CO2 Reactivity as a Biomarker of Non-Response to Exposure-Based Therapy

Anxiety-, obsessive-compulsive and trauma- and stressor-related disorders reflect a significant public health problem. This study is designed to evaluate the predictive power of a novel biomarker based on a CO2 challenge, thus addressing the central question "can this easy-to-administer assay aid clinicians in deciding whether or not to initiate exposure-based therapy?"

Inclusion Criteria: * A primary DSM-5 diagnosis of panic disorder (with or without an agoraphobia diagnosis), social anxiety disorder, generalized anxiety disorder, obsessive-compulsive disorder, or post-traumatic stress disorder as assessed by the Structured Clinical Interview for the DSM-5 (SCID-5) * A score of 8 or greater on the Overall Anxiety Severity and Impairment Scale (OASIS) * Ages 18 to 70 * Willingness and ability to provide informed consent and comply with the requirements of the study protocol. * Proficiency in English (because assessment instruments have only been validated in English) Exclusion Criteria: * A lifetime history of bipolar or psychotic disorders, substance use disorders (other than nicotine) or eating disorder in the past 6 months; serious cognitive impairment. * Active suicidal ideation with at least some intent to act with or without specific plan (a rating of 4 for suicidal ideation on the Columbia-Suicide Severity Rating Scale) or suicidal behaviors (actual attempt, interrupted attempt, aborted or self-interrupted attempt, or preparatory acts or behavior) within the past 6 months. * Medical conditions contraindicating CO2 inhalation or hyperventilation challenge (e.g., cardiac arrhythmia, cardiac failure, asthma, lung fibrosis, high blood pressure, epilepsy, or stroke). * Pregnancy or lactation * Ongoing psychotherapy directed toward the primary disorder. * Pharmacological treatment started within 8 weeks prior to the screen (patients "stable" on their medication regimen will be included and their medication status will be included as a variable in the model)