{"title":"Candidate serum protein biomarkers for active pulmonary tuberculosis diagnosis in tuberculosis endemic settings.","authors":"Sosina Ayalew, Teklu Wegayehu, Biniam Wondale, Azeb Tarekegn, Bamlak Tessema, Filippos Admasu, Anne Piantadosi, Maryam Sahi, Tewodros Tariku Gebresilase, Claudia Fredolini, Adane Mihret","doi":"10.1186/s12879-024-10224-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Identification of non-sputum diagnostic markers for tuberculosis (TB) is urgently needed. This exploratory study aimed to discover potential serum protein biomarkers for the diagnosis of active pulmonary TB (PTB).</p><p><strong>Method: </strong>We employed Proximity Extension Assay (PEA) to measure levels of 92 protein biomarkers related to inflammation in serum samples from three patient groups: 30 patients with active PTB, 29 patients with other respiratory diseases with latent TB (ORD with LTBI+), and 29 patients with other respiratory diseases without latent TB (ORD with LTBI-). To understand the functional mechanisms associated with differentially expressed proteins, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify potential TB diagnostic protein biomarkers. Network interactions among the identified candidate diagnostic markers were then analyzed, and their diagnostic performance was evaluated using logistic regression and receiver operating characteristic (ROC) analysis.</p><p><strong>Result: </strong>The analysis revealed 37 differentially expressed proteins (DEPs) in the active PTB group compared to both ORD with LTBI + and ORD with LTBI- groups. Gene Ontology analysis indicated that these DEPs were primarily involved in the inflammatory response, while KEGG enrichment analysis highlighted the cytokine-cytokine receptor interaction pathway as the top significant hit. LASSO regression identified eight promising candidate protein biomarkers: IFN-gamma, LIF, uPA, CSF-1, SCF, SIRT2, 4E-BP1, and GDNF. The combined set of these eight proteins yielded an AUC of 0.943 for differentiating active PTB from ORD with LTBI+, and an AUC of 0.927 for distinguishing PTB from ORD with LTBI-.</p><p><strong>Conclusion: </strong>We have identified eight protein markers that reliably differentiate active PTB from ORD irrespective of LTBI presence. Further large-scale validation and translation of these protein markers into a user-friendly and affordable point-of-care test hold the potential to significantly enhance TB control in high-burden regions.</p>","PeriodicalId":8981,"journal":{"name":"BMC Infectious Diseases","volume":"24 1","pages":"1329"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Infectious Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12879-024-10224-3","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Identification of non-sputum diagnostic markers for tuberculosis (TB) is urgently needed. This exploratory study aimed to discover potential serum protein biomarkers for the diagnosis of active pulmonary TB (PTB).
Method: We employed Proximity Extension Assay (PEA) to measure levels of 92 protein biomarkers related to inflammation in serum samples from three patient groups: 30 patients with active PTB, 29 patients with other respiratory diseases with latent TB (ORD with LTBI+), and 29 patients with other respiratory diseases without latent TB (ORD with LTBI-). To understand the functional mechanisms associated with differentially expressed proteins, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify potential TB diagnostic protein biomarkers. Network interactions among the identified candidate diagnostic markers were then analyzed, and their diagnostic performance was evaluated using logistic regression and receiver operating characteristic (ROC) analysis.
Result: The analysis revealed 37 differentially expressed proteins (DEPs) in the active PTB group compared to both ORD with LTBI + and ORD with LTBI- groups. Gene Ontology analysis indicated that these DEPs were primarily involved in the inflammatory response, while KEGG enrichment analysis highlighted the cytokine-cytokine receptor interaction pathway as the top significant hit. LASSO regression identified eight promising candidate protein biomarkers: IFN-gamma, LIF, uPA, CSF-1, SCF, SIRT2, 4E-BP1, and GDNF. The combined set of these eight proteins yielded an AUC of 0.943 for differentiating active PTB from ORD with LTBI+, and an AUC of 0.927 for distinguishing PTB from ORD with LTBI-.
Conclusion: We have identified eight protein markers that reliably differentiate active PTB from ORD irrespective of LTBI presence. Further large-scale validation and translation of these protein markers into a user-friendly and affordable point-of-care test hold the potential to significantly enhance TB control in high-burden regions.
期刊介绍:
BMC Infectious Diseases is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of infectious and sexually transmitted diseases in humans, as well as related molecular genetics, pathophysiology, and epidemiology.