Asadiof Farnaz, Zamanpour Mona, Al-Hussainy Ali Fawzi, Shalal Alhan Abd Al-Hassan, Ubaid Mohammed, Aluquaily Zinab H, Hashemian Seyed Hamidreza
Educational Psychology, Payame Noor University, Tehran, Iran.
Medical Education Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Iran J Psychiatry. 2025 Jan;20(1):111-125. doi: 10.18502/ijps.v20i1.17405.
Identifying individuals at ultra-high risk for psychosis (UHRP) is crucial for early intervention and prevention strategies. Neurocognitive deficits have been increasingly recognized as potential predictors of psychosis onset. This overview aims to consolidate current evidence and elucidate the role of neurocognitive predictors in identifying UHRP individuals. we systematically searched three scientific databases, i.e., PubMed, Scopus, and Google Scholar using predefined keywords related to predictive neurocognitive markers and ultra-high risk psychosis. By following the PRISMA procedure, we included all relevant systematic-reviews and meta-analyses in our data-synthesis. Neurocognitive deficits, including impairments in working memory, attentional control, verbal learning, and executive functions, have been consistently identified as predictors of psychosis conversion in individuals at UHRP. Structural and functional neuroimaging studies have further revealed aberrant brain connectivity, reduced gray matter volume, and altered neural activation patterns in key brain regions to be involved in psychosis. Moreover, the combination of neurocognitive and clinical risk factors has been shown to enhance the accuracy of predicting psychosis onset and inform personalized intervention strategies. Neurocognitive deficits serve as valuable predictors of the risk of psychosis in individuals with UHRP, offering insights into the underlying neurobiological mechanisms and potential targets for early intervention. Future research should focus on refining predictive models, elucidating the neurodevelopmental trajectories, and evaluating the efficacy of targeted interventions in mitigating the psychosis risk.
识别超高危精神病个体（UHRP）对于早期干预和预防策略至关重要。神经认知缺陷日益被视为精神病发作的潜在预测指标。本综述旨在整合现有证据，并阐明神经认知预测指标在识别UHRP个体中的作用。我们使用与预测性神经认知标志物和超高危精神病相关的预定义关键词，系统检索了三个科学数据库，即PubMed、Scopus和谷歌学术。按照PRISMA流程，我们将所有相关的系统评价和荟萃分析纳入数据合成。神经认知缺陷，包括工作记忆、注意力控制、言语学习和执行功能的损害，一直被确定为UHRP个体精神病转化的预测指标。结构和功能神经影像学研究进一步揭示了关键脑区异常的脑连接、灰质体积减少以及参与精神病的神经激活模式改变。此外，神经认知和临床危险因素的组合已被证明可提高预测精神病发作的准确性，并为个性化干预策略提供依据。神经认知缺陷是UHRP个体精神病风险的有价值预测指标，为潜在的神经生物学机制和早期干预的潜在靶点提供了见解。未来的研究应侧重于完善预测模型、阐明神经发育轨迹，以及评估针对性干预措施在降低精神病风险方面的效果。
