Multiancestral Genomic Approach to SLE Precision Medicine
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease in which the immune system mistakenly attacks an individual’s own cells, causing inflammation and organ damage. Those diagnosed with SLE have higher risk of renal disease, cardiovascular disease, stroke, breast and cervical cancer, and premature death. Clinical variation (e.g., severity and symptoms) in SLE has been observed for decades, and there are sex and ethnic differences in the prevalence, severity, pattern of organ involvement, progression to renal failure, and age of onset. Over 90% of SLE cases are female; and African American (AA) women are four times more likely than European American (EA) women to have SLE. While several factors contribute to SLE (e.g., environmental exposures), genetics play an important role, as inherited DNA variations (“genetic variants”) are strongly correlated with SLE risk. Many of these variants likely influence risk through altering gene (functional unit of DNA) activity, such as protein production. There are more than 110 genetic variants that increase risk of SLE. Notably, the clinical differences (or heterogeneity) of SLE is mirrored in SLE genetics, where the specific subsets of SLE risk variants can vary from person to person. Furthermore, some SLE risk variants are consistently found across ancestries (ancestry-shared), while others tend to be observed in specific ancestries (ancestry-specific). Given the extensive clinical and genetic heterogeneity, it is not surprising that the “one size fits all” approach to drug discovery does not work for SLE. In the past 60 years, only one new drug for SLE (belimumab) has been Food and Drug Administration-approved, and current evidence shows it is only modestly effective and particularly ineffectual in AA. SLE drug discovery requires a precision medicine pipeline, where drugs are evaluated based on an individual’s clinical features and genetic markers. We propose a new analytic approach that uses genetic diversity to identify drugs novel to SLE treatment. Aim 1: Connect existing SLE risk variants to biologically relevant genes in women. Over two decades of genome-wide association data will be analyzed for statistically robust SLE associations in thousands of women of African, Asian, European, and Hispanic ancestries. We will examine SLE epigenetic studies, which track genetic changes that are often mediated by environmental factors. Through bioinformatic analyses, we will link genetic variants to the genes they are most likely to influence, generating a list of SLE-relevant genes. Aim 2: For genes identified in Aim 1, pathway analyses will identify a comprehensive list of potential drug targets. Genes do not act in isolation and instead, work with other genes (forming networks) for specific biological functions. Identifying connections among genes (pathway analysis) is an important step in identifying novel therapies because it increases the number of relevant drug targets. That is, if a gene identified by SLE associations is not targetable, another (non-SLE risk) gene within the same network could provide an alternative drug target to correct irregular biological processes. Aim 3: Bioinformatics tools and molecular docking strategies will identify Food and Drug Administration-approved molecules that may be effective in the treatment of SLE. Advancements in large-scale drug interaction resources provide opportunities to identify drugs for genetically informed targets. Using a novel high-throughput molecular docking application, we can efficiently test thousands of FDA-approved molecules for binding to SLE drug targets. The proposed research specifically addresses several of the Fiscal Year 2019 Lupus Research Program (LRP) Focus Areas. Through comprehensive analysis and integration of genetic data, we will study how lupus disease heterogeneity impacts risk of disease. Identification of novel drugs through genetically motivated biological pathways contributes toward imp
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010686
Entities
People
- Carl Langefeld
Organizations
- United States Army
- Wake Forest University