Başaran Ahmet Selim, Türkel Nur Nihal, Koparal Buket, Kuruoğlu Aslı
Unye State Hospital, Ordu, Türkiye.
Penitentiary Campus State Hospital, Ankara, Türkiye.
Front Psychiatry. 2025 Apr 29;16:1541469. doi: 10.3389/fpsyt.2025.1541469. eCollection 2025.
Treatment resistance in schizophrenia is a major clinical challenge. While autistic traits are often more pronounced in patients with treatment-resistant schizophrenia (TRS), limited data exist on clozapine-resistant schizophrenia (CRS). This study aims to explore the relationship between autistic traits and treatment resistance in schizophrenia, with a focus on both TRS and CRS and to evaluate whether these traits could predict treatment outcomes.
A total of 86 patients were included, divided into three groups: non-treatment-resistant schizophrenia (NRS, n=37), treatment-resistant schizophrenia (TRS, n=26), and clozapine-resistant schizophrenia (CRS, n=23). Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS), while autistic traits were measured with the PANSS Autism Severity Scale (PAUSS) and the Autism Spectrum Quotient (AQ). Multinomial logistic regression models were used to determine the predictive value of autistic traits for TRS and CRS.
Statistically significant differences were identified between the groups in PAUSS (p<0.001) and AQ (p<0.001) scores, indicating variations in autistic traits. PAUSS scores were predictive of TRS and CRS relative to NRS but did not differ between TRS and CRS. In contrast, AQ scores showed significant differences between TRS and CRS. Both PAUSS and AQ were negatively correlated with functionality as measured by the Global Assessment of Functioning, highlighting the impact of autistic traits on daily functioning.
The results indicate that autistic traits are associated with resistance to treatment, as PAUSS scores are predictive of the development of treatment-resistant and clozapine-resistant schizophrenia. However, the lack of statistically significant differences between TRS and CRS in PAUSS scores suggests that clozapine resistance may be influenced by additional factors beyond the autistic traits measured by PAUSS. To better understand the relationship between clozapine resistance and autistic traits, future research should not only focus on the autistic traits captured by PAUSS but also consider broader autism phenotypes or other distinct psychopathological processes. Such studies could offer deeper insights into the complex mechanisms that drive clozapine resistance and help identify new paths for treatment and intervention.
精神分裂症的治疗抵抗是一项重大的临床挑战。虽然自闭症特征在难治性精神分裂症(TRS)患者中往往更为明显,但关于氯氮平难治性精神分裂症(CRS)的数据有限。本研究旨在探讨精神分裂症中自闭症特征与治疗抵抗之间的关系,重点关注TRS和CRS,并评估这些特征是否能够预测治疗结果。
共纳入86例患者,分为三组:非难治性精神分裂症(NRS,n = 37)、难治性精神分裂症(TRS,n = 26)和氯氮平难治性精神分裂症(CRS,n = 23)。使用阳性和阴性症状量表(PANSS)评估精神病理学,同时用PANSS自闭症严重程度量表(PAUSS)和自闭症谱系商数(AQ)测量自闭症特征。采用多项逻辑回归模型确定自闭症特征对TRS和CRS的预测价值。
在PAUSS(p < 0.001)和AQ(p < 0.001)得分上,各组之间存在统计学显著差异,表明自闭症特征存在差异。相对于NRS,PAUSS得分可预测TRS和CRS,但TRS和CRS之间无差异。相比之下,AQ得分在TRS和CRS之间存在显著差异。PAUSS和AQ均与功能总体评定量表所测量的功能呈负相关,突出了自闭症特征对日常功能的影响。
结果表明,自闭症特征与治疗抵抗相关,因为PAUSS得分可预测难治性和氯氮平难治性精神分裂症的发生。然而,TRS和CRS在PAUSS得分上缺乏统计学显著差异,这表明氯氮平抵抗可能受到PAUSS所测量的自闭症特征之外的其他因素影响。为了更好地理解氯氮平抵抗与自闭症特征之间的关系,未来研究不仅应关注PAUSS所捕捉的自闭症特征,还应考虑更广泛的自闭症表型或其他独特的精神病理过程。此类研究可以更深入地洞察导致氯氮平抵抗的复杂机制,并有助于确定新的治疗和干预途径。