Evidence map›Paper›PMID 26676835›Full record

ArticleJAMA psychiatry2016

Early Childhood Depression and Alterations in the Trajectory of Gray Matter Maturation in Middle Childhood and Early Adolescence.

Joan L Luby, Andy C Belden, Joshua J Jackson, Christina N Lessov-Schlaggar, Michael P Harms, Rebecca Tillman, Kelly Botteron, Diana Whalen, Deanna M Barch

Open access · bronzeAbstract read
In one paragraph

Article in JAMA psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 100 citations in OpenAlex.

  1. Pooled it
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  5. Neural Correlates of Reward Processing in Depressed and Healthy Preschool-Age Children.Journal of the American Academy of Child and Adolescent Psychiatry · 2016
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  10. Associations of Child Amygdala Development With Borderline Personality Symptoms During Adolescence.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Joan L LubyDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Andy C BeldenDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Joshua J JacksonDepartment of Psychology, Washington University, St Louis, Missouri.
Christina N Lessov-SchlaggarDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Michael P HarmsDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Rebecca TillmanDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Kelly BotteronDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri3Department of Radiology, Washington University School of Medicine, St Louis, Missouri.
Diana WhalenDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri.
Deanna M BarchDepartment of Psychiatry, Washington University School of Medicine, St Louis, Missouri2Department of Psychology, Washington University, St Louis, Missouri3Department of Radiology, Washington University School of Medicine, St Louis, Missouri4The Program in.
Washington University in St. Louis · US

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
NEUROIMAGING IN EARLY ONSET DEPRESSION: LONGITUDINAL ASSESSMENT OF BRAIN CHANGESR01MH090786 · NIMH · WASHINGTON UNIVERSITY · PI GILBERT, KIRSTEN, WHALEN, DIANA J · 2010 to 2025
$10.4M
Cognitive Neurocomputational Task Reliability and Clinical Applications ConsortiumR01MH084840 · NIMH · WASHINGTON UNIVERSITY · PI Deanna Barch, Cameron S. Carter · 2008 to 2026
$8.5M
Validation of Preschool Depressive SyndromeR01MH064769 · NIMH · WASHINGTON UNIVERSITY · PI LUBY, JOAN L. · 2003 to 2012
$7.7M
Developmental Neuroscience and Child PsychopathologyT32MH100019 · NIMH · WASHINGTON UNIVERSITY · PI Deanna Barch, JOAN L. LUBY · 2013 to 2026
$4.8M
A RANDOMIZED CONTROLLED TRIAL OF PCIT-ED FOR PRESCHOOL DEPRESSIONR01MH098454 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA, LUBY, JOAN L. · 2013 to 2017
$4.6M
Schizophrenia, Prefrontal Cortex, and Emotion RegulationR01MH066031 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA · 2004 to 2014
$4.1M
Neurobehavioral Correlates of Emotion Regulation in Healthy & Depressed ChildrenK01MH090515 · NIMH · WASHINGTON UNIVERSITY · PI BELDEN, ANDY C · 2010 to 2013
$574k
NIMH NIH HHS 2R01 MH064769-06A1NIMH NIH HHS 5K01MH090515-04NIMH NIH HHS K01 MH090515NIMH NIH HHS R01 MH064769NIMH NIH HHS R01 MH066031NIMH NIH HHS R01 MH084840NIMH NIH HHS R01MH084840NIMH NIH HHS R01 MH090786NIMH NIH HHS R01MH090786NIMH NIH HHS R01 MH098454NIMH NIH HHS R01MH098454-SNIMH NIH HHS R01MH66031NIMH NIH HHS T32 MH100019NIMH NIH HHS U54 MH091657NIMH NIH HHS U54MH091657
6 · The paper itself

Abstract

importanceThe trajectory of cortical gray matter development in childhood has been characterized by early neurogenesis and volume increase, peaking at puberty followed by selective elimination and myelination, resulting in volume loss and thinning. This inverted U-shaped trajectory, as well as cortical thickness, has been associated with cognitive and emotional function. Synaptic pruning-based volume decline has been related to experience-dependent plasticity in animals. To date, there have been no data to inform whether and how childhood depression might be associated with this trajectory.

objectiveTo examine the effects of early childhood depression, from the preschool age to the school age period, on cortical gray matter development measured across 3 waves of neuroimaging from late school age to early adolescence. DESIGN, SETTING, AND

participantsData were collected in an academic research setting from September 22, 2003, to December 13, 2014, on 193 children aged 3 to 6 years from the St Louis, Missouri, metropolitan area who were observed for up to 11 years in a longitudinal behavioral and neuroimaging study of childhood depression. Multilevel modeling was applied to explore the association between the number of childhood depression symptoms and prior diagnosis of major depressive disorder and the trajectory of gray matter change across 3 scan waves. Data analysis was conducted from October 29, 2014, to September 28, 2015. MAIN OUTCOMES AND MEASURES: Volume, thickness, and surface area of cortical gray matter measured using structural magnetic resonance imaging at 3 scan waves.

resultsOf the 193 children, 90 had a diagnosis of major depressive disorder; 116 children had 3 full waves of neuroimaging scans. Findings demonstrated marked alterations in cortical gray matter volume loss (slope estimate, -0.93 cm³; 95% CI, -1.75 to -0.10 cm³ per scan wave) and thinning (slope estimate, -0.0044 mm; 95% CI, -0.0077 to -0.0012 mm per scan wave) associated with experiencing an episode of major depressive disorder before the first magnetic resonance imaging scan. In contrast, no significant associations were found between development of gray matter and family history of depression or experiences of traumatic or stressful life events during this period. CONCLUSIONS AND RELEVANCE: This study demonstrates an association between early childhood depression and the trajectory of cortical gray matter development in late school age and early adolescence. These findings underscore the significance of early childhood depression on alterations in neural development.

Indexed as

AdolescentCerebral CortexChildChild, PreschoolDepressive DisorderFemaleGray MatterHumansLongitudinal StudiesMagnetic Resonance ImagingMajor Depressive DisorderMaleOrgan SizeProspective Studies

Identifiers

PMID26676835
PMCPMC5206762
OpenAlexW2213415910

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.