Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA.
Institute of Health Informatics, University of Minnesota School of Medicine, Minneapolis, MN, USA.
Transl Psychiatry. 2020 Aug 11;10(1):233. doi: 10.1038/s41398-020-00910-6.
This article reports on a study aimed to elucidate the complex etiology of post-traumatic stress (PTS) in a longitudinal cohort of police officers, by applying rigorous computational causal discovery (CCD) methods with observational data. An existing observational data set was used, which comprised a sample of 207 police officers who were recruited upon entry to police academy training. Participants were evaluated on a comprehensive set of clinical, self-report, genetic, neuroendocrine and physiological measures at baseline during academy training and then were re-evaluated at 12 months after training was completed. A data-processing pipeline-the Protocol for Computational Causal Discovery in Psychiatry (PCCDP)-was applied to this data set to determine a causal model for PTS severity. A causal model of 146 variables and 345 bivariate relations was discovered. This model revealed 5 direct causes and 83 causal pathways (of four steps or less) to PTS at 12 months of police service. Direct causes included single-nucleotide polymorphisms (SNPs) for the Histidine Decarboxylase (HDC) and Mineralocorticoid Receptor (MR) genes, acoustic startle in the context of low perceived threat during training, peritraumatic distress to incident exposure during first year of service, and general symptom severity during training at 1 year of service. The application of CCD methods can determine variables and pathways related to the complex etiology of PTS in a cohort of police officers. This knowledge may inform new approaches to treatment and prevention of critical incident related PTS.
本文报告了一项研究，旨在通过应用严格的计算因果发现 (CCD) 方法和观察数据，阐明创伤后应激 (PTS) 的复杂病因。该研究使用了一个现有的观察性数据集，其中包括 207 名警察的样本，他们在进入警察学院培训时被招募。参与者在学院培训期间的基线进行了一系列全面的临床、自我报告、遗传、神经内分泌和生理测量，并在培训结束 12 个月后进行了重新评估。应用数据处理管道——精神科计算因果发现协议 (PCCDP)——对该数据集进行分析，以确定 PTS 严重程度的因果模型。发现了一个包含 146 个变量和 345 个二变量关系的因果模型。该模型揭示了 5 个直接原因和 83 条因果途径（不超过 4 步）与警察服务 12 个月后的 PTS 有关。直接原因包括组氨酸脱羧酶 (HDC) 和盐皮质激素受体 (MR) 基因的单核苷酸多态性 (SNP)、训练期间低感知威胁背景下的听觉惊跳反应、服务第一年事件暴露期间的创伤后痛苦以及服务 1 年时训练中的一般症状严重程度。CCD 方法的应用可以确定与警察队列中 PTS 的复杂病因相关的变量和途径。这些知识可能为治疗和预防与关键事件相关的 PTS 提供新的方法。
