Comprehensive multiomic analysis of the basis for cardiovascular risk in rheumatic disease

People with rheumatic diseases often face a higher risk of heart problems, but this risk can differ depending on the specific condition. For example, people with lupus are more likely to have inflammation around their heart, and those with rheumatoid arthritis are at higher risk of developing heart failure. We do not yet fully understand why different rheumatic diseases lead to different heart-related issues. Understanding more about the biology of these problems could lead to new opportunities to develop better treatments for them. Our recent preliminary work has identified several genes that might help explain these differences, but there is more work to be done.

This project extends our analysis to different molecules, like proteins and metabolites, involved in these heart-related problems. Using some of the largest data sets available, we will study how these molecules change in people with different rheumatic diseases who develop heart issues. Furthermore, we will build on our initial genetic analyses by conducting experiments to find out exactly how these genes might be causing problems in these patients.

This research has several important benefits. First, medications often target proteins or small molecules in the body, so understanding which molecules are involved in heart problems for rheumatology patients is an important first step for developing new treatments. Second, once we know which molecules are affected, we can then create tests to help doctors identify patients who are at higher risk of problems so that they can intervene sooner. Third, the genetic studies will fill in a key part of the story that we are currently missing: how the genes we identified are linked to heart problems in rheumatology patients.

Motivation. Across rheumatic diseases, one of the greatest risks patients face is cardiovascular disease (CVD). The specific kind of CVD varies by rheumatic disease, indicating different biological causes, but our understanding is limited. Our long-term goal is to develop better CVD risk prediction tools and therapeutics, but a more detailed molecular roadmap is needed first. Based on our recent genetic analysis, our hypothesis is that antigen-processing and inflammation-related pathways will be among those driving CVD risk in rheumatic disease.

Specific aims. Our global objective is to identify the molecular mediators of CVD across rheumatic conditions by using a dual bioinformatic-experimental approach, combining the power and depth of the largest multiomic population cohorts with the robustness of cell/tissue functional assays to experimentally validate implicated pathways. On the bioinformatics side, we will conduct a comprehensive mediation and causal inference analysis to identify shared and disease-specific risk pathways for 8 CVDs among 8 major rheumatic diseases, using both proteomics (Aim 1) and metabolomics (Aim 2) data. On the experimental side (Aim 3), we will use single-cell genomics assays and gene knockdown experiments in heart and coronary tissue to validate the strongest signals from our recent genetic analysis, which implicated several genes for CVD risk in rheumatoid arthritis.

Expected results. The result of this proposal will be a prioritized list of biological pathways and molecules mediating elevated CVD risk for different rheumatic diseases, with experimental validation of target genes in rheumatoid arthritis. These findings will be the springboard for several follow-up projects that will develop novel risk prediction and therapeutic tools for use in the clinic. Finally, this proposal would provide critical support for the PI in establishing independence as an early career investigator.