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在多模态预测模型中,多巴胺合成能力以及γ-氨基丁酸(GABA)和谷氨酸水平可将首次发作精神病的未服用抗精神病药物患者与健康对照者区分开来。

Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model.

作者信息

Sigvard Anne K, Bojesen Kirsten Borup, Ambrosen Karen S, Nielsen Mette Ødegaard, Gjedde Albert, Tangmose Karen, Kumakura Yoshitaka, Edden Richard, Fuglø Dan, Jensen Lars Thorbjørn, Rostrup Egill, Ebdrup Bjørn H, Glenthøj Birte Yding

机构信息

Center for Neuropsychiatric Schizophrenia Research & Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark.

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

出版信息

Biol Psychiatry Glob Open Sci. 2022 May 30;3(3):500-509. doi: 10.1016/j.bpsgos.2022.05.004. eCollection 2023 Jul.

Abstract

BACKGROUND

Disturbances in presynaptic dopamine activity and levels of GABA (gamma-aminobutyric acid) and glutamate plus glutamine collectively may have a role in the pathophysiology of psychosis, although separately they are poor diagnostic markers. We tested whether these neurotransmitters in combination improve the distinction of antipsychotic-naïve patients with first-episode psychosis from healthy control subjects.

METHODS

We included 23 patients (mean age 22.3 years, 9 male) and 20 control subjects (mean age 22.4 years, 8 male). We determined dopamine metabolism in the nucleus accumbens and striatum from F-fluorodopa (F-FDOPA) positron emission tomography. We measured GABA levels in the anterior cingulate cortex (ACC) and glutamate plus glutamine levels in the ACC and left thalamus with 3T proton magnetic resonance spectroscopy. We used binominal logistic regression for unimodal prediction when we modeled neurotransmitters individually and for multimodal prediction when we combined the 3 neurotransmitters. We selected the best combination based on Akaike information criterion.

RESULTS

Individual neurotransmitters failed to predict group. Three triple neurotransmitter combinations significantly predicted group after Benjamini-Hochberg correction. The best model (Akaike information criterion 48.5) carried 93.5% of the cumulative model weight. It reached a classification accuracy of 83.7% ( = .003) and included dopamine synthesis capacity (K) in the nucleus accumbens ( = .664), GABA levels in the ACC ( = .019), glutamate plus glutamine levels in the thalamus ( = .678), and the interaction term K × GABA ( = .016).

CONCLUSIONS

Our multimodal approach proved superior classification accuracy, implying that the pathophysiology of patients represents a combination of neurotransmitter disturbances rather than aberrations in a single neurotransmitter. Particularly aberrant interrelations between K in the nucleus accumbens and GABA values in the ACC appeared to contribute diagnostic information.

摘要

背景

尽管突触前多巴胺活性以及γ-氨基丁酸(GABA)和谷氨酸加谷氨酰胺水平单独作为诊断标志物效果不佳,但它们共同作用可能在精神病的病理生理学中发挥作用。我们测试了这些神经递质联合使用是否能更好地区分首次发作且未服用过抗精神病药物的精神病患者与健康对照者。

方法

我们纳入了23例患者(平均年龄22.3岁,9例男性)和20名对照者(平均年龄22.4岁,8例男性)。通过F-氟多巴(F-FDOPA)正电子发射断层扫描确定伏隔核和纹状体中的多巴胺代谢。使用3T质子磁共振波谱测量前扣带回皮质(ACC)中的GABA水平以及ACC和左侧丘脑的谷氨酸加谷氨酰胺水平。当我们单独对神经递质进行建模时,使用二项逻辑回归进行单峰预测;当我们将这三种神经递质组合时,进行多峰预测。我们根据赤池信息准则选择最佳组合。

结果

单个神经递质无法预测组别。经过本雅明尼-霍奇伯格校正后,三种三联神经递质组合显著预测了组别。最佳模型(赤池信息准则为48.5)占累积模型权重的93.5%。其分类准确率达到83.7%(P = 0.003),包括伏隔核中的多巴胺合成能力(K)(P = 0.664)、ACC中的GABA水平(P = 0.019)、丘脑中的谷氨酸加谷氨酰胺水平(P = 0.678)以及交互项K×GABA(P = 0.016)。

结论

我们的多峰方法证明具有更高的分类准确率,这意味着患者的病理生理学表现为神经递质紊乱的组合,而非单一神经递质的异常。特别是伏隔核中的K与ACC中的GABA值之间异常的相互关系似乎提供了诊断信息。

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