The AURORA Study: a longitudinal, multimodal library of brain biology and function after traumatic stress exposure

Abstract

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, post-concussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/ treatment interventions. Progress in overcoming these limitations has been challenging, because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large scale (n = 5,000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for one year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.

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

“… 141 These different symptom profiles may also have differences in their potential etiologies and biomarker profiles, thus examining PTSD and other APNS as single diagnostic categories may severely limit our ability to discover reliable biomarkers. However, as the field moves towards a more succinct definition of APNS outcomes that better characterize the full symptom profiles of trauma survivors (versus traditional syndromic classifications studied in isolation) 4 , we will increase our ability to identify accurate target groups to which blood-based risk biomarkers can more specifically identify vulnerable individuals.…”

“…Using this data, AURORA investigators and other individuals in the research community can improve outcome phenotypes, develop prediction tools, and improve understanding of molecular mechanisms driving APNS. For a more detailed description of the full study, please refer to the AURORA methods paper 4 .…”

“…While many individuals recover following trauma exposure, a substantial subset develop adverse posttraumatic neuropsychiatric sequelae (APNS). APNS, as previously defined 4 , can include a wide range of neuropsychiatric outcomes; three of the most common APNS are posttraumatic stress (PTS), major depression, and regional or widespread chronic musculoskeletal pain (CMP). These APNS cause tremendous suffering, functional impairment, high health care costs, and are a leading cause of disability among current and former members of the armed forces.…”

Anxiety Sensitivity Prospectively Predicts Increased Acute Posttraumatic Stress and Related Symptoms After Sexual Assault

“…worry that I might be mentally ill") were selected to match those used in a large-scale U.S. National Institute of Mental Healthfunded study of trauma survivors (McLean et al, 2019). In the current study, the possible score range for the brief ASI was 0-12, with higher scores indicating higher levels of AS.…”

Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges

“…The discovery of noninvasive biomarkers for disease is a main goal in contemporary biomedicine 16 . A key emerging question is whether high-dimensional behavioral data can be used for clinical diagnosis 17,18 , particularly in the domain of mental health [19][20][21][22] . Instead of relying on the use of ratings by clinicians or selfreports from patients, the goal is to use objective and quantifiable behavioral data combined with artificial intelligence analyses to predict disease vulnerability or progression.…”