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Psychobiology of Suicidal Behavior in Borderline Personality Disorder

PI: Alexandre Y. Dombrovski

Supported by the National Institute of Mental Health

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:

The longitudinal study represents a decades-long effort examining psychosocial factors in subjects with characteristics of BPD. Participants are recruited from outpatient and inpatient treatment settings, as well as from the greater Pittsburgh community. Those interested in joining the study undergo a series of diagnostic interviews and self-reports to determine eligibility, administered by a clinician. Once enrolled, participants work with a clinician to compile baseline data on demographic information such as family history, education, and work history, as well as clinical data related to suicidal behavior, impulsivity, aggression, quality of life, and other relevant areas.

Contact is maintained over the ensuing years through follow-up interviews. Participants touch base with the study at regular intervals to report updates in demographics, treatment, socioeconomic factors, and other life changes, while also sharing experiences related to suicidality, impulsivity, and further behavioral indicators. Brief diagnostic assessments are conducted at follow-up to track changes in BPD and other comorbid presentations.

The larger study is in its fourth decade and continues to actively enroll new participants, many of whom have passed follow-up milestones of 10, 20, even 30-plus years. Aside from the immediate material compensation, those who remain active say they stay motivated by contributing to a large body of work that aims to increase understanding of BPD and its outcomes. Through maintaining long-term contact, many also find some benefit in tracking and reflecting on their own changes over time.

 

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.