TY - JOUR T1 - A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease JF - bioRxiv DO - 10.1101/682856 SP - 682856 AU - Christoph Preuss AU - Ravi Pandey AU - Erin Piazza AU - Alexander Fine AU - Asli Uyar AU - Thanneer Perumal AU - Dylan Garceau AU - Kevin P Kotredes AU - Harriet Williams AU - Lara M Mangravite AU - Bruce T. Lamb AU - Adrian L. Oblak AU - Gareth R. Howell AU - Michael Sasner AU - Benjamin A Logsdon AU - Gregory W. Carter Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/06/26/682856.abstract N2 - Background Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.Results This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of three mouse models based on LOAD genetics, carrying APOE4 and TREM2*R47H alleles, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq shows strong correlation between gene expression changes independent of experimental platform.Conclusions Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models. ER -