| First Author | Preuss C | Year | 2020 |
| Journal | Mol Neurodegener | Volume | 15 |
| Issue | 1 | Pages | 67 |
| PubMed ID | 33172468 | Mgi Jnum | J:341531 |
| Mgi Id | MGI:6827212 | Doi | 10.1186/s13024-020-00412-5 |
| Citation | Preuss C, et al. (2020) A novel systems biology approach to evaluate mouse models of late-onset Alzheimer's disease. Mol Neurodegener 15(1):67 |
| abstractText | 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(R) Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of the 5xFAD mouse, a widely used amyloid pathology model, and three mouse models based on LOAD genetics carrying APOE4 and TREM2*R47H alleles demonstrated overlaps with distinct human AD modules that, in turn, were functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq showed 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. |
