OBJECTIVE A major challenge in understanding and treating posttraumatic stress disorder (PTSD) is its clinical heterogeneity, which is likely determined by various neurobiological perturbations. This heterogeneity likely also reduces the effectiveness of standard group comparison approaches. The authors tested whether a statistical approach aimed at identifying individual-level neuroimaging abnormalities that are more prevalent in case subjects than in control subjects could reveal new clinically meaningful insights into the heterogeneity of PTSD. METHODS Resting-state functional MRI data were recorded from 87 unmedicated PTSD case subjects and 105 war zone-exposed healthy control subjects. Abnormalities were modeled using tolerance intervals, which referenced the distribution of healthy control subjects as the "normative population." Out-of-norm functional connectivity values were examined for enrichment in cases and then used in a clustering analysis to identify biologically defined PTSD subgroups based on their abnormality profiles. RESULTS The authors identified two subgroups among PTSD cases, each with a distinct pattern of functional connectivity abnormalities with respect to healthy control subjects. Subgroups differed clinically on levels of reexperiencing symptoms and improved case-control discriminability and were detectable using independently recorded resting-state EEG data. CONCLUSIONS The results provide proof of concept for the utility of abnormality-based approaches for studying heterogeneity within clinical populations. Such approaches, applied not only to neuroimaging data, may allow detection of subpopulations with distinct biological signatures so that further clinical and mechanistic investigations can be focused on more biologically homogeneous subgroups.

中文翻译：

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静止状态功能连接中的个别异常模式显示了两个数据驱动的PTSD子组。

目的了解和治疗创伤后应激障碍（PTSD）的主要挑战是其临床异质性，这可能是由各种神经生物学扰动决定的。这种异质性也可能降低标准组比较方法的有效性。作者测试了一种旨在确定病例个体中比对照个体中更普遍的个体水平神经影像异常的统计方法是否可以揭示出对PTSD异质性的新的临床有意义的见解。方法记录了87名未经药物治疗的PTSD病例受试者和105名暴露于战区的健康对照受试者的静息状态MRI数据。使用耐受区间对异常进行建模，该区间将健康对照受试者的分布称为“正常人群”。检查超出正常范围的功能连接性值是否丰富病例，然后用于聚类分析中，以根据其异常概况识别生物学定义的PTSD子组。结果作者确定了PTSD病例中的两个亚组，相对于健康对照受试者，每个亚组具有明显的功能连接异常模式。亚组在临床症状再发水平和病例对照可分辨性上有所不同，临床上可使用独立记录的静息状态EEG数据进行检测。结论结果为基于异常的方法在临床人群中研究异质性的实用性提供了概念验证。这样的方法不仅适用于神经影像数据，