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.

临床前研究表明，肠道微生物群可以通过肠-脑轴在精神分裂症（SCH）发病机制中发挥作用。然而，其在抗精神病药物治疗反应中的作用尚不清楚。在此，我们提出了一项为期 24 周的随访研究，旨在确定用于 SCH 诊断和治疗反应的肠道微生物生物标志物，该研究使用 107 名初治 SCH 患者和 107 名健康对照 (HC) 样本。我们在基线（所有参与者）和利培酮治疗后的随访时间点（SCH 患者）收集了生物样本。使用阳性和阴性症状量表总分（PANSS-T）评估治疗反应。错误发现率用于纠正多重测试。我们发现，与基线时的 HC 相比，SCH 患者表现出较低的 α 多样性（香农指数和辛普森指数）（分别为p  = 1.21 × 10 ^-9、 1.23 × 10 ^-8）。我们还发现 SCH 患者和 HC 之间的 β 多样性存在显着差异 ( p  = 0.001)。在基线时，使用患者和对照之间表现出不同丰度的微生物作为预测因子，预测模型可以将患者与曲线下面积 (AUC) 为 0.867 的 HC 区分开来。在 SCH 患者中，利培酮治疗 24 周后，我们观察到 HC 的 α 多样性向基础水平增加。在属水平上，我们观察到Lachnoclostridium丰度下降（p  = 0.019），而Romboutsia丰度增加（p  = 0.067）。此外，SCH 患者的治疗反应与毛梭菌和Romboutsia的基础水平显着相关（分别为p  = 0.005 和 0.006）。我们的结果表明 SCH 患者可能呈现特征性微生物群，并且某些微生物群生物标志物可以预测该患者群体的治疗反应。