Browsing by Author "Preuss, Christoph"

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    In vivo validation of late-onset Alzheimer's disease genetic risk factors
    (bioRxiv, 2023-12-24) Sasner, Michael; Preuss, Christoph; Pandey, Ravi S.; Uyar, Asli; Garceau, Dylan; Kotredes, Kevin P.; Williams, Harriet; Oblak, Adrian L.; Lin, Peter Bor-Chian; Perkins, Bridget; Soni, Disha; Ingraham, Cindy; Lee-Gosselin, Audrey; Lamb, Bruce T.; Howell, Gareth R.; Carter, Gregory W.; Radiology and Imaging Sciences, School of Medicine
    Introduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. Results: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. Discussion: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.
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    A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease
    (BMC, 2020-11-10) Preuss, Christoph; Pandey, Ravi; Piazza, Erin; Fine, Alexander; Uyar, Asli; Perumal, Thanneer; Garceau, Dylan; Kotredes, Kevin P.; Williams, Harriet; Mangravite, Lara M.; Lamb, Bruce T.; Oblak, Adrian L.; Howell, Gareth R.; Sasner, Michael; Logsdon, Benjamin A.; Carter, Gregory W.; Psychiatry, School of Medicine
    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. Supplementary information Supplementary information accompanies this paper at 10.1186/s13024-020-00412-5.