Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk

Abstract

Genome-wide association studies of late-onset Alzheimer's disease risk have previously identified genes primarily expressed in microglia that form a transcriptional network. Using transgenic mouse models of amyloid deposition, we previously showed that many of the mouse orthologues of these risk genes are co-expressed and associated with amyloid pathology. In this new study, we generate an improved RNA-seq-derived network that is expressed in amyloid-responsive mouse microglia and we statistically compare this with gene-level variation in previous human Alzheimer's disease genome-wide association studies to predict at least four new risk genes for the disease (<i>OAS1</i>, <i>LAPTM5</i>, <i>ITGAM/</i>CD11b and <i>LILRB4</i>). Of the mouse orthologues of these genes <i>Oas1a</i> is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene <i>Trem2</i>, because the increase in <i>Oas1a</i> and <i>Trem2</i> transcripts in response to amyloid deposition in transgenic mice is significantly higher than both the increase of the average microglial transcript and the increase in microglial number. In contrast, the mouse orthologues of <i>LAPTM5</i>, <i>ITGAM</i>/CD11b and <i>LILRB4</i> (<i>Laptm5</i>, <i>Itgam</i>/CD11b and <i>Lilra5</i>) show increased transcripts in the presence of amyloid plaques similar in magnitude to the increase of the average microglial transcript and the increase in microglia number, except that <i>Laptm5</i> and <i>Lilra5</i> transcripts increase significantly quicker than the average microglial transcript as the plaque load becomes dense. This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer's disease risk, and identification of these genes may help to predict the risk of developing Alzheimer's disease. These findings also provide further insights into the mechanisms underlying Alzheimer's disease for potential drug discovery.