{"title":"在结核病流行地区诊断活动性肺结核的候选血清蛋白生物标志物。","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":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583743/pdf/","citationCount":"0","resultStr":"{\"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\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583743/pdf/\",\"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}","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
摘要
背景:亟需鉴定结核病(TB)的非痰诊断标志物。这项探索性研究旨在发现诊断活动性肺结核(PTB)的潜在血清蛋白生物标志物:方法:我们采用近距离延伸测定法(PEA)测量了三组患者血清样本中与炎症相关的 92 种蛋白质生物标记物的水平,这三组患者分别是:30 名活动性肺结核患者、29 名患有其他呼吸道疾病并伴有肺结核潜伏期的患者(ORD with LTBI+)和 29 名患有其他呼吸道疾病但不伴有肺结核潜伏期的患者(ORD with LTBI-)。为了解与差异表达蛋白相关的功能机制,我们进行了基因本体(GO)和京都基因与基因组百科全书(KEGG)通路分析。我们采用最小绝对收缩和选择算子(LASSO)回归法来识别潜在的结核病诊断蛋白生物标记物。然后分析了已确定的候选诊断标记物之间的网络交互作用,并使用逻辑回归和接收者操作特征(ROC)分析评估了它们的诊断性能:结果:分析结果显示,在活动性肺结核组中,与ORD伴LTBI+组和ORD伴LTBI-组相比,有37个差异表达蛋白(DEPs)。基因本体分析表明,这些差异表达蛋白主要参与炎症反应,而 KEGG 富集分析则强调细胞因子-细胞因子受体相互作用通路是最重要的表达途径。LASSO 回归确定了八个有希望的候选蛋白质生物标记物:IFN-γ、LIF、uPA、CSF-1、SCF、SIRT2、4E-BP1 和 GDNF。这八种蛋白质的组合在区分活动性PTB和LTBI+ ORD时的AUC为0.943,在区分PTB和LTBI- ORD时的AUC为0.927:结论:我们发现了八种蛋白质标记物,无论是否存在LTBI,它们都能可靠地区分活动性PTB和ORD。进一步大规模验证这些蛋白标记物并将其转化为方便用户且价格合理的床旁检测方法,有望显著提高高负担地区的结核病控制水平。
Candidate serum protein biomarkers for active pulmonary tuberculosis diagnosis in tuberculosis endemic settings.
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.