Behavioral and neurocognitive factors distinguishing post-traumatic stress comorbidity in substance use disorders

Abstract

Significant trauma histories and post-traumatic stress disorder (PTSD) are common in persons with substance use disorders (SUD) and often associate with increased SUD severity and poorer response to SUD treatment. As such, this sub-population has been associated with unique risk factors and treatment needs. Understanding the distinct etiological profile of persons with co-occurring SUD and PTSD is therefore crucial for advancing our knowledge of underlying mechanisms and the development of precision treatments. To this end, we employed supervised machine learning algorithms to interrogate the responses of 160 participants with SUD on the multidimensional NIDA Phenotyping Assessment Battery. Significant PTSD symptomatology was correctly predicted in 75% of participants (sensitivity: 80%; specificity: 72.22%) using a classification-based model based on anxiety and depressive symptoms, perseverative thinking styles, and interoceptive awareness. A regression-based machine learning model also utilized similar predictors, but failed to accurately predict severity of PTSD symptoms. These data indicate that even in a population already characterized by elevated negative affect (individuals with SUD), especially severe negative affect was predictive of PTSD symptomatology. In a follow-up analysis of a subset of 102 participants who also completed neurocognitive tasks, comorbidity status was correctly predicted in 86.67% of participants (sensitivity: 91.67%; specificity: 66.67%) based on depressive symptoms and fear-related attentional bias. However, a regression-based analysis did not identify fear-related attentional bias as a splitting factor, but instead split and categorized the sample based on indices of aggression, metacognition, distress tolerance, and interoceptive awareness. These data indicate that within a population of individuals with SUD, aberrations in tolerating and regulating aversive internal experiences may also characterize those with significant trauma histories, akin to findings in persons with anxiety without SUD. The results also highlight the need for further research on PTSD-SUD comorbidity that includes additional comparison groups (i.e., persons with only PTSD), captures additional comorbid diagnoses that may influence the PTSD-SUD relationship, examines additional types of SUDs (e.g., alcohol use disorder), and differentiates between subtypes of PTSD.

Fig. 1. CART decision tree—regression—full sample.

White rectangles represent intermediate nodes (i.e., cohorts that could be further split); gray rectangles represent terminal nodes; PROMIS-A PROMIS Anxiety, MCQ-UD Metacognitions Questionnaire—Uncontrollability/Danger, SUPPS Short Urgency-Premeditation-Perseverance-Sensation Seeking-Positive Urgency Impulsive Behavior Scale, BPAS Buss–Perry Aggression Scale.

Fig. 2. CART decision tree—classification—full sample.

White rectangles represent intermediate nodes (i.e., cohorts that could be further split); gray rectangles represent final nodes; Class 0 = PCL-5 < 33; Class 1 = PCL-5 ≥ 33; PROMIS-A PROMIS Anxiety, MCQ-UD Metacognitions Questionnaire—Uncontrollability/Danger, MAIA-ND Multidimensional Assessment of Interoceptive Awareness—Not Distracting, PROMIS-D PROMIS Depression, MAIA-AR Multidimensional Assessment of Interoceptive Awareness—Attention Regulation.

Fig. 3. CART decision tree—regression—neurocognitive sample.

White rectangles represent intermediate nodes (i.e., cohorts that could be further split); gray rectangles represent terminal nodes; PROMIS-A PROMIS Anxiety, MCQ Metacognition Questionnaire, BPAS Buss–Perry Aggression Scale, DTS Distress Tolerance Scale, MAIA Multidimensional Assessment of Interoceptive Awareness.

Fig. 4. CART decision tree—neurocognitive sub-sample.

White rectangles represent intermediate nodes (i.e., cohorts that could be further split); gray rectangles represent final nodes; Class 0 = PCL-5 < 33; Class 1 = PCL-5 ≥ 33; PROMIS-D PROMIS Depression, Fear Effect RT Fear effect reaction time from Emotional Go-NoGo Task.