Evidence map›Paper›PMID 41713208›Full record

ArticleDevelopmental cognitive neuroscience2026

Effects of genetic risk for depression and household socioeconomic status on emotional behavior and brain development in early adolescence.

Claire E Campbell, Jessica Morrel, W James Gauderman, Megan M Herting

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Article in Developmental cognitive neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Claire E CampbellDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089-2520, USA.
Jessica MorrelDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089-2520, USA.
W James GaudermanDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
Megan M HertingDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.

Funding

Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David V Conti · 2016 to 2026
$25.5M
NCI NIH HHS P01 CA196569
6 · The paper itself

Abstract

backgroundThe World Health Organization ranks depression as the leading non-fatal contributor to the global burden of disease. Research shows that early intervention before clinical onset leads to better outcomes. To study depression at this pre-onset stage, risk can be evaluated through depressive prodromal behaviors and associated brain biomarkers. Both environmental and genetic factors independently contribute to depression vulnerability, yet little work has examined how they interact. We therefore examined whether the socioeconomic status (SES) predictor of family income-to-needs ratio (INR) has independent and/or interactive effects with a depression polygenic risk score (D-PRS) on youth behavior and brain structure and function.

methodsWe leveraged the longitudinal ABCD Study®; this work examined 8442 subjects (53% male), 9-10 years-of-age at baseline to 11-12 years-of-age at 2-year follow-up. The prior genetic analysis was conducted in a European-like sample. Therefore, our work first assessed effects in youth with European-like genetic ancestry. Next, to improve generalizability, the same analyses were conducted in not European-like youths.

resultsD-PRS was associated with behavior and brain within the European-like youths, with less effect in the not European-like sample. There were moderating effects of INR, with lower INR associating with a lower slope.

conclusionsOur findings suggest brain-behavior biomarkers associated with SES and D-PRS vary by genetic ancestry; this difference between ancestry groups is likely caused by systemic differences in SES distributions and varying D-PRS predictability from genetic research homogeneity. These outcomes further highlight the importance of equitable and inclusive precision-based research to improve depression early detection and treatment.

Indexed as

BrainDepressionEmotionsSocial ClassAdolescentChildFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansLongitudinal StudiesMagnetic Resonance ImagingMaleSocioeconomic Disparities in HealthAdolescent Brain DevelopmentDepressionEmotional BehaviorMagnetic Resonance Imaging (MRI)Polygenic Risk Score (PRS)Socioeconomic Status

Identifiers

PMID41713208
PMCPMC12933472

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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.