Matthew T. Weirauch, Ph.D.

Children's Hospital Medical Center - Research Foundation, Cincinnati, OH

2016 DNA, Genetics

Researchers to harness the power of Big Data, creating an innovative, free website to define the genetic links to lupus

The study and what it means to patients

“By bringing together all of the available data on genes and lupus, our novel website will provide scientists worldwide with a powerful, new tool to research the links between genetics and lupus. This resource will contribute significantly to our collective understanding of how genetics plays a role in the disease and lay the foundation for the development of new therapies.”

Summary

By consolidating all of the available data-sets on genes and lupus onto one free website, we will provide a vital, free tool that will enable investigators to advance our understanding of how genetics influences lupus onset and progression.

Our unique initiative will create an interactive website that enables researchers to develop and test their hypothesis regarding the connections between genes and lupus using the website’s sophisticated analysis capabilities.

Technical Summary

Despite incredible advances in sequencing and genotyping, we lack effective tools for leveraging the resulting data to identify causal non-coding lupus-associated genetic variants and their mechanistic modes of action. The vast majority of lupus-associated variants are non-coding, and we currently lack a comprehensive system for effectively predicting their functional impact. The goal of this proposal is to create a computational system that will combine lupus-relevant data in a single framework for identifying and prioritizing lupus-associated variants, based on their likelihood of impacting the binding of specific regulatory molecules such as transcription factors, RNA binding proteins, and micro RNAs. We will populate this system with publically available lupus-relevant datasets, and enhance it with data from ChIP-seq experiments for transcription factors likely to play key roles in lupus, which we will perform in lupus patient-derived cell lines. We will create a freely-available, user-friendly web server that will provide sophisticated analysis capabilities to the entire lupus research community. The proposed work is significant because it will enable any lupus researcher to form testable hypotheses for understanding the function of non-coding lupus-associated genetic variants. This resource will produce knowledge that will form a foundation for lupus diagnosis and the development of therapies.