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揭示精神分裂症的肠道微生物群蓝图:一种多组学方法。

Unveiling the gut microbiota blueprint of schizophrenia: a multilevel omics approach.

作者信息

Qi DongDong, Liu Peng, Wang YiMeng, Tai XuGuang, Ma ShiFa

机构信息

Basic and Clinical Laboratory of Mental Illness, Hulunbuir Third People's Hospital (Hulunbuir Mental Health Center), Yakeshi, Inner Mongolia, China.

School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.

出版信息

Front Psychiatry. 2024 Sep 25;15:1452604. doi: 10.3389/fpsyt.2024.1452604. eCollection 2024.

Abstract

BACKGROUND

Schizophrenia is a persistent incurable mental disorder and is characterized by the manifestation of negative emotions and behaviors with anxiety and depression, fear and insecurity, self-harm and social withdrawal. The intricate molecular mechanisms underlying this phenomenon remain largely elusive. Accumulating evidence points towards the gut microbiota exerting an influence on brain function via the gut-brain axis, potentially contributing to the development of schizophrenia. Therefore, the objective of this study is to delineate the gut microbial composition and metabolic profile of fecal samples from individuals with schizophrenia.

METHODS

Liquid chromatography-mass spectrometry (LC-MS) and 16S ribosomal RNA (16S rRNA) gene sequencing were employed to analyze fecal metabolites and gut microbiota profiles in a cohort of 29 patients diagnosed with schizophrenia and 30 normal controls. The microbial composition of fecal samples was determined through the 16S rRNA gene sequencing, and microbial α-diversity and β-diversity indices were calculated. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to analyze the distribution of samples. The metabolites and gut microbiota exhibiting differential expression were identified through the application of biological variance criteria. Co-occurrence analysis of bacteria and metabolites was conducted using the spearman's rank correlation coefficient and visualized in a circular layout with the Cytoscape software.

RESULTS

The findings of the study indicated a lack of substantial evidence supporting significant disparities in α-diversity and β-diversity between individuals with schizophrenia and normal controls. In terms of metabolomics, a discernible pattern in sample distribution between the two groups was observed. Our analysis has revealed 30 bacterial species and 45 fecal metabolites that exhibited notable differences in abundance between individuals diagnosed with schizophrenia and normal controls. These alterations in multilevel omics have led to the development of a co-expression network associated with schizophrenia. The perturbed microbial genes and fecal metabolites consistently demonstrated associations with amino acid and lipid metabolism, which play essential roles in regulating the central nervous system.

CONCLUSION

Our results offered profound insights into the impact of imbalanced gut microbiota and metabolism on brain function in individuals with schizophrenia.

摘要

背景

精神分裂症是一种持续性的不治之症,其特征表现为负面情绪和行为,包括焦虑和抑郁、恐惧和不安全感、自我伤害以及社交退缩。这种现象背后复杂的分子机制在很大程度上仍然难以捉摸。越来越多的证据表明,肠道微生物群通过肠-脑轴对大脑功能产生影响,这可能在精神分裂症的发展中起作用。因此,本研究的目的是描绘精神分裂症患者粪便样本的肠道微生物组成和代谢谱。

方法

采用液相色谱-质谱联用(LC-MS)和16S核糖体RNA(16S rRNA)基因测序技术分析确诊为精神分裂症的29例患者和30例正常对照人群的粪便代谢物和肠道微生物群谱。通过16S rRNA基因测序确定粪便样本的微生物组成,并计算微生物α多样性和β多样性指数。进行主成分分析(PCA)和正交偏最小二乘法判别分析(OPLS-DA)以分析样本分布。通过应用生物学差异标准鉴定出表达差异的代谢物和肠道微生物群。使用斯皮尔曼等级相关系数进行细菌和代谢物的共现分析,并使用Cytoscape软件以圆形布局进行可视化。

结果

研究结果表明,缺乏充分证据支持精神分裂症患者与正常对照人群在α多样性和β多样性上存在显著差异。在代谢组学方面,观察到两组样本分布存在明显模式。我们的分析揭示了30种细菌物种和45种粪便代谢物,在确诊为精神分裂症的个体与正常对照人群之间,它们的丰度存在显著差异。这些多层次组学的改变导致了与精神分裂症相关的共表达网络的形成。受干扰的微生物基因和粪便代谢物始终显示与氨基酸和脂质代谢有关,而氨基酸和脂质代谢在调节中枢神经系统中起着重要作用。

结论

我们的结果为肠道微生物群和代谢失衡对精神分裂症患者大脑功能的影响提供了深刻见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7654/11461293/188e776766f5/fpsyt-15-1452604-g001.jpg

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