Identification of Transdiagnostic Childhood Externalizing Pathology Within an Electronic Medical Records Database and Application to the Analysis of Rare Copy Number Variation

India A Reddy; Lide Han; Sandra Sanchez-Roige; Maria Niarchou; Douglas M Ruderfer; Lea K Davis

doi:10.1002/ajmg.b.33020

Identification of Transdiagnostic Childhood Externalizing Pathology Within an Electronic Medical Records Database and Application to the Analysis of Rare Copy Number Variation

Am J Med Genet B Neuropsychiatr Genet. 2025 Jan 2:e33020. doi: 10.1002/ajmg.b.33020. Online ahead of print.

Authors

India A Reddy¹, Lide Han^{2

3

4}, Sandra Sanchez-Roige^{2

5

6}, Maria Niarchou^{2

3}, Douglas M Ruderfer^{1

2

3

4}, Lea K Davis^{1

2

3

4

7

8}

Affiliations

¹ Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
² Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
³ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
⁴ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
⁵ Department of Psychiatry, University of California San Diego, La Jolla, California, USA.
⁶ Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA.
⁷ Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA.
⁸ Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

PMID: 39744833
DOI: 10.1002/ajmg.b.33020

Abstract

Externalizing traits and behaviors are broadly defined by impairments in self-regulation and impulse control that typically begin in childhood and adolescence. Externalizing behaviors, traits, and symptoms span a range of traditional psychiatric diagnostic categories. In this study, we sought to generate an algorithm that could reliably identify transdiagnostic childhood-onset externalizing cases and controls within a university hospital electronic health record (EHR) database. Within the Vanderbilt University Medical Center (VUMC) EHR, our algorithm identified cases with a clinician-validated positive predictive value of 90% and controls with a negative predictive value of 88%. In individuals of genetically defined European ancestry (CEU-clustered; N_case = 487, N_control = 5638), case status was significantly associated with psychiatric comorbidity and with elevated externalizing polygenic scores (OR: 1.20; 95% CI: 1.09-1.33; p = 1.14 × 10^-3; based on published genome-wide association data). To test whether our cohort definitions could be applied to generate novel genetic insights, we examined rare (allele frequency < 0.5%) copy number variation. An association (OR: 9.70; CI: 3.24-29.0) was identified in the CEU-clustered cohort on chromosome 2 (chr2: 45,408,678-45,551,530; duplication), although the statistical strength of this association was modest (p = 0.052). We also examined the role of an externalizing burden score based on the number of externalizing diagnoses present in cases and found similar results to our case-control analysis. This analysis identified several other statistically significant CNV region associations. This study provides a framework for identifying childhood externalizing case-control cohorts within an EHR. Future work should validate this framework within other health systems. A broadly applicable algorithm, like this one, may allow for detection of rare outcomes or outcomes in populations historically excluded from genomic research through meta-analysis of data across health care systems.

Abstract

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