# Circulating causal protein networks linked to future risk of myocardial infarction

## TL;DR

This study identifies causal protein networks in the blood that are linked to future heart attack risk and related conditions.

## Contribution

The paper introduces a causal network inference framework using large-scale serum proteomics data to uncover high-confidence protein subnetworks.

## Key findings

- 185 high-confidence causal serum protein subnetworks were identified, interacting with 5611 targets.
- Several subnetworks are significantly associated with cardiometabolic traits and future myocardial infarction risk.
- Some subnetworks form hierarchical frameworks of directional relationships and are linked to heart failure.

## Abstract

Variations in blood protein levels have been linked to numerous complex diseases, including cardiovascular conditions. These associations highlight the intricate interplay between local and systemic factors in cardiovascular disease development, emphasizing the need for a comprehensive, systems-level understanding of its etiology. To address this, we develop a causal network inference framework using data from one of the largest serum proteomics studies to date, comprising measurements of 7523 serum proteins in the prospective, population-based Age, Gene/Environment Susceptibility-Reykjavik Study (AGES) cohort of 5376 older adults. Using cis-acting protein quantitative trait loci (pQTLs) as instrumental variables within a causal inference framework designed to mitigate hidden confounding, we identify 185 high-confidence causal serum protein subnetworks collectively interacting with 5611 targets. Several subnetworks, many forming hierarchical frameworks of directional relationships, are significantly associated with multiple cardiometabolic traits and with future risk of myocardial infarction and its long-term complication, heart failure.

A broad systems-level approach is necessary to understand the intricate etiology of clinical complications from atherosclerotic cardiovascular disease. Here, the authors reconstruct a causal network of circulating proteins and identify subnetworks linked to future risk of myocardial infarction and other cardiometabolic traits.