Inflammatory markers as predictors of depression and anxiety in adolescents: Statistical model building with component-wise gradient boosting.
Inflammatory markers as predictors of depression and anxiety in adolescents: Statistical model building with component-wise gradient boosting.
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DOI：
10.1016/j.jad.2018.03.006
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发表时间：
2018-07
影响因子：
6.6
通讯作者：
Williamson DE
中科院分区：
文献类型：
--
作者：
Walss-Bass C;Suchting R;Olvera RL;Williamson DE
免疫系统异常在一些精神疾病中反复被观察到，包括严重的抑郁和焦虑。然而，特异性免疫介质是否在这些疾病的发病机制中起早期作用尚不清楚。在纵向设计中，成分梯度增强用于建立抑郁模型，通过情绪-情感问卷-儿童（MFQC）进行评估，并通过儿童焦虑相关情绪障碍筛查（SCARED）评估254名青少年的焦虑，这些预测因素包括性别，种族，39种炎症蛋白以及这些蛋白与时间之间的相互作用。每个模型都通过逆向消去来简化，以最大限度地简化和推广。成分梯度增强和模型还原发现，女性性别、生长调节癌基因（GRO）和转化生长因子α (tgf - α)预测抑郁，而女性性别预测焦虑。在目前的研究中，青春期的不同开始以及对月经周期的缺乏控制也可能是造成男女之间差异的原因。此外，对预测因子与结果之间所有可能的非线性关系的研究超出了本研究的计算能力和范围。这项研究强调需要新的统计模型来识别异常心理行为的可靠生物学预测因子。
Immune system abnormalities have been repeatedly observed in several psychiatric disorders, including severe depression and anxiety. However, whether specific immune mediators play an early role in the etiopathogenesis of these disorders remains unknown. In a longitudinal design, component-wise gradient boosting was used to build models of depression, assessed by the Mood-Feelings Questionnaire-Child (MFQC), and anxiety, assessed by the Screen for Child Anxiety Related Emotional Disorders (SCARED) in 254 adolescents from a large set of candidate predictors, including sex, race, 39 inflammatory proteins, and the interactions between those proteins and time. Each model was reduced via backward elimination to maximize parsimony and generalizability. Component-wise gradient boosting and model reduction found that female sex, growth-regulated oncogene (GRO), and transforming growth factor alpha (TGF-alpha) predicted depression, while female sex predicted anxiety. Differential onset of puberty as well as a lack of control for menstrual cycle may also have been responsible for differences between males and females in the present study. In addition, investigation of all possible nonlinear relationships between the predictors and the outcomes was beyond the computational capacity and scope of the present research. This study highlights the need for novel statistical modeling to identify reliable biological predictors of aberrant psychological behavior.
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影响因子：
25.8
作者：
Khandaker GM;Pearson RM;Zammit S;Lewis G;Jones PB
通讯作者：
Jones PB
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
10.1111/j.1600-0897.2009.00725.x
发表时间：
2009-09-01
影响因子：
3.6
作者：
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通讯作者：
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影响因子：
2.4
作者：
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通讯作者：
Dantzer, Robert