# Identification of novel drug targets through integrative PWAS of brain and plasma proteins with Ulcerative Colitis GWAS

## TL;DR

This study combines genetic and protein data to find new drug targets for ulcerative colitis by identifying genes and proteins linked to the disease.

## Contribution

The novel contribution is the integration of brain and plasma proteomic data with UC GWAS to identify new risk genes and their causal roles.

## Key findings

- Multiple UC-associated genes, including TYK2, STAT3, and NARS2, were identified in brain and plasma proteomes.
- PPI networks revealed strong interactions among key proteins like TYK2, STAT3, and IL23R.
- Causal analysis identified 11 risk genes, including FCGR2A, linked to immune regulation and inflammation in UC.

## Abstract

Previous genome-wide association studies (GWAS) have identified various risk variants for ulcerative colitis (UC), but there is a lack of evidence showing how these variants contribute to the development of UC. We employed an integrated pipeline to effectively translate genetic associations in order to identify pathogenic genes for UC.By combining GWAS data for UC with proteomic data from the human brain and plasma, we conducted a protein-wide association study (PWAS) and utilized protein-protein interaction (PPI) network analysis to screen for potential key proteins. Subsequently, causal analysis was performed to assess the potential causal relationships between these proteins and the risk of developing UC.Multiple genes associated with UC were identified in the human brain and plasma proteomes, including known genes such as TYK2 and STAT3, as well as newly discovered genes such as NARS2. PPI networks revealed strong interactions among proteins, including TYK2, STAT3, and IL23R. Causal analysis indicated that 11 risk genes, including FCGR2A, showed significant causal associations with UC, and were linked to key processes related to immune regulation and inflammatory responses, suggesting their potential roles in the pathogenesis of UC.This study integrated GWAS and PWAS data to identify risk genes associated with UC, providing new insights into the disease’s pathogenesis and potential therapeutic targets.