Gut microbial biomarkers for the treatment response in first-episode, drug-naïve schizophrenia: a 24-week follow-up study

• Published in: Translational psychiatry 2021-08, Vol.11 (1), p.422-422, Article 422
• Main Authors: Yuan, Xiuxia, Wang, Yunpeng, Li, Xue, Jiang, Jiajun, Kang, Yulin, Pang, Lijuan, Zhang, Peifen, Li, Ang, Lv, Luxian, Andreassen, Ole A., Fan, Xiaoduo, Hu, Shaohua, Song, Xueqin
• Format: Article
• Language: English
• Subjects: 631/477/2811; 692/699/476/1799; Behavioral Sciences; Biological Psychology; Biomarkers; Medicine; Medicine & Public Health; Microbiota; Neurosciences; Pharmacotherapy; Psychiatry; Schizophrenia
• ISSN: 2158-3188; 2158-3188
• DOI: 10.1038/s41398-021-01531-3

Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naïve SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower α-diversity (the Shannon and Simpson’s indices) compared to HCs at baseline ( p  = 1.21 × 10 −9 , 1.23 × 10 −8 , respectively). We also found a significant difference in β-diversity between SCH patients and HCs ( p  = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of α-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium ( p  = 0.019) and increased abundance Romboutsia ( p  = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia ( p  = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.