The present longitudinal study aims at (i) identifying neurobiological mechanisms associated with successful social integration during the treatment of inpatients with Borderline Personality Disorder (BPD) and (ii) improving biomarker-based predictions of treatment response by incorporating core metrics of social integration.

Social connections have a strong impact on mental and physical health. Surprisingly, however, there is a paucity of studies probing the predictive validity of perceived social connections such as subjective social support and loneliness for the outcomes of inpatient treatment of BPD. Although social impairments are key features of BPD psychopathology, social integration has been largely neglected, which may therefore explain the minimal translation of predictive molecular or imaging-based biomarkers into the clinic. The investigators hypothesize that the assessment of negative cognitive biases at baseline will help to identify BPD patients who will experience less social support and more loneliness during inpatient treatment. Furthermore, an inclusion of social integration indices may increase the incremental validity for the biomarker-based prediction of treatment response. In this longitudinal, observational study, data from 56 BPD patients will be analyzed to assess negative cognitive biases and the underlying neurobiological mechanisms with behavioral, neuroendocrine, psychophysiological, and neural readouts before and after one month of inpatient Dialectical Behavior Therapy (DBT). To evaluate pathological biases, the patients' data will be compared with a control group of 31 healthy participants who will also be tested twice. Neural readouts include structural and functional magnetic resonance imaging (fMRI) measurements. The fMRI tasks will probe the processing of social touch, interpersonal trust, and interoception. To further investigate pathological distortions of social touch and interoception, interoceptive accuracy and comfort zones of social touch will be assessed. Further, patients and healthy participants will perform a positive social interaction task, accompanied by psychophysiological and neuroendocrinological measures. Psychometric questionnaires and semi-structured interviews will be used to monitor symptom load and social indices before, during, and after the inpatient treatment. Long-term effects will be assessed by questionnaires and interviews 8 and 20 weeks after inpatient treatment/waiting time, as well as after each DBT module (follow-ups). The investigators plan to conduct uni- and multivariate analyses of the baseline measurements to predict patients' social integration and treatment response during the inpatient therapy and examine treatment-related changes. The findings of this project may help identify vulnerable patients that benefit from adjunct therapies targeting negative social biases and improve biomarker-based models of treatment prediction.