基于神经生物学的认知生物型:多尺度内在连接网络在精神病中的应用。

IF 3 Q2 PSYCHIATRY
Pablo Andrés-Camazón, Covadonga M Diaz-Caneja, Ram Ballem, Jiayu Chen, Vince D Calhoun, Armin Iraji
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引用次数: 0

摘要

理解神经生物学和发展有效的干预精神障碍的认知功能障碍仍然是难以捉摸的。对认知功能障碍的生物学异质性认识不足阻碍了进展。我们的目的是确定精神病患者亚组和与认知相关的功能性脑改变的不同模式(认知生物型)。我们分析了B-SNIP联盟的数据(2 270名参与者,包括精神病患者、亲属和对照组,55%为女性)。我们使用参考信息独立成分分析与标准化和全自动框架NeuroMark和100k多尺度内在连接网络(ICN)模板获得受试者特异性ICN和全脑功能网络连接(FNC)。使用多变量联合分析确定与认知表现相关的FNC特征。K-means聚类基于这些特征识别患者亚组。鉴定出两种具有不同脑功能改变模式的生物型。与对照组相比,生物型1表现出小脑-皮质下网络和躯体运动-视觉网络的低连通性,认知表现更差。生物型2在躯体运动-皮质下网络中表现出超连通性,在躯体运动-高认知加工网络中表现出低连通性,并且更好地保留了认知表现。生物型的人口学、临床、认知和FNC特征在发现和复制集以及亲属中是一致的。76.56%的亲属归属于精神病生物型,其中70.12%的亲属与其患病家庭成员具有相同的生物型。这些发现表明两种不同的精神病相关认知生物型与不同的大脑功能模式共享与他们的亲属。代替传统的诊断,基于这些生物型的患者分层可能有助于优化未来的研究,并确定治疗精神病认知功能障碍的生物学靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neurobiology-based cognitive biotypes using multi-scale intrinsic connectivity networks in psychotic disorders.

Understanding neurobiology and developing effective interventions for cognitive dysfunction in psychotic disorders remain elusive. Insufficient knowledge about the biological heterogeneity of cognitive dysfunction hinders progress. We aimed to identify subgroups of patients with psychosis and distinct patterns of functional brain alterations related to cognition (cognitive biotypes). We analyzed B-SNIP consortium data (2 270 participants including participants with psychotic disorders, relatives, and controls, 55% females). We used reference-informed independent component analysis with the standardized and fully automated framework NeuroMark and the 100k multi-scale intrinsic connectivity networks (ICN) template to obtain subject-specific ICNs and whole-brain functional network connectivity (FNC). FNC features associated with cognitive performance were identified using multivariate joint analysis. K-means clustering identified patient subgroups based on these features. Two biotypes with different functional brain alteration patterns were identified. Relative to controls, biotype 1 exhibited hypoconnectivity in cerebellar-subcortical and somatomotor-visual networks and worse cognitive performance. Biotype 2 exhibited hyperconnectivity in somatomotor-subcortical networks, hypoconnectivity in somatomotor-high cognitive processing networks, and better-preserved cognitive performance. Demographic, clinical, cognitive, and FNC characteristics of biotypes were consistent in discovery and replication sets and in relatives. 76.56% of relatives were assigned to a psychosis biotype, of those, 70.12% were to the same biotype as their affected family members. These findings suggest two distinctive psychosis-related cognitive biotypes with differing functional brain patterns shared with their relatives. Instead of traditional diagnosis, patient stratification based on these biotypes may help optimize future research and identify biological targets for the treatment of cognitive dysfunction in psychosis.

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