First Author | Haure-Mirande JV | Year | 2019 |
Journal | Mol Psychiatry | Volume | 24 |
Issue | 3 | Pages | 431-446 |
PubMed ID | 30283032 | Mgi Jnum | J:295554 |
Mgi Id | MGI:6453958 | Doi | 10.1038/s41380-018-0255-6 |
Citation | Haure-Mirande JV, et al. (2019) Integrative approach to sporadic Alzheimer's disease: deficiency of TYROBP in cerebral Abeta amyloidosis mouse normalizes clinical phenotype and complement subnetwork molecular pathology without reducing Abeta burden. Mol Psychiatry 24(3):431-446 |
abstractText | Integrative gene network approaches enable new avenues of exploration that implicate causal genes in sporadic late-onset Alzheimer's disease (LOAD) pathogenesis, thereby offering novel insights for drug-discovery programs. We previously constructed a probabilistic causal network model of sporadic LOAD and identified TYROBP/DAP12, encoding a microglial transmembrane signaling polypeptide and direct adapter of TREM2, as the most robust key driver gene in the network. Here, we show that absence of TYROBP/DAP12 in a mouse model of AD-type cerebral Abeta amyloidosis (APP(KM670/671NL)/PSEN1(Deltaexon9)) recapitulates the expected network characteristics by normalizing the transcriptome of APP/PSEN1 mice and repressing the induction of genes involved in the switch from homeostatic microglia to disease-associated microglia (DAM), including Trem2, complement (C1qa, C1qb, C1qc, and Itgax), Clec7a and Cst7. Importantly, we show that constitutive absence of TYROBP/DAP12 in the amyloidosis mouse model prevented appearance of the electrophysiological and learning behavior alterations associated with the phenotype of APP(KM670/671NL)/PSEN1(Deltaexon9) mice. Our results suggest that TYROBP/DAP12 could represent a novel therapeutic target to slow, arrest, or prevent the development of sporadic LOAD. These data establish that the network pathology observed in postmortem human LOAD brain can be faithfully recapitulated in the brain of a genetically manipulated mouse. These data also validate our multiscale gene networks by demonstrating how the networks intersect with the standard neuropathological features of LOAD. |