tryptophan-indole metabolism

  • 文章类型: Journal Article
    新的证据表明,肠道微生物群与骨骼稳态密切相关。然而,关于骨密度(BMD)指数之间的关系知之甚少,骨转换标记,以及绝经后妇女的肠道菌群及其代谢产物。
    在这项研究中,了解绝经后BMD降低妇女的肠道微生物群特征和血清代谢物变化,我们招募绝经后BMD正常或降低的个体,并将其分为正常组和OS组.收集粪便和血清样品进行16SrRNA基因测序,基于液相色谱与质谱联用(LC-MS)的代谢组学和综合分析。
    结果表明,OS组的细菌丰富度和多样性大于正常组。此外,在两组中发现了区别细菌,并与BMD指数和骨转换标志物密切相关。代谢组学分析显示,血清代谢物的表达,例如etiocholanolone,硫酸睾酮,和吲哚-3-丙酮酸,以及相应的信号通路,尤其是那些参与色氨酸代谢的人,脂肪酸降解和类固醇激素的生物合成,也发生了重大变化。相关分析显示,富含正常组的拟杆菌丰度与富含正常组的etocholanone和硫酸睾酮丰度呈正相关;特别是,拟杆菌与BMD呈正相关。重要的是,色氨酸-吲哚代谢途径由肠道细菌来源的tnaA基因独特地代谢,正常组的预测丰度明显高于对照组,拟杆菌的丰度与tnaA基因密切相关。
    我们的结果表明,绝经后妇女的肠道微生物群和血清代谢物存在明显差异。特定改变的细菌和衍生的代谢物与BMD指数和骨转换标志物密切相关,表明肠道微生物群和血清代谢物作为预防骨质疏松症的可改变因子和治疗靶点的潜力。
    UNASSIGNED: Emerging evidence suggests that the gut microbiota is closely associated with bone homeostasis. However, little is known about the relationships among the bone mineral density (BMD) index, bone turnover markers, and the gut microbiota and its metabolites in postmenopausal women.
    UNASSIGNED: In this study, to understand gut microbiota signatures and serum metabolite changes in postmenopausal women with reduced BMD, postmenopausal individuals with normal or reduced BMD were recruited and divided into normal and OS groups. Feces and serum samples were collected for 16S rRNA gene sequencing, liquid chromatography coupled with mass spectrometry (LC-MS)-based metabolomics and integrated analysis.
    UNASSIGNED: The results demonstrated that bacterial richness and diversity were greater in the OS group than in the normal group. Additionally, distinguishing bacteria were found among the two groups and were closely associated with the BMD index and bone turnover markers. Metabolomic analysis revealed that the expression of serum metabolites, such as etiocholanolone, testosterone sulfate, and indole-3-pyruvic acid, and the corresponding signaling pathways, especially those involved in tryptophan metabolism, fatty acid degradation and steroid hormone biosynthesis, also changed significantly. Correlation analysis revealed positive associations between normal group-enriched Bacteroides abundance and normal group-enriched etiocholanolone and testosterone sulfate abundances; in particular, Bacteroides correlated positively with BMD. Importantly, the tryptophan-indole metabolism pathway was uniquely metabolized by the gut bacteria-derived tnaA gene, the predicted abundance of which was significantly greater in the normal group than in the control group, and the abundance of Bacteroides was strongly correlated with the tnaA gene.
    UNASSIGNED: Our results indicated a clear difference in the gut microbiota and serum metabolites of postmenopausal women. Specifically altered bacteria and derived metabolites were closely associated with the BMD index and bone turnover markers, indicating the potential of the gut microbiota and serum metabolites as modifiable factors and therapeutic targets for preventing osteoporosis.
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  • 文章类型: Journal Article
    背景:韩国人的膀胱癌(BLCA)研究仍然缺乏,特别是在关注BLCA的预测方面。目前的研究旨在发现与BLCA发病相关的代谢特征,并确认其作为生物标志物的潜力。
    方法:我们使用韩国癌症预防研究(KCPS)-II设计了两项巢式病例对照研究。仅随机选择35-69岁的男性,并由招募组织分为两组[第1组,BLCA(n=35)与对照(n=35);组2,BLCA(n=31)与控制(n=31)]。通过非靶向代谢组学分析基线血清样品,进行了OPLS-DA和网络分析。来自所有KCPS参与者的BLCA的计算的遗传风险评分(GRS)用于解释代谢组学数据。
    结果:在BLCA组中显示的关键代谢特征是赖氨酸代谢和色氨酸-吲哚代谢的失调。此外,由代谢物(赖氨酸,色氨酸,吲哚,吲哚丙烯酸,和吲哚乙醛)反映这些代谢特征显示出强大的BLCA预测能力(AUC:0.959[0.929-0.989])。BLCA中GRS高组和GRS低组之间的代谢差异结果表明,BLCA的发病机理与遗传易感性有关。此外,在使用GRS和5种显著代谢物的模型上,BLCA的预测能力是强大的(AUC:0.990[0.980-1.000])。
    结论:本研究显示的代谢特征可能与BLCA发病机制密切相关。参与这些的代谢物可能是BLCA的预测性生物标志物。它可以用于早期诊断,预后诊断,和BLCA的治疗目标。
    BACKGROUND: Bladder cancer (BLCA) research in Koreans is still lacking, especially in focusing on the prediction of BLCA. The current study aimed to discover metabolic signatures related to BLCA onset and confirm its potential as a biomarker.
    METHODS: We designed two nested case-control studies using Korean Cancer Prevention Study (KCPS)-II. Only males aged 35-69 were randomly selected and divided into two sets by recruitment organizations [set 1, BLCA (n = 35) vs. control (n = 35); set 2, BLCA (n = 31) vs. control (n = 31)]. Baseline serum samples were analyzed by non-targeted metabolomics profiling, and OPLS-DA and network analysis were performed. Calculated genetic risk score (GRS) for BLCA from all KCPS participants was utilized for interpreting metabolomics data.
    RESULTS: Critical metabolic signatures shown in the BLCA group were dysregulation of lysine metabolism and tryptophan-indole metabolism. Furthermore, the prediction model consisting of metabolites (lysine, tryptophan, indole, indoleacrylic acid, and indoleacetaldehyde) reflecting these metabolic signatures showed mighty BLCA predictive power (AUC: 0.959 [0.929-0.989]). The results of metabolic differences between GRS-high and GRS-low groups in BLCA indicated that the pathogenesis of BLCA is associated with a genetic predisposition. Besides, the predictive ability for BLCA on the model using GRS and five significant metabolites was powerful (AUC: 0.990 [0.980-1.000]).
    CONCLUSIONS: Metabolic signatures shown in the present research may be closely associated with BLCA pathogenesis. Metabolites involved in these could be predictive biomarkers for BLCA. It could be utilized for early diagnosis, prognostic diagnosis, and therapeutic targets for BLCA.
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