Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics.
Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics.
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DOI：
10.1111/jcpp.13512
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发表时间：
2022-06
期刊：
影响因子：
--
通讯作者：
Gotlib IH
中科院分区：
文献类型：
--
作者：
Kirshenbaum JS;Chahal R;Ho TC;King LS;Gifuni AJ;Mastrovito D;Coury SM;Weisenburger RL;Gotlib IH
自杀念头（SI）通常出现在青春期，但很难预测。鉴于SI的潜在致命后果，重要的是要确定神经生物学和心理社会变量解释SI在青少年中的严重程度。在从社区招募的106名参与者（59名女性）中，我们评估了青少年早期（基线：9-13岁）的心理社会特征并获得了静息状态fMRI数据。在250个大脑区域中，我们评估了基于局部图论的互连特性：局部效率、特征向量中心性、节点度、模块内z分数和参与系数。四年后（随访：13-19岁），参与者自我报告了他们的SI严重程度。我们使用最小绝对收缩和选择算子（LASSO）回归来确定心理社会和基于大脑的变量的线性组合，这些变量最能解释随访时SI症状的严重程度。嵌套交叉验证产生了所有LASSO模型的模型性能统计。社会心理和大脑为基础的变量的组合解释了随后的严重程度SI（R2=0.55），最强的内在和外在的症状严重程度在后续。随访LASSO回归的心理社会和脑为基础的变量表明，心理社会的变量解释了55%的SI严重程度的方差，相比之下，脑为基础的变量比零模型表现更差。基线和随访心理社会变量的线性组合最能解释SI的严重程度。随访分析表明，图论静息状态指标并没有增加对青少年SI严重程度的预测。注意内化和外化症状在青春期早期是很重要的;静息状态连接特性而不是局部图论指标可能会对SI的严重程度产生更强的预测。
Suicidal ideation (SI) typically emerges during adolescence but is challenging to predict. Given the potentially lethal consequences of SI, it is important to identify neurobiological and psychosocial variables explaining severity of SI in adolescents. In 106 participants (59 female) recruited from the community, we assessed psychosocial characteristics and obtained resting-state fMRI data in early adolescence (baseline: ages 9-13 years). Across 250 brain regions, we assessed local graph-theory based properties of interconnectedness: local efficiency, eigenvector centrality, nodal degree, within-module z-score, and participation coefficient. Four years later (follow-up: ages 13-19 years), participants self-reported their SI severity. We used least absolute shrinkage and selection operator (LASSO) regressions to identify a linear combination of psychosocial and brain-based variables that best explain severity of SI symptoms at follow-up. Nested-cross-validation yielded model performance statistics for all LASSO models. A combination of psychosocial and brain-based variables explained subsequent severity of SI (R2=0.55); the strongest were internalizing and externalizing symptom severity at follow-up. Follow-up LASSO regressions of psychosocial-only and brain-based-only variables indicated that psychosocial-only variables explained 55% of the variance in SI severity; in contrast, brain-based-only variables performed worse than the null model. A linear combination of baseline and follow-up psychosocial variables best explained severity of SI. Follow-up analyses indicated that graph-theory resting-state metrics did not increase the prediction of severity of SI in adolescents. Attending to internalizing and externalizing symptoms is important in early adolescence; resting-state connectivity properties other than local graph-theory metrics might yield a stronger prediction of the severity of SI.
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DOI：
10.1523/jneurosci.1929-08.2008
发表时间：
2008-09-10
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Bassett DS;Bullmore E;Verchinski BA;Mattay VS;Weinberger DR;Meyer-Lindenberg A
通讯作者：
Meyer-Lindenberg A
人脑网络组图谱：基于连接架构的新大脑图谱
DOI：
10.1093/cercor/bhw157
发表时间：
2016-08
期刊：
Cerebral cortex (New York, N.Y. : 1991)
影响因子：
--
作者：
Fan L;Li H;Zhuo J;Zhang Y;Wang J;Chen L;Yang Z;Chu C;Xie S;Laird AR;Fox PT;Eickhoff SB;Yu C;Jiang T
通讯作者：
Jiang T
影响因子：
48
作者：
Esteban, Oscar;Markiewicz, Christopher J.;Gorgolewski, Krzysztof J.
通讯作者：
Gorgolewski, Krzysztof J.
影响因子：
7.6
作者：
Adrian, Molly;Miller, Adam Bryant;Vander Stoep, Ann
通讯作者：
Vander Stoep, Ann
静息态功能网络连接的改变与年轻抑郁症患者的自杀企图有关
影响因子：
11.3
作者：
Cao, Jun;Ai, Ming;Kuang, Li
通讯作者：
Kuang, Li