ABSTRACT Chest pain, the main symptom of acute myocardial infarction (AMI), accounts for ~5% of all emergency department (ED) visits. In the absence of ECG abnormalities, diagnostic gold standard for AMI relies on serial troponin (cTn) measurements which are inconclusive in 20-40% of patients, requiring additional testing and prolonged observation in the ED. A missed diagnosis of AMI without proper treatment is life threatening and thus rule-out diagnosis requires very high sensitivity. Hence, a rapid point of care (POC) test utilized as an adjunct to cTn with enhanced diagnostic performance would be revolutionary for risk stratification and timely and safe triaging of patients with suspected MI in ED. Inflammatix is a molecular diagnostics company focused on developing and bringing to market best in class, immune response based, data-driven testing. We developed a point-of-care instrument, MyRNA™, capable of quantitating up to 64 mRNAs in under 30 minutes (with <2 minutes operator time), directly from patients’ blood, in a fully disposable cartridge. We specialize in use of state-of-art multi-cohort analysis and machine learning (ML) to identify and validate robust biomarkers that generalize across real-world data heterogeneity, in diverse clinical contexts. Previous work demonstrated the potential of blood gene expression as a biomarker for MI, however a clinical test based on immune response in blood gene expression is yet to be developed. We applied our analytical framework to 6 publicly available datasets and identified a multi-gene AMI signature in peripheral blood that allows us to differentiate patients with AMI from clinically relevant controls with AUC ~ 0.95. In this project, we propose to take the AMI signature from preliminary results through research and initial development stages, up to formal clinical diagnostic development. We will generate a significant amount of independent data, leverage Inflammatix ML capabilities to further refine the mRNA signature and deliver a robust classifier ready for validation in prospective studies. In Specific Aim 1, we will generate, process, and analyze RNA-seq data for 900 blood samples from retrospective cohorts closely representing the target test population. In Specific Aim 2, we will first refine, optimize, and validate the mRNA signature; and then develop a prototype ML classifier. Specifically, we will 1) integrate expression data from all cohorts while minimizing bias; 2) apply Bayesian multi-cohort framework for final gene set selection with 300 new samples; 3) develop and evaluate discriminatory performance of AMI classifier prototype; and 4) validate the AMI classifier prototype on 600 unseen samples. These steps will produce: i) a validated set of genes for AMI; ii) an integrated dataset; and iii) a classifier prototype (AUC > 0.90), ready for clinical validation via prospective studies in Phase 2 research. This test, when developed as a cartridge on Inflammatix’s POC instrument, MyRN...