# Genetic Prediction for Treatment Resistance in Kawasaki Disease

> **NIH NIH R01** · SEATTLE CHILDREN'S HOSPITAL · 2021 · $846,959

## Abstract

PROJECT SUMMARY/ABSTRACT
Kawasaki Disease (KD) is a major contributor to cardiovascular morbidity in children. Poor response to IVIG
remains one of the critical determinants of coronary artery risk in KD. The inability to predict this response
and the potential for developing persistent coronary artery aneurysms serves as a major impediment to
progress and development of intensified therapy. Currently available data indicate that KD susceptibility and
treatment response, as well as the propensity for coronary artery disease, depend on an individual patient's
genetic background. Studies directed at identifying appropriate genetic biomarkers have been impaired by: 1)
phenotyping lacking rigor, 2) use of genome wide association studies often employing chips or arrays for
detection of common variants rather than low frequency or rare variants, 3) lack of clarity for the mechanisms
of IVIG anti-inflammation in KD (necessary for guiding most pharmacogenomics studies) 4) focus on gene
candidates, which are impractical for clinical testing, and 5) vague racial assignment methodology
confounding pharmacogenomics. Furthermore, exome sequencing and analyses likely would miss potential
important variants as IVIG anti-inflammatory mechanism includes transcriptional regulation at intergenic
regions. We hypothesize that, by using improved and rigorous phenotyping techniques in combination with
whole genome sequencing (WGS) and analyses, we will be able to identify select biomarkers for accurate
prediction of KD treatment response and development of coronary aneurysms. The Pacific Northwest
Kawasaki Disease Data-Biobank, established mainly through funding via PI Portman, R21HL090558,
Thrasher Research Foundation; and PI, Shrestha, Southeastern AHA has accumulated DNA and clinical
data from over 800 KD patients, eligible for pharmacogenomics analyses. We will leverage this wealth of
DNA and clinical data along with recently updated AHA clinical KD criteria in order to identify rare and
common variants, which determine IVIG treatment response. WGS will also allow a) identification of
individual private SNPs (rare variants), b) identification of population-specific private SNPs, c) building a
complete picture of genetic variations including structural variants (CNVs and insertion/deletions), d) gene-
based analysis of both common and rare variants, and e) identification of actual functional SNPs as opposed
to common imputed or SNPs in linkage disequilibrium (LD). Additionally, we will account for race, an
important variant in KD, by rigorous racial assignment using ancestry information markers and principal
component analyses. We will use rigorous methodology to achieve the following specific aims 1) Perform
whole genome sequencing to identify genetic variations, which could serve as clinical biomarkers for IVIG
resistance in KD patients. 2) Determine novel genomic variants associated with giant coronary artery
aneurysms (GCA) among children with KD. 3) Prepare to ...

## Key facts

- **NIH application ID:** 10065014
- **Project number:** 5R01HL146130-03
- **Recipient organization:** SEATTLE CHILDREN'S HOSPITAL
- **Principal Investigator:** Michael A Portman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $846,959
- **Award type:** 5
- **Project period:** 2018-12-15 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10065014

## Citation

> US National Institutes of Health, RePORTER application 10065014, Genetic Prediction for Treatment Resistance in Kawasaki Disease (5R01HL146130-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10065014. Licensed CC0.

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