Differential splicing analyses of late‐onset AD models reveal alterations in neuronal genes associated with disease. (1st February 2022)

• Record Type: Journal Article
• Authors: Pandey, Ravi S; Kotredes, Kevin P; Howell, Gareth R; Sasner, Michael; Carter, Gregory W
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.052496
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Late‐onset Alzheimer's disease (LOAD) is the leading cause of dementia in the elderly. However, current animal models of AD do not fully recapitulate human disease, hence are limited as tools for developing therapies. Animal models based on LOAD‐associated genes can potentially connect common genetic variation with LOAD transcriptomes. Therefore, novel late‐onset mouse strains expressing either alone or combination of two common risk alleles in human LOAD patients, APOE4 and Trem2*R47H on a C57BL/6J background, were developed and aged to 24 months. Method: We performed a combination of differential expression of gene (DEG) and differential splicing analyses on whole brain transcriptomic data from novel LOAD mouse strains at 4, 8, 12 and 24 months of age. To better understand the difference between differentially expressed and differentially spliced genes, we evaluated enrichment of cell‐type specific gene signatures of the adult brain in these gene sets for each mouse model. Next, we compared differential splicing results from our mouse models with multiple human AD splicing studies. Result: Differentially expressed genes in Trem2*R47H mice were significantly enriched in multiple AD‐related pathways, including immune response, osteoclast differentiation, and metabolism, whereas differentially spliced genes were enriched for neuronal related functions, including GABAergic synapse and glutamatergic synapse. Next, we identified that differentially spliced genes in Trem2*R47H mice were enriched in the neuronal cell signatures while DEGs were enriched in the microglial signatures. We observed significant overlap between differentially spliced genes in Trem2*R47H mice model and human AD brains. Conclusion: We investigated the molecular signatures in the brain transcriptomes of LOAD mouse models using differential expression and splicing analyses. We identified several genes undergoing differential splicing that were enriched for neuronal cell signatures, specifically in middle‐aged Trem2*R47H mice, in common with human LOAD. These genes are overlooked in classical differential expression analysis but can be detected through differential transcript usage analysis. This suggests that alternative splicing could be an important mechanism for pathological progression of LOAD. Further studies on Trem2*R47H driven alternative splicing mechanism is required for a more comprehensive understanding of Trem2 genotype effects on neuronal system related functions.