The performance of long non-coding rnas in the differential diagnosis of elderly pulmonary tuberculosis
10.3760/cma.j.issn.0254-9026.2025.06.022
- VernacularTitle:长链非编码RNA在老年肺结核鉴别诊断中的价值评估
- Author:
Xiuxiu JI
1
;
Siyu YAO
;
Jing DONG
;
Qiuyue LIU
;
Yingchao WANG
;
Xuetian SHANG
;
Hongyan JIA
;
Lanyue ZHANG
;
Chuanzhi ZHU
;
Zongde ZHANG
;
Liping PAN
Author Information
1. 首都医科大学附属北京胸科医院分子生物学实验室 耐药结核病研究北京市重点实验室 北京市结核病胸部肿瘤研究所，北京 101149
- Publication Type:Journal Article
- Keywords:
Mycobacterium tuberculosis;
Diagnosis;
ROC curve;
Non-TB pulmonary diseases;
Long non-coding RNA
- From:
Chinese Journal of Geriatrics
2025;44(6):801-807
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To detect the expression levels of long non-coding RNAs(lncRNA)in elderly patients with pulmonary tuberculosis(PTB)and those with non-tuberculous lung diseases(non-TB), and to assess the performance of these lncRNA in the differential diagnosis of PTB.Methods:A total of 300 elderly patients with suspected PTB were recruited from Beijing Chest Hospital between January 2024 and September 2024, and were further divided into the PTB group and the non-TB lung disease group based on the results of mycobacterium tuberculosis(MTB)pathogenicity testing.Peripheral blood mononuclear cells were isolated using a lymphocyte separation solution, and RNA was extracted using the TRIzol method.Nine lncRNAs, previously identified as differentially expressed in PTB through our group's microarray analysis, were selected and detected by real-time fluorescence quantitative polymerase chain reaction to evaluate the expression levels of these lncRNAs between the PTB and non-TB lung disease groups.The overall patients were randomly divided into training and validation sets in a 7∶3 ratio.Lasso regression was employed to select the characteristic variables, and a random forest algorithm was then used to construct the lncRNA diagnostic portfolio.Receiver operating characteristic(ROC)curves were generated to evaluate the diagnostic performance of individual lncRNAs and the combined panel in differentiating elderly patients with PTB from those with other non-TB lung diseases.Results:A total of 201 cases were included, with 105 confirmed elderly patients diagnosed with PTB(52.2%)and 96 elderly patients suffering from non-TB lung disease(47.8%).Compared to the elderly patients with non-TB lung disease, the expression levels of ENST00000417346.1, ENST00000620744.1, lncRNA PWP1, ENST00000583184.1, lncRNA ABHD17B, ENST00000607464.1, ENST00000516057.1, and NR_003000 were significantly downregulated in the PTB patients, whereas the expression level of lncRNA BCL2L10 was significantly upregulated in the PTB patients.ROC analysis revealed that the area under the curve(AUC)for each lncRNA ranged from 0.659 to 0.848.The diagnostic panel, which included NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1 as determined by Lasso analysis, exhibited AUC values of 0.917 and 0.906 in the training and validation sets, respectively.The performance of this panel was superior to that of each individual lncRNA.Conclusions:The random forest model, which incorporates NR_003000, ENST00000607464.1, ENST00000583184.1, and ENST00000620744.1, demonstrates potential in differentiating between PTB and non-TB lung diseases.
