Introduction: Animal models of human diseases are used extensively to interrogate molecular mechanisms in a reductionist fashion. We tested whether aggregation and integration of preclinical data can identify new causative pathways that faithfully model human disease mechanisms. We have termed this novel technique, the Preclinical Science Integration and Translation (PRESCIANT) method. Methods and Results: Data were extracted from 716 manuscripts in the journal Arteriosclerosis, Thrombosis, and Vascular Biology from 1995-2019 using the apolipoprotein E knockout mouse (ApoE-KO) to study atherosclerosis. We identified 360 unique studies in which genes were experimentally perturbed in ApoE-KO mice to impact atherosclerotic plaque size and/or composition. Impacts of the interventions on plaque size, inflammation, and lipid content were analyzed using Ingenuity Pathway Analysis. The top upstream regulatory network (sc-58125, a COX2 inhibitor) linked 37.2% (134) of the genes implicated in atherosclerosis into a single network. Further, Ingenuity Pathway Analysis identified TREM1 signaling, LXR/RXR activation, and renin-angiotensin signaling as the top 3 pathways associated with changes in atherosclerosis parameters. Specifically, early atherogenesis genes were enriched with pathways associated with inflammatory cell migration and infiltration (including TREM1) whereas late atherosclerosis genes were associated with cell metabolism and survival (including LXR/RXR activation). These two pathways were interrogated in a clinical cohort of 88,660 patients by testing for association between genetically predicted expression of the human homologs of mouse pathway genes and a composite phenotype composed of 27 human atherosclerosis diagnoses. There was a significant enrichment (p<0.01 for both pathways) in the number of human homologs associated with atherosclerosis, including 12 (57.2%) genes in the TREM1 pathway and 15 (53.6%) in the LXR/RXR pathway. Conclusion: PRESCIANT can successfully leverage decades of animal investigations to translate results from large-volume singular preclinical studies to make novel causal inferences into human disease.