Department of Andrology, Dongzhimen Hospital, Beijing University of Chinese Medicine, China.
Hebei College of Traditional Chinese Medicine, Shijiazhuang, People's Republic of China.
Biomed Chromatogr. 2023 Jun;37(6):e5622. doi: 10.1002/bmc.5622. Epub 2023 Apr 9.
Helicobacter pylori (H. pylori), as a harmful bacteria associated with gastric cancer, can have adverse effects on human normal flora and metabolism. However, the effects of H. pylori on human metabolism have not been fully elucidated. The C breathing test was used as the basis for distinguishing negative and positive groups. Serum samples were collected from the two groups for targeted quantitative metabolomics detection; multidimensional statistics were used, including partial least squares discriminant analysis (PLS-DA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and differential metabolites were screened. Unidimensional statistics combined with multidimensional statistics were used to further screen potential biomarkers, and finally pathway analysis was performed. SPSS 21.0 software package was used for statistical analysis of experimental data. Multivariate statistical analysis such as PLS-DA, PCA, and OPLS-DA was performed using Simca-P 13.0 to search for differential metabolites. This study confirmed that H. pylori caused significant changes in human metabolism. In this experiment, 211 metabolites were detected in the serum of the two groups. Multivariate statistical analysis showed that PCA of metabolites was not significantly different between the two groups. PLS-DA indicated that the serum of the two groups was well clustered. There were significant differences in metabolites between OPLS-DA groups. By setting the variable importance in projection (VIP) threshold as one and the corresponding P-value <0.05, a total of 40 metabolites were screened in this study. P <0.05 and ∣log2FC∣>0 (where FC is the fold change) were used together as a unidimensional statistical filter condition. The analysis found that the expression of 15 metabolites such as propionic acid, acetic acid, adipic acid increased, and the metabolism of six products such as deoxycholic acid (DCA), 4-hydroxyphenylpyruvic acid, pyruvic acid decreased. P <0.05, false discovery rate <0.5, ∣log2FC∣>1, and OPLSDA_VIP>1 were used together as a condition for filter screening potential biomarkers. Four potential biomarkers were screened, which were sebacic acid, isovaleric acid, DCA, and indole-3-carboxylic acid. Finally, the different metabolites were added to the pathway-associated metabolite sets (SMPDB) library for the corresponding pathway enrichment analysis. The significant abnormal metabolic pathways were taurine and subtaurine metabolism, tyrosine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, etc. This study shows that H. pylori has an impact on human metabolism. Not only a variety of metabolites have significant changes, but also metabolic pathways are abnormal, which may be the reason for the high risk of H. pylori causing gastric cancer.
幽门螺杆菌(H. pylori)作为一种与胃癌相关的有害细菌,会对人体正常菌群和代谢产生不良影响。然而,H. pylori 对人体代谢的影响尚未完全阐明。本研究采用 C 呼吸试验作为区分阴性和阳性组的依据。收集两组的血清样本进行靶向定量代谢组学检测;采用多维统计分析,包括偏最小二乘判别分析(PLS-DA)、主成分分析(PCA)、正交偏最小二乘判别分析(OPLS-DA),筛选差异代谢物。使用单维统计与多维统计相结合的方法进一步筛选潜在的生物标志物,最后进行通路分析。采用 SPSS 21.0 软件包对实验数据进行统计分析。使用 Simca-P 13.0 进行 PLS-DA、PCA 和 OPLS-DA 等多变量统计分析,以寻找差异代谢物。本研究证实 H. pylori 导致了人体代谢的显著变化。在本实验中,检测了两组血清中的 211 种代谢物。多变量统计分析显示,两组之间的代谢物 PCA 无显著差异。PLS-DA 表明两组血清聚类良好。OPLS-DA 组之间的代谢物存在显著差异。设置变量重要性投影(VIP)阈值为 1,相应 P 值<0.05,共筛选出 40 种代谢物。P<0.05 且∣log2FC∣>0(其中 FC 是倍数变化)共同作为一维统计筛选条件。分析发现丙酸、乙酸、己二酸等 15 种代谢物表达增加,脱氧胆酸(DCA)、4-羟基苯丙酮酸、丙酮酸等 6 种产物代谢减少。P<0.05、错误发现率<0.5、∣log2FC∣>1、OPLSDA_VIP>1 共同作为筛选潜在生物标志物的过滤条件。筛选出 4 种潜在生物标志物,分别为癸酸、异戊酸、DCA 和吲哚-3-羧酸。最后,将不同的代谢物添加到通路相关代谢物集(SMPDB)库中进行相应的通路富集分析。异常代谢途径有牛磺酸和次牛磺酸代谢、酪氨酸代谢、糖酵解或糖异生、丙酮酸代谢等。本研究表明 H. pylori 对人体代谢有影响。不仅多种代谢物发生显著变化,而且代谢途径也异常,这可能是 H. pylori 导致胃癌风险高的原因。