Literature review and methodological considerations for understanding circulating risk biomarkers following trauma exposure

Abstract

Exposure to traumatic events is common. While many individuals recover following trauma exposure, a substantial subset develop adverse posttraumatic neuropsychiatric sequelae (APNS) such as posttraumatic stress, major depression, and regional or widespread chronic musculoskeletal pain. APNS cause substantial burden to the individual and to society, causing functional impairment and physical disability, risk for suicide, lost workdays, and increased health care costs. Contemporary treatment is limited by an inability to identify individuals at high risk of APNS in the immediate aftermath of trauma, and an inability to identify optimal treatments for individual patients. Our purpose is to provide a comprehensive review describing candidate blood-based biomarkers that may help to identify those at high risk of APNS and/or guide individual intervention decision-making. Such blood-based biomarkers include circulating biological factors such as hormones, proteins, immune molecules, neuropeptides, neurotransmitters, mRNA, and noncoding RNA expression signatures, while we do not review genetic and epigenetic biomarkers due to other recent reviews of this topic. The current state of the literature on circulating risk biomarkers of APNS is summarized, and key considerations and challenges for their discovery and translation are discussed. We also describe the AURORA study, a specific example of current scientific efforts to identify such circulating risk biomarkers and the largest study to date focused on identifying risk and prognostic factors in the aftermath of trauma exposure.

Figure 1.

Circulating blood-based risk biomarkers that have been assessed in previous studies for their ability to predict the development of adverse posttraumatic neuropsychiatric sequelae (APNS). General categories for these risk biomarkers include hormones, proteins, immune mediators, nucleic acids, and neuropeptides and neurotransmitters. Note that not all circulating risk biomarkers that have been examined to date showed a statistically significantly relationship with APNS. See Table 1 for more details. Validation of the significantly associated risk biomarkers and identification of novel circulating risk biomarkers within the described categories or outside of these categories (e.g. metabolites, microvesicles, immune cells) will be a high priority for APNS-focused researchers in the coming years.

Figure 2.

Key steps (top) and methodological considerations (bottom) in the discovery of circulating blood-based risk biomarkers of adverse posttraumatic neuropsychiatric sequelae (APNS). While the steps and considerations included in this figure are not exhaustive, it represents a subset of the myriad factors that can influence blood based biomarker discovery and translation. For instance, the epidemiological design of the cohort from which samples are drawn, and characteristics/factors of participants can determine whether there is sufficient statistical power to detect a risk biomarker, whether adjustors should be included in statistical models and whether the findings are generalizable to additional populations. SES = socioeconomic status, FDA = U.S. Food and Drug Administration. Adapted from a variety of sources including:^{, ,}

Figure 3.

The AURORA study is an on-going longitudinal cohort study assessing APNS development following trauma exposure. Individuals are enrolled in the Emergency Department and followed over the course of a year. Consistent with the theme of this review article, one main goal of the AURORA study is to discover circulating risk biomarkers that identify vulnerable individuals in the early aftermath of trauma exposure. Therefore, blood samples are collected from all individuals immediately following enrollment (n=5,000; left). Additional blood samples are collected from a subset of participants two weeks (n=800; middle) and six months (n=3,000; right) following trauma exposure. These longitudinal samples are collected at either Deep Phenotyping sessions when additional multilayered data are collected (e.g. functional and structural MRI, pain physiology, startle response) or via Mobile phlebotomy/participant return to the Emergency Department. Longitudinal blood samples can be used to assess trajectories of risk biomarkers and/or to identify diagnostic biomarkers using nested case-control samples. D = DNA PAXgene tube, R = RNA PAXgene tube, P = EDTA tube for plasma, ED = Emergency Department. All sample sizes represent planned cohort sizes based on enrollment rates and funding as of the date of publication of this review. All samples and processed data derived from the AURORA cohort will be available to the full research community in Fall 2022.