# Identifying Genetic and Epigenetic Risk Factors Regulating Gene Expression for Childhood Asthma

> **NIH NIH K01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $139,018

## Abstract

Candidate: Dr. Soyeon Kim obtained her Ph.D. degree in Statistics at Rice University. For her doctoral
research, she developed statistical machine learning methods to identify biomarkers for precision medicine
approaches to treating lung cancer. She is currently a post-doctoral fellow at UPMC Children’s Hospital of
Pittsburgh (CHP) and supported by a T32 grant awarded to one of her mentors, Dr. Juan C. Celedón. The goal
of her research is to understand the pathogenesis of diseases by developing statistical methods for integrative
analysis of multi-omics data. She is an author and co-author of eight manuscripts, including ones in high-profile
journals such as Nature Genetics.
Environment: CHP, affiliated with the University of Pittsburgh, School of Medicine, is a leading pediatric center
for clinical care, research, and educational excellence. Dr. Kim works in the Rangos Research Center, comprised
of nine floors of state-of-the-art laboratories, offices, and conference facilities. In addition to superb mentoring
by Drs. Wei Chen, Juan C. Celedón and George Tseng, she will use the Pittsburgh supercomputing center (PSC),
an excellent source of computing powers for intensive bioinformatics work.
Research: Although both single-nucleotide polymorphisms (SNPs) and DNA methylation play important roles
in regulating gene expression, the associations between SNPs/DNA methylation and expression of disease
genes in childhood asthma are mostly unknown. Due to the multiple-testing problem, most studies focus on
identifying the regulation of gene expression by cis- (nearby) DNA features, rather than a combination of cis-
and trans (far from genes) regulation. To overcome the major multiple-testing problem, we will develop a novel
statistical machine learning method that can handle a large number of variables of omics data without multiple-
testing correction issues. In Aim 1, I will identify cis and trans genetic (SNPs) and epigenetic
(methylation) factors that regulate gene expression in the nasal epithelium of asthmatic and healthy
subjects. Through this analysis, I will uncover novel SNPs and methylation CpGs that may have not been
found in genome-wide association studies (GWAS) or epigenome-wide association studies (EWAS). In Aim 2,
I will estimate the genetic and epigenetic contributions to the expressions of genes that are associated
with atopic asthma. This study also will classify genes that are affected the most by genetic factors and
genes that are affected mostly by epigenetic factors, which include environmental factors. In Aim 3, I will
develop statistical methods to identify SNPs that indirectly regulate gene expression through
methylation in nasal epithelium of asthmatic and healthy subjects. The outcome of this work will be a
better understanding of the abnormal molecular and cellular mechanisms through which asthma develops, and
the application of this knowledge to help to produce new therapies for asthma.

## Key facts

- **NIH application ID:** 10831030
- **Project number:** 5K01HL153792-04
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Soyeon Kim
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $139,018
- **Award type:** 5
- **Project period:** 2020-08-05 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10831030

## Citation

> US National Institutes of Health, RePORTER application 10831030, Identifying Genetic and Epigenetic Risk Factors Regulating Gene Expression for Childhood Asthma (5K01HL153792-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10831030. Licensed CC0.

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