Symptoms of borderline personality disorder (BPD) often manifest during adolescence, but the underlying relationship between these debilitating symptoms and the development of functional brain networks is not well understood. Here, we aimed to investigate how multivariate patterns of functional connectivity are associated with borderline personality traits in large samples of young adults and adolescents. We used functional magnetic resonance imaging data from young adults and adolescents from the HCP-YA (Human Connectome Project Young Adult) ( = 870, ages 22–37 years, 457 female) and the HCP-D (Human Connectome Project Development) ( = 223, ages 16–21 years, 121 female). A previously validated BPD proxy score was derived from the NEO Five-Factor Inventory. A ridge regression model with cross-validation and nested hyperparameter tuning was trained and tested in HCP-YA to predict BPD scores in unseen data from regional functional connectivity. The trained model was further tested on data from HCP-D without further tuning. Finally, we tested how the connectivity patterns associated with BPD aligned with age-related changes in connectivity. Multivariate functional connectivity patterns significantly predicted out-of-sample BPD scores in unseen data in young adults (HCP-YA = .001) and older adolescents (HCP-D = .001). Regional predictive capacity was heterogeneous; the most predictive regions were found in functional systems relevant for emotion regulation and executive function, including the ventral attention network. Finally, regional functional connectivity patterns that predicted BPD scores aligned with those associated with development in youth. Individual differences in functional connectivity in developmentally sensitive regions are associated with borderline personality traits.

中文翻译：

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边缘人格特征与功能连通性之间的普遍联系


边缘性人格障碍（BPD）的症状通常在青春期出现，但这些使人衰弱的症状与功能性大脑网络发育之间的潜在关系尚不清楚。在这里，我们的目的是研究功能连接的多元模式如何与大量年轻人和青少年样本中的边缘人格特征相关。我们使用来自 HCP-YA（人类连接组项目青年）（= 870，年龄 22-37 岁，457 名女性）和 HCP-D（人类连接组项目开发）（= 223 名，年龄 16-21 岁，121 名女性）。先前验证的 BPD 代理评分源自 NEO 五因素清单。在 HCP-YA 中训练和测试具有交叉验证和嵌套超参数调整的岭回归模型，以预测来自区域功能连接的未见数据中的 BPD 分数。训练后的模型在 HCP-D 的数据上进行了进一步测试，无需进一步调整。最后，我们测试了与 BPD 相关的连接模式如何与年龄相关的连接变化保持一致。多变量功能连接模式显着预测了年轻人 (HCP-YA = .001) 和老年青少年 (HCP-D = .001) 未见数据中的样本外 BPD 评分。区域预测能力参差不齐；最具预测性的区域存在于与情绪调节和执行功能相关的功能系统中，包括腹侧注意力网络。最后，预测 BPD 分数的区域功能连接模式与与青年发展相关的模式一致。 发育敏感区域功能连接的个体差异与边缘人格特征相关。