Molecular Neurodegeneration (Nov 2020)

A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease

  • Christoph Preuss,
  • Ravi Pandey,
  • Erin Piazza,
  • Alexander Fine,
  • Asli Uyar,
  • Thanneer Perumal,
  • Dylan Garceau,
  • Kevin P. Kotredes,
  • Harriet Williams,
  • Lara M. Mangravite,
  • Bruce T. Lamb,
  • Adrian L. Oblak,
  • Gareth R. Howell,
  • Michael Sasner,
  • Benjamin A. Logsdon,
  • the MODEL-AD Consortium,
  • Gregory W. Carter

DOI
https://doi.org/10.1186/s13024-020-00412-5
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 16

Abstract

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Abstract 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 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.