Psychobiology of Suicidal Behavior in Borderline Personality Disorder

PUBLIC HEALTH RELEVANCE:

Clinicians caring for patients with borderline personality disorder (BPD) are faced with a high rate of suicide attempts (70% in our sample) and non-suicidal self-injury. Against this background, it is difficult to judge which patients are at the highest risk for dying by suicide. This study seeks to describe emotional, behavioral, and brain signatures of medically serious suicidal behavior in BPD, distinguishing it from less severe forms.

Learn More: Interpersonal dysfunction in borderline personality: a decision neuroscience perspective

A Clinician's Perspective Words from Nathan Stimmel, M.A.

PROJECT SUMMARY:

This is a longitudinal study of suicidal behavior in >300 people with borderline personality disorder (BPD), >60% of whom have attempted suicide. Our earlier studies focused on the pathway from interpersonal experiences to suicidal behavior, integrating three timescales: (1) naturalistic prediction of suicidal behavior over years; (2) prediction of suicidal ideation over days; and (3) experimental interrogation of decision processes over minutes. Taken together, our findings show that the emergence of suicidal ideation from interpersonal conflict is catalyzed by internalizing psychopathology, whereas the transition to suicidal behavior is facilitated by externalizing psychopathology and neurobehavioral alterations in decision-making.

Building on this work, we will (1) examine interpersonal traits and specific facets that cause decompensation in BPD and facilitate transitions in the suicidal process on a timescale of years, (2) improve individualized prediction of emotion dysregulation and suicidal thoughts on a timescale of hours to days, and (3) advance a neurocomputational account of the failed search for solutions in a crisis on a timescale of minutes. Our team has expertise in suicide research (Alex Dombrovski, PI), borderline personality and experience sampling (co-investigators Michael Hallquist [UNC] and Aidan Wright [U Michigan], and consultant Pilkonis), decision neuroscience (Dombrovski and Hallquist), and quantitative methods including machine learning (Hallquist and Wright, consultant Nick Jacobson, Dartmouth).

Innovations include a focus on clinically salient facets of interpersonal traits, integration of intensive and extended ecological momentary assessment (EMA) with passive sensing, an investigation of dynamic decision-making under high cognitive load supported by an original computational model, and a recently developed and validated multi-level approach to functional magnetic resonance imaging (fMRI) analysis. Clinically, understanding the suicidogenic effects of interpersonal trait facets and elaboration of personalized models of suicide risk will advance suicide prediction and development of just-in-time interventions. Expected results will advance the field of suicide research by unifying conceptual models of the suicidal process with hierarchical dimensional models of psychopathology, identifying general vs. person-specific suicidogenic processes, and elucidating decision-making under cognitive demands representative of the suicidal crisis.