Relationships among the gut microbiome, brain networks, and symptom severity in schizophrenia patients: A mediation analysis

IF 3.4 2区 医学 Q2 NEUROIMAGING
Liqin Liang , Shijia Li , Yuanyuan Huang , Jing Zhou , Dongsheng Xiong , Shaochuan Li , Hehua Li , Baoyuan Zhu , Xiaobo Li , Yuping Ning , Xiaohui Hou , Fengchun Wu , Kai Wu
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Abstract

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p < 0.05) was identified. Importantly, the PANSS scores were linearly correlated with both the gut microbiome (r = 0.5, FDR-corrected p < 0.05) and brain networks (r = 0.59, FDR-corrected p < 0.05). The abundance of genus Sellimonas significantly affected the PANSS negative scores of SZ patients via the betweenness centrality of white matter networks in the inferior frontal gyrus and amygdala. Moreover, 19 significant mediation models demonstrated that the nodal properties of 7 brain regions, predominately from the systems of visual, language, and control of action, showed significant mediating effects on the PANSS scores with the gut microbiome as mediators. Together, our findings indicated the tripartite relationships among the gut microbiome, brain networks, and PANSS scores and suggested their potential role in the neuropathology of SZ.

精神分裂症患者肠道微生物组、大脑网络和症状严重程度之间的关系:中介分析
微生物组-肠-脑轴(MGBA)在精神分裂症(SZ)中起着至关重要的作用。然而,精神分裂症患者的肠道微生物组、大脑网络和症状严重程度之间相互作用的内在机制在很大程度上仍然未知。研究人员分别收集了38名精神分裂症患者和38名正常对照者的粪便样本、结构和功能磁共振成像(MRI)数据以及阳性和阴性综合征量表(PANSS)评分。16S rRNA基因测序数据用于分析肠道微生物组的丰度,人脑网络分析用于计算90个脑区的节点属性。根据 SZ 患者的 261 种肠道细菌、810 个节点属性和 4 个 PANSS 评分,共构建了 1,691,280 个中介模型。结果发现,肠道微生物组与大脑网络之间存在很强的相关性(r = 0.89,误发现率(FDR)校正 p < 0.05)。重要的是,PANSS 评分与肠道微生物组(r = 0.5,经 FDR 校正 p < 0.05)和大脑网络(r = 0.59,经 FDR 校正 p < 0.05)均呈线性相关。通过额叶下回和杏仁核白质网络的间度中心性,Sellimonas属植物的丰富程度显著影响了SZ患者的PANSS负分。此外,19 个重要的中介模型表明,7 个脑区(主要来自视觉、语言和行动控制系统)的节点特性对 PANSS 评分有明显的中介效应,而肠道微生物组则是中介因子。总之,我们的研究结果表明了肠道微生物组、大脑网络和 PANSS 评分之间的三方关系,并提示了它们在 SZ 神经病理学中的潜在作用。
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来源期刊
Neuroimage-Clinical
Neuroimage-Clinical NEUROIMAGING-
CiteScore
7.50
自引率
4.80%
发文量
368
审稿时长
52 days
期刊介绍: NeuroImage: Clinical, a journal of diseases, disorders and syndromes involving the Nervous System, provides a vehicle for communicating important advances in the study of abnormal structure-function relationships of the human nervous system based on imaging. The focus of NeuroImage: Clinical is on defining changes to the brain associated with primary neurologic and psychiatric diseases and disorders of the nervous system as well as behavioral syndromes and developmental conditions. The main criterion for judging papers is the extent of scientific advancement in the understanding of the pathophysiologic mechanisms of diseases and disorders, in identification of functional models that link clinical signs and symptoms with brain function and in the creation of image based tools applicable to a broad range of clinical needs including diagnosis, monitoring and tracking of illness, predicting therapeutic response and development of new treatments. Papers dealing with structure and function in animal models will also be considered if they reveal mechanisms that can be readily translated to human conditions.
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