@article{3d3534859bf94acbb6cb36bee8574f6d,
title = "Intrinsic Functional Brain Connectivity Predicts Onset of Major Depression Disorder in Adolescence: A Pilot Study",
abstract = "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.",
keywords = "children, depression risk, machine learning, resilience, resting-state fMRI, subgenual ACC",
author = "Hirshfeld-Becker, {Dina R.} and Gabrieli, {John D.E.} and Shapero, {Benjamin G.} and Joseph Biederman and Susan Whitfield-Gabrieli and Chai, {Xiaoqian J.}",
note = "Funding Information: The authors thank Christian Hoover, Lauren Jacobs, Flavia Vaz de Souza, Gretchen Reynolds, Daniel O'Young and Jiahe Zhang, Elana Kagen and Tara Kenworthy for their help in data collection. This research was carried out in the Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research at the Massachusetts Institute of Technology and in the Child Cognitive Behavioral Therapy Program at the Massachusetts General Hospital. The follow-up study was supported by a Harvard University Catalyst Award, which draws its funding from the National Institutes of Health (NIH 5UL1TR001102-03). The baseline study was carried out in the MGH Clinical and Research Program in Pediatric Psychopharmacology and was supported by the Tommy Fuss Fund, the Poitras Center for Psychiatric Disorders Research, and the MGH Pediatric Psychopharmacology Council Fund. The funding sources had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the article; or in the decision to submit the article for publication. Funding Information: The authors report no conflicts of interest. Dr. Joseph Biederman is currently receiving research support from the following sources: The Department of Defense, AACAP, Alcobra, Forest Research Institute, Ironshore, Lundbeck, Magceutics, Inc., Merck, PamLab, Pfizer, Shire Pharmaceuticals, Inc., SPRITES, Sunovion, Vaya Pharma/Enzymotec, and NIH. In 2014, Dr. Joseph Biederman received honoraria from the MGH Psychiatry Academy for tuition-funded CME courses. He has a U.S. Patent Application pending (Provisional No. #61/233,686) through MGH corporate licensing, on a method to prevent stimulant abuse. Dr. Biederman received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Ingenix, Prophase, Shire, Bracket Global, Sunovion, and Theravance; these royalties were paid to the Department of Psychiatry at MGH. Funding Information: The authors thank Christian Hoover, Lauren Jacobs, Flavia Vaz de Souza, Gretchen Reynolds, Daniel O{\textquoteright}Young and Jiahe Zhang, Elana Kagen and Tara Kenworthy for their help in data collection. This research was carried out in the Athinoula A. Martinos Imaging Center at the McGov-ern Institute for Brain Research at the Massachusetts Institute of Technology and in the Child Cognitive Behavioral Therapy Program at the Massachusetts General Hospital. The follow-up study was supported by a Harvard University Catalyst Award, which draws its funding from the National Institutes of Health (NIH 5UL1TR001102-03). The baseline study was carried out in the MGH Clinical and Research Program in Pediatric Psychopharmacology and was supported by the Tommy Fuss Fund, the Poitras Center for Psychiatric Disorders Research, and the MGH Pediatric Psychopharmacology Council Fund. The funding sources had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the article; or in the decision to submit the article for publication. Publisher Copyright: {\textcopyright} 2019, Mary Ann Liebert, Inc., publishers.",
year = "2019",
doi = "10.1089/brain.2018.0646",
language = "English (US)",
volume = "9",
pages = "388--398",
journal = "Brain connectivity",
issn = "2158-0014",
publisher = "Mary Ann Liebert Inc.",
number = "5",
}