利用探索性无监督机器学习识别青少年重度抑郁障碍的心血管疾病风险内型

Anisa F. Khalfan BSc , Susan C. Campisi PhD , Ronda F. Lo PhD , Brian W. McCrindle MD, MPH , Daphne J. Korczak MD, MSc
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引用次数: 0

摘要

青少年重度抑郁障碍(MDD)发生过早动脉粥样硬化和心血管疾病(CVD)的风险增加。识别患有重度抑郁症的青少年心血管疾病风险增加的能力将促进个性化干预,并推进关于重度抑郁症与心血管疾病关联的知识。本研究旨在确定青少年MDD内源性疾病增加CVD风险。方法MDD青少年(n = 189;74%的女性;平均[SD]年龄15.03[1.85]岁)通过一家大型城市医院的门诊精神病学项目招募。收集个人和家庭(人口统计、抑郁、焦虑症状、家庭冲突)、体格检查(生命体征、体重指数)和实验室(血脂、葡萄糖、c反应蛋白)数据。使用人口统计学、临床和实验室数据,进行k均值聚类;随后的模型只包括脂质。连续测量和分类测量在集群之间进行比较。结果包含所有变量的模型产生1个高、1个低心血管疾病风险集群,在种族、人体测量学、实验室数据和家庭冲突方面存在显著差异,但在抑郁或焦虑严重程度方面无显著差异。仅脂质模型产生了2个高和2个低CVD风险集群,这些集群在性别、种族、体重指数、脂质、抑郁和焦虑严重程度上存在显著差异。在2个CVD风险集群中,一个表明心脏代谢风险增加,而另一个包括患有MDD的青少年,他们具有高的低密度脂蛋白,没有其他心血管风险因素。结论青少年MDD的内型与不同CVD风险水平相关。结果强调了青少年MDD的异质性,以及在MDD管理中需要精确的医学方法来改善CVD和抑郁结果。本研究在加拿大多伦多病童医院调查了患有重度抑郁症(MDD)的青少年的心血管危险因素。利用空腹血脂浓度进行聚类分析,得出了青少年抑郁症的4种内源性类型,涉及青年人口统计学、临床和心脏代谢因素,并强调了心血管疾病(CVD)风险增加的不同潜在机制。结果强调了青少年重度抑郁症的异质性,以及需要精确的医学方法来改善心血管疾病和抑郁症的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Cardiovascular Disease Risk Endotypes of Adolescent Major Depressive Disorder Using Exploratory Unsupervised Machine Learning

Objective

Adolescents with major depressive disorder (MDD) are at increased risk of premature atherosclerosis and cardiovascular disease (CVD). The ability to identify adolescents with MDD who are at increased CVD risk would facilitate personalized interventions and advance knowledge regarding the MDD–CVD association. This study aimed to identify adolescent MDD endotypes of increased CVD risk.

Method

Youth with MDD (n = 189; 74% female; mean [SD] age 15.03 [1.85] years) were recruited through an outpatient psychiatry program in a large urban hospital. Individual and family (demographics, depression, anxiety symptoms, family conflict), physical examination (vital signs, body mass index), and laboratory (lipid profile, glucose, C-reactive protein) data were collected. Using demographic, clinical, and laboratory data, k-means clustering was performed; a subsequent model included only lipids. Continuous and categorical measures were compared between clusters.

Results

The model containing all variables yielded 1 high and 1 low CVD risk cluster, which differed significantly in ethnicity, anthropometrics, laboratory data, and family conflict, but not in depression or anxiety severity. The lipid-only model yielded 2 high and 2 low CVD risk clusters that differed significantly in sex, ethnicity, body mass index, lipids, depression, and anxiety severity. Of the 2 CVD risk clusters, one was indicative of increased cardiometabolic risk, while the other comprised adolescents with MDD who had high low-density lipoprotein and no other cardiovascular risk factors.

Conclusion

Endotypes of adolescent MDD associated with varying levels of CVD risk were identified. Results highlight the heterogeneity of adolescent MDD and the need for precision medicine approaches in management of MDD to improve both CVD and depression outcomes.

Plain language summary

This study examined cardiovascular risk factors among adolescents with major depressive disorder (MDD) at the Hospital for Sick Children in Toronto, Canada. Cluster analysis using fasting serum lipid concentrations yielded 4 endotypes of adolescent depression with respect to youth demographic, clinical, and cardiometabolic factors and highlighted different potential mechanisms of increased cardiovascular disease (CVD) risk. Results underscore the heterogeneity of adolescent MDD and the need for precision medicine approaches to improve both CVD and depression outcomes.
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JAACAP open
JAACAP open Psychiatry and Mental Health
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