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      Transcriptional signatures of human peripheral blood mononuclear cells can identify the risk of tuberculosis progression from latent infection among individuals with silicosis

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          ABSTRACT

          Host immune factor plays an important role in the progression of latent tuberculosis infection (LTBI) to active tuberculosis (TB) disease. However, whether global gene expression measured in blood biomarkers allows the identification of prospective signatures for TB risk remains unknown. Hence, we aimed to assess the ability of the transcriptome signatures in the human peripheral blood mononuclear cells (PBMCs) of LTBI subjects to differentiate future TB progressors from non-progressors. In a randomized clinical trial of TB preventive treatment of 513 participants with silicosis, we randomly collected PBMC samples from 50 LTBI subjects in the observational group, which was monitored for TB disease progression for 37 months. The prospective signatures of TB risk between the two participants who developed active TB (progressors) and four matched individuals who remained healthy (non-progressors) were compared using differential expression analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Weighted Gene Co-expression Network Analysis. The 20 TB-specific differentially expressed genes, which were significantly downregulated in TB progressors, were revealed to be associated with interferon-gamma response-related genes. Therefore, the PBMC transcriptome profiles analyzed in this study may help identify LTBI individuals who are at risk of progressing to active TB among silicosis patients and may provide new insights for targeted intervention to prevent disease progression.

          Clinical trial registration

          www.clinicaltrials.gov (NCT02430259)

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          Most cited references33

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Journal
                Emerg Microbes Infect
                Emerg Microbes Infect
                Emerging Microbes & Infections
                Taylor & Francis
                2222-1751
                6 August 2021
                2021
                : 10
                : 1
                : 1536-1544
                Affiliations
                [a ]Department of Infectious Diseases, Huashan Hospital, School of Life Science, Fudan University , Shanghai, People’s Republic of China
                [b ]National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University , Shanghai, People’s Republic of China
                [c ]Key Laboratory of Medical Molecular Virology (MOE/MOH) and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University , Shanghai, People’s Republic of China
                Author notes
                [CONTACT ] Wen-hong Zhang zhangwenhong@ 123456fudan.edu.cn
                [*]

                These authors contributed equally to this work.

                [**]

                Present address: Key Laboratory of Infectious Diseases and Biosafety Emergency Response, Fudan University, Shanghai, People's Republic of China.

                Supplemental data for this article can be accessed online at https://doi.org/10.1080/22221751.2021.1915184.

                Article
                1915184
                10.1080/22221751.2021.1915184
                8354161
                34042560
                354be4f4-9bd9-4c9f-8a2a-561c3a7460f8
                © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 34, Pages: 9
                Categories
                Research Article
                Research Article

                tuberculosis,peripheral blood mononuclear cell,biomarker,latent tuberculosis infection,rna sequencing,interferon-gamma

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