Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
Department of Biology, College of Natural and Computational Sciences, Arba Minch University, Arba Minch, Ethiopia.
BMC Infect Dis. 2024 Nov 21;24(1):1329. doi: 10.1186/s12879-024-10224-3.
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).
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.
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-.
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.
迫切需要鉴定非痰液诊断标志物用于结核病(TB)。本探索性研究旨在发现用于诊断活动性肺结核(PTB)的潜在血清蛋白生物标志物。
我们采用临近延伸分析(PEA)检测三组患者血清样本中 92 种与炎症相关的蛋白生物标志物的水平:30 例活动性 PTB 患者、29 例潜伏性结核病合并其他呼吸道疾病(ORD with LTBI+)患者和 29 例潜伏性结核病合并其他呼吸道疾病(ORD with LTBI-)患者。为了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论(GO)和京都基因与基因组百科全书(KEGG)通路分析。采用最小绝对收缩和选择算子(LASSO)回归鉴定潜在的 TB 诊断蛋白生物标志物。然后分析鉴定出的候选诊断标志物之间的网络相互作用,并采用逻辑回归和受试者工作特征(ROC)分析评估其诊断性能。
与 ORD with LTBI+和 ORD with LTBI-组相比,PTB 组有 37 个差异表达蛋白(DEPs)。GO 分析表明这些 DEPs 主要参与炎症反应,KEGG 富集分析突出细胞因子-细胞因子受体相互作用通路为最显著的命中。LASSO 回归鉴定出 8 种有前途的候选蛋白生物标志物:IFN-γ、LIF、uPA、CSF-1、SCF、SIRT2、4E-BP1 和 GDNF。这 8 种蛋白的组合对区分活动性 PTB 与 ORD with LTBI+的 AUC 为 0.943,区分 PTB 与 ORD with LTBI-的 AUC 为 0.927。
我们鉴定出 8 种蛋白标志物,可可靠地区分活动性 PTB 与无论 LTBI 存在与否的 ORD。进一步对这些蛋白标志物进行大规模验证并转化为用户友好且负担得起的即时检测方法,有可能显著加强高负担地区的结核病控制。