Post-transcriptional regulatory networks in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease is a leading cause of death worldwide, yet the molecular basis of the disease is still unclear. While recent large-scale transcriptomic studies have identified many genes whose RNA levels are altered between COPD cases and controls, there has been comparatively little investigation in COPD into the post-transcriptional changes in RNAs, which can critically affect protein abundance and function. Post-transcriptional regulation of RNA is controlled by RNA binding proteins (RBPs), which regulate their target RNA isoforms in a context-specific manner, and disruptions to the complex network formed by RBPs and their target RNA isoforms can negatively impact cellular function. Work by our group and others has shown that multiple RBPs, including IRP2, QKI, and TTP, influence COPD phenotypes. In a recent transcriptomic analysis of COPD lung tissue, we found over 180 RBPs that are differentially expressed, suggesting widespread dysregulation of the RBP regulatory network in COPD. The long-term goal of this project is to generate RBP regulatory networks, identify COPD-specific changes, and characterize the functional consequences of the network changes. We will build on our previous work inferring regulatory networks from multi-omic data in disease cohorts and perturbation experiments. In Aim 1, we will develop a method to identify RBP-to-isoform regulatory networks by integrating RBP binding assays with isoform co-expression data from lung (N = 1,078) COPD transcriptomics studies. Using this method, we will infer COPD case and control networks and identify COPD-specific network nodes, edges, and communities (clusters). In Aim 2, we will functionally characterize COPD-associated RBP subnetworks by knocking down COPD-associated RBPs and determining RBP-RNA interactions to identify RBP functional isoform targets and refine our network inference method in Aim 1 based on these findings. In Aim 3, we will use long-read sequencing to characterize known and novel transcript isoforms from 60 COPD lung samples. Using a state-of-the-art proteo-genomics pipeline, we will predict protein-level consequences of COPD-associated RBP network changes and differential isoform expression. We will confirm these changes in existing mass spectrometry lung proteomics data from the same study subjects. Our team of network and RBP biologists, along with experts in COPD and long-read sequencing has the necessary expertise to identify COPD-specific RBP regulatory changes and characterize their functional effects. Project Number: 1R01HL176576-01 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: John Platig | Institution: UNIVERSITY OF VIRGINIA, CHARLOTTESVILLE, VA | Award Amount: $708,063 | Activity Code: R01 | Study Section: Genetics of Health and Disease Study Section[GHD] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HL17657601