ArticleNature communications2025
Circulating causal protein networks linked to future risk of myocardial infarction.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Circulating causal protein networks linked to future risk of myocardial infarction.Nature communications · 2025Article
- Systematic comparison of observational and Mendelian Randomization estimates for cardiometabolic proteomic signatures.medRxiv : the preprint server for health sciences · 2025Article
- Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson's disease and overlap with other neurodegenerative disorders.medRxiv : the preprint server for health sciences · 2025Article
- Mechanistic Insights into Tumorigenesis from Serum Proteins.medRxiv : the preprint server for health sciences · 2025Article
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17 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.