Circulating causal protein networks linked to future risk of myocardial infarction

Variations in blood protein levels have been associated with a broad spectrum of complex diseases, including atherosclerotic cardiovascular disease (ACVD). These associations highlight the intricate interplay between local (e.g., cardiovascular) and systemic (non-cardiovascular) factors for the development of ACVD, emphasizing the need for a comprehensive, systems-level understanding of its etiology. To accomplish this, we developed a causal network inference framework by analyzing one of the largest serum proteomics studies to date, the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES), a prospective population-based study of 7,523 serum proteins measured in 5,376 older adults. To reconstruct a causal network of serum proteins, we used cis-acting protein quantitative trait loci (pQTLs) as instrumental variables to infer causal relationships between protein pairs, while accounting for potential unobserved confounding factors. We identified 185 causal protein subnetworks (FDR = 1%, n [≥] 10 members), which collectively interacted with 5,611 target proteins, offering valuable biological insights and an overview of systemic homeostasis. Several subnetworks, many of which interact to establish a hierarchy of directional relationships, were significantly associated with future myocardial infarction and/or its long-term complications like heart failure, as well as with key cardiometabolic traits that contribute to the onset of ACVD.