# Joint analysis of genomic and electronic medical record data to assess outcomes and drug response in pediatric epilepsies

> **NIH NIH K02** · CHILDREN'S HOSP OF PHILADELPHIA · 2024 · $195,582

## Abstract

PROJECT SUMMARY
Up to 40% of children with epilepsy do not respond to available antiepileptic drugs (AEDs), and identifying genes
for outcome and AED response will provide critical insight into underlying pathways. Genotyping can readily be
performed on tens of thousands of patients, but phenotyping remains a largely manual task. Electronic medical
records (EMR) have been implemented over the last two decades. This readily available data source has enabled
large studies linking EMR and biorepositories to identify novel disease genes. However, EMR data have not
been used in epilepsy genetic studies so far. The long-term goal is to better understand how genetic changes in
childhood epilepsies predict specific phenotypes, medication responses, and outcomes. The overall objective of
this study is to detect genetic risk factors by utilizing EMR data to identify new biological mechanisms. The central
hypothesis is that while the complexity of the age-related clinical patterns of the childhood epilepsies creates a
major obstacle in generating universally applicable phenotyping algorithms, alternative methods leveraging the
similarity of the clinical disease course and medication trajectory can be used to identify causative genetic
variants associated with outcome and AED response. The rationale of this study is that understanding the genetic
contribution for outcome and AED response will translate into personalized medication choices, early
identification of patients at risk for a more severe outcome, and elucidation of novel biological pathways for
therapy development. The central hypothesis will be tested by pursuing two specific aims. As a first aim, this
study will determine genetic factors associated with a similar longitudinal disease course. Preliminary data
demonstrates that applying computational methods to determine the similarity of phenotypes enable the
identification of novel genetic etiologies. This study will analyze EMR-derived longitudinal phenotypes in 2,500
individuals with available genetic data and identify genetic etiologies with related disease trajectories. As a
second aim, this study aims to identify genetic factors that influence AED trajectories. AED response is not easily
extracted from EMR datasets. However, longitudinal AED histories between patients can be compared, which
may indicate biologically determined shared response patterns. This study will test whether patients with rare
variants in shared genes have longitudinal AED trajectories that are more similar than expected by chance,
highlighting empirical treatment patterns that may indicate gene-specific AED responses. This approach is
innovative, as it leverages EMR as a ubiquitous, easily accessible, but previously unexamined data source in
order to identify novel genetic risk factors in childhood epilepsies. The proposed research is significant as it is
expected to expand understanding of genetic risk factors for outcome and AED response, which was previously
not po...

## Key facts

- **NIH application ID:** 10783754
- **Project number:** 5K02NS112600-05
- **Recipient organization:** CHILDREN'S HOSP OF PHILADELPHIA
- **Principal Investigator:** Ingo Helbig
- **Activity code:** K02 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $195,582
- **Award type:** 5
- **Project period:** 2020-03-01 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10783754

## Citation

> US National Institutes of Health, RePORTER application 10783754, Joint analysis of genomic and electronic medical record data to assess outcomes and drug response in pediatric epilepsies (5K02NS112600-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10783754. Licensed CC0.

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