Xiamen Xianyue Hospital, Xianyue Hospital Affiliated with Xiamen Medical College, Fujian Psychiatric Center, Fujian Clinical Research Center for Mental Disorders, Xiamen, Fujian, China; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Asian J Psychiatr. 2024 Nov;101:104202. doi: 10.1016/j.ajp.2024.104202. Epub 2024 Sep 3.
Schizophrenia is a heterogeneous psychotic disorder. Recent theories have emphasized the importance of interactions among psychiatric symptoms in understanding the pathological mechanisms of schizophrenia. In the current study, we examined the symptom network in patients with first-episode schizophrenia (FES) at four time points during a six-month follow-up period.
In total, 565 patients with FES were recruited from the Chinese First-Episode Schizophrenia Trial (CNFEST) project. Clinical symptoms were measured using the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up (514 patients at one month, 429 at three months, and 392 at six months). We used a network analysis approach to estimate symptom networks with individual symptoms as nodes and partial correlation coefficients between symptoms as edges. A cross-lagged panel network (CLPN) model was used to identify predictive pathways for clinical symptoms.
We found stable and strongly connected edges in patients across the time points, such as links between delusions and suspiciousness/persecution (P1:P6), and emotional withdrawal and passive/apathetic social withdrawal (N2:N4). Emotional withdrawal (N2), poor rapport (N3), and passive/apathetic social withdrawal (N4) had high centrality estimates across all four time points. CLPN analysis showed that negative symptoms, including emotional withdrawal (N2), poor rapport (N3), and passive/apathetic social withdrawal (N4), and stereotyped thinking (N7) may have predictive effects for negative and general symptoms at follow-ups.
The symptom network of schizophrenia may be dynamic as treatment progresses. Negative symptoms remain the central and stable symptoms of schizophrenia. Negative symptoms may be potential therapeutic targets that predict other symptoms.
精神分裂症是一种异质性的精神病。最近的理论强调了在理解精神分裂症病理机制时，精神症状之间相互作用的重要性。在目前的研究中，我们在六个月的随访期间四个时间点检查了首发精神分裂症（FES）患者的症状网络。
共有 565 名首发精神分裂症患者（CNFEST）项目。在基线和随访时（514 名患者在一个月，429 名患者在三个月，392 名患者在六个月）使用阳性和阴性综合征量表（PANSS）测量临床症状。我们使用网络分析方法来估计症状网络，将个体症状作为节点，症状之间的偏相关系数作为边。使用交叉滞后面板网络（CLPN）模型识别临床症状的预测途径。
我们发现，在整个时间点上，患者的稳定且强连接的边，如妄想与可疑/迫害（P1：P6）之间的联系，以及情感退缩与被动/冷漠的社会退缩（N2：N4）之间的联系。在所有四个时间点，情感退缩（N2）、共情缺乏（N3）和被动/冷漠的社会退缩（N4）都具有较高的中心度估计值。CLPN 分析表明，阴性症状，包括情感退缩（N2）、共情缺乏（N3）、被动/冷漠的社会退缩（N4）和刻板思维（N7），可能对随访时的阴性和一般症状具有预测作用。
精神分裂症的症状网络可能随着治疗的进展而发生变化。阴性症状仍然是精神分裂症的核心和稳定症状。阴性症状可能是潜在的治疗靶点，可预测其他症状。
