Multi-Omics Data Integration for Understanding the Biology of VWD

Washington University, Saint Louis MO

Investigators

Abstract

Project Summary – ESI Project 2 Low von Willebrand Factor (VWF) and Type 1 von Willebrand Disease (VWD) are complex, polygenic pathological bleeding phenotypes with genetic, cellular, pathologic, and clinical heterogeneity. There is a need for novel, unbiased approaches to identify and describe the pathways that lead to low-VWF and Type 1 VWD, and to determine how those pathways interact with one another, as well as the role of aging on bleeding risk in these patients. An integrative biology approach, including clinical and molecular data, will be able to identify disrupted pathways. The identification of those pathways and networks will help to uncover novel, high-value therapeutic targets for the management of low-VWF, Type 1 VWD and related bleeding disorders. Here, in Aim 1, we will use high-throughput multi-omic technologies on multiple tissues/cell types (plasma, ECFCs, platelet RNA), including on hundreds of patients with multiple time points, to generate a detailed molecular landscape of low-VWF/Type 1 VWD. We will then leverage this large genomic, transcriptomic, proteomic, and other -omic data to identify molecular signatures of low-VWF/Type 1 VWD and age-related changes in VWF levels, which will lead to novel insights into pathways associated with disease etiology. In Aim 2, we will use multi-omic QTL and Mendelian randomization to resolve additional GWAS loci and identify novel causal genes, proteins and analytes associated with VWF levels and other related clinical phenotypes. These findings will reveal essential disease mechanisms (e.g. glycosphingolipid biosynthesis, intracellular signaling/inflammation, or angiogenesis, among others), uncover the effects of aging on bleeding risk, as well as aid the identification of novel biomarkers and drug targets. The goals of this proposal are to 1) Identify molecular signatures and new prediction models for low-VWF and Type 1 VWD cases 2) Resolve additional GWAS loci by using multi-omic QTL and Mendelian randomization and create a multi-omics plasma QTL atlas, and 3) Elucidate the underlying mechanisms of age- related increases in VWF levels. Bleeding disorders are an excellent candidate for a large-scale genomics approach. Characterizing multiple -omic layers in several tissues/cell types for low-VWF and Type 1 VWD cases will help to deconvolute the mechanistic complexity of the disease.