Attenuated cognitive control network connectivity as a mechanism in mother–daughter intergenerational transmission of depression: a preliminary study

  • Katie L. Burkhouse
  • , Matthew B. Thompson
  • , Eda Naz Dinc
  • , Noah H. Kingston
  • , Cope Feurer
  • , Robert C. Welsh
  • , Ian H. Gotlib
  • , K. Luan Phan
  • , Scott A. Langenecker

Research output: Contribution to journalArticlepeer-review

Abstract

Identifying brain mechanisms implicated in the intergenerational transmission of major depressive disorder (MDD) is crucial for early detection and developing novel interventions. One promising mechanism involves altered intrinsic connectivity patterns in brain networks supporting emotion processing, including within the cognitive control network (CCN). The current preliminary study used resting state functional magnetic resonance imaging (fMRI) to examine whether altered CCN connectivity patterns are a brain-based mechanism of intergenerational risk for depression. We tested whether CCN connectivity patterns (1) differentiated mothers with and without recurrent MDD, (2) differentiated their high-risk (HR) and low-risk (LR) daughters, and (3) served as prospective predictors of daughters’ depressive symptoms over a multi-wave follow-up. Participants were 56 mother–daughter pairs who completed a resting state fMRI scan. Mothers with, versus without, a history of MDD exhibited reduced connectivity between the CCN and other regions within the CCN, such as the middle frontal gyrus and dorsal anterior cingulate cortex (ACC). Reduced connectivity between the CCN and dorsal ACC was also observed in HR, relative to LR, daughters, correlated significantly among mothers and daughters, and associated with higher depression symptoms in daughters across 18 months. Reduced connectivity within the CCN may constitute one brain-based marker to further investigate as a target for prevention to attenuate the intergenerational transmission of depression.

Original languageEnglish (US)
Article number41056
JournalScientific reports
Volume15
Issue number1
DOIs
StatePublished - Dec 2025

All Science Journal Classification (ASJC) codes

  • General

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