Systems Approach to Integrating Preclinical Apolipoprotein E-Knockout Investigations Reveals Novel Etiologic Pathways and Master Atherosclerosis Network in Humans
Objective: Animal models of atherosclerosis are used extensively to interrogate molecular mechanisms in serial fashion. We tested whether a novel systems biology approach to integration of preclinical data identifies novel pathways and regulators in human disease. Approach and Results: Of 716 articles published in ATVB from 1995 to 2019 using the apolipoprotein E knockout mouse to study atherosclerosis, data were extracted from 360 unique studies in which a gene was experimentally perturbed to impact plaque size or composition and analyzed using Ingenuity Pathway Analysis software. TREM1 (triggering receptor expressed on myeloid cells) signaling and liver×receptor/retinoid×receptor activation were identified as the top atherosclerosis-associated pathways in mice (both P <1.93×10 − 4 , TREM1 implicated early and liver×receptor/retinoid×receptor in late atherogenesis). The top upstream regulatory network in mice (sc-58125, a COX2 inhibitor) linked 64.0% of the genes into a single network. The pathways and networks identified in mice were interrogated by testing for associations between the genetically predicted gene expression of each mouse pathway-identified human homolog with clinical atherosclerosis in a cohort of 88 660 human subjects. Homologous human pathways and networks were significantly enriched for gene-atherosclerosis associations (empirical P <0.01 for TREM1 and liver×receptor/retinoid×receptor pathways and COX2 network). This included 12(60.0%) TREM1 pathway genes, 15(53.6%) liver×receptor/retinoid×receptor pathway genes, and 67(49.3%) COX2 network genes. Mouse analyses predicted, and human study validated, the strong association of COX2 expression ( PTGS2 ) with increased likelihood of atherosclerosis (odds ratio, 1.68 per SD of genetically predicted gene expression; P =1.07×10 − 6 ). Conclusions: Preclinical Science Integration and Translation leverages published preclinical investigations to identify high-confidence pathways, networks, and regulators of human disease.