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基于扩散张量成像和血脂谱多水平信息的内表型组合面板作为抑郁症的预测指标。

Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression.

作者信息

Liu Juan, Liu Zhuang, Wei Yange, Zhang Yanbo, Womer Fay Y, Jia Duan, Wei Shengnan, Wu Feng, Kong Lingtao, Jiang Xiaowei, Zhang Luheng, Tang Yanqing, Zhang Xizhe, Wang Fei

机构信息

Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.

Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China.

出版信息

Aust N Z J Psychiatry. 2022 Sep;56(9):1187-1198. doi: 10.1177/00048674211031477. Epub 2022 May 27.

Abstract

OBJECTIVE

Clinical heterogeneity in major depressive disorder likely reflects the range of etiology and contributing factors in the disorder, such as genetic risk. Identification of more refined subgroups based on biomarkers such as white matter integrity and lipid-related metabolites could facilitate precision medicine in major depressive disorder.

METHODS

A total of 148 participants (15 genetic high-risk participants, 57 patients with first-episode major depressive disorder and 76 healthy controls) underwent diffusion tensor imaging and plasma lipid profiling. Alterations in white matter integrity and lipid metabolites were identified in genetic high-risk participants and patients with first-episode major depressive disorder. Then, shared alterations between genetic high-risk and first-episode major depressive disorder were used to develop an imaging x metabolite diagnostic panel for genetically based major depressive disorder via factor analysis and logistic regression. A fivefold cross-validation test was performed to evaluate the diagnostic panel.

RESULTS

Alterations of white matter integrity in corona radiata, superior longitudinal fasciculus and the body of corpus callosum and dysregulated unsaturated fatty acid metabolism were identified in both genetic high-risk participants and patients with first-episode major depressive disorder. An imaging x metabolite diagnostic panel, consisting of measures for white matter integrity and unsaturated fatty acid metabolism, was identified that achieved an area under the receiver operating characteristic curve of 0.86 and had a significantly higher diagnostic performance than that using either measure alone. And cross-validation confirmed the adequate reliability and accuracy of the diagnostic panel.

CONCLUSION

Combining white matter integrity in corpus callosum, superior longitudinal fasciculus and corona radiata, and unsaturated fatty acid profile may improve the identification of genetically based endophenotypes in major depressive disorder to advance precision medicine strategies.

摘要

目的

重度抑郁症的临床异质性可能反映了该疾病病因和促成因素的范围,如遗传风险。基于白质完整性和脂质相关代谢物等生物标志物识别更精细的亚组,可能有助于重度抑郁症的精准医疗。

方法

共有148名参与者(15名遗传高危参与者、57名首发重度抑郁症患者和76名健康对照)接受了扩散张量成像和血浆脂质谱分析。在遗传高危参与者和首发重度抑郁症患者中识别出白质完整性和脂质代谢物的改变。然后,通过因子分析和逻辑回归,利用遗传高危组和首发重度抑郁症组之间的共同改变,开发出一种用于基于基因的重度抑郁症的影像x代谢物诊断面板。进行了五重交叉验证测试以评估该诊断面板。

结果

在遗传高危参与者和首发重度抑郁症患者中均发现了放射冠、上纵束和胼胝体体部白质完整性的改变以及不饱和脂肪酸代谢失调。确定了一个由白质完整性和不饱和脂肪酸代谢测量指标组成的影像x代谢物诊断面板,其受试者操作特征曲线下面积为0.86,诊断性能显著高于单独使用任何一种测量指标。交叉验证证实了诊断面板具有足够的可靠性和准确性。

结论

结合胼胝体、上纵束和放射冠的白质完整性以及不饱和脂肪酸谱,可能会改善对重度抑郁症基于基因的内表型的识别,以推进精准医疗策略。

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