Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method (“3C”) was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants’ cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala’s functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results’ robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.

基于创伤后应激障碍（PTSD）的当代基于症状的诊断很大程度上忽略了相关的神经行为机制，并且完全依赖于主观的人际交往。以前的将生物标志物与PTSD相关联的研究大多将基于症状的诊断作为主要结果指标，而忽略了PTSD表型特征的广泛变异性和丰富性。在这里，我们旨在通过计算得出潜在的生物标记物，这些标记物可有效区分最近的创伤幸存者中的PTSD亚型。使用三阶段半无监督方法（“ 3C”）首先根据当前PTSD症状的严重程度对个体进行分类，然后根据与PTSD相关的临床特征（例如焦虑和抑郁）得出聚类，最后对参与者的聚类成员进行分类使用客观的多域功能。从心理测量，认知功能以及结构和功能MRI数据中总共提取了256个特征，这些数据来自在暴露于创伤后1个月内评估的101位成年平民（年龄= 34.80±11.95； 51位女性）。通过重要性分析，分类树和方差分析评估了最能区分集群成员的功能。结果显示，内嗅和鼻前扣带回皮层体积（结构性MRI域），任务内杏仁核与岛状和丘脑的功能连接性（功能性MRI域），执行功能和认知灵活性（认知测试域）能最好地区分与PTSD严重性。交叉验证建立了该样本中结果的鲁棒性和一致性。3C分析揭示的神经和认知潜在生物标记物为创伤后不久的创伤后发病率提供了客观的分类器。他们还映射到先前记录的与PTSD相关的神经行为机制，并证明了标准化和客观测量作为区分创伤后不久的临床亚类的有用性。