Analysis of Gut Microbiota Composition in Lung Adenocarcinoma Patients with TCM Qi-Yin Deficiency

普雷沃菌属 厚壁菌 拟杆菌 医学 生物 蛋白质细菌 肠道菌群 内科学 双歧杆菌 胃肠病学 免疫学 16S核糖体RNA 遗传学 乳酸菌 细菌
作者
Jiabin Chen,Sheng Wang,Jianfei Shen,Qinqin Hu,Yongjun Zhang,Dehua Ma,Kequn Chai
出处
期刊:The American Journal of Chinese Medicine [World Scientific]
卷期号:49 (07): 1667-1682 被引量:8
标识
DOI:10.1142/s0192415x21500786
摘要

In Lung adenocarcinoma (ADC), Qi-Yin deficiency syndrome (QY) is the most common Traditional Chinese medicine (TCM) syndrome. This study aimed to investigate the diversity and composition of gut microbiota in ADC patients with QY syndrome. 90 stool samples, including 30 healthy individuals (H), 30 ADC patients with QY syndrome, and 30 ADC patients with another syndrome (O) were collected. Then, 16s-RNA sequencing was used to analyze stool samples to clarify the structure of gut microbiota, and linear discriminant analysis (LDA) effect size (LEfSe) was applied to identify biomarkers for ADC with QY syndrome. Logistic regression analysis was performed to establish a diagnostic model for the diagnosis of QY syndrome in ADC patients, which was assessed with the AUC. Finally, 20 fecal samples (QY: 10; O: 10) were analyzed with Metagenomics to validate the diagnostic model. The [Formula: see text] diversity and [Formula: see text] diversity demonstrated that the structure of gut microbiota in the QY group was different from that of the H group and O group. In the QY group, the top 3 taxonomies at phylum level were Firmicutes, Bacteroidetes, and Proteobacteria, and at genus level were Faecalibacterium, Prevotella_9, and Bifidobacterium. LEfSe identified Prevotella_9 and Streptococcus might be the biomarkers for QY syndrome. A diagnostic model was constructed using those 2 genera with the AUC = 0.801, similar to the AUC based on Metagenomics (0.842). The structure of gut microbiota in ADC patients with QY syndrome was investigated, and a diagnostic model was developed for the diagnosis of QY syndrome in ADC patients, which provides a novel idea for the understanding and diagnosis of TCM syndrome.
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