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精神分裂症中的两个神经解剖学特征:治疗最初 2 年内的表达强度及其与神经发育受损和抗精神病药物治疗的关系。

Two Neuroanatomical Signatures in Schizophrenia: Expression Strengths Over the First 2 Years of Treatment and Their Relationships to Neurodevelopmental Compromise and Antipsychotic Treatment.

机构信息

Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa.

Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.

出版信息

Schizophr Bull. 2023 Jul 4;49(4):1067-1077. doi: 10.1093/schbul/sbad040.

Abstract

BACKGROUND AND HYPOTHESIS

Two machine learning derived neuroanatomical signatures were recently described. Signature 1 is associated with widespread grey matter volume reductions and signature 2 with larger basal ganglia and internal capsule volumes. We hypothesized that they represent the neurodevelopmental and treatment-responsive components of schizophrenia respectively.

STUDY DESIGN

We assessed the expression strength trajectories of these signatures and evaluated their relationships with indicators of neurodevelopmental compromise and with antipsychotic treatment effects in 83 previously minimally treated individuals with a first episode of a schizophrenia spectrum disorder who received standardized treatment and underwent comprehensive clinical, cognitive and neuroimaging assessments over 24 months. Ninety-six matched healthy case-controls were included.

STUDY RESULTS

Linear mixed effect repeated measures models indicated that the patients had stronger expression of signature 1 than controls that remained stable over time and was not related to treatment. Stronger signature 1 expression showed trend associations with lower educational attainment, poorer sensory integration, and worse cognitive performance for working memory, verbal learning and reasoning and problem solving. The most striking finding was that signature 2 expression was similar for patients and controls at baseline but increased significantly with treatment in the patients. Greater increase in signature 2 expression was associated with larger reductions in PANSS total score and increases in BMI and not associated with neurodevelopmental indices.

CONCLUSIONS

These findings provide supporting evidence for two distinct neuroanatomical signatures representing the neurodevelopmental and treatment-responsive components of schizophrenia.

摘要

背景与假说

最近描述了两种基于机器学习的神经解剖学特征。特征 1 与广泛的灰质体积减少有关,特征 2 与更大的基底节和内囊体积有关。我们假设它们分别代表精神分裂症的神经发育和治疗反应成分。

研究设计

我们评估了这些特征的表达强度轨迹,并评估了它们与神经发育受损指标以及抗精神病药物治疗效果的关系,这些指标在 83 名以前接受过最低限度治疗的首发精神分裂症谱系障碍患者中得到了评估,他们接受了标准化治疗,并在 24 个月内接受了全面的临床、认知和神经影像学评估。纳入了 96 名匹配的健康对照组。

研究结果

线性混合效应重复测量模型表明,患者的特征 1 表达强度强于对照组,且随时间保持稳定,与治疗无关。更强的特征 1 表达与较低的受教育程度、较差的感觉整合以及较差的工作记忆、语言学习和推理以及解决问题的认知表现呈趋势相关。最引人注目的发现是,基线时患者和对照组的特征 2 表达相似,但患者的表达随着治疗显著增加。特征 2 表达的增加与 PANSS 总分的降低、BMI 的增加以及与神经发育指标无关有关。

结论

这些发现为代表精神分裂症的神经发育和治疗反应成分的两种不同的神经解剖学特征提供了支持性证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70c9/10318886/cecdde00b8cf/sbad040_fig1.jpg

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