Prevalence of Comorbid Phenotypic Features in Genetic Epilepsies
Abstract number :
3.094
Submission category :
12. Genetics / 12A. Human Studies
Year :
2025
Submission ID :
658
Source :
www.aesnet.org
Presentation date :
12/8/2025 12:00:00 AM
Published date :
Authors :
Presenting Author: Chloe Hooker, BS – Children's National Hospital
Julie Ziobro, MD, PhD – Michigan Medicine
Nadee Dayananda, BS – Oregon Health Sciences University
Kristina Julich, MD – Dell Medical School
Gozde Erdemir, MD – Penn State Health, Penn State College of Medicine. Department of Pediatrics. Hershey, Pennsylvania.
Chethan Rao, DO, MS – University of Maryland School of Medicine
Senyene Hunter, MD, PhD – University of North Carolina - Chapel Hill
Puck Reeders, PhD – Nicklaus Children's Hospital
Khloe Fleming, n/a – Children's National Hospital
Rachel Weaver, MS – Children's National Hospital
Susan Fong, MD, PhD – Cincinnati Children's Hospital Medical Center
Suad Khalil, MD – Michigan State University
Brittany Sprigg, MD – University of Iowa Health Care
Sonal Bhatia, MD – Medical University of South Carolina
Jason Coryell, MD – Oregon Health Sciences University
John Schreiber, M.D. – Children's National Hospital, Washington D.C.
Rationale: Complex comorbidities across the are common amongst patients with rare diagnoses of epilepsy. However, the standard for multidisciplinary care for these patients remains imprecise. This project aims to understand comorbidities for patients with rare epilepsy diagnoses to better inform clinical care across multidisciplinary teams.
Methods: 371 participants with Human Phenotype Ontology (HPO) base terms in the Pediatric Epilepsy Research Consortium (PERC) Genetics Registry were sorted into groups based on which gene is etiologically related to their epilepsy. Patients variant were categorized as “Unknown”. Base HPO terms for each participant were propagated to the broadest category of phenotypic abnormality. Frequencies of comorbidities 4 or more levels down in the HPO tree were evaluated.
Results: Nervous system comorbidities were the most common in the sample, with abnormality of mental function (n= 209, 56.3%) expressed in over half of the sample. At lower/more specific levels, the proportion of participants with diagnostic behavioral phenotypes (including autistic behavior and autism) differed across genetic groupings (Chi Square, 15.9, p = .02), with the SCN1A group exhibiting increased frequency of diagnostic behavioral phenotypes (standardized residuals = 3.536). Differences in proportion across genetic groups were also seen amongst the most common non-nervous system comorbidities including abnormalities of muscle tone (Chi Square, 15.6, p = .05) and physiology (Chi Square, 15.5, p = .05), abnormalities of skeletal morphology (Chi Square, 18.5, p = .02), and strabismus (Chi Square, 16.9, p = .03).
Conclusions: There is an overall trend of brain function impact with cascading effects expressed in socio-communicative behavior and brain-to-body communication. Differences in proportions of diagnostic behavioral phenotypes and non-behavioral phenotypes across genetic groups indicate the need for specialized, multidisciplinary care. Understanding and predicting these comorbidities will allow a streamlined use of informed referrals, interventions, and increased surveillance.
Funding: Pediatric Epilepsy Research Foundation Grant
Genetics