Intrinsic Functional Brain Connectivity Predicts Onset of Major Depression Disorder in Adolescence: A Pilot Study

Dina R. Hirshfeld-Becker, John D.E. Gabrieli, Benjamin G. Shapero, Joseph Biederman, Susan Whitfield-Gabrieli, Xiaoqian J. Chai

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Children with familial risk for major depressive disorder (MDD) have elevated risk for developing depression as adolescents. Here, we investigated longitudinally whether resting-state functional connectivity (RSFC) could predict the onset of MDD. In this pilot study, we followed a group of never-depressed children with familial risk for MDD and a group of age-matched controls without familial risk who had undergone an MRI study at 8-14 years of age. Participants were reassessed 3-4 years later with diagnostic interviews. We first investigated group differences in RSFC from regions in the emotion regulation, cognitive control, and default mode networks in the children who later developed MDD (converted), the children who did not develop MDD (nonconverted), and the control group. We then built a prediction model based on baseline RSFC that was independent of the group differences to classify the individuals who later developed MDD. Compared with the nonconverted group, the converted group exhibited hypoconnectivity between subgenual anterior cingulate cortex (sgACC) and inferior parietal lobule (IPL) and between left and right dorsolateral prefrontal cortices. The nonconverted group exhibited higher sgACC-IPL connectivity than did both the converted and control groups, suggesting a possible resilience factor to MDD. Classification between converted and nonconverted individuals based on baseline RSFC yielded high predictive accuracy with high sensitivity and specificity that was superior to classification based on baseline clinical rating scales. Intrinsic brain connectivity measured in healthy children with familial risk for depression has the potential to predict MDD onset, and it can be a useful neuromarker in early identification of children for preventive treatment.

Original languageEnglish (US)
Pages (from-to)388-398
Number of pages11
JournalBrain connectivity
Issue number5
StatePublished - 2019


  • children
  • depression risk
  • machine learning
  • resilience
  • resting-state fMRI
  • subgenual ACC

ASJC Scopus subject areas

  • Neuroscience(all)


Dive into the research topics of 'Intrinsic Functional Brain Connectivity Predicts Onset of Major Depression Disorder in Adolescence: A Pilot Study'. Together they form a unique fingerprint.

Cite this