# Project 5: Computational Genomics of Preeclampsia

> **NIH NIH P20** · BROWN UNIVERSITY · 2020 · $244,811

## Abstract

Project Summary/Abstract: In the post genome era, biological research and genomic medicine have been 
transformed by high-throughput technologies. New techniques have enabled researchers to investigate 
biological systems in great detail. Nonetheless, the extraordinary amount of information in the large number of 
emerging high-dimension datasets has not been fully exploited. Increasingly, pathway analysis and other a 
priori biological knowledge based approaches have improved success in extraction of valuable information 
from high-throughput experiments and genome-wide association studies. Preeclampsia is a complex disease 
and one of the most common causes of fetal and maternal morbidity and mortality worldwide. It is one of the 
great but enigmatic health problems. Despite many studies, there has been little fundamental improvement in 
our understanding in decades. It is a multi-system hypertensive disorder of pregnancy, characterized by 
variable degrees of maternal symptoms including elevated blood pressure, proteinuria and fetal growth 
retardation that affects 2-8 % of deliveries in the US. Many clinicians believe there is a difference between mild 
and severe or early and late preeclampsia. However, to date there is little direct evidence that they represent 
different genetic ideologies. We hypothesize that preeclampsia is a complex, polygenic disorder that entails 
activation of a network of genes. We further hypothesize that rare variants in the genes that contribute to the 
risk of preeclampsia can be identified using new bioinformatic approaches coupled with high-throughput 
technologies applied to appropriate cohorts of patients. We propose novel computational approaches to 
identify relevant genes and high-throughput technologies on appropriately selected patients that will help to 
identify the genetic architecture of this a multifactorial, polygenic disease.

## Key facts

- **NIH application ID:** 9882539
- **Project number:** 5P20GM109035-05
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Alper Uzun
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $244,811
- **Award type:** 5
- **Project period:** 2020-03-01 → 2021-08-03

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9882539

## Citation

> US National Institutes of Health, RePORTER application 9882539, Project 5: Computational Genomics of Preeclampsia (5P20GM109035-05). Retrieved via AI Analytics 2026-09-03 from https://api.ai-analytics.org/grant/nih/9882539. Licensed CC0.

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