1. Multiomics Analyses Reveal Microbiome–Gut–Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia.
- Author
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Wang, Zhuo, Yuan, Xiuxia, Zhu, Zijia, Pang, Lijuan, Ding, Shizhi, Li, Xue, Kang, Yulin, Hei, Gangrui, Zhang, Liyuan, Zhang, Xiaoyun, Wang, Shuying, Jian, Xuemin, Li, Zhiqiang, Zheng, Chenxiang, Fan, Xiaoduo, Hu, Shaohua, Shi, Yongyong, and Song, Xueqin
- Subjects
BLOOD serum analysis ,TRYPTOPHAN metabolism ,SCHIZOPHRENIA risk factors ,GENETICS of schizophrenia ,FECAL analysis ,BRAIN ,GASTROINTESTINAL system ,GRAY matter (Nerve tissue) ,SCHIZOPHRENIA ,GUT microbiome ,METABOLOMICS ,HUMAN genome ,SINGLE nucleotide polymorphisms ,METHYLTRANSFERASES ,MAGNETIC resonance imaging ,CASE-control method ,METABOLISM ,RANDOM forest algorithms ,FUNCTIONAL connectivity ,COGNITION ,CELLULAR signal transduction ,GENETIC risk score ,RISK assessment ,MULTIOMICS ,GABA ,RESEARCH funding ,LACTOBACILLUS ,METABOLITES ,NEURORADIOLOGY ,SHORT-chain fatty acids ,GRAM-positive bacteria - Abstract
Background and Hypothesis Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ. Study Design We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome–gut–brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis. Study Results We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l -2,4-diaminobutyric acid and N -acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor. Conclusions This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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