Cargando…
Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk
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 gen...
Autores principales: | , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145452/ https://www.ncbi.nlm.nih.gov/pubmed/32274467 http://dx.doi.org/10.1093/braincomms/fcz022 |
_version_ | 1783520002621571072 |
---|---|
author | Salih, Dervis A Bayram, Sevinc Guelfi, Sebastian Reynolds, Regina H Shoai, Maryam Ryten, Mina Brenton, Jonathan W Zhang, David Matarin, Mar Botia, Juan A Shah, Runil Brookes, Keeley J Guetta-Baranes, Tamar Morgan, Kevin Bellou, Eftychia Cummings, Damian M Escott-Price, Valentina Hardy, John |
author_facet | Salih, Dervis A Bayram, Sevinc Guelfi, Sebastian Reynolds, Regina H Shoai, Maryam Ryten, Mina Brenton, Jonathan W Zhang, David Matarin, Mar Botia, Juan A Shah, Runil Brookes, Keeley J Guetta-Baranes, Tamar Morgan, Kevin Bellou, Eftychia Cummings, Damian M Escott-Price, Valentina Hardy, John |
author_sort | Salih, Dervis A |
collection | PubMed |
description | 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 (OAS1, LAPTM5, ITGAM/CD11b and LILRB4). Of the mouse orthologues of these genes Oas1a is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene Trem2, because the increase in Oas1a and Trem2 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 LAPTM5, ITGAM/CD11b and LILRB4 (Laptm5, Itgam/CD11b and Lilra5) 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 Laptm5 and Lilra5 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. |
format | Online Article Text |
id | pubmed-7145452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71454522020-04-09 Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk Salih, Dervis A Bayram, Sevinc Guelfi, Sebastian Reynolds, Regina H Shoai, Maryam Ryten, Mina Brenton, Jonathan W Zhang, David Matarin, Mar Botia, Juan A Shah, Runil Brookes, Keeley J Guetta-Baranes, Tamar Morgan, Kevin Bellou, Eftychia Cummings, Damian M Escott-Price, Valentina Hardy, John Brain Commun Original Article 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 (OAS1, LAPTM5, ITGAM/CD11b and LILRB4). Of the mouse orthologues of these genes Oas1a is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene Trem2, because the increase in Oas1a and Trem2 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 LAPTM5, ITGAM/CD11b and LILRB4 (Laptm5, Itgam/CD11b and Lilra5) 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 Laptm5 and Lilra5 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. Oxford University Press 2019-10-10 /pmc/articles/PMC7145452/ /pubmed/32274467 http://dx.doi.org/10.1093/braincomms/fcz022 Text en © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Salih, Dervis A Bayram, Sevinc Guelfi, Sebastian Reynolds, Regina H Shoai, Maryam Ryten, Mina Brenton, Jonathan W Zhang, David Matarin, Mar Botia, Juan A Shah, Runil Brookes, Keeley J Guetta-Baranes, Tamar Morgan, Kevin Bellou, Eftychia Cummings, Damian M Escott-Price, Valentina Hardy, John Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title | Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title_full | Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title_fullStr | Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title_full_unstemmed | Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title_short | Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk |
title_sort | genetic variability in response to amyloid beta deposition influences alzheimer’s disease risk |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145452/ https://www.ncbi.nlm.nih.gov/pubmed/32274467 http://dx.doi.org/10.1093/braincomms/fcz022 |
work_keys_str_mv | AT salihdervisa geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT bayramsevinc geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT guelfisebastian geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT reynoldsreginah geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT shoaimaryam geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT rytenmina geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT brentonjonathanw geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT zhangdavid geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT matarinmar geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT botiajuana geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT shahrunil geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT brookeskeeleyj geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT guettabaranestamar geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT morgankevin geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT belloueftychia geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT cummingsdamianm geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT escottpricevalentina geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk AT hardyjohn geneticvariabilityinresponsetoamyloidbetadepositioninfluencesalzheimersdiseaserisk |