1
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Elkahwagy DMAS, Kiriacos CJ, Mansour M. Logistic regression and other statistical tools in diagnostic biomarker studies. Clin Transl Oncol 2024; 26:2172-2180. [PMID: 38530558 PMCID: PMC11333519 DOI: 10.1007/s12094-024-03413-8] [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: 12/20/2023] [Accepted: 02/16/2024] [Indexed: 03/28/2024]
Abstract
A biomarker is a measured indicator of a variety of processes, and is often used as a clinical tool for the diagnosis of diseases. While the developmental process of biomarkers from lab to clinic is complex, initial exploratory stages often focus on characterizing the potential of biomarkers through utilizing various statistical methods that can be used to assess their discriminatory performance, establish an appropriate cut-off that transforms continuous data to apt binary responses of confirming or excluding a diagnosis, or establish a robust association when tested against confounders. This review aims to provide a gentle introduction to the most common tools found in diagnostic biomarker studies used to assess the performance of biomarkers with an emphasis on logistic regression.
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Affiliation(s)
| | - Caroline Joseph Kiriacos
- Pharmaceutical Biology Department, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, 11835, Egypt
| | - Manar Mansour
- Pharmaceutical Biology Department, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, 11835, Egypt
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2
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Mukhtar F, Guarnieri A, Brancazio N, Falcone M, Di Naro M, Azeem M, Zubair M, Nicolosi D, Di Marco R, Petronio Petronio G. The role of Mycobacterium tuberculosis exosomal miRNAs in host pathogen cross-talk as diagnostic and therapeutic biomarkers. Front Microbiol 2024; 15:1441781. [PMID: 39176271 PMCID: PMC11340542 DOI: 10.3389/fmicb.2024.1441781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Accepted: 07/25/2024] [Indexed: 08/24/2024] Open
Abstract
Tuberculosis (TB) is a global threat, affecting one-quarter of the world's population. The World Health Organization (WHO) reports that 6 million people die annually due to chronic illnesses, a statistic that includes TB-related deaths. This high mortality is attributed to factors such as the emergence of drug-resistant strains and the exceptional survival mechanisms of Mycobacterium tuberculosis (MTB). Recently, microRNAs (miRNAs) have garnered attention for their crucial role in TB pathogenesis, surpassing typical small RNAs (sRNA) in their ability to alter the host's immune response. For instance, miR-155, miR-125b, and miR-29a have been identified as key players in the immune response to MTB, particularly in modulating macrophages, T cells, and cytokine production. While sRNAs are restricted to within cells, exo-miRNAs are secreted from MTB-infected macrophages. These exo-miRNAs modify the function of surrounding cells to favor the bacterium, perpetuating the infection cycle. Another significant aspect is that the expression of these miRNAs affects specific genes and pathways involved in immune functions, suggesting their potential use in diagnosing TB and as therapeutic targets. This review compiles existing information on the immunomodulatory function of exosomal miRNAs from MTB, particularly focusing on disease progression and the scientific potential of this approach compared to existing diagnostic techniques. Thus, the aim of the study is to understand the role of exosomal miRNAs in TB and to explore their potential for developing novel diagnostic and therapeutic methods.
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Affiliation(s)
- Farwa Mukhtar
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
| | - Antonio Guarnieri
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
| | - Natasha Brancazio
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
| | - Marilina Falcone
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
| | - Maria Di Naro
- Department of Drug and Health Sciences, Università degli Studi di Catania, Catania, Italy
| | - Muhammad Azeem
- Department of Precision Medicine in the Medical, Surgical and Critical Care Area (Me.Pre.C.C.), University of Palermo, Palermo, Italy
| | - Muhammad Zubair
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Daria Nicolosi
- Department of Drug and Health Sciences, Università degli Studi di Catania, Catania, Italy
| | - Roberto Di Marco
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
| | - Giulio Petronio Petronio
- Department of Medicina e Scienze della Salute “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy
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3
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Shi L, Han X, Liu F, Long J, Jin Y, Chen S, Duan G, Yang H. Review on Long Non-Coding RNAs as Biomarkers and Potentially Therapeutic Targets for Bacterial Infections. Curr Issues Mol Biol 2024; 46:7558-7576. [PMID: 39057090 PMCID: PMC11276060 DOI: 10.3390/cimb46070449] [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: 06/19/2024] [Revised: 07/13/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
The confrontation between humans and bacteria is ongoing, with strategies for combating bacterial infections continually evolving. With the advancement of RNA sequencing technology, non-coding RNAs (ncRNAs) associated with bacterial infections have garnered significant attention. Recently, long ncRNAs (lncRNAs) have been identified as regulators of sterile inflammatory responses and cellular defense against live bacterial pathogens. They are involved in regulating host antimicrobial immunity in both the nucleus and cytoplasm. Increasing evidence indicates that lncRNAs are critical for the intricate interactions between host and pathogen during bacterial infections. This paper emphatically elaborates on the potential applications of lncRNAs in clinical hallmarks, cellular damage, immunity, virulence, and drug resistance in bacterial infections in greater detail. Additionally, we discuss the challenges and limitations of studying lncRNAs in the context of bacterial infections and highlight clear directions for this promising field.
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Affiliation(s)
| | | | | | | | | | | | | | - Haiyan Yang
- Department of Epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China; (L.S.); (X.H.); (F.L.); (J.L.); (Y.J.); (S.C.); (G.D.)
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4
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Huang S, Kang X, Zeng Z, Zhang Q, Huang Z, Luo K, Yao Q, Chen B, Qing C. Neutrophil lncRNA ZNF100-6:2 is a potential diagnostic marker for active pulmonary tuberculosis. Eur J Med Res 2024; 29:162. [PMID: 38475909 PMCID: PMC10929138 DOI: 10.1186/s40001-024-01755-1] [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: 10/16/2023] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Active pulmonary tuberculosis (PTB) poses challenges in rapid diagnosis within complex clinical conditions. Given the close association between neutrophils and tuberculosis, we explored differentially expressed long non-coding RNAs (lncRNAs) in neutrophils as potential molecular markers for diagnosing active PTB. We employed a gene microarray to screen for lncRNA alterations in neutrophil samples from three patients with active PTB and three healthy controls. The results revealed differential expression of 1457 lncRNAs between the two groups, with 916 lncRNAs upregulated and 541 lncRNAs down-regulated in tuberculosis patients. Subsequent validation tests demonstrated down-regulation of lncRNA ZNF100-6:2 in patients with active PTB, which was restored following anti-tuberculosis treatment. Our findings further indicated a high diagnostic potential for lncRNA ZNF100-6:2, as evidenced by an area under the receiver operating characteristic (ROC) curve of 0.9796 (95% confidence interval: 0.9479 to 1.000; P < 0.0001). This study proposes lncRNA ZNF100-6:2 as a promising and novel diagnostic biomarker for active PTB.
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Affiliation(s)
- Shuying Huang
- Department of Reproductive Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Xiuhua Kang
- Infection Control Department of the First Affiliated Hospital of Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
- Major Public Health Medical Center of Jiangxi Province, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Zhenguo Zeng
- Department of Intensive Care Medicine, Medical Center of Anesthesiology and Pain, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
- Key Laboratory of Critical Care Medicine, Jiangxi Provincial Health Commission, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Qilong Zhang
- Department of Neurology, Chest Hospital of Jiangxi Province, Nanchang, 330006, China
| | - Zikun Huang
- Nanchang Key Laboratory of Diagnosis of Infectious Diseases, Nanchang, China
- Department of Clinical Laboratory, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Kaihang Luo
- Department of Intensive Care Medicine, Medical Center of Anesthesiology and Pain, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Qinqin Yao
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Bing Chen
- Department of Infection, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China
| | - Cheng Qing
- Department of Intensive Care Medicine, Medical Center of Anesthesiology and Pain, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Zhengjie, Nanchang, 330000, China.
- Key Laboratory of Critical Care Medicine, Jiangxi Provincial Health Commission, 17 Yongwai Zhengjie, Nanchang, 330000, China.
- Nanchang Key Laboratory of Diagnosis of Infectious Diseases, Nanchang, China.
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5
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Rocha EF, Vinhaes CL, Araújo-Pereira M, Mota TF, Gupte AN, Kumar NP, Arriaga MB, Sterling TR, Babu S, Gaikwad S, Karyakarte R, Mave V, Kulkarni V, Paradkar M, Viswanathan V, Kornfeld H, Gupta A, Andrade BB, Queiroz ATLD. The sound of silent RNA in tuberculosis and the lncRNA role on infection. iScience 2024; 27:108662. [PMID: 38205253 PMCID: PMC10777062 DOI: 10.1016/j.isci.2023.108662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 01/12/2024] Open
Abstract
Tuberculosis (TB) is one of the leading causes of death worldwide, and Diabetes Mellitus is one of the major comorbidities (TB/DM) associated with the disease. A total of 103 differentially expressed ncRNAs have been identified in the TB and TB/DM comparisons. A machine learning algorithm was employed to identify the most informative lncRNAs: ADM-DT, LINC02009, LINC02471, SOX2-OT, and GK-AS1. These lncRNAs presented substantial accuracy in classifying TB from HC (AUCs >0.85) and TB/DM from HC (AUCs >0.90) in the other three countries. Genes with significant correlations with the five lncRNAs enriched common pathways in Brazil and India for both TB and TB/DM. This suggests that lncRNAs play an important role in the regulation of genes related to the TB immune response.
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Affiliation(s)
- Eduardo Fukutani Rocha
- Centro de Integração de Dados e Conhecimentos para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
| | - Caian Leal Vinhaes
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador 40290-150, Brazil
| | - Mariana Araújo-Pereira
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador 40290-150, Brazil
- Faculdade de Tecnologia e Ciências, Instituto de Pesquisa Clínica e Translacional, Salvador, Brazil
| | - Tiago Feitosa Mota
- Centro de Integração de Dados e Conhecimentos para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
| | | | | | - Maria Belen Arriaga
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
| | - Timothy R. Sterling
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
| | - Subash Babu
- National Institutes of Health- NIRT - International Center for Excellence in Research, Chennai, India
| | - Sanjay Gaikwad
- Department of Pulmonary Medicine, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
| | - Rajesh Karyakarte
- Department of Microbiology, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
| | - Vidya Mave
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins Center for Infectious Diseases in India, Pune, India
| | - Vandana Kulkarni
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins Center for Infectious Diseases in India, Pune, India
| | - Mandar Paradkar
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins Center for Infectious Diseases in India, Pune, India
| | | | - Hardy Kornfeld
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA USA
- UMass Chan Medical School, Worcester, MA USA
| | - Amita Gupta
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | - Bruno Bezerril Andrade
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador 40290-150, Brazil
- Faculdade de Tecnologia e Ciências, Instituto de Pesquisa Clínica e Translacional, Salvador, Brazil
| | - Artur Trancoso Lopo de Queiroz
- Centro de Integração de Dados e Conhecimentos para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
| | - RePORT Brazil
- Centro de Integração de Dados e Conhecimentos para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador 40290-150, Brazil
- Boston University School of Public Health, Boston, MA USA
- National Institutes of Health- NIRT - International Center for Excellence in Research, Chennai, India
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
- Department of Pulmonary Medicine, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
- Department of Microbiology, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins Center for Infectious Diseases in India, Pune, India
- Prof. M. Viswanathan Diabetes Research Centre, Chennai, India
- Faculdade de Tecnologia e Ciências, Instituto de Pesquisa Clínica e Translacional, Salvador, Brazil
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA USA
- UMass Chan Medical School, Worcester, MA USA
- ICMR-National Institute for Research in Tuberculosis, Chennai, India
| | - RePORT India Consortia
- Centro de Integração de Dados e Conhecimentos para Saúde, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Laboratório de Inflamação e Biomarcadores, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador 40290-150, Brazil
- Boston University School of Public Health, Boston, MA USA
- National Institutes of Health- NIRT - International Center for Excellence in Research, Chennai, India
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
- Department of Pulmonary Medicine, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
- Department of Microbiology, Byramjee-Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
- Byramjee-Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Johns Hopkins Center for Infectious Diseases in India, Pune, India
- Prof. M. Viswanathan Diabetes Research Centre, Chennai, India
- Faculdade de Tecnologia e Ciências, Instituto de Pesquisa Clínica e Translacional, Salvador, Brazil
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA USA
- UMass Chan Medical School, Worcester, MA USA
- ICMR-National Institute for Research in Tuberculosis, Chennai, India
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6
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Zhang W, Zhang M, Sun M, Hu M, Yu M, Sun J, Zhang X, Du B. Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma. Front Immunol 2024; 14:1345734. [PMID: 38239355 PMCID: PMC10794662 DOI: 10.3389/fimmu.2023.1345734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 12/14/2023] [Indexed: 01/22/2024] Open
Abstract
High-grade neuroblastoma (HG-NB) exhibits a significantly diminished survival rate in comparison to low-grade neuroblastoma (LG-NB), primarily attributed to the mechanism of HG-NB is unclear and the lacking effective therapeutic targets and diagnostic model. Therefore, the current investigation aims to study the dysregulated network between HG-NB and LG-NB based on transcriptomics and metabolomics joint analysis. Meanwhile, a risk diagnostic model to distinguish HG-NB and LG-NB was also developed. Metabolomics analysis was conducted using plasma samples obtained from 48 HG-NB patients and 36 LG-NB patients. A total of 39 metabolites exhibited alterations, with 20 showing an increase and 19 displaying a decrease in HG-NB. Additionally, transcriptomics analysis was performed on NB tissue samples collected from 31 HG-NB patients and 20 LG-NB patients. Results showed that a significant alteration was observed in a total of 1,199 mRNAs in HG-NB, among which 893 were upregulated while the remaining 306 were downregulated. In particular, the joint analysis of both omics data revealed three aberrant pathways, namely the cAMP signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway, which were found to be associated with cell death. Notably, a diagnostic model for HG-NB risk classification was developed based on the genes MGST1, SERPINE1, and ERBB3 with an area under the receiver operating characteristic curve of 0.915. In the validation set, the sensitivity and specificity were determined to be 75.0% and 80.0%, respectively.
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Affiliation(s)
- Wancun Zhang
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
- Henan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Mengxin Zhang
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Meng Sun
- Henan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Minghui Hu
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Muchun Yu
- Henan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Jushan Sun
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Xianwei Zhang
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Bang Du
- Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
- Henan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, China
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7
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Li G, Feng Z, Song H, Wang Y, Zhu L, Li Y. Long non-coding RNA expression in PBMCs of patients with active pulmonary tuberculosis. Front Microbiol 2023; 14:1257267. [PMID: 38156018 PMCID: PMC10753990 DOI: 10.3389/fmicb.2023.1257267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/06/2023] [Indexed: 12/30/2023] Open
Abstract
Purpose Mycobacterium tuberculosis (Mtb) infection is the primary cause of the chronic infectious illness tuberculosis (TB). Long non-coding RNAs (lncRNAs) are functional RNA molecules that cannot be translated into proteins and play a crucial role in regulating the immune system's innate and adaptive responses. It has been demonstrated that the dysregulation of lncRNA expression is associated with various human diseases. However, the mechanism underlying the involvement of so many lncRNAs in the immune response to TB infection remains unclear. The objective of our current study was to identify a number of significantly differentially expressed lncRNAs in peripheral blood mononuclear cells (PBMCs) from TB patients and to select the most indicative lncRNAs as potential biomarkers for active pulmonary tuberculosis. Methods Microarray analysis was performed to determine the lncRNA and mRNA expression profiles in TB patients using a case-control model. The differentially expressed lncRNAs were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to investigate potential roles and pathways associated with the pathogenesis of TB infection, and to screen lncRNAs specifically linked to TB infection. Using real-time fluorescence quantitative PCR (QRT-PCR), specific lncRNAs were identified in TB patients and latent infections. Results Our findings revealed that various signaling pathways were differentially expressed in TB-infected individuals, suggesting a potential role for lncRNAs in the immunological responses driven by TB infection. This study provides crucial guidelines for future functional research. Upregulated lncRNAs were mainly enriched in Neutrophil extracellular trap formation and Chemokine signaling pathways, while downregulated lncRNAs were enriched in Neuroactive ligand-receptor interaction and Cushing syndrome in TB PBMCs. Furthermore, we found that lnc-XPNPEP1-5, lnc-CASKIN2-2, lnc-HSPA13-6, lnc-CLIC5-1, and LINC02502 were significantly downregulated in TB-infected patients, while LINC00528, lnc-SLC45A4-3, and LINC00926 were significantly upregulated in TB patients and latent infections. These eight lncRNAs, identified as novel biological marker candidates for diagnosing TB infection, were validated by real-time fluorescence quantitative PCR (QRT-PCR). Conclusion The abnormally expressed lncRNAs identified in this research may provide crucial information for understanding the pathophysiological characteristics of TB patients and the dysfunction of PBMCs. Our findings reveal potential targets for early TB diagnosis and therapy, as well as offer new insights into the mechanisms underlying TB infection.
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Affiliation(s)
- Guoli Li
- Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Zhelong Feng
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Honghuan Song
- Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yajing Wang
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Limei Zhu
- Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yan Li
- Integrated Service and Management Office, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
- Department of Chronic Communicable Disease, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
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8
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Xia J, Liu Y, Ma Y, Yang F, Ruan Y, Xu JF, Pi J. Advances of Long Non-Coding RNAs as Potential Biomarkers for Tuberculosis: New Hope for Diagnosis? Pharmaceutics 2023; 15:2096. [PMID: 37631310 PMCID: PMC10458399 DOI: 10.3390/pharmaceutics15082096] [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: 07/12/2023] [Revised: 07/31/2023] [Accepted: 08/03/2023] [Indexed: 08/27/2023] Open
Abstract
Tuberculosis (TB), one of the top ten causes of death globally induced by the infection of Mycobacterium tuberculosis (Mtb), remains a grave public health issue worldwide. With almost one-third of the world's population getting infected by Mtb, between 5% and 10% of these infected individuals are predicted to develop active TB disease, which would not only result in severe tissue damage and necrosis, but also pose serious threats to human life. However, the exact molecular mechanisms underlying the pathogenesis and immunology of TB remain unclear, which significantly restricts the effective control of TB epidemics. Despite significant advances in current detection technologies and treatments for TB, there are still no appropriate solutions that are suitable for simultaneous, early, rapid, and accurate screening of TB. Various cellular events can perturb the development and progression of TB, which are always associated with several specific molecular signaling events controlled by dysregulated gene expression patterns. Long non-coding RNAs (lncRNAs), a kind of non-coding RNA (ncRNA) with a transcript of more than 200 nucleotides in length in eukaryotic cells, have been found to regulate the expression of protein-coding genes that are involved in some critical signaling events, such as inflammatory, pathological, and immunological responses. Increasing evidence has claimed that lncRNAs might directly influence the susceptibility to TB, as well as the development and progression of TB. Therefore, lncRNAs have been widely expected to serve as promising molecular biomarkers and therapeutic targets for TB. In this review, we summarized the functions of lncRNAs and their regulatory roles in the development and progression of TB. More importantly, we widely discussed the potential of lncRNAs to act as TB biomarkers, which would offer new possibilities in novel diagnostic strategy exploration and benefit the control of the TB epidemic.
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Affiliation(s)
- Jiaojiao Xia
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China
| | - Yilin Liu
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- Institute of Laboratory Medicine, School of Medical Technology, Guangdong Medical University, Dongguan 523808, China
| | - Yuhe Ma
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- Institute of Laboratory Medicine, School of Medical Technology, Guangdong Medical University, Dongguan 523808, China
| | - Fen Yang
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- Institute of Laboratory Medicine, School of Medical Technology, Guangdong Medical University, Dongguan 523808, China
| | - Yongdui Ruan
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
| | - Jun-Fa Xu
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang 524023, China
| | - Jiang Pi
- Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China; (J.X.); (Y.L.); (Y.M.); (F.Y.); (Y.R.)
- Institute of Laboratory Medicine, School of Medical Technology, Guangdong Medical University, Dongguan 523808, China
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang 524023, China
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9
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Lyu M, Zhou J, Zhou Y, Chong W, Xu W, Lai H, Niu L, Hai Y, Yao X, Gong S, Wang Q, Chen Y, Wang Y, Chen L, Zengwanggema, Zeng J, Wang C, Ying B. From tuberculosis bedside to bench: UBE2B splicing as a potential biomarker and its regulatory mechanism. Signal Transduct Target Ther 2023; 8:82. [PMID: 36828823 PMCID: PMC9958017 DOI: 10.1038/s41392-023-01346-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/08/2023] [Accepted: 02/08/2023] [Indexed: 02/26/2023] Open
Abstract
Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.
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Affiliation(s)
- Mengyuan Lyu
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Jian Zhou
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Yanbing Zhou
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Weelic Chong
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Wei Xu
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, M5G 1L7, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, M5T 3M7, Canada
| | - Hongli Lai
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Lu Niu
- Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Yang Hai
- Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, PA, 19107, USA
| | - Xiaojun Yao
- Department of Thoracic Surgery, The Public and Health Clinic Centre of Chengdu, Chengdu, Sichuan, 610066, China
| | - Sheng Gong
- Department of Thoracic Surgery, The Public and Health Clinic Centre of Chengdu, Chengdu, Sichuan, 610066, China
| | - Qinglan Wang
- Department of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, 610213, China
| | - Yi Chen
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Yili Wang
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Liyu Chen
- Department of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
- Zhaojue People's Hospital of Liangshan Prefecture, Liangshan Prefecture, Sichuan, 616150, China
| | - Zengwanggema
- Department of Laboratory Medicine, Ganzi People's Hospital, Ganzi Prefecture, Sichuan, 626099, China
| | - Jiongjiong Zeng
- Department of Laboratory Medicine, Ganzi People's Hospital, Ganzi Prefecture, Sichuan, 626099, China
| | - Chengdi Wang
- Department of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, 610213, China
| | - Binwu Ying
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
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10
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Liang S, Ma J, Gong H, Shao J, Li J, Zhan Y, Wang Z, Wang C, Li W. Immune regulation and emerging roles of noncoding RNAs in Mycobacterium tuberculosis infection. Front Immunol 2022; 13:987018. [PMID: 36311754 PMCID: PMC9608867 DOI: 10.3389/fimmu.2022.987018] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 08/29/2022] [Indexed: 05/10/2024] Open
Abstract
Tuberculosis, caused by Mycobacterium tuberculosis, engenders an onerous burden on public hygiene. Congenital and adaptive immunity in the human body act as robust defenses against the pathogens. However, in coevolution with humans, this microbe has gained multiple lines of mechanisms to circumvent the immune response to sustain its intracellular persistence and long-term survival inside a host. Moreover, emerging evidence has revealed that this stealthy bacterium can alter the expression of demic noncoding RNAs (ncRNAs), leading to dysregulated biological processes subsequently, which may be the rationale behind the pathogenesis of tuberculosis. Meanwhile, the differential accumulation in clinical samples endows them with the capacity to be indicators in the time of tuberculosis suffering. In this article, we reviewed the nearest insights into the impact of ncRNAs during Mycobacterium tuberculosis infection as realized via immune response modulation and their potential as biomarkers for the diagnosis, drug resistance identification, treatment evaluation, and adverse drug reaction prediction of tuberculosis, aiming to inspire novel and precise therapy development to combat this pathogen in the future.
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Affiliation(s)
- Shufan Liang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Jiechao Ma
- Artificial Intelligence (AI) Lab, Deepwise Healthcare, Beijing, China
| | - Hanlin Gong
- Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jun Shao
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Jingwei Li
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Yuejuan Zhan
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Zhoufeng Wang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Chengdi Wang
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
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11
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Zhang X, Chen C, Xu Y. Long Non-coding RNAs in Tuberculosis: From Immunity to Biomarkers. Front Microbiol 2022; 13:883513. [PMID: 35633669 PMCID: PMC9130765 DOI: 10.3389/fmicb.2022.883513] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 03/24/2022] [Indexed: 12/05/2022] Open
Abstract
Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is the leading lethal infectious disease with 1.3 million deaths in 2020. Despite significant advances have been made in detection techniques and therapeutic approaches for tuberculosis, no suitable diagnostic tools are available for early and precise screening. Many studies have reported that Long non-coding RNAs (lncRNAs) play a regulatory role in gene expression in the host immune response against Mtb. Dysregulation of lncRNAs expression patterns associated with immunoregulatory pathways arose in mycobacterial infection. Meanwhile, host-induced lncRNAs regulate antibacterial processes such as apoptosis and autophagy to limit bacterial proliferation. In this review, we try to summarize the latest reports on how dysregulated expressed lncRNAs influence host immune response in tuberculosis infection. We also discuss their potential clinical prospects for tuberculosis diagnosis and development as molecular biomarkers.
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Affiliation(s)
- Xianyi Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,The People's Hospital of Baoan Shenzhen, Southern Medical University, Shenzhen, China
| | - Chan Chen
- The People's Hospital of Baoan Shenzhen, Southern Medical University, Shenzhen, China
| | - Yuzhong Xu
- The People's Hospital of Baoan Shenzhen, Southern Medical University, Shenzhen, China
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12
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Sun X, Liu K, Zhao Y, Zhang T. High miRNA-378 expression has high diagnostic values for pulmonary tuberculosis and predicts adverse outcomes. BMC Mol Cell Biol 2022; 23:14. [PMID: 35305574 PMCID: PMC8934448 DOI: 10.1186/s12860-022-00413-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 02/28/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Pulmonary tuberculosis (TB) is a chronic infectious disease. microRNA (miR)-378 is involved in TB diagnosis. This study explored the effects of miR-378 on TB patients. METHODS A total of 126 TB patients were selected, including 63 active TB and 63 latent TB, with 62 healthy subjects as controls. Serum miR-378 expression was detected. The diagnostic value of miR-378 in TB was analyzed using the ROC curve. Immune inflammatory factor levels were detected and their correlations with miR-378 expression were analyzed. The drug resistance of active TB patients was recorded after standard treatment. miR-378 expression in drug-resistant TB patients was detected. The effects of miR-378 on adverse outcome incidence were analyzed. RESULTS miR-378 expression was highly expressed in TB and the expression was higher in the active group than the latent group. Serum miR-378 expression > 1.490 had high sensitivity and specificity in TB diagnosis. miR-378 expression was correlated with TB clinical indexes. IL-4, IL-6, and IL-1β levels were highly expressed, while IFN-γ, TNF-α, and IL-12 levels were lowly expressed in TB patients. Serum miR-378 level in the active group was positively correlated with serum IL-4, IL-6, and IL-1β, and negatively correlated with serum IFN-γ, TNF-α, and IL-12 concentrations. miR-378 expression was downregulated in the TB treated, single (SDR TB) and multi-drug resistance (MDR TB) groups, the miR-378 expression in SDR TB and MDR TB groups was higher than the TB treated group and lower in the SDR TB group than the MDR TB group. High miR-378 expression predicted higher adverse outcome incidence. CONCLUSIONS High miR-378 expression assisted TB diagnosis and predicted adverse outcomes.
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Affiliation(s)
- Xiaolu Sun
- Department of Tuberculosis Treatmen and Prevention, Shaanxi Provincial Institute for Tuberculosis Control and Prevention, 4# of Xingqing South Road, Xi'an, 710048, Shaanxi, China.
| | - Kai Liu
- Department of Orthopedics, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yan Zhao
- Department of Tuberculosis Treatmen and Prevention, Shaanxi Provincial Institute for Tuberculosis Control and Prevention, 4# of Xingqing South Road, Xi'an, 710048, Shaanxi, China
| | - Tianhua Zhang
- Department of Tuberculosis Treatmen and Prevention, Shaanxi Provincial Institute for Tuberculosis Control and Prevention, 4# of Xingqing South Road, Xi'an, 710048, Shaanxi, China
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13
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Zhao J, Gao S, Chen C, Li H, Wang S, Yu Y, Ming L. Screening and identification of differentially expressed long non-coding RNAs in multidrug-resistant tuberculosis. PeerJ 2022; 10:e12776. [PMID: 35111403 PMCID: PMC8772445 DOI: 10.7717/peerj.12776] [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: 09/22/2021] [Accepted: 12/21/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Efforts to eradicate tuberculosis are largely threatened by drug-resistant tuberculosis, particularly, multidrug-resistant tuberculosis (MDR-TB). Screening and identification potential biomarkers for MDR-TB is crucial to diagnose early and reduce the incidence of MDR-TB. METHODS To screen the differentially expressed long non-coding RNAs in MDR-TB, the lncRNA and mRNA expression profiles in serum derived from healthy controls (HCs), individuals with MDR-TB and drug-sensitive tuberculosis (DS-TB) were analyzed by microarray assay and 10 lncRNAs were randomly selected for further validation by reverse transcription-quantitative real-time PCR(RT-qPCR). The biological functions of differentially expressed mRNAs as well as relationships between genes and signaling pathways were investigated using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), respectively. RESULTS A total of 353 differentially expressed lncRNAs (312 upregulated) and 202 mRNAs (99 upregulated) were found in the MDR-TB group compared to HCs. And compared with the DS-TB group, 442 differentially expressed lncRNAs (115 upregulated) and 190 mRNAs (87 upregulated) were found in the MDR-TB group. The expression levels of lncRNA n335659 were found to differ significantly between each group by RT-qPCR. Compared with DS-TB group, the GO analysis showed that the differential mRNAs were mainly enriched in the processes associated with the detection of the chemical stimulus, the regulation of mRNA metabolic process and neutrophil activation in the MDR-TB group; the KEGG analysis indicated that the differential mRNAs between DS-TB and MDR-TB were mainly enriched in proteasome and Notch signaling pathway, which might reveal a fraction of the mechanism of MDR-TB. The discovery of the serum lncRNA n335659 might serve as a potential biomarker for MDR-TB and Notch signaling pathway provided a new clue for the investigation of the pathological mechanism of MDR-TB.
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Affiliation(s)
- Junwei Zhao
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - ShuHui Gao
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chunguang Chen
- Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, China
| | - Hui Li
- Tuberculosis Reference Laboratory, Centers for Disease Control and Prevention of Henan Province, Zhengzhou, China
| | - Shaohua Wang
- Tuberculosis Reference Laboratory, Centers for Disease Control and Prevention of Henan Province, Zhengzhou, China
| | - Yongmin Yu
- Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, China
| | - Liang Ming
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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14
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Feng J, Bian Q, He X, Zhang H, He J. A LncRNA-miRNA-mRNA ceRNA regulatory network based tuberculosis prediction model. Microb Pathog 2021; 158:105069. [PMID: 34175436 DOI: 10.1016/j.micpath.2021.105069] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/14/2021] [Accepted: 06/21/2021] [Indexed: 12/16/2022]
Abstract
The high incidence of tuberculosis (TB) has brought serious social burdens and it is urgent to explore the mechanism of TB development. This study was conducted to analyze the role of lncRNA-miRNA-mRNA regulatory network and its contained nodes involved in TB to identify crucial biomarkers for early diagnosis of TB. Long-noncoding RNAs (lncRNAs), messenger RNA (mRNAs) and microRNAs (miRNAs) expression profiles of TB patients and healthy individuals were downloaded from the GSE34608 dataset. Weighted gene co-expression network analysis (WGCNA) was performed to identified the key modules related to TB and the highly related mRNA-lncRNA pair in the module. Based on highly related mRNAs and lncRNAs in greenyellow module, lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed. The DE-mRNAs in the network were functionally enriched with Gene ontology (GO) and Gene set enrichment analysis (GSEA). Least absolute shrinkage and selection operator (LASSO) algorithm and receiver operating characteristic curve (ROC) were used to construct and evaluate the prediction model of TB. We identified 3267 DE-mRNAs, 484 DE-lncRNAs and 69 DE-miRNAs between the TB and healthy subjects, from which 8 DE-mRNAs, 14 DE-lncRNAs and 3 DE-miRNAs were used to construct the ceRNA network. The genes contained in the ceRNA network were mainly enriched in neutrophil mediated immune response, including neutrophil activation, degradation and signal transduction. ROC analysis revealed that has-miR-140-5p, has-miR-142-3p and the LASSO cox prediction model based on HMGA1 and CAPN1 have potential value for forecasting TB (AUC > 0.7). Hence, our study provides a new perspective from the lncRNA-miRNA-mRNA ceRNA regulatory network for TB diagnosis and treatment.
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Affiliation(s)
- Jinfang Feng
- Clinical Laboratory Department, Guangyuan Central Hospital, Guangyuan, 628000, China
| | - Qin Bian
- Clinical Laboratory Department, Guangyuan Central Hospital, Guangyuan, 628000, China.
| | - Xianwei He
- Clinical Laboratory Department, Guangyuan Central Hospital, Guangyuan, 628000, China
| | - Han Zhang
- Clinical Laboratory Department, Guangyuan Central Hospital, Guangyuan, 628000, China
| | - Jiujiang He
- Clinical Laboratory Department, Guangyuan Central Hospital, Guangyuan, 628000, China
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15
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Kundu M, Basu J. The Role of microRNAs and Long Non-Coding RNAs in the Regulation of the Immune Response to Mycobacterium tuberculosis Infection. Front Immunol 2021; 12:687962. [PMID: 34248974 PMCID: PMC8264550 DOI: 10.3389/fimmu.2021.687962] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/09/2021] [Indexed: 12/16/2022] Open
Abstract
Non-coding RNAs have emerged as critical regulators of the immune response to infection. MicroRNAs (miRNAs) are small non-coding RNAs which regulate host defense mechanisms against viruses, bacteria and fungi. They are involved in the delicate interplay between Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), and its host, which dictates the course of infection. Differential expression of miRNAs upon infection with M. tuberculosis, regulates host signaling pathways linked to inflammation, autophagy, apoptosis and polarization of macrophages. Experimental evidence suggests that virulent M. tuberculosis often utilize host miRNAs to promote pathogenicity by restricting host-mediated antibacterial signaling pathways. At the same time, host- induced miRNAs augment antibacterial processes such as autophagy, to limit bacterial proliferation. Targeting miRNAs is an emerging option for host-directed therapies. Recent studies have explored the role of long non-coding RNA (lncRNAs) in the regulation of the host response to mycobacterial infection. Among other functions, lncRNAs interact with chromatin remodelers to regulate gene expression and also function as miRNA sponges. In this review we attempt to summarize recent literature on how miRNAs and lncRNAs are differentially expressed during the course of M. tuberculosis infection, and how they influence the outcome of infection. We also discuss the potential use of non-coding RNAs as biomarkers of active and latent tuberculosis. Comprehensive understanding of the role of these non-coding RNAs is the first step towards developing RNA-based therapeutics and diagnostic tools for the treatment of TB.
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Affiliation(s)
| | - Joyoti Basu
- Department of Chemistry, Bose Institute, Kolkata, India
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16
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Gao SH, Chen CG, Zhuang CB, Zeng YL, Zeng ZZ, Wen PH, Yu YM, Ming L, Zhao JW. Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis. J Clin Lab Anal 2021; 35:e23871. [PMID: 34106501 PMCID: PMC8373357 DOI: 10.1002/jcla.23871] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 04/29/2021] [Accepted: 05/25/2021] [Indexed: 12/14/2022] Open
Abstract
Background To verify the differential expression of miR‐30c and miR‐142‐3p between tuberculosis patients and healthy controls and to investigate the performance of microRNA (miRNA) and subsequently models for the diagnosis of tuberculosis (TB). Methods We followed up 460 subjects suspected of TB, and finally enrolled 132 patients, including 60 TB patients, 24 non‐TB disease controls (TB‐DCs), and 48 healthy controls (HCs). The differential expression of miR‐30c and miR‐142‐3p in serum samples of the TB patients, TB‐DCs, and HCs were identified by reverse transcription–quantitative real‐time PCR. Diagnostic models were developed by analyzing the characteristics of miRNA and electronic health records (EHRs). These models evaluated by the area under the curves (AUC) and calibration curves were presented as nomograms. Results There were differential expression of miR‐30c and miR‐142‐3p between TB patients and HCs (p < 0.05). Individual miRNA has a limited diagnostic value for TB. However, diagnostic performance has been both significantly improved when we integrated miR‐142‐3p and ordinary EHRs to develop two models for the diagnosis of tuberculosis. The AUC of the model for distinguishing tuberculosis patients from healthy controls has increased from 0.75 (95% CI: 0.66–0.84) to 0.96 (95% CI: 0.92–0.99) and the model for distinguishing tuberculosis patients from non‐TB disease controls has increased from 0.67 (95% CI: 0.55–0.79) to 0.94 (95% CI: 0.89–0.99). Conclusions Integrating serum miR‐142‐3p and EHRs is a good strategy for improving TB diagnosis.
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Affiliation(s)
- Shu-Hui Gao
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chun-Guang Chen
- Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, 450000, China
| | - Chun-Bo Zhuang
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yu-Ling Zeng
- Department of Clinical Laboratory, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhen-Zhen Zeng
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Pei-Hao Wen
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yong-Min Yu
- Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou, 450000, China
| | - Liang Ming
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jun-Wei Zhao
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
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17
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Li Z, Liu L, Jiang S, Li Q, Feng C, Du Q, Zou D, Xiao J, Zhang Z, Ma L. LncExpDB: an expression database of human long non-coding RNAs. Nucleic Acids Res 2021; 49:D962-D968. [PMID: 33045751 PMCID: PMC7778919 DOI: 10.1093/nar/gkaa850] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 09/12/2020] [Accepted: 09/22/2020] [Indexed: 12/14/2022] Open
Abstract
Expression profiles of long non-coding RNAs (lncRNAs) across diverse biological conditions provide significant insights into their biological functions, interacting targets as well as transcriptional reliability. However, there lacks a comprehensive resource that systematically characterizes the expression landscape of human lncRNAs by integrating their expression profiles across a wide range of biological conditions. Here, we present LncExpDB (https://bigd.big.ac.cn/lncexpdb), an expression database of human lncRNAs that is devoted to providing comprehensive expression profiles of lncRNA genes, exploring their expression features and capacities, identifying featured genes with potentially important functions, and building interactions with protein-coding genes across various biological contexts/conditions. Based on comprehensive integration and stringent curation, LncExpDB currently houses expression profiles of 101 293 high-quality human lncRNA genes derived from 1977 samples of 337 biological conditions across nine biological contexts. Consequently, LncExpDB estimates lncRNA genes' expression reliability and capacities, identifies 25 191 featured genes, and further obtains 28 443 865 lncRNA-mRNA interactions. Moreover, user-friendly web interfaces enable interactive visualization of expression profiles across various conditions and easy exploration of featured lncRNAs and their interacting partners in specific contexts. Collectively, LncExpDB features comprehensive integration and curation of lncRNA expression profiles and thus will serve as a fundamental resource for functional studies on human lncRNAs.
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Affiliation(s)
- Zhao Li
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Lin Liu
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Shuai Jiang
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Qianpeng Li
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Changrui Feng
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Du
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Dong Zou
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jingfa Xiao
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Zhang Zhang
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100101, China
| | - Lina Ma
- China National Center for Bioinformation, Beijing 100101, China.,National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
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Li Y, He D, Che Y, Zhao X. Monokine induced by gamma interferon for detecting pulmonary tuberculosis: A diagnostic meta-analysis. Medicine (Baltimore) 2020; 99:e23302. [PMID: 33217864 PMCID: PMC7676613 DOI: 10.1097/md.0000000000023302] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUNDS Pulmonary tuberculosis (PTB) is an oldest-known and most formidable disease. The standard microbiology culture is time-wasting. Monokine induced by gamma interferon (MIG) has been reported as a new biomarker to auxiliarily detect PTB. In our study, we used meta-analysis to assess the diagnostic value of MIG for PTB. METHODS PubMed, Embase, Web of Science, and Cochrane Library were searched for relative records up to April 2, 2020. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, area under the curve, and summary receiver operating characteristic curve were estimated. RESULTS Eight studies including 1487 participants were included. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of MIG for detecting PTB were 84%, 84%, 5.19, and 0.19, respectively. The diagnostic odds ratio and area under the curve were 27.88 and 0.90, respectively, indicating a good diagnostic ability of MIG. Meta-regression analysis showed that human immunodeficiency virus status might be a source of heterogeneity (P = .02). CONCLUSIONS Our results showed that MIG had a good diagnostic value for PTB.
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