关键词: 序列分析,RNA, 结核,肺, 淋巴细胞

Abstract:

Objective: To investigate the differences in immune cell subsets between young and elderly patients with severe pulmonary tuberculosis, with particular emphasis on the functions and pathways of natural killer (NK) cell subsets. Methods: Single-cell sequencing data and other clinically relevant indicators were obtained by contacting the corresponding authors of publicly available research literature. Data were collected from four patients with severe pulmonary tuberculosis, comprising two young patients (age ≤40 years) and two elderly patients (age ≥65 years). The single-cell RNA sequencing data underwent quality control and statistical analysis. After excluding unqualified cells, the data were subjected to nonlinear dimensionality reduction and clustering. Recognized cellular markers were used to annotate immune cells and determine the percentage of each cell type in each sample and group. This enabled the comparison of cell subtype trends across different groups. Differential gene expression between cell types was analyzed, and the roles of these genes in biological processes and pathways were investigated using enrichment analysis in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Results: A total of 15359 cells from young patients and 9571 cells from elderly patients with severe pulmonary tuberculosis were analyzed, leading to the identification of 11 distinct cell subpopulations. The most prevalent cell types included monocytes (61%), CD4⁺ T cells (17%), CD8⁺ T cells (8%), megakaryocytes (5%), B cells (4%), and NK cells (3%). The analysis revealed that the percentage of NK cells was higher in young patients (median (IQR): 4.339% (3.955%, 4.722%)) compared to elderly patients (median (IQR): 0.822% (0.813%, 0.831%)), although this difference was not statistically significant (Z=-0.431, P=0.667). Statistical analysis using the ratio of observed to expected cell numbers indicated an increasing trend of NK cells in the young group. Further clustering analysis identified three distinct NK cell subgroups. The median percentage of NK cells with high CD16 expression was 44.409% (IQR: 41.672%, 47.147%) in young patients, slightly higher than the 35.172% (IQR: 32.169%, 38.174%) observed in elderly patients; however, this difference was not statistically significant (Z=-0.431, P=0.667). A comparison between NK cells with high CD16 expression and those with moderate expression revealed 435 significantly altered genes, comprising 388 upregulated genes and 47 downregulated genes. KEGG pathway analysis indicated that these differentially expressed genes were predominantly involved in signaling pathways related to cell perception, cytokine signaling, B cell receptor activity, and antigen processing and presentation. Conclusion: This study examined the differences in peripheral blood immune cells between young and elderly patients with severe pulmonary tuberculosis, highlighting an increased percentage of NK cells and CD16⁺ NK cells in young patients. These findings may offer a new theoretical basis and identify potential therapeutic targets for the stratified clinical management of tuberculosis patients.

Key words: Sequence analysis, RNA, Tuberculosis, pulmonary, Lymphocytes