0-1). In secondary analyses, we explored the association between IPT or NTM positivity and four other TB transcriptional signatures. RESULTS Among 381 participants, 99.7% were receiving antiretroviral therapy and 86.6% had received IPT (completed median of 1.1 years prior). RISK6 scores were lower (mean difference 0.10; 95% confidence interval (CI): 0.06-0.15; P < 0.001) among participants who received IPT than those who did not. In a model that adjusted for age, sex, duration of ART, and plasma HIV RNA, the RISK6 score was 52.8% lower in those with a history of IPT ( P < 0.001). No significant association between year of IPT receipt and RISK6 scores was detected. There was no association between NTM sputum culture positivity and RISK6 scores. CONCLUSION In people with HIV, IPT was associated with significantly lower RISK6 scores compared with persons who did not receive IPT. These data support investigations of its performance as a TB preventive therapy response biomarker.
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Affiliation(s)
- Ethan D Valinetz
- Department of Medicine, University of Washington, Seattle, Washington
- Division of Infectious Disease, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Daniel Matemo
- Department of Research and Programs, Kenyatta National Hospital, Nairobi
- School of Public Health and Community Development Maseno University, Kisumu, Kenya
| | - Jill K Gersh
- Department of Medicine, University of Washington, Seattle, Washington
| | - Lara L Joudeh
- Department of Medicine, University of Washington, Seattle, Washington
| | - Simon C Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, South Africa
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, South Africa
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, South Africa
| | - John Kinuthia
- Department of Research and Programs, Kenyatta National Hospital, Nairobi
- Department of Global Health
| | - Anna Wald
- Department of Medicine, University of Washington, Seattle, Washington
- Department of Epidemiology
- Department of Lab Medicine & Pathology, University of Washington
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Ruanne V Barnabas
- Department of Medicine, University of Washington, Seattle, Washington
- Department of Global Health
- Department of Epidemiology
| | - Thomas R Hawn
- Department of Medicine, University of Washington, Seattle, Washington
| | - David J Horne
- Department of Medicine, University of Washington, Seattle, Washington
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17
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van Doorn CLR, Eckold C, Ronacher K, Ruslami R, van Veen S, Lee JS, Kumar V, Kerry-Barnard S, Malherbe ST, Kleynhans L, Stanley K, Hill PC, Joosten SA, van Crevel R, Wijmenga C, Critchley JA, Walzl G, Alisjahbana B, Haks MC, Dockrell HM, Ottenhoff THM, Vianello E, Cliff JM. Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment. EBioMedicine 2022; 82:104173. [PMID: 35841871 PMCID: PMC9297076 DOI: 10.1016/j.ebiom.2022.104173] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/28/2022] [Accepted: 07/01/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control. METHODS Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n = 94) and Indonesia (n = 81), who had concomitant DM (n = 59), intermediate hyperglycaemia (n = 79) or normal glycaemia/no DM (n = 37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA. FINDINGS We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749). INTERPRETATION These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM. FUNDING The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).
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Affiliation(s)
- Cassandra L R van Doorn
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Clare Eckold
- Dept of Infection Biology and TB Centre, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, United Kingdom
| | - Katharina Ronacher
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa; Mater Research Institute - The University of Queensland, Translational Research Institute, Brisbane, QLD, Australia
| | - Rovina Ruslami
- TB-HIV Research Center, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia; Hasan Sadikin General Hospital, Bandung, Indonesia
| | - Suzanne van Veen
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Ji-Sook Lee
- Dept of Infection Biology and TB Centre, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, United Kingdom
| | - Vinod Kumar
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands; Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Sarah Kerry-Barnard
- Population Health Research Institute, St George's Hospital Medical School, University of London
| | - Stephanus T Malherbe
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Léanie Kleynhans
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Kim Stanley
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Philip C Hill
- Centre for International Health, Division of Health Sciences, University of Otago, Dunedin, New Zealand
| | - Simone A Joosten
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Reinout van Crevel
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Julia A Critchley
- Population Health Research Institute, St George's Hospital Medical School, University of London
| | - Gerhard Walzl
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Bachti Alisjahbana
- TB-HIV Research Center, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia; Hasan Sadikin General Hospital, Bandung, Indonesia
| | - Mariëlle C Haks
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Hazel M Dockrell
- Dept of Infection Biology and TB Centre, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, United Kingdom
| | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Eleonora Vianello
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands.
| | - Jacqueline M Cliff
- Dept of Infection Biology and TB Centre, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, United Kingdom; Department of Life Sciences, Brunel University London, United Kingdom
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Correia CN, McHugo GP, Browne JA, McLoughlin KE, Nalpas NC, Magee DA, Whelan AO, Villarreal-Ramos B, Vordermeier HM, Gormley E, Gordon SV, MacHugh DE. High-resolution transcriptomics of bovine purified protein derivative-stimulated peripheral blood from cattle infected with Mycobacterium bovis across an experimental time course. Tuberculosis (Edinb) 2022; 136:102235. [DOI: 10.1016/j.tube.2022.102235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/08/2022] [Accepted: 07/14/2022] [Indexed: 11/16/2022]
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19
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Kelly E, Whelan SO, Harriss E, Murphy S, Pollard AJ, O' Connor D. Systematic review of host genomic biomarkers of invasive bacterial disease: Distinguishing bacterial from non-bacterial causes of acute febrile illness. EBioMedicine 2022; 81:104110. [PMID: 35792524 PMCID: PMC9256842 DOI: 10.1016/j.ebiom.2022.104110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/27/2022] [Accepted: 05/28/2022] [Indexed: 12/03/2022] Open
Abstract
Background Infectious diseases play a significant role in the global burden of disease. The gold standard for the diagnosis of bacterial infection, bacterial culture, can lead to diagnostic delays and inappropriate antibiotic use. The advent of high- throughput technologies has led to the discovery of host-based genomic biomarkers of infection, capable of differentiating bacterial from other causes of infection, but few have achieved validation for use in a clinical setting. Methods A systematic review was performed. PubMed/Ovid Medline, Ovid Embase and Scopus databases were searched for relevant studies from inception up to 30/03/2022 with forward and backward citation searching of key references. Studies assessing the diagnostic performance of human host genomic biomarkers of bacterial infection were included. Study selection and assessment of quality were conducted by two independent reviewers. A meta-analysis was undertaken using a diagnostic random-effects model. The review was registered with PROSPERO (ID: CRD42021208462). Findings Seventy-two studies evaluating the performance of 116 biomarkers in 16,216 patients were included. Forty-six studies examined TB-specific biomarker performance and twenty-four studies assessed biomarker performance in a paediatric population. The results of pooled sensitivity, specificity, negative and positive likelihood ratio, and diagnostic odds ratio of genomic biomarkers of bacterial infection were 0.80 (95% CI 0.78 to 0.82), 0.86 (95% CI 0.84 to 0.88), 0.18 (95% CI 0.16 to 0.21), 5.5 (95% CI 4.9 to 6.3), 30.1 (95% CI 24 to 37), respectively. Significant between-study heterogeneity (I2 77%) was present. Interpretation Host derived genomic biomarkers show significant potential for clinical use as diagnostic tests of bacterial infection however, further validation and attention to test platform is warranted before clinical implementation can be achieved. Funding No funding received.
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Affiliation(s)
- Eimear Kelly
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford. UK; NIHR Oxford Biomedical Research Centre, Oxford, UK.
| | - Seán Olann Whelan
- Department of Clinical Microbiology, Galway University Hospital, Galway, Ireland
| | - Eli Harriss
- Bodleian Health Care Libraries, University of Oxford
| | - Sarah Murphy
- Department of Paediatrics, Cork University Maternity Hospital, Wilton, Cork, Ireland
| | - Andrew J Pollard
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford. UK; NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Daniel O' Connor
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford. UK; NIHR Oxford Biomedical Research Centre, Oxford, UK
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20
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Kalesinskas L, Gupta S, Khatri P. Increasing reproducibility, robustness, and generalizability of biomarker selection from meta-analysis using Bayesian methodology. PLoS Comput Biol 2022; 18:e1010260. [PMID: 35759523 PMCID: PMC9269905 DOI: 10.1371/journal.pcbi.1010260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 07/08/2022] [Accepted: 05/29/2022] [Indexed: 01/07/2023] Open
Abstract
A major limitation of gene expression biomarker studies is that they are not reproducible as they simply do not generalize to larger, real-world, heterogeneous populations. Frequentist multi-cohort gene expression meta-analysis has been frequently used as a solution to this problem to identify biomarkers that are truly differentially expressed. However, the frequentist meta-analysis framework has its limitations-it needs at least 4-5 datasets with hundreds of samples, is prone to confounding from outliers and relies on multiple-hypothesis corrected p-values. To address these shortcomings, we have created a Bayesian meta-analysis framework for the analysis of gene expression data. Using real-world data from three different diseases, we show that the Bayesian method is more robust to outliers, creates more informative estimates of between-study heterogeneity, reduces the number of false positive and false negative biomarkers and selects more generalizable biomarkers with less data. We have compared the Bayesian framework to a previously published frequentist framework and have developed a publicly available R package for use.
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Affiliation(s)
- Laurynas Kalesinskas
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, United States of America
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America
| | - Sanjana Gupta
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, United States of America
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, California, United States of America
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, United States of America
- * E-mail:
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21
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Qiu Q, Peng A, Zhao Y, Liu D, Liu C, Qiu S, Xu J, Cheng H, Xiong W, Chen Y. Diagnosis of pulmonary tuberculosis via identification of core genes and pathways utilizing blood transcriptional signatures: a multicohort analysis. Respir Res 2022; 23:125. [PMID: 35568895 PMCID: PMC9107189 DOI: 10.1186/s12931-022-02035-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Accepted: 04/25/2022] [Indexed: 12/04/2022] Open
Abstract
Background Blood transcriptomics can be used for confirmation of tuberculosis diagnosis or sputumless triage, and a comparison of their practical diagnostic accuracy is needed to assess their usefulness. In this study, we investigated potential biomarkers to improve our understanding of the pathogenesis of active pulmonary tuberculosis (PTB) using bioinformatics methods. Methods Differentially expressed genes (DEGs) were analyzed between PTB and healthy controls (HCs) based on two microarray datasets. Pathways and functional annotation of DEGs were identified and ten hub genes were selected. They were further analyzed and selected, then verified with an independent sample set. Finally, their diagnostic power was further evaluated between PTB and HCs or other diseases. Results 62 DEGs mostly related to type I IFN pathway, IFN-γ-mediated pathway, etc. in GO term and immune process, and especially RIG-I-like receptor pathway were acquired. Among them, OAS1, IFIT1 and IFIT3 were upregulated and were the main risk factors for predicting PTB, with adjusted risk ratios of 1.36, 3.10, and 1.32, respectively. These results further verified that peripheral blood mRNA expression levels of OAS1, IFIT1 and IFIT3 were significantly higher in PTB patients than HCs (all P < 0.01). The performance of a combination of these three genes (three-gene set) had exceeded that of all pairwise combinations of them in discriminating TB from HCs, with mean AUC reaching as high as 0.975 with a sensitivity of 94.4% and a specificity of 100%. The good discernibility capacity was evaluated d via 7 independent datasets with an AUC of 0.902, as well as mean sensitivity of 87.9% and mean specificity of 90.2%. In regards to discriminating PTB from other diseases (i.e., initially considered to be possible TB, but rejected in differential diagnosis), the three-gene set equally exhibited an overall strong ability to separate PTB from other diseases with an AUC of 0.999 (sensitivity: 99.0%; specificity: 100%) in the training set, and 0.974 with a sensitivity of 96.4% and a specificity of 98.6% in the test set. Conclusion The described commonalities and unique signatures in the blood profiles of PTB and the other control samples have considerable implications for PTB biosignature design and future diagnosis, and provide insights into the biological processes underlying PTB. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-02035-4.
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Affiliation(s)
- Qian Qiu
- Division of Infectious Diseases, Chongqing Public Health Medical Center, Southwest University, Chongqing, China
| | - Anzhou Peng
- Department of Tuberculosis, Chongqing Public Health Medical Center, Southwest University, Chongqing, China
| | - Yanlin Zhao
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dongxin Liu
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chunfa Liu
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shi Qiu
- Department of Nutrition, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, 100700, China
| | - Jinhong Xu
- Department of Oncology, Tongren People's Hospital Affiliated to Guizhou Medical University, Tongren, China
| | | | - Wei Xiong
- Department of Geriatrics, First Affiliated Hospital, Army Medical University, Chongqing, China.
| | - Yaokai Chen
- Division of Infectious Diseases, Chongqing Public Health Medical Center, Southwest University, Chongqing, China.
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22
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Mendelsohn SC, Mbandi SK, Fiore-Gartland A, Penn-Nicholson A, Musvosvi M, Mulenga H, Fisher M, Hadley K, Erasmus M, Nombida O, Tameris M, Walzl G, Naidoo K, Churchyard G, Hatherill M, Scriba TJ. Prospective multicentre head-to-head validation of host blood transcriptomic biomarkers for pulmonary tuberculosis by real-time PCR. COMMUNICATIONS MEDICINE 2022; 2:26. [PMID: 35342900 PMCID: PMC8954216 DOI: 10.1038/s43856-022-00086-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/10/2022] [Indexed: 01/31/2023] Open
Abstract
Background Sensitive point-of-care screening tests are urgently needed to identify individuals at highest risk of tuberculosis. We prospectively tested performance of host-blood transcriptomic tuberculosis signatures. Methods Adults without suspicion of tuberculosis were recruited from five endemic South African communities. Eight parsimonious host-blood transcriptomic tuberculosis signatures were measured by microfluidic RT-qPCR at enrolment. Upper respiratory swab specimens were tested with a multiplex bacterial-viral RT-qPCR panel in a subset of participants. Diagnostic and prognostic performance for microbiologically confirmed prevalent and incident pulmonary tuberculosis was tested in all participants at baseline and during active surveillance through 15 months follow-up, respectively. Results Among 20,207 HIV-uninfected and 963 HIV-infected adults screened; 2923 and 861 were enroled. There were 61 HIV-uninfected (weighted prevalence 1.1%) and 10 HIV-infected (prevalence 1.2%) tuberculosis cases at baseline. Parsimonious signature diagnostic performance was superior among symptomatic (AUCs 0.85-0.98) as compared to asymptomatic (AUCs 0.61-0.78) HIV-uninfected participants. Thereafter, 24 HIV-uninfected and 9 HIV-infected participants progressed to incident tuberculosis (1.1 and 1.0 per 100 person-years, respectively). Among HIV-uninfected individuals, prognostic performance for incident tuberculosis occurring within 6-12 months was higher relative to 15 months. 1000 HIV-uninfected participants were tested for respiratory microorganisms and 413 HIV-infected for HIV plasma viral load; 7/8 signature scores were higher (p < 0.05) in participants with viral respiratory infections or detectable HIV viraemia than those without. Conclusions Several parsimonious tuberculosis transcriptomic signatures met triage test targets among symptomatic participants, and incipient test targets within 6 months. However, the signatures were upregulated with viral infection and offered poor specificity for diagnosing sub-clinical tuberculosis.
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Affiliation(s)
- Simon C. Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Stanley Kimbung Mbandi
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Andrew Fiore-Gartland
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 USA
| | - Adam Penn-Nicholson
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Munyaradzi Musvosvi
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Humphrey Mulenga
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Michelle Fisher
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Katie Hadley
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Mzwandile Erasmus
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Onke Nombida
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Michèle Tameris
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Gerhard Walzl
- DST/NRF Centre of Excellence for Biomedical TB Research; South African Medical Research Council Centre for TB Research; Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, 7505 Cape Town, South Africa
| | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), 4001 Durban, South Africa
- MRC-CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Doris Duke Medical Research Institute, University of KwaZulu-Natal, 4001 Durban, South Africa
| | - Gavin Churchyard
- The Aurum Institute, 2194 Johannesburg, South Africa
- School of Public Health, University of Witwatersrand, 2193 Johannesburg, South Africa
- Department of Medicine, Vanderbilt University, Nashville, TN 37232 USA
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
| | - Thomas J. Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, 7925 Cape Town, South Africa
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23
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Guo Q, Zhong Y, Wang Z, Cao T, Zhang M, Zhang P, Huang W, Bi J, Yuan Y, Ou M, Zou X, Xiao G, Yang Y, Liu S, Liu L, Wang Z, Zhang G, Wu L. Single-cell transcriptomic landscape identifies the expansion of peripheral blood monocytes as an indicator of HIV-1-TB co-infection. CELL INSIGHT 2022; 1:100005. [PMID: 37192986 PMCID: PMC10120323 DOI: 10.1016/j.cellin.2022.100005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/27/2021] [Accepted: 01/18/2022] [Indexed: 05/18/2023]
Abstract
Certain circulating cell subsets are involved in immune dysregulation in human immunodeficiency virus type 1 (HIV-1) and tuberculosis (TB) co-infection; however, the characteristics and role of these subclusters are unknown. Peripheral blood mononuclear cells (PBMCs) of patients with HIV-1 infection alone (HIV-pre) and those with HIV-1-TB co-infection without anti-TB treatment (HIV-pre & TB-pre) and with anti-TB treatment for 2 weeks (HIV-pre & TB-pos) were subjected to single-cell RNA sequencing (scRNA-seq) to characterize the transcriptome of different immune cell subclusters. We obtained > 60,000 cells and identified 32 cell subclusters based on gene expression. The proportion of immune-cell subclusters was altered in HIV-1-TB co-infected individuals compared with that in HIV-pre-group, indicating immune dysregulation corresponding to different disease states. The proportion of an inflammatory CD14+CD16+ monocyte subset was higher in the HIV-pre & TB-pre group than in the HIV-pre group; this was validated in an additional cohort (n = 80) via a blood cell differential test, which also demonstrated a good discriminative performance (area under the curve, 0.8046). These findings depicted the atlas of immune PBMC subclusters in HIV-1-TB co-infection and demonstrate that monocyte subsets in peripheral blood might serve as a discriminating biomarker for diagnosis of HIV-1-TB co-infection.
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Affiliation(s)
- Qinglong Guo
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Yu Zhong
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Zhifeng Wang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Tingzhi Cao
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Mingyuan Zhang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Peiyan Zhang
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Waidong Huang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jing Bi
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Yue Yuan
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Min Ou
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Xuanxuan Zou
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guohui Xiao
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Yuan Yang
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Shiping Liu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Single-cell Omics, BGI-Shenzhen, Shenzhen, 518100, China
| | - Longqi Liu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Zhaoqin Wang
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Guoliang Zhang
- National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Liang Wu
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Single-cell Omics, BGI-Shenzhen, Shenzhen, 518100, China
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Kaipilyawar V, Zhao Y, Wang X, Joseph NM, Knudsen S, Prakash Babu S, Muthaiah M, Hochberg NS, Sarkar S, Horsburgh CR, Ellner JJ, Johnson WE, Salgame P. Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform. Clin Infect Dis 2022; 75:1022-1030. [PMID: 35015839 PMCID: PMC9522394 DOI: 10.1093/cid/ciac010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers. METHODS The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker. RESULTS Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB. CONCLUSIONS The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.
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Affiliation(s)
| | | | | | - Noyal M Joseph
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | | | - Senbagavalli Prakash Babu
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Muthuraj Muthaiah
- Department of Microbiology, State TB Training and Demonstration Center, Government Hospital for Chest Disease, Gorimedu, Puducherry, India
| | - Natasha S Hochberg
- Boston Medical Center, Boston, Massachusetts, USA,Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA,Department of Medicine, Section of Infectious Diseases, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Sonali Sarkar
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Charles R Horsburgh
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Jerrold J Ellner
- Department of Medicine, Center for Emerging Pathogens, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | | | - Padmini Salgame
- Correspondence: Padmini Salgame, Rutgers–New Jersey Medical School, International Center for Public Health, 225 Warren St, Room W250H, Newark, NJ 07103 ()
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Tabone O, Verma R, Singhania A, Chakravarty P, Branchett WJ, Graham CM, Lee J, Trang T, Reynier F, Leissner P, Kaiser K, Rodrigue M, Woltmann G, Haldar P, O'Garra A. Blood transcriptomics reveal the evolution and resolution of the immune response in tuberculosis. J Exp Med 2021; 218:212624. [PMID: 34491266 PMCID: PMC8493863 DOI: 10.1084/jem.20210915] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/08/2021] [Accepted: 08/05/2021] [Indexed: 12/02/2022] Open
Abstract
Blood transcriptomics have revealed major characteristics of the immune response in active TB, but the signature early after infection is unknown. In a unique clinically and temporally well-defined cohort of household contacts of active TB patients that progressed to TB, we define minimal changes in gene expression in incipient TB increasing in subclinical and clinical TB. While increasing with time, changes in gene expression were highest at 30 d before diagnosis, with heterogeneity in the response in household TB contacts and in a published cohort of TB progressors as they progressed to TB, at a bulk cohort level and in individual progressors. Blood signatures from patients before and during anti-TB treatment robustly monitored the treatment response distinguishing early and late responders. Blood transcriptomics thus reveal the evolution and resolution of the immune response in TB, which may help in clinical management of the disease.
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Affiliation(s)
- Olivier Tabone
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Raman Verma
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Akul Singhania
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | | | - William J Branchett
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Christine M Graham
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Jo Lee
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Tran Trang
- Bioaster Microbiology Technology Institute, Lyon, France
| | | | | | - Karine Kaiser
- Medical Diagnostic Discovery Department, bioMérieux SA, Marcy l'Etoile, France
| | - Marc Rodrigue
- Global Medical Affairs, bioMérieux SA, Marcy l'Etoile, France
| | - Gerrit Woltmann
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Pranabashis Haldar
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Anne O'Garra
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK.,National Heart and Lung Institute, Imperial College London, London, UK
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Heyckendorf J, Marwitz S, Reimann M, Avsar K, DiNardo AR, Günther G, Hoelscher M, Ibraim E, Kalsdorf B, Kaufmann SHE, Kontsevaya I, van Leth F, Mandalakas AM, Maurer FP, Müller M, Nitschkowski D, Olaru ID, Popa C, Rachow A, Rolling T, Rybniker J, Salzer HJF, Sanchez-Carballo P, Schuhmann M, Schaub D, Spinu V, Suárez I, Terhalle E, Unnewehr M, Weiner J, Goldmann T, Lange C. Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model. Eur Respir J 2021; 58:13993003.03492-2020. [PMID: 33574078 DOI: 10.1183/13993003.03492-2020] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 01/20/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND The World Health Organization recommends standardised treatment durations for patients with tuberculosis (TB). We identified and validated a host-RNA signature as a biomarker for individualised therapy durations for patients with drug-susceptible (DS)- and multidrug-resistant (MDR)-TB. METHODS Adult patients with pulmonary TB were prospectively enrolled into five independent cohorts in Germany and Romania. Clinical and microbiological data and whole blood for RNA transcriptomic analysis were collected at pre-defined time points throughout therapy. Treatment outcomes were ascertained by TBnet criteria (6-month culture status/1-year follow-up). A whole-blood RNA therapy-end model was developed in a multistep process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment time points. RESULTS 50 patients with DS-TB and 30 patients with MDR-TB were recruited in the German identification cohorts (DS-GIC and MDR-GIC, respectively); 28 patients with DS-TB and 32 patients with MDR-TB in the German validation cohorts (DS-GVC and MDR-GVC, respectively); and 52 patients with MDR-TB in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model (TB22) that defined cure-associated end-of-therapy time points was derived from the DS- and MDR-GIC data. The TB22 model was superior to other published signatures to accurately predict clinical outcomes for patients in the DS-GVC (area under the curve 0.94, 95% CI 0.9-0.98) and suggests that cure may be achieved with shorter treatment durations for TB patients in the MDR-GIC (mean reduction 218.0 days, 34.2%; p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%; p<0.001) and the MDR-RVC (mean reduction of 161.0 days, 23.4%; p=0.001). CONCLUSION Biomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.
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Affiliation(s)
- Jan Heyckendorf
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany .,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany.,Authors contributed equally
| | - Sebastian Marwitz
- Pathology of the Universal Medical Center Schleswig-Holstein (UKSH) and the Research Center Borstel, Campus Borstel, Airway Research Center North (ARCN), Borstel, Germany.,German Center for Lung Research (DZL), Germany.,Authors contributed equally
| | - Maja Reimann
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany.,Authors contributed equally
| | - Korkut Avsar
- Asklepios Fachkliniken München-Gauting, Munich, Germany
| | - Andrew R DiNardo
- The Global TB Program, Dept of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
| | - Gunar Günther
- Dept of Medicine, University of Namibia School of Medicine, Windhoek, Namibia.,Inselspital Bern, Dept of Pulmonology, Bern, Switzerland
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.,German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Elmira Ibraim
- Institutul de Pneumoftiziologie "Marius Nasta", MDR-TB Research Department, Bucharest, Romania
| | - Barbara Kalsdorf
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Stefan H E Kaufmann
- Max Planck Institute for Infection Biology, Berlin, Germany.,Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.,Hagler Institute for Advanced Study, Texas A&M University, College Station, TX, USA
| | - Irina Kontsevaya
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Frank van Leth
- Dept of Global Health, Amsterdam University Medical Centres, Location AMC, Amsterdam, The Netherlands.,Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | - Anna M Mandalakas
- The Global TB Program, Dept of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
| | - Florian P Maurer
- National and WHO Supranational Reference Laboratory for Mycobacteria, Research Center Borstel, Borstel, Germany.,Institute of Medical Microbiology, Virology and Hygiene, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Dörte Nitschkowski
- Pathology of the Universal Medical Center Schleswig-Holstein (UKSH) and the Research Center Borstel, Campus Borstel, Airway Research Center North (ARCN), Borstel, Germany.,German Center for Lung Research (DZL), Germany
| | - Ioana D Olaru
- London School of Hygiene and Tropical Medicine, London, UK.,Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Cristina Popa
- Institutul de Pneumoftiziologie "Marius Nasta", MDR-TB Research Department, Bucharest, Romania
| | - Andrea Rachow
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.,German Center for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Thierry Rolling
- German Center for Infection Research (DZIF), Germany.,Division of Infectious Diseases, I. Dept of Internal Medicine, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.,Dept of Clinical Immunology of Infectious Diseases, Bernhard-Nocht-Institute for Tropical Medicine, Hamburg, Germany
| | - Jan Rybniker
- Dept I of Internal Medicine, Division of Infectious Diseases, University of Cologne, Cologne, Germany.,German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
| | | | - Patricia Sanchez-Carballo
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | | | - Dagmar Schaub
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Victor Spinu
- Institutul de Pneumoftiziologie "Marius Nasta", MDR-TB Research Department, Bucharest, Romania
| | - Isabelle Suárez
- Dept I of Internal Medicine, Division of Infectious Diseases, University of Cologne, Cologne, Germany
| | - Elena Terhalle
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Markus Unnewehr
- Dept of Respiratory Medicine and Infectious Diseases, St. Barbara-Klinik, Hamm, Germany.,University of Witten-Herdecke, Witten, Germany
| | - January Weiner
- Berlin Institute of HealthCUBI (Core Unit Bioinformatics), Berlin, Germany
| | - Torsten Goldmann
- Pathology of the Universal Medical Center Schleswig-Holstein (UKSH) and the Research Center Borstel, Campus Borstel, Airway Research Center North (ARCN), Borstel, Germany.,German Center for Lung Research (DZL), Germany.,Authors contributed equally
| | - Christoph Lange
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany.,German Center for Infection Research (DZIF), Germany.,International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany.,Dept of Medicine, Karolinska Institute, Stockholm, Sweden.,Authors contributed equally
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27
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Domaszewska T, Zyla J, Otto R, Kaufmann SHE, Weiner J. Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients. Front Immunol 2021; 12:694680. [PMID: 34421903 PMCID: PMC8375662 DOI: 10.3389/fimmu.2021.694680] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/19/2021] [Indexed: 11/22/2022] Open
Abstract
Group-aggregated responses to tuberculosis (TB) have been well characterized on a molecular level. However, human beings differ and individual responses to infection vary. We have combined a novel approach to individual gene set analysis (GSA) with the clustering of transcriptomic profiles of TB patients from seven datasets in order to identify individual molecular endotypes of transcriptomic responses to TB. We found that TB patients differ with respect to the intensity of their hallmark interferon (IFN) responses, but they also show variability in their complement system, metabolic responses and multiple other pathways. This variability cannot be sufficiently explained with covariates such as gender or age, and the molecular endotypes are found across studies and populations. Using datasets from a Cynomolgus macaque model of TB, we revealed that transcriptional signatures of different molecular TB endotypes did not depend on TB progression post-infection. Moreover, we provide evidence that patients with molecular endotypes characterized by high levels of IFN responses (IFN-rich), suffered from more severe lung pathology than those with lower levels of IFN responses (IFN-low). Harnessing machine learning (ML) models, we derived gene signatures classifying IFN-rich and IFN-low TB endotypes and revealed that the IFN-low signature allowed slightly more reliable overall classification of TB patients from non-TB patients than the IFN-rich one. Using the paradigm of molecular endotypes and the ML-based predictions allows more precisely tailored treatment regimens, predicting treatment-outcome with higher accuracy and therefore bridging the gap between conventional treatment and precision medicine.
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Affiliation(s)
- Teresa Domaszewska
- Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany
- Department for Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany
| | - Joanna Zyla
- Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Raik Otto
- Knowledge Management in Bioinformatics, Institute for Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan H. E. Kaufmann
- Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany
- Max Planck Institute for Biophysical Chemistry, Emeritus Group Systems Immunology, Göttingen, Germany
- Hagler Institute for Advanced Study, Texas A&M University, College Station, TX, United States
| | - January Weiner
- Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany
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28
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Bayaa R, Ndiaye MDB, Chedid C, Kokhreidze E, Tukvadze N, Banu S, Uddin MKM, Biswas S, Nasrin R, Ranaivomanana P, Raherinandrasana AH, Rakotonirina J, Rasolofo V, Delogu G, De Maio F, Goletti D, Endtz H, Ader F, Hamze M, Ismail MB, Pouzol S, Rakotosamimanana N, Hoffmann J. Multi-country evaluation of RISK6, a 6-gene blood transcriptomic signature, for tuberculosis diagnosis and treatment monitoring. Sci Rep 2021; 11:13646. [PMID: 34211042 PMCID: PMC8249600 DOI: 10.1038/s41598-021-93059-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/21/2021] [Indexed: 12/31/2022] Open
Abstract
There is a crucial need for non-sputum-based TB tests. Here, we evaluate the performance of RISK6, a human-blood transcriptomic signature, for TB screening, triage and treatment monitoring. RISK6 performance was also compared to that of two IGRAs: one based on RD1 antigens (QuantiFERON-TB Gold Plus, QFT-P, Qiagen) and one on recombinant M. tuberculosis HBHA expressed in Mycobacterium smegmatis (IGRA-rmsHBHA). In this multicenter prospective nested case-control study conducted in Bangladesh, Georgia, Lebanon and Madagascar, adult non-immunocompromised patients with bacteriologically confirmed active pulmonary TB (ATB), latent TB infection (LTBI) and healthy donors (HD) were enrolled. ATB patients were followed-up during and after treatment. Blood RISK6 scores were assessed using quantitative real-time PCR and evaluated by area under the receiver-operating characteristic curve (ROC AUC). RISK6 performance to discriminate ATB from HD reached an AUC of 0.94 (95% CI 0.89-0.99), with 90.9% sensitivity and 87.8% specificity, thus achieving the minimal WHO target product profile for a non-sputum-based TB screening test. Besides, RISK6 yielded an AUC of 0.93 (95% CI 0.85-1) with 90.9% sensitivity and 88.5% specificity for discriminating ATB from LTBI. Moreover, RISK6 showed higher performance (AUC 0.90, 95% CI 0.85-0.94) than IGRA-rmsHBHA (AUC 0.75, 95% CI 0.69-0.82) to differentiate TB infection stages. Finally, RISK6 signature scores significantly decreased after 2 months of TB treatment and continued to decrease gradually until the end of treatment reaching scores obtained in HD. We confirmed the performance of RISK6 signature as a triage TB test and its utility for treatment monitoring.
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Affiliation(s)
- Rim Bayaa
- Medical and Scientific Department, Fondation Mérieux, Lyon, France. .,Laboratoire Microbiologie, Santé et Environnement (LMSE), Doctoral School of Sciences and Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon.
| | - Mame Diarra Bousso Ndiaye
- Medical and Scientific Department, Fondation Mérieux, Lyon, France.,Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - Carole Chedid
- Medical and Scientific Department, Fondation Mérieux, Lyon, France.,Department of Biology, Ecole Normale Supérieure de Lyon, Lyon, France.,Equipe Pathogénèse des Légionelles, International Center for Research in Infectiology, INSERM U1111, University Lyon 1, CNRS UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Eka Kokhreidze
- National Center for Tuberculosis and Lung Diseases (NCTLD), Tbilisi, Georgia
| | - Nestani Tukvadze
- National Center for Tuberculosis and Lung Diseases (NCTLD), Tbilisi, Georgia
| | - Sayera Banu
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | | | - Samanta Biswas
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Rumana Nasrin
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | | | | | - Julio Rakotonirina
- Centre Hospitalier Universitaire de Soins et Santé Publique Analakely (CHUSSPA), Antananarivo, Madagascar
| | | | - Giovanni Delogu
- Dipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
| | - Flavio De Maio
- Dipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
| | - Delia Goletti
- Translational Research Unit, Department of Epidemiology and Preclinical Research, "L. Spallanzani" National Institute for Infectious Diseases (INMI), IRCCS, Rome, Italy
| | - Hubert Endtz
- Erasmus MC, Medical Microbiology and Infectious Diseases, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Florence Ader
- Service des Maladies Infectieuses et Tropicales, Hospices Civils de Lyon, Lyon, France
| | - Monzer Hamze
- Laboratoire Microbiologie, Santé et Environnement (LMSE), Doctoral School of Sciences and Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon
| | - Mohamad Bachar Ismail
- Laboratoire Microbiologie, Santé et Environnement (LMSE), Doctoral School of Sciences and Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon
| | - Stéphane Pouzol
- Medical and Scientific Department, Fondation Mérieux, Lyon, France
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29
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Gong Z, Gu Y, Xiong K, Niu J, Zheng R, Su B, Fan L, Xie J. The Evaluation and Validation of Blood-Derived Novel Biomarkers for Precise and Rapid Diagnosis of Tuberculosis in Areas With High-TB Burden. Front Microbiol 2021; 12:650567. [PMID: 34194403 PMCID: PMC8236956 DOI: 10.3389/fmicb.2021.650567] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 04/27/2021] [Indexed: 12/12/2022] Open
Abstract
Tuberculosis (TB) remains a highly contagious public health threat. Precise and prompt diagnosis and monitoring of treatment responses are urgently needed for clinics. To pursue novel and satisfied host blood-derived biomarkers, we streamlined a bioinformatic pipeline by integrating differentially expressed genes, a gene co-expression network, and short time-series analysis to mine the published transcriptomes derived from whole blood of TB patients in the GEO database, followed by validating the diagnostic performance of biomarkers in both independent datasets and blood samples of Chinese patients using quantitative real-time PCR (qRT-PCR). We found that four genes, namely UBE2L6 (Ubiquitin/ISG15-conjugating enzyme E2 L6), BATF2 (Basic leucine zipper transcriptional factor ATF-like), SERPING1 (Plasma protease C1 inhibitor), and VAMP5 (Vesicle-associated membrane protein 5), had high diagnostic value for active TB. The transcription levels of these four gene combinations can reach up to 88% sensitivity and 78% specificity (average) for the diagnosis of active TB; the highest sensitivity can achieve 100% by parallel of BATF2 and VAMP5, and the highest specificity can reach 89.5% through a combination of SERPIG1, UBE2L6, and VAMP5, which were significantly higher than 75.3% sensitivity and 69.1% specificity by T-SPOT.TB in the same patients. Quite unexpectedly, the gene set can assess the efficacy of anti-TB response and differentiate active TB from Latent TB infection. The data demonstrated these four biomarkers might have great potency and advantage over IGRAs in the diagnosis of TB.
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Affiliation(s)
- Zhen Gong
- State Key Laboratory Breeding Base of Eco-Environment and Bio-Resource of the Three Gorges Area, Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Ministry of Education, School of Life Sciences, Institute of Modern Biopharmaceuticals, Southwest University, Chongqing, China
| | - Yinzhong Gu
- State Key Laboratory Breeding Base of Eco-Environment and Bio-Resource of the Three Gorges Area, Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Ministry of Education, School of Life Sciences, Institute of Modern Biopharmaceuticals, Southwest University, Chongqing, China
| | - Kunlong Xiong
- Shanghai Key Laboratory of Tuberculosis, Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jinxia Niu
- College of Fisheries and Life Sciences, Shanghai Ocean University, Shanghai, China
| | - Ruijuan Zheng
- Shanghai Key Laboratory of Tuberculosis, Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Bo Su
- Shanghai Key Laboratory of Tuberculosis, Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lin Fan
- Shanghai Key Laboratory of Tuberculosis, Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jianping Xie
- State Key Laboratory Breeding Base of Eco-Environment and Bio-Resource of the Three Gorges Area, Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Ministry of Education, School of Life Sciences, Institute of Modern Biopharmaceuticals, Southwest University, Chongqing, China
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30
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McLoughlin KE, Correia CN, Browne JA, Magee DA, Nalpas NC, Rue-Albrecht K, Whelan AO, Villarreal-Ramos B, Vordermeier HM, Gormley E, Gordon SV, MacHugh DE. RNA-Seq Transcriptome Analysis of Peripheral Blood From Cattle Infected With Mycobacterium bovis Across an Experimental Time Course. Front Vet Sci 2021; 8:662002. [PMID: 34124223 PMCID: PMC8193354 DOI: 10.3389/fvets.2021.662002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/06/2021] [Indexed: 12/14/2022] Open
Abstract
Bovine tuberculosis, caused by infection with members of the Mycobacterium tuberculosis complex, particularly Mycobacterium bovis, is a major endemic disease affecting cattle populations worldwide, despite the implementation of stringent surveillance and control programs in many countries. The development of high-throughput functional genomics technologies, including RNA sequencing, has enabled detailed analysis of the host transcriptome to M. bovis infection, particularly at the macrophage and peripheral blood level. In the present study, we have analysed the transcriptome of bovine whole peripheral blood samples collected at −1 week pre-infection and +1, +2, +6, +10, and +12 weeks post-infection time points. Differentially expressed genes were catalogued and evaluated at each post-infection time point relative to the −1 week pre-infection time point and used for the identification of putative candidate host transcriptional biomarkers for M. bovis infection. Differentially expressed gene sets were also used for examination of cellular pathways associated with the host response to M. bovis infection, construction of de novo gene interaction networks enriched for host differentially expressed genes, and time-series analyses to identify functionally important groups of genes displaying similar patterns of expression across the infection time course. A notable outcome of these analyses was identification of a 19-gene transcriptional biosignature of infection consisting of genes increased in expression across the time course from +1 week to +12 weeks post-infection.
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Affiliation(s)
- Kirsten E McLoughlin
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Carolina N Correia
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - John A Browne
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - David A Magee
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Nicolas C Nalpas
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Kevin Rue-Albrecht
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Adam O Whelan
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - Bernardo Villarreal-Ramos
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - H Martin Vordermeier
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - Eamonn Gormley
- UCD School of Veterinary Medicine, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Stephen V Gordon
- UCD School of Veterinary Medicine, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - David E MacHugh
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
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31
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Xu F, Qi H, Li J, Sun L, Gong J, Chen Y, Shen A, Li W. Mycobacterium tuberculosis infection up-regulates MFN2 expression to promote NLRP3 inflammasome formation. J Biol Chem 2021; 295:17684-17697. [PMID: 33454007 PMCID: PMC7762945 DOI: 10.1074/jbc.ra120.014077] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 10/08/2020] [Indexed: 12/18/2022] Open
Abstract
Tuberculosis (TB), caused by the infection of Mycobacterium tuberculosis (MTB), is one of the leading causes of death worldwide, especially in children. However, the mechanisms by which MTB infects its cellular host, activates an immune response, and triggers inflammation remain unknown. Mitochondria play important roles in the initiation and activation of the nucleotide-binding oligomerization domain-like receptor with a pyrin domain 3 (NLRP3) inflammasome, where mitochondria-associated endoplasmic reticulum membranes (MAMs) may serve as the platform for inflammasome assembly and activation. Additionally, mitofusin 2 (MFN2) is implicated in the formation of MAMs, but, the roles of mitochondria and MFN2 in MTB infection have not been elucidated. Using mircroarry profiling of TB patients and in vitro MTB stimulation of macrophages, we observed an up-regulation of MFN2 in the peripheral blood mononuclear cells of active TB patients. Furthermore, we found that MTB stimulation by MTB-specific antigen ESAT-6 or lysate of MTB promoted MFN2 interaction with NLRP3 inflammasomes, resulting in the assembly and activation of the inflammasome and, subsequently, IL-1β secretion. These findings suggest that MFN2 and mitochondria play important role in the pathogen-host interaction during MTB infection.
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Affiliation(s)
- Fang Xu
- Beijing Key Laboratory for Respiratory and Infectious Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Hui Qi
- Beijing Key Laboratory for Respiratory and Infectious Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Jieqiong Li
- Beijing Key Laboratory for Respiratory and Infectious Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Lin Sun
- Beijing Key Laboratory for Respiratory and Infectious Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Juanjuan Gong
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yuanying Chen
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Adong Shen
- Beijing Key Laboratory for Respiratory and Infectious Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
| | - Wei Li
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
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32
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Perumal P, Abdullatif MB, Garlant HN, Honeyborne I, Lipman M, McHugh TD, Southern J, Breen R, Santis G, Ellappan K, Kumar SV, Belgode H, Abubakar I, Sinha S, Vasan SS, Joseph N, Kempsell KE. Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR. Front Immunol 2021; 11:612564. [PMID: 33841389 PMCID: PMC8029985 DOI: 10.3389/fimmu.2020.612564] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/23/2020] [Indexed: 12/18/2022] Open
Abstract
Tuberculosis (TB) remains a major global threat and diagnosis of active TB ((ATB) both extra-pulmonary (EPTB), pulmonary (PTB)) and latent TB (LTBI) infection remains challenging, particularly in high-burden countries which still rely heavily on conventional methods. Although molecular diagnostic methods are available, e.g., Cepheid GeneXpert, they are not universally available in all high TB burden countries. There is intense focus on immune biomarkers for use in TB diagnosis, which could provide alternative low-cost, rapid diagnostic solutions. In our previous gene expression studies, we identified peripheral blood leukocyte (PBL) mRNA biomarkers in a non-human primate TB aerosol-challenge model. Here, we describe a study to further validate select mRNA biomarkers from this prior study in new cohorts of patients and controls, as a prerequisite for further development. Whole blood mRNA was purified from ATB patients recruited in the UK and India, LTBI and two groups of controls from the UK (i) a low TB incidence region (CNTRLA) and (ii) individuals variably-domiciled in the UK and Asia ((CNTRLB), the latter TB high incidence regions). Seventy-two mRNA biomarker gene targets were analyzed by qPCR using the Roche Lightcycler 480 qPCR platform and data analyzed using GeneSpring™ 14.9 bioinformatics software. Differential expression of fifty-three biomarkers was confirmed between MTB infected, LTBI groups and controls, seventeen of which were significant using analysis of variance (ANOVA): CALCOCO2, CD52, GBP1, GBP2, GBP5, HLA-B, IFIT3, IFITM3, IRF1, LOC400759 (GBP1P1), NCF1C, PF4V1, SAMD9L, S100A11, TAF10, TAPBP, and TRIM25. These were analyzed using receiver operating characteristic (ROC) curve analysis. Single biomarkers and biomarker combinations were further assessed using simple arithmetic algorithms. Minimal combination biomarker panels were delineated for primary diagnosis of ATB (both PTB and EPTB), LTBI and identifying LTBI individuals at high risk of progression which showed good performance characteristics. These were assessed for suitability for progression against the standards for new TB diagnostic tests delineated in the published World Health Organization (WHO) technology product profiles (TPPs).
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Affiliation(s)
- Prem Perumal
- Public Health England, Porton Down, Salisbury, Wiltshire, United Kingdom
| | | | - Harriet N. Garlant
- Public Health England, Porton Down, Salisbury, Wiltshire, United Kingdom
| | - Isobella Honeyborne
- Centre for Clinical Microbiology, University College London, Royal Free Campus, London, United Kingdom
| | - Marc Lipman
- UCL Respiratory, University College London, Royal Free Campus, London, United Kingdom
| | - Timothy D. McHugh
- Centre for Clinical Microbiology, University College London, Royal Free Campus, London, United Kingdom
| | - Jo Southern
- Institute for Global Health, University College London, London, United Kingdom
| | - Ronan Breen
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - George Santis
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Kalaiarasan Ellappan
- Jawaharlal Institute of Postgraduate Medical Education and Research, Dhanvantri Nagar, Gorimedu, Puducherry, India
| | - Saka Vinod Kumar
- Jawaharlal Institute of Postgraduate Medical Education and Research, Dhanvantri Nagar, Gorimedu, Puducherry, India
| | - Harish Belgode
- Jawaharlal Institute of Postgraduate Medical Education and Research, Dhanvantri Nagar, Gorimedu, Puducherry, India
| | - Ibrahim Abubakar
- Institute for Global Health, University College London, London, United Kingdom
| | - Sanjeev Sinha
- Department of Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
| | - Seshadri S. Vasan
- Public Health England, Porton Down, Salisbury, Wiltshire, United Kingdom
- Department of Health Sciences, University of York, York, United Kingdom
| | - Noyal Joseph
- Jawaharlal Institute of Postgraduate Medical Education and Research, Dhanvantri Nagar, Gorimedu, Puducherry, India
| | - Karen E. Kempsell
- Public Health England, Porton Down, Salisbury, Wiltshire, United Kingdom
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Suliman S, Gela A, Mendelsohn SC, Iwany SK, Tamara KL, Mabwe S, Bilek N, Darboe F, Fisher M, Corbett AJ, Kjer-Nielsen L, Eckle SBG, Huang CC, Zhang Z, Lewinsohn DM, McCluskey J, Rossjohn J, Hatherill M, León SR, Calderon RI, Lecca L, Murray M, Scriba TJ, Van Rhijn I, Moody DB. Peripheral Blood Mucosal-Associated Invariant T Cells in Tuberculosis Patients and Healthy Mycobacterium tuberculosis-Exposed Controls. J Infect Dis 2021; 222:995-1007. [PMID: 32267943 DOI: 10.1093/infdis/jiaa173] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 04/06/2020] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND In human blood, mucosal-associated invariant T (MAIT) cells are abundant T cells that recognize antigens presented on non-polymorphic major histocompatibility complex-related 1 (MR1) molecules. The MAIT cells are activated by mycobacteria, and prior human studies indicate that blood frequencies of MAIT cells, defined by cell surface markers, decline during tuberculosis (TB) disease, consistent with redistribution to the lungs. METHODS We tested whether frequencies of blood MAIT cells were altered in patients with TB disease relative to healthy Mycobacterium tuberculosis-exposed controls from Peru and South Africa. We quantified their frequencies using MR1 tetramers loaded with 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil. RESULTS Unlike findings from prior studies, frequencies of blood MAIT cells were similar among patients with TB disease and latent and uninfected controls. In both cohorts, frequencies of MAIT cells defined by MR1-tetramer staining and coexpression of CD161 and the T-cell receptor alpha variable gene TRAV1-2 were strongly correlated. Disease severity captured by body mass index or TB disease transcriptional signatures did not correlate with MAIT cell frequencies in patients with TB. CONCLUSIONS Major histocompatibility complex (MHC)-related 1-restrictied MAIT cells are detected at similar levels with tetramers or surface markers. Unlike MHC-restricted T cells, blood frequencies of MAIT cells are poor correlates of TB disease but may play a role in pathophysiology.
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Affiliation(s)
- Sara Suliman
- Division of Rheumatology, Immunity and Inflammation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Anele Gela
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Simon C Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Sarah K Iwany
- Division of Rheumatology, Immunity and Inflammation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kattya Lopez Tamara
- Division of Rheumatology, Immunity and Inflammation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Socios En Salud Sucursal Peru, Lima, Peru
| | - Simbarashe Mabwe
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Nicole Bilek
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Fatoumatta Darboe
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Michelle Fisher
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Alexandra J Corbett
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Lars Kjer-Nielsen
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Sidonia B G Eckle
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Chuan-Chin Huang
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Zibiao Zhang
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - David M Lewinsohn
- Pulmonary and Critical Care Medicine, Oregon Health and Science University, Portland VA Medical Center, Portland, Oregon, USA
| | - James McCluskey
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Jamie Rossjohn
- Infection and Immunity Program and The Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.,Australian Research Council Centre of Excellence in Advanced Molecular Imaging, Monash University, Clayton, Victoria, Australia.,Institute of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, United Kingdom
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | | | | | - Leonid Lecca
- Socios En Salud Sucursal Peru, Lima, Peru.,Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Megan Murray
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Ildiko Van Rhijn
- Division of Rheumatology, Immunity and Inflammation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - D Branch Moody
- Division of Rheumatology, Immunity and Inflammation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Gliddon HD, Kaforou M, Alikian M, Habgood-Coote D, Zhou C, Oni T, Anderson ST, Brent AJ, Crampin AC, Eley B, Heyderman R, Kern F, Langford PR, Ottenhoff THM, Hibberd ML, French N, Wright VJ, Dockrell HM, Coin LJ, Wilkinson RJ, Levin M. Identification of Reduced Host Transcriptomic Signatures for Tuberculosis Disease and Digital PCR-Based Validation and Quantification. Front Immunol 2021; 12:637164. [PMID: 33763081 PMCID: PMC7982854 DOI: 10.3389/fimmu.2021.637164] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 02/03/2021] [Indexed: 12/18/2022] Open
Abstract
Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.
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Affiliation(s)
- Harriet D Gliddon
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,National Public Health Speciality Training Programme, South West, United Kingdom
| | - Myrsini Kaforou
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Mary Alikian
- Imperial Molecular Pathology, Imperial Healthcare Trust, Hammersmith Hospital, London, United Kingdom.,Centre for Haematology, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Dominic Habgood-Coote
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Chenxi Zhou
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Tolu Oni
- School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Suzanne T Anderson
- Brighton and Sussex Medical School, Brighton, United Kingdom.,Brighton and Malawi Liverpool Wellcome Trust Unit, Blantyre, Malawi
| | - Andrew J Brent
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,Oxford University Hospitals National Health Service (NHS) Foundation Trust, Oxford, United Kingdom
| | - Amelia C Crampin
- Malawi Epidemiology and Intervention Research Unit, Chilumba, Malawi.,London School of Hygiene & Tropical Medicine, London, United Kingdom.,Karonga Prevention Study, Chilumba, Malawi
| | - Brian Eley
- Paediatric Infectious Diseases Unit, Red Cross War Memorial Children's Hospital, Cape Town, South Africa.,Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa
| | - Robert Heyderman
- Division of Infection and Immunity, Faculty of Medical Sciences, University College London, London, United Kingdom
| | - Florian Kern
- Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom.,Brighton and Sussex University Hospitals National Health Service (NHS) Trust, Brighton, United Kingdom
| | - Paul R Langford
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, Netherlands
| | - Martin L Hibberd
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Neil French
- Tropical and Infectious Disease Unit, Royal Liverpool and Broadgreen University Hospitals National Health Service (NHS) Trust, Liverpool, United Kingdom.,Centre for Global Vaccine Research, Institute of Infection & Global Health, University of Liverpool, Liverpool, United Kingdom
| | - Victoria J Wright
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Hazel M Dockrell
- Department of Immunology and Infection, and Tuberculosis (TB) Centre, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Lachlan J Coin
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Robert J Wilkinson
- The Francis Crick Institute, London, United Kingdom.,Department of Medicine, Imperial College London, London, United Kingdom.,Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Michael Levin
- Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
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Kanabalan RD, Lee LJ, Lee TY, Chong PP, Hassan L, Ismail R, Chin VK. Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery. Microbiol Res 2021; 246:126674. [PMID: 33549960 DOI: 10.1016/j.micres.2020.126674] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 12/09/2020] [Accepted: 12/16/2020] [Indexed: 12/16/2022]
Abstract
Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.
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Affiliation(s)
- Renuga Devi Kanabalan
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
| | - Le Jie Lee
- Prima Nexus Sdn. Bhd., Menara CIMB, Jalan Stesen Sentral 2, Kuala Lumpur, Malaysia
| | - Tze Yan Lee
- Perdana University School of Liberal Arts, Science and Technology (PUScLST), Suite 9.2, 9th Floor, Wisma Chase Perdana, Changkat Semantan Damansara Heights, Kuala Lumpur, 50490, Malaysia
| | - Pei Pei Chong
- School of Biosciences, Faculty of Health and Medical Sciences, Taylor's University Lakeside Campus, Subang Jaya, 47500, Malaysia
| | - Latiffah Hassan
- Department of Veterinary Laboratory Diagnostics, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Serdang, Selangor, 43400 UPM, Malaysia
| | - Rosnah Ismail
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia.
| | - Voon Kin Chin
- Department of Medical Microbiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, 43400 UPM, Malaysia; Integrative Pharmacogenomics Institute (iPROMISE), Universiti Teknologi MARA, Puncak Alam Campus, Bandar Puncak Alam, Selangor, 42300, Malaysia.
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Hoang LT, Jain P, Pillay TD, Tolosa-Wright M, Niazi U, Takwoingi Y, Halliday A, Berrocal-Almanza LC, Deeks JJ, Beverley P, Kon OM, Lalvani A. Transcriptomic signatures for diagnosing tuberculosis in clinical practice: a prospective, multicentre cohort study. THE LANCET. INFECTIOUS DISEASES 2021; 21:366-375. [PMID: 33508221 PMCID: PMC7907671 DOI: 10.1016/s1473-3099(20)30928-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/15/2020] [Accepted: 11/23/2020] [Indexed: 12/23/2022]
Abstract
Background Blood transcriptomic signatures for diagnosis of tuberculosis have shown promise in case-control studies, but none have been prospectively designed or validated in adults presenting with the full clinical spectrum of suspected tuberculosis, including extrapulmonary tuberculosis and common differential diagnoses that clinically resemble tuberculosis. We aimed to evaluate the diagnostic accuracy of transcriptomic signatures in patients presenting with clinically suspected tuberculosis in routine practice. Methods The Validation of New Technologies for Diagnostic Evaluation of Tuberculosis (VANTDET) study was nested within a prospective, multicentre cohort study in secondary care in England (IDEA 11/H0722/8). Patients (aged ≥16 years) suspected of having tuberculosis in the routine clinical inpatient and outpatient setting were recruited at ten National Health Service hospitals in England for IDEA and were included in VANTDET if they provided consent for genomic analysis. Patients had whole blood taken for microarray analysis to measure abundance of transcripts and were followed up for 6–12 months to determine final diagnoses on the basis of predefined diagnostic criteria. The diagnostic accuracy of six signatures derived from the cohort and three previously published transcriptomic signatures with potentially high diagnostic performance were assessed by calculating area under the receiver-operating characteristic curves (AUC-ROCs), sensitivities, and specificities. Findings Between Nov 25, 2011, and Dec 31, 2013, 1162 participants were enrolled. 628 participants (aged ≥16 years) were included in the analysis, of whom 212 (34%) had culture-confirmed tuberculosis, 89 (14%) had highly probable tuberculosis, and 327 (52%) had tuberculosis excluded. The novel signature with highest performance for identifying all active tuberculosis gave an AUC-ROC of 0·87 (95% CI 0·81–0·92), sensitivity of 77% (66–87), and specificity of 84% (74–91). The best-performing published signature gave an AUC-ROC of 0·83 (0·80–0·86), sensitivity of 78% (73–83), and specificity of 76% (70–80). For detecting highly probable tuberculosis, the best novel signature yielded results of 0·86 (0·71–0·95), 77% (56–94%), and 77% (57–95%). None of the relevant cohort-derived or previously published signatures achieved the WHO-defined targets of paired sensitivity and specificity for a non-sputum-based diagnostic test. Interpretation In a clinically representative cohort in routine practice in a low-incidence setting, transcriptomic signatures did not have adequate accuracy for diagnosis of tuberculosis, including in patients with highly probable tuberculosis where the unmet need is greatest. These findings suggest that transcriptomic signatures have little clinical utility for diagnostic assessment of suspected tuberculosis. Funding National Institute for Health Research.
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Affiliation(s)
- Long T Hoang
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Pooja Jain
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Timesh D Pillay
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Mica Tolosa-Wright
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Umar Niazi
- Guy's and St Thomas' National Health Service Foundation Trust and King's College London National Institute for Health Research Biomedical Research Centre Translational Bioinformatics Platform, Guy's Hospital, London, UK
| | - Yemisi Takwoingi
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK; National Institute of Health Research Birmingham Biomedical Research Centre, University Hospitals Birmingham National Health Service Foundation Trust and University of Birmingham, Birmingham, UK
| | - Alice Halliday
- Bristol Children's Vaccine Centre, University of Bristol, UK
| | - Luis C Berrocal-Almanza
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK; National Institute of Health Research Birmingham Biomedical Research Centre, University Hospitals Birmingham National Health Service Foundation Trust and University of Birmingham, Birmingham, UK
| | - Peter Beverley
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK
| | - Onn Min Kon
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK; Tuberculosis Service, Imperial College Healthcare National Health Service Trust, London, UK
| | - Ajit Lalvani
- Tuberculosis Research Centre, National Heart and Lung Institute, Imperial College London, London, UK.
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Abstract
The emergence and spread of infectious diseases with pandemic potential occurred regularly throughout history. Major pandemics and epidemics such as plague, cholera, flu, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) have already afflicted humanity. The world is now facing the new coronavirus disease 2019 (COVID-19) pandemic. Many infectious diseases leading to pandemics are caused by zoonotic pathogens that were transmitted to humans due to increased contacts with animals through breeding, hunting and global trade activities. The understanding of the mechanisms of transmission of pathogens to humans allowed the establishment of methods to prevent and control infections. During centuries, implementation of public health measures such as isolation, quarantine and border control helped to contain the spread of infectious diseases and maintain the structure of the society. In the absence of pharmaceutical interventions, these containment methods have still been used nowadays to control COVID-19 pandemic. Global surveillance programs of water-borne pathogens, vector-borne diseases and zoonotic spillovers at the animal-human interface are of prime importance to rapidly detect the emergence of infectious threats. Novel technologies for rapid diagnostic testing, contact tracing, drug repurposing, biomarkers of disease severity as well as new platforms for the development and production of vaccines are needed for an effective response in case of pandemics.
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Affiliation(s)
- Jocelyne Piret
- CHU de Québec - Laval University, Quebec City, QC, Canada
| | - Guy Boivin
- CHU de Québec - Laval University, Quebec City, QC, Canada
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Zafari P, Golpour M, Hafezi N, Bashash D, Esmaeili SA, Tavakolinia N, Rafiei A. Tuberculosis comorbidity with rheumatoid arthritis: Gene signatures, associated biomarkers, and screening. IUBMB Life 2020; 73:26-39. [PMID: 33217772 DOI: 10.1002/iub.2413] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/01/2020] [Accepted: 11/04/2020] [Indexed: 12/19/2022]
Abstract
Rheumatoid arthritis (RA) is known to be related to an elevated risk of infections because of its pathobiology and the use of immunosuppressive therapies. Reactivation of latent tuberculosis (TB) infection is a serious issue in patients with RA, especially after receiving anti-TNFs therapy. TNF blocking reinforces the TB granuloma formation and maintenance and the growth of Mycobacterium tuberculosis (Mtb). After intercurrent of TB infection, the standard recommendation is that the treatment with TNF inhibitors to be withheld despite its impressive effect on suppression of inflammation until the infection has resolved. Knowing pathways and mechanisms that are common between two diseases might help to find the mechanistic basis of this comorbidity, as well as provide us a new approach to apply them as therapeutic targets or diagnostic biomarkers. Also, screening for latent TB before initiation of an anti-TNF therapy can minimize complications. This review summarizes the shared gene signature between TB and RA and discusses the biomarkers for early detection of this infection, and screening procedures as well.
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Affiliation(s)
- Parisa Zafari
- Department of Immunology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran.,Student Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
| | - Monireh Golpour
- Molecular and Cellular Biology Research Center, Student Research Committee, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Nasim Hafezi
- Department of Immunology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Davood Bashash
- Department of Hematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed-Alireza Esmaeili
- Immunology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.,Department of Immunology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Naeimeh Tavakolinia
- Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Rafiei
- Department of Immunology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
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Tuberculosis-Associated MicroRNAs: From Pathogenesis to Disease Biomarkers. Cells 2020; 9:cells9102160. [PMID: 32987746 PMCID: PMC7598604 DOI: 10.3390/cells9102160] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 09/20/2020] [Accepted: 09/23/2020] [Indexed: 12/25/2022] Open
Abstract
Tuberculosis (TB) caused by Mycobacterium tuberculosis is one of the most lethal infectious diseases with estimates of approximately 1.4 million human deaths in 2018. M. tuberculosis has a well-established ability to circumvent the host immune system to ensure its intracellular survival and persistence in the host. Mechanisms include subversion of expression of key microRNAs (miRNAs) involved in the regulation of host innate and adaptive immune response against M. tuberculosis. Several studies have reported differential expression of miRNAs during active TB and latent tuberculosis infection (LTBI), suggesting their potential use as biomarkers of disease progression and response to anti-TB therapy. This review focused on the miRNAs involved in TB pathogenesis and on the mechanism through which miRNAs induced during TB modulate cell antimicrobial responses. An attentive study of the recent literature identifies a group of miRNAs, which are differentially expressed in active TB vs. LTBI or vs. treated TB and can be proposed as candidate biomarkers.
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40
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Otero ML, Menezes RC, Ferreira IBB, Issa FL, Agareno G, Carmo TA, Arriaga MB, Fukutani KF, Pamplona Neto L, Agareno S, Filgueiras Filho NM, Akrami KM, Andrade BB. Factors Associated with Mortality in Critically Ill Patients Diagnosed with Hospital Acquired Infections. Infect Drug Resist 2020; 13:2811-2817. [PMID: 32848430 PMCID: PMC7430765 DOI: 10.2147/idr.s264276] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 07/05/2020] [Indexed: 11/24/2022] Open
Abstract
Objective Evaluate host and pathogen factors associated with mortality in those with hospital acquired infections (HAI) in a tertiary intensive care unit in Brazil. Methods Observational and analytical cohort single center study in a general intensive care unit (ICU) in Northeastern Brazil between January 2016 and August 2018, including those over 18 years of age admitted to the ICU found to have a HAI. Results A total of 165 patients were included, with a mean age of 72 years and male predominance (53.3%) and observed mortality of 46%. Mortality in those with HAI was significantly associated with older age, increased ICU length of stay and readmission to the ICU in univariate analysis. Multivariate analysis revealed that development of septic shock and obtundation during ICU admission was significantly associated with an increased risk of death (OR: 6.94, 95% CI 1.23–39.27, OR: 2.48, 95% CI 1.17–5.29, respectively). A trend towards mortality risk was noted in those with increased age and prior cardiovascular disease. Surprisingly, mortality risk was independent of site of infection, type of pathogen and antibiotic resistance. Furthermore, having more than one HAI over the course of the ICU admission did not impact mortality. Conclusion Risk of death in those with HAI is associated with obtundation and septic shock, in addition to vasopressor use. Host factors, rather than pathogen-specific characteristics or infecting site, impact risk of death related to HAI in the ICU.
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Affiliation(s)
- Matheus L Otero
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate Universities, Salvador, Bahia, Brazil
| | - Rodrigo C Menezes
- Curso de Medicina, União Metropolitana Para o Desenvolvimento da Educação e Cultura (UNIME), Salvador, Bahia, Brazil
| | | | - Francine L Issa
- Curso de Medicina, Universidade do Estado da Bahia, Salvador, Bahia, Brazil
| | - Gabriel Agareno
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate Universities, Salvador, Bahia, Brazil
| | - Thomas Azevedo Carmo
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate Universities, Salvador, Bahia, Brazil
| | - María B Arriaga
- Curso de Medicina, Universidade do Estado da Bahia, Salvador, Bahia, Brazil.,Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.,Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Bahia, Brazil
| | - Kiyoshi F Fukutani
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.,Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Bahia, Brazil
| | | | - Sydney Agareno
- Hospital Da Cidade, Intensive Care Unit, Salvador, Bahia, Brazil
| | - Nivaldo M Filgueiras Filho
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate Universities, Salvador, Bahia, Brazil.,Universidade Do Estado Da Bahia (UNEB), Salvador, Bahia, Brazil.,Hospital Da Cidade, Intensive Care Unit, Salvador, Bahia, Brazil
| | - Kevan M Akrami
- Division of Infectious Diseases and Pulmonary Critical Care and Sleep Medicine, Department of Medicine, University of California, San Diego, California, USA
| | - Bruno B Andrade
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate Universities, Salvador, Bahia, Brazil.,Curso de Medicina, Universidade do Estado da Bahia, Salvador, Bahia, Brazil.,Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.,Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Bahia, Brazil.,Escola Bahiana De Medicina e Saúde Pública (EBMSP), Salvador, Bahia, Brazil
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Li B, Tan Q, Fan Z, Xiao K, Liao Y. Next‐generation Theranostics: Functionalized Nanomaterials Enable Efficient Diagnosis and Therapy of Tuberculosis. ADVANCED THERAPEUTICS 2020. [DOI: 10.1002/adtp.201900189] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Bin Li
- Center for Infection and Immunity the Fifth Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University Zhuhai 519000 China
| | - Qingqin Tan
- Center for Infection and Immunity the Fifth Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University Zhuhai 519000 China
| | - Zhijin Fan
- Center for Infection and Immunity the Fifth Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University Zhuhai 519000 China
| | - Keng Xiao
- Center for Infection and Immunity the Fifth Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University Zhuhai 519000 China
| | - Yuhui Liao
- Center for Infection and Immunity the Fifth Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University Zhuhai 519000 China
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Penn-Nicholson A, Mbandi SK, Thompson E, Mendelsohn SC, Suliman S, Chegou NN, Malherbe ST, Darboe F, Erasmus M, Hanekom WA, Bilek N, Fisher M, Kaufmann SHE, Winter J, Murphy M, Wood R, Morrow C, Van Rhijn I, Moody B, Murray M, Andrade BB, Sterling TR, Sutherland J, Naidoo K, Padayatchi N, Walzl G, Hatherill M, Zak D, Scriba TJ. RISK6, a 6-gene transcriptomic signature of TB disease risk, diagnosis and treatment response. Sci Rep 2020; 10:8629. [PMID: 32451443 PMCID: PMC7248089 DOI: 10.1038/s41598-020-65043-8] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 04/27/2020] [Indexed: 11/17/2022] Open
Abstract
Improved tuberculosis diagnostics and tools for monitoring treatment response are urgently needed. We developed a robust and simple, PCR-based host-blood transcriptomic signature, RISK6, for multiple applications: identifying individuals at risk of incident disease, as a screening test for subclinical or clinical tuberculosis, and for monitoring tuberculosis treatment. RISK6 utility was validated by blind prediction using quantitative real-time (qRT) PCR in seven independent cohorts. Prognostic performance significantly exceeded that of previous signatures discovered in the same cohort. Performance for diagnosing subclinical and clinical disease in HIV-uninfected and HIV-infected persons, assessed by area under the receiver-operating characteristic curve, exceeded 85%. As a screening test for tuberculosis, the sensitivity at 90% specificity met or approached the benchmarks set out in World Health Organization target product profiles for non-sputum-based tests. RISK6 scores correlated with lung immunopathology activity, measured by positron emission tomography, and tracked treatment response, demonstrating utility as treatment response biomarker, while predicting treatment failure prior to treatment initiation. Performance of the test in capillary blood samples collected by finger-prick was noninferior to venous blood collected in PAXgene tubes. These results support incorporation of RISK6 into rapid, capillary blood-based point-of-care PCR devices for prospective assessment in field studies.
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Affiliation(s)
- Adam Penn-Nicholson
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Stanley Kimbung Mbandi
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Ethan Thompson
- Center for Infectious Disease Research, Seattle, WA, USA
| | - Simon C Mendelsohn
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Sara Suliman
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.,Brigham and Women's Hospital, Division of Rheumatology, Immunity and Inflammation, Harvard Medical School, Boston, USA
| | - Novel N Chegou
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Stephanus T Malherbe
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Fatoumatta Darboe
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Mzwandile Erasmus
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Willem A Hanekom
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Nicole Bilek
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Michelle Fisher
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Stefan H E Kaufmann
- Max Planck Institute for Infection Biology, Berlin, Germany.,Hagler Institute for Advanced Study at Texas A&M University, College Station, TX, USA
| | - Jill Winter
- Catalysis Foundation for Health, San Ramon, CA, USA
| | - Melissa Murphy
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Robin Wood
- Desmond Tutu HIV Centre, and Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, Cape Town, South Africa
| | - Carl Morrow
- Desmond Tutu HIV Centre, and Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, Cape Town, South Africa
| | - Ildiko Van Rhijn
- Brigham and Women's Hospital, Division of Rheumatology, Immunity and Inflammation, Harvard Medical School, Boston, USA
| | - Branch Moody
- Brigham and Women's Hospital, Division of Rheumatology, Immunity and Inflammation, Harvard Medical School, Boston, USA
| | - Megan Murray
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruno B Andrade
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Timothy R Sterling
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, USA
| | - Jayne Sutherland
- Vaccines and Immunity, Medical Research Council Unit, Fajara, The Gambia
| | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in Africa, Durban, South Africa.,South African Medical Research Council-CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
| | - Nesri Padayatchi
- Centre for the AIDS Programme of Research in Africa, Durban, South Africa.,South African Medical Research Council-CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban, South Africa
| | - Gerhard Walzl
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Daniel Zak
- Center for Infectious Disease Research, Seattle, WA, USA
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
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Ho J, Bokil NJ, Nguyen PTB, Nguyen TA, Liu MY, Hare N, Fox GJ, Saunders BM, Marks GB, Britton WJ. A transcriptional blood signature distinguishes early tuberculosis disease from latent tuberculosis infection and uninfected individuals in a Vietnamese cohort. J Infect 2020; 81:72-80. [PMID: 32330522 DOI: 10.1016/j.jinf.2020.03.066] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 03/09/2020] [Accepted: 03/12/2020] [Indexed: 02/08/2023]
Abstract
OBJECTIVES Global tuberculosis (TB) control is restricted by the failure to detect an estimated 3.3 million TB cases annually. In the majority of TB endemic settings, sputum smear microscopy is used to diagnose TB, but this test is insensitive for TB in its early stages. The objective of this study is to establish a concise gene signature that discriminates between individuals with early TB disease, latent TB infection (LTBI) and those without infection. METHODS This is a case control study nested within a cluster-randomised trial of population screening for active TB using Xpert MTB/RIF. Whole blood samples from 303 participants with active TB (97), LTBI (92) and uninfected individuals (114) were subject to transcriptomic analysis of selected target genes based on a systematic review of previous studies. RESULTS Analysis of 82 genes identified a pattern of differentially expressed genes in TB disease. A seven gene signature was identified that distinguished between TB disease and no TB disease with an AUC of 0.86 (95% CI: 0.80-0.91), and between TB disease from LTBI with an AUC of 0.88 (95% CI: 0.82-0.93). CONCLUSION This gene signature accurately distinguishes early TB disease from those without TB disease or infection, in the context of community-wide TB screening. It could be used as a non-sputum based screening tool or triage test to detect prevalent cases of TB in the community.
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Affiliation(s)
- Jennifer Ho
- Woolcock Institute of Medical Research, The University of Sydney, 431 Glebe Point Rd, Glebe NSW 2037, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, Australia; Centenary Institute, The University of Sydney, Sydney, Australia.
| | - Nilesh J Bokil
- School of Life Sciences, University of Technology Sydney, Sydney, Australia
| | - Phuong Thi Bich Nguyen
- Woolcock Institute of Medical Research, The University of Sydney, 431 Glebe Point Rd, Glebe NSW 2037, Australia
| | - Thu Anh Nguyen
- Woolcock Institute of Medical Research, The University of Sydney, 431 Glebe Point Rd, Glebe NSW 2037, Australia
| | - Michael Y Liu
- The ithree Institute, University of Technology Sydney, Sydney, Australia
| | - Nathan Hare
- Centenary Institute, The University of Sydney, Sydney, Australia
| | - Greg J Fox
- Woolcock Institute of Medical Research, The University of Sydney, 431 Glebe Point Rd, Glebe NSW 2037, Australia; Central Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Bernadette M Saunders
- Centenary Institute, The University of Sydney, Sydney, Australia; School of Life Sciences, University of Technology Sydney, Sydney, Australia
| | - Guy B Marks
- Woolcock Institute of Medical Research, The University of Sydney, 431 Glebe Point Rd, Glebe NSW 2037, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, Australia
| | - Warwick J Britton
- Centenary Institute, The University of Sydney, Sydney, Australia; Central Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
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Dheda K, Davids M. Latent Tuberculosis Infection–associated Immunodiagnostic Test Responses as Biomarkers of Incipient Tuberculosis: Fruitful or Futile? Am J Respir Crit Care Med 2020; 201:895-898. [PMID: 31951482 PMCID: PMC7159435 DOI: 10.1164/rccm.201912-2425ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Affiliation(s)
- Keertan Dheda
- Centre for Lung Infection and ImmunityUCT Lung InstituteCape Town, South Africa
- Faculty of Infectious and Tropical DiseasesLondon School of Hygiene and Tropical MedicineLondon, United Kingdomand
- South African MRC/UCT Centre for the Study of Antimicrobial ResistanceUniversity of Cape TownCape Town, South Africa
| | - Malika Davids
- Centre for Lung Infection and ImmunityUCT Lung InstituteCape Town, South Africa
- Faculty of Infectious and Tropical DiseasesLondon School of Hygiene and Tropical MedicineLondon, United Kingdomand
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Asnaghi MA, Power L, Barbero A, Haug M, Köppl R, Wendt D, Martin I. Biomarker Signatures of Quality for Engineering Nasal Chondrocyte-Derived Cartilage. Front Bioeng Biotechnol 2020; 8:283. [PMID: 32318561 PMCID: PMC7154140 DOI: 10.3389/fbioe.2020.00283] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 03/18/2020] [Indexed: 01/06/2023] Open
Abstract
The definition of quality controls for cell therapy and engineered product manufacturing processes is critical for safe, effective, and standardized clinical implementation. Using the example context of cartilage grafts engineered from autologous nasal chondrocytes, currently used for articular cartilage repair in a phase II clinical trial, we outlined how gene expression patterns and generalized linear models can be introduced to define molecular signatures of identity, purity, and potency. We first verified that cells from the biopsied nasal cartilage can be contaminated by cells from a neighboring tissue, namely perichondrial cells, and discovered that they cannot deposit cartilaginous matrix. Differential analysis of gene expression enabled the definition of identity markers for the two cell populations, which were predictive of purity in mixed cultures. Specific patterns of expression of the same genes were significantly correlated with cell potency, defined as the capacity to generate tissues with histological and biochemical features of hyaline cartilage. The outlined approach can now be considered for implementation in a good manufacturing practice setting, and offers a paradigm for other regenerative cellular therapies.
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Affiliation(s)
- M Adelaide Asnaghi
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Laura Power
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Andrea Barbero
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Martin Haug
- Department of Surgery, University Hospital Basel, Basel, Switzerland
| | - Ruth Köppl
- Otorhinolaryngology, Head and Neck Surgery, University Hospital Basel, Basel, Switzerland
| | - David Wendt
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ivan Martin
- Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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Turner CT, Gupta RK, Tsaliki E, Roe JK, Mondal P, Nyawo GR, Palmer Z, Miller RF, Reeve BW, Theron G, Noursadeghi M. Blood transcriptional biomarkers for active pulmonary tuberculosis in a high-burden setting: a prospective, observational, diagnostic accuracy study. THE LANCET. RESPIRATORY MEDICINE 2020; 8:407-419. [PMID: 32178775 PMCID: PMC7113842 DOI: 10.1016/s2213-2600(19)30469-2] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 12/09/2019] [Accepted: 12/10/2019] [Indexed: 02/08/2023]
Abstract
BACKGROUND Blood transcriptional signatures are candidates for non-sputum triage or confirmatory tests of tuberculosis. Prospective head-to-head comparisons of their diagnostic accuracy in real-world settings are necessary to assess their clinical use. We aimed to compare the diagnostic accuracy of candidate transcriptional signatures identified by systematic review, in a setting with a high burden of tuberculosis and HIV. METHODS We did a prospective observational study nested within a diagnostic accuracy study of sputum Xpert MTB/RIF (Xpert) and Xpert MTB/RIF Ultra (Ultra) tests for pulmonary tuberculosis. We recruited consecutive symptomatic adults aged 18 years or older self-presenting to a tuberculosis clinic in Cape Town, South Africa. Participants provided blood for RNA sequencing, and sputum samples for liquid culture and molecular testing using Xpert and Ultra. We assessed the diagnostic accuracy of candidate blood transcriptional signatures for active tuberculosis (including those intended to distinguish active tuberculosis from other diseases) identified by systematic review, compared with culture or Xpert MTB/RIF positivity as the standard reference. In our primary analysis, patients with tuberculosis were defined as those with either a positive liquid culture or Xpert result. Patients with missing blood RNA or sputum results were excluded. Our primary objective was to benchmark the diagnostic accuracy of candidate transcriptional signatures against the WHO target product profile (TPP) for a tuberculosis triage test. FINDINGS Between Feb 12, 2016, and July 18, 2017, we obtained paired sputum and RNA sequencing data from 181 participants, 54 (30%) of whom had confirmed pulmonary tuberculosis. Of 27 eligible signatures identified by systematic review, four achieved the highest diagnostic accuracy with similar area under the receiver operating characteristic curves (Sweeney3: 90·6% [95% CI 85·6-95·6]; Kaforou25: 86·9% [80·9-92·9]; Roe3: 86·9% [80·3-93·5]; and BATF2: 86·8% [80·6-93·1]), independent of age, sex, HIV status, previous tuberculosis, or sputum smear result. At test thresholds that gave 70% specificity (the minimum WHO TPP specificity for a triage test), these four signatures achieved sensitivities between 83·3% (95% CI 71·3-91·0) and 90·7% (80·1-96·0). No signature met the optimum criteria, of 95% sensitivity and 80% specificity proposed by WHO for a triage test, or the minimum criteria (of 65% sensitivity and 98% specificity) for a confirmatory test, but all four correctly identified Ultra-positive, culture-negative patients. INTERPRETATION Selected blood transcriptional signatures met the minimum WHO benchmarks for a tuberculosis triage test but not for a confirmatory test. Further development of the signatures is warranted to investigate their possible effects on clinical and health economic outcomes as part of a triage strategy, or when used as add-on confirmatory test in conjunction with the highly sensitive Ultra test for Mycobacterium tuberculosis DNA. FUNDING Royal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, and UK Medical Research Council.
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Affiliation(s)
- Carolin T Turner
- Division of Infection and Immunity, University College London, London, UK
| | - Rishi K Gupta
- Institute for Global Health, University College London, London, UK
| | - Evdokia Tsaliki
- Division of Infection and Immunity, University College London, London, UK
| | - Jennifer K Roe
- Division of Infection and Immunity, University College London, London, UK
| | - Prasenjit Mondal
- Division of Infection and Immunity, University College London, London, UK
| | - Georgina R Nyawo
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; and Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Zaida Palmer
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; and Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Robert F Miller
- Institute for Global Health, University College London, London, UK
| | - Byron Wp Reeve
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; and Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Grant Theron
- DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; and Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, London, UK.
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Gupta RK, Turner CT, Venturini C, Esmail H, Rangaka MX, Copas A, Lipman M, Abubakar I, Noursadeghi M. Concise whole blood transcriptional signatures for incipient tuberculosis: a systematic review and patient-level pooled meta-analysis. THE LANCET. RESPIRATORY MEDICINE 2020; 8:395-406. [PMID: 31958400 PMCID: PMC7113839 DOI: 10.1016/s2213-2600(19)30282-6] [Citation(s) in RCA: 103] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 08/15/2019] [Accepted: 08/16/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Multiple blood transcriptional signatures have been proposed for identification of active and incipient tuberculosis. We aimed to compare the performance of systematically identified candidate signatures for incipient tuberculosis and to benchmark these against WHO targets. METHODS We did a systematic review and individual participant data meta-analysis. We searched Medline and Embase for candidate whole blood mRNA signatures discovered with the primary objective of diagnosis of active or incipient tuberculosis, compared with controls who were healthy or had latent tuberculosis infection. We tested the performance of eligible signatures in whole blood transcriptomic datasets, in which sampling before tuberculosis diagnosis was done and time to disease was available. Culture-confirmed and clinically or radiologically diagnosed pulmonary or extrapulmonary tuberculosis cases were included. Non-progressor (individuals who remained tuberculosis-free during follow-up) samples with less than 6 months of follow-up from the date of sample collection were excluded, as were participants with prevalent tuberculosis and those who received preventive therapy. Scores were calculated for candidate signatures for each participant in the pooled dataset. Receiver operating characteristic curves, sensitivities, and specificities were examined using prespecified intervals to tuberculosis (<3 months, <6 months, <1 year, and <2 years) from sample collection. This study is registered with PROSPERO, number CRD42019135618. RESULTS We tested 17 candidate mRNA signatures in a pooled dataset from four eligible studies comprising 1126 samples. This dataset included 183 samples from 127 incipient tuberculosis cases in South Africa, Ethiopia, The Gambia, and the UK. Eight signatures (comprising 1-25 transcripts) that predominantly reflect interferon and tumour necrosis factor-inducible gene expression, had equivalent diagnostic accuracy for incipient tuberculosis over a 2-year period with areas under the receiver operating characteristic curves ranging from 0·70 (95% CI 0·64-0·76) to 0·77 (0·71-0·82). The sensitivity of all eight signatures declined with increasing disease-free time interval. Using a threshold derived from two SDs above the mean of uninfected controls to prioritise specificity and positive-predictive value, the eight signatures achieved sensitivities of 24·7-39·9% over 24 months and of 47·1-81·0% over 3 months, with corresponding specificities of more than 90%. Based on pre-test probability of 2%, the eight signatures achieved positive-predictive values ranging from 6·8-9·4% over 24 months and 11·2-14·4% over 3 months. When using biomarker thresholds maximising sensitivity and specificity with equal weighting to both, no signature met the minimum WHO target product profile parameters for incipient tuberculosis biomarkers over a 2-year period. INTERPRETATION Blood transcriptional biomarkers reflect short-term risk of tuberculosis and only exceed WHO benchmarks if applied to 3-6-month intervals. Serial testing among carefully selected target groups might be required for optimal implementation of these biomarkers. FUNDING Wellcome Trust and National Institute for Health Research.
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Affiliation(s)
- Rishi K Gupta
- Institute for Global Health, University College London, London, UK
| | - Carolin T Turner
- Division of Infection & Immunity, University College London, London, UK
| | | | - Hanif Esmail
- Institute for Global Health, University College London, London, UK; Medical Research Council Clinical Trials Unit, University College London, London, UK; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Molebogeng X Rangaka
- Institute for Global Health, University College London, London, UK; Medical Research Council Clinical Trials Unit, University College London, London, UK; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa; Division of Epidemiology and Biostatistics, School of Public Health, University of Cape Town, Cape Town, South Africa
| | - Andrew Copas
- Institute for Global Health, University College London, London, UK; Medical Research Council Clinical Trials Unit, University College London, London, UK
| | - Marc Lipman
- UCL-TB and UCL Respiratory, University College London, London, UK; Department of Respiratory Medicine, Royal Free London NHS Foundation Trust, London, UK
| | - Ibrahim Abubakar
- Institute for Global Health, University College London, London, UK
| | - Mahdad Noursadeghi
- Division of Infection & Immunity, University College London, London, UK.
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Lubbers R, Sutherland JS, Goletti D, de Paus RA, Dijkstra DJ, van Moorsel CHM, Veltkamp M, Vestjens SMT, Bos WJW, Petrone L, Malherbe ST, Walzl G, Gelderman KA, Groeneveld GH, Geluk A, Ottenhoff THM, Joosten SA, Trouw LA. Expression and production of the SERPING1-encoded endogenous complement regulator C1-inhibitor in multiple cohorts of tuberculosis patients. Mol Immunol 2020; 120:187-195. [PMID: 32179338 DOI: 10.1016/j.molimm.2020.02.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 02/03/2020] [Accepted: 02/10/2020] [Indexed: 01/04/2023]
Abstract
BACKGROUND To facilitate better discrimination between patients with active tuberculosis (TB) and latent TB infection (LTBI), whole blood transcriptomic studies have been performed to identify novel candidate host biomarkers. SERPING1, which encodes C1-inhibitor (C1-INH), the natural inhibitor of the C1-complex has emerged as candidate biomarker. Here we collated and analysed SERPING1 expression data and subsequently determined C1-INH protein levels in four cohorts of patients with TB. METHODS SERPING1 expression data were extracted from online deposited datasets. C1-INH protein levels were determined by ELISA in sera from individuals with active TB, LTBI as well as other disease controls in geographically diverse cohorts. FINDINGS SERPING1 expression was increased in patients with active TB compared to healthy controls (8/11 cohorts), LTBI (13/14 cohorts) and patients with other (non-TB) lung-diseases (7/7 cohorts). Serum levels of C1-INH were significantly increased in The Gambia and Italy in patients with active TB relative to the endemic controls but not in South Africa or Korea. In the largest cohort (n = 50), with samples collected longitudinally, normalization of C1-INH levels following successful TB treatment was observed. This cohort, also showed the most abundant increase in C1-INH, and a positive correlation between C1q and C1-INH levels. Combined presence of increased levels of both C1q and C1-INH had high specificity for active TB (96 %) but only very modest sensitivity 38 % compared to the endemic controls. INTERPRETATION SERPING1 transcript expression is increased in TB patients, while serum protein levels of C1-INH were increased in half of the cohorts analysed.
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Affiliation(s)
- Rosalie Lubbers
- Department of Rheumatology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jayne S Sutherland
- Vaccines and Immunity Theme, Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | - Delia Goletti
- Translational Research Unit, Department of Epidemiology and Preclinical Research, National Institute for Infectious Diseases L. Spallanzani-IRCCS, Rome, Italy
| | - Roelof A de Paus
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Douwe J Dijkstra
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marcel Veltkamp
- Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Stefan M T Vestjens
- Department of Internal Medicine, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Willem J W Bos
- Department of Internal Medicine, St. Antonius Hospital, Nieuwegein, the Netherlands; Department of Nephrology, Leiden University Medical Center, Leiden, the Netherlands
| | - Linda Petrone
- Translational Research Unit, Department of Epidemiology and Preclinical Research, National Institute for Infectious Diseases L. Spallanzani-IRCCS, Rome, Italy
| | - Stephanus T Malherbe
- DST/NRF Centre of Excellence for Biomedical TB Research and SAMRC Centre for TB Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Gerhard Walzl
- DST/NRF Centre of Excellence for Biomedical TB Research and SAMRC Centre for TB Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | | | - Geert H Groeneveld
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Annemieke Geluk
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Simone A Joosten
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Leendert A Trouw
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, the Netherlands.
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Cai Y, Dai Y, Wang Y, Yang Q, Guo J, Wei C, Chen W, Huang H, Zhu J, Zhang C, Zheng W, Wen Z, Liu H, Zhang M, Xing S, Jin Q, Feng CG, Chen X. Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis. EBioMedicine 2020; 53:102686. [PMID: 32114394 PMCID: PMC7047188 DOI: 10.1016/j.ebiom.2020.102686] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 02/09/2020] [Accepted: 02/10/2020] [Indexed: 12/14/2022] Open
Abstract
Background Tuberculosis (TB) continues to be a critical global health problem, which killed millions of lives each year. Certain circulating cell subsets are thought to differentially modulate the host immune response towards Mycobacterium tuberculosis (Mtb) infection, but the nature and function of these subsets is unclear. Methods Peripheral blood mononuclear cells (PBMC) were isolated from healthy controls (HC), latent tuberculosis infection (LTBI) and active tuberculosis (TB) and then subjected to single-cell RNA sequencing (scRNA-seq) using 10 × Genomics platform. Unsupervised clustering of the cells based on the gene expression profiles using the Seurat package and passed to tSNE for clustering visualization. Flow cytometry was used to validate the subsets identified by scRNA-Seq. Findings Cluster analysis based on differential gene expression revealed both known and novel markers for all main PBMC cell types and delineated 29 cell subsets. By comparing the scRNA-seq datasets from HC, LTBI and TB, we found that infection changes the frequency of immune-cell subsets in TB. Specifically, we observed gradual depletion of a natural killer (NK) cell subset (CD3-CD7+GZMB+) from HC, to LTBI and TB. We further verified that the depletion of CD3-CD7+GZMB+ subset in TB and found an increase in this subset frequency after anti-TB treatment. Finally, we confirmed that changes in this subset frequency can distinguish patients with TB from LTBI and HC. Interpretation We propose that the frequency of CD3-CD7+GZMB+ in peripheral blood could be used as a novel biomarker for distinguishing TB from LTBI and HC. Fund The study was supported by Natural Science Foundation of China (81770013, 81525016, 81772145, 81871255 and 91942315), National Science and Technology Major Project (2017ZX10201301), Science and Technology Project of Shenzhen (JCYJ20170412101048337) and Guangdong Provincial Key Laboratory of Regional Immunity and Diseases (2019B030301009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Affiliation(s)
- Yi Cai
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Youchao Dai
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China; Research Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou 510000, China
| | - Yejun Wang
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Qianqing Yang
- Guangdong Key Lab for Diagnosis &Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen 518000, China
| | - Jiubiao Guo
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Cailing Wei
- Guangdong Key Lab for Diagnosis &Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen 518000, China
| | - Weixin Chen
- Guangdong Key Lab for Diagnosis &Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen 518000, China
| | - Huanping Huang
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Jialou Zhu
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Chi Zhang
- Shenzhen University General Hospital, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Weidong Zheng
- Shenzhen University General Hospital, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Zhihua Wen
- Yuebei Second People's Hospital, Shaoguan 512000, China
| | - Haiying Liu
- The MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Centre for Tuberculosis, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100176, China
| | - Mingxia Zhang
- Guangdong Key Lab for Diagnosis &Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen 518000, China
| | - Shaojun Xing
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China
| | - Qi Jin
- The MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Centre for Tuberculosis, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100176, China
| | - Carl G Feng
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China; Department of Infectious Diseases and Immunology, Sydney Medical School, the University of Sydney, Sydney, NSW 2006, Australia
| | - Xinchun Chen
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518000, China.
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Shi SD, Hsueh PR, Yang PC, Chou CC. Use of DosR Dormancy Antigens from Mycobacterium tuberculosis for Serodiagnosis of Active and Latent Tuberculosis. ACS Infect Dis 2020; 6:272-280. [PMID: 31815418 DOI: 10.1021/acsinfecdis.9b00329] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
As more than two billion people possibly have a latent tuberculosis (LTB) infection, early LTB diagnosis is crucial for the efficient control and elimination of tuberculosis (TB). The aim of this study is to detect the serum antibody responses to dormancy-related DosR regulon antigens of Mycobacterium tuberculosis for the diagnosis of active and latent TB infections. A membrane array with 25 latency antigens detected by silver-enhanced gold nanoparticles was used to determine the corresponding cognate antibody levels in clinical serum samples from healthy controls, TB patients, and individuals with LTB. The array is sized to fit into a 24-well ELISA plate and follows an ELISA-like experimental procedure without expensive instrumentation. Linear discriminant analysis (LDA) of the resulting antibody profiling data set identified a panel of nine DosR antigens with significant discriminatory capability among different subjects with ≥90% sensitivity, specificity, and overall accuracy. Furthermore, the high predictive performance validated by an independent test sample set reflects the robustness and reliability of the LDA classification model. Our current data demonstrate that the nine DosR antigen combination associated with the proposed membrane array platform is a clinically feasible approach for distinguishing different TB infection statuses. The proposed methodology in this study could be further developed for multiple disease serodiagnoses with high sensitivity and specificity.
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Affiliation(s)
- Sheng-Dong Shi
- Department of Biomedical Sciences and Institute of Molecular Biology, National Chung Cheng University, No. 168 University Road, Min-Hsiung, Chia-Yi, Taiwan 62102, ROC
- Division of Laboratory Medicine, Chia-Yi and Wanqiao Branch, Taichung Veterans General Hospital, No. 600 Shixian Rd., Chia-Yi City, Taiwan 60090, ROC
| | - Po-Ren Hsueh
- Department of Laboratory Medicine, National Taiwan University College of Medicine, No. 1 Jen Ai Road, Taipei, Taiwan 10051, ROC
| | - Pan-Chyr Yang
- Department of Internal Medicine, National Taiwan University College of Medicine, No. 1 Jen Ai Road, Taipei, Taiwan 10051, ROC
| | - Cheng-Chung Chou
- Department of Biomedical Sciences and Institute of Molecular Biology, National Chung Cheng University, No. 168 University Road, Min-Hsiung, Chia-Yi, Taiwan 62102, ROC
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