Gut microbial signatures and differences in bipolar disorder and schizophrenia of emerging adulthood

Introduction Gut microbial disturbance has been established as potential pathogenesis of mental disorders. However, the signatures and differences regarding patients with schizophrenia (SCH) or bipolar disorder (BD) in emerging adulthood as well as their subtypes have been poorly addressed. Methods In the present study, stool samples obtained from 63 emerging adult patients with schizophrenia (SCH), 50 with bipolar disorder (BD), and 40 healthy controls (HC) were analyzed by 16 S rRNA gene sequencing; psychiatric symptoms and psychological, social, and professional functioning were also assessed. Results We found that gut microbiota composition was remarkably changed in the patients with SCH and BD. Moreover, the distinct gut microbiome signatures and their potential function in bipolar depression (BP‐D) and SCH with predominantly negative symptoms (SCH‐N) as well as bipolar mania (BP‐M) and SCH with predominantly positive symptoms (SCH‐P) were also observed. Furthermore, we identified diagnostic potential biomarkers that can distinguish BD from HC (38 genera, AUC = 0.961), SCH from HC (32 genera, AUC = 0.962), and BD from Scheme (13 genera, AUC = 0.823). Potential diagnostic biomarkers that can distinguish BD‐D from SCH‐N (16 genera, AUC = 0.969) and BD‐M from SCH‐P (31 genera, AUC = 0.938) were also identified. Conclusion This study provides further understanding of abnormal gut microbiome in emerging adulthood patients with SCH and BD and lay the potential foundation for the development of microbe‐based clinical diagnosis for BD and SCH. The present study observed the signatures and differences of gut microbiome regarding patients with schizophrenia (SCH) or bipolar disorder (BD) in emerging adulthood as well as their subtypes and identified diagnostic potential biomarkers that can distinguish BD from HC (38 microbial panels, AUC = 0.961), SCH from HC (32 microbial panels, AUC = 0.962), and BD from Scheme (13 microbial panels, AUC = 0.823). Potential diagnostic biomarkers that can distinguish BD‐D from SCH‐N (16 microbial panels, AUC = 0.969) and BD‐M from SCH‐P (31 microbial panels, AUC = 0.938) were also identified.