Structural and Functional Neural Correlates of Treatment Response for Interpersonal Psychotherapy for Depressed Adolescents

Bonnie Klimes-Dougan, Zeynep Başgöze, Bryon Mueller, Andrea Wiglesworth, Kathrine A. Carosella, Melinda Westlund Schreiner, Ana Bortnova, Kristina Reigstad, Kathryn R. Cullen, Meredith Gunlicks-Stoessel

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Precision medicine approaches hold tremendous promise to advance current clinical practice by providing information about which individuals will benefit from which treatments. This pilot study evaluated if baseline structure and function of the salience and emotion brain regions implicated in adolescent depression, specifically the amygdala and anterior cingulate cortex (ACC), predict response to Interpersonal Psychotherapy for Depressed Adolescents (IPT-A). Adolescents (n = 15; mean age = 14.5 (1.6); 80.0% female) diagnosed with a depressive disorder completed brain scans before the start of a 16 week trial of IPT-A. Clinical measures assessing depressive symptoms were completed before, during, and after a trial of therapy. Results show that at baseline, greater ACC activation in the context of an emotion-matching task and greater amygdala-ACC resting-state functional connectivity was related to greater improvement in depression symptoms. There was minimal evidence that brain structure predicted changes in depressive symptoms. The present study is the first to evaluate neural predictors of IPT-A response. While the results are preliminary, these findings suggest some avenues for future research to pursue in the hopes that more will benefit from treatment.

Original languageEnglish (US)
Article number1878
JournalJournal of Clinical Medicine
Volume11
Issue number7
DOIs
StatePublished - Apr 1 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • adolescent
  • depression
  • interpersonal psychotherapy
  • magnetic resonance imaging
  • predictor

PubMed: MeSH publication types

  • Journal Article

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