Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains

Abstract Alzheimer’s disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain co...

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Autores principales: Diego Marques-Coelho, Lukas da Cruz Carvalho Iohan, Ana Raquel Melo de Farias, Amandine Flaig, The Brainbank Neuro–CEB Neuropathology Network, Jean-Charles Lambert, Marcos Romualdo Costa
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Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/d9b5cd0c8e78499db37977012745cbe4
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spelling oai:doaj.org-article:d9b5cd0c8e78499db37977012745cbe42021-12-02T14:23:46ZDifferential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains10.1038/s41514-020-00052-52056-3973https://doaj.org/article/d9b5cd0c8e78499db37977012745cbe42021-01-01T00:00:00Zhttps://doi.org/10.1038/s41514-020-00052-5https://doaj.org/toc/2056-3973Abstract Alzheimer’s disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.Diego Marques-CoelhoLukas da Cruz Carvalho IohanAna Raquel Melo de FariasAmandine FlaigThe Brainbank Neuro–CEB Neuropathology NetworkJean-Charles LambertMarcos Romualdo CostaNature PortfolioarticleGeriatricsRC952-954.6ENnpj Aging and Mechanisms of Disease, Vol 7, Iss 1, Pp 1-15 (2021)
institution DOAJ
collection DOAJ
language EN
topic Geriatrics
RC952-954.6
spellingShingle Geriatrics
RC952-954.6
Diego Marques-Coelho
Lukas da Cruz Carvalho Iohan
Ana Raquel Melo de Farias
Amandine Flaig
The Brainbank Neuro–CEB Neuropathology Network
Jean-Charles Lambert
Marcos Romualdo Costa
Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
description Abstract Alzheimer’s disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.
format article
author Diego Marques-Coelho
Lukas da Cruz Carvalho Iohan
Ana Raquel Melo de Farias
Amandine Flaig
The Brainbank Neuro–CEB Neuropathology Network
Jean-Charles Lambert
Marcos Romualdo Costa
author_facet Diego Marques-Coelho
Lukas da Cruz Carvalho Iohan
Ana Raquel Melo de Farias
Amandine Flaig
The Brainbank Neuro–CEB Neuropathology Network
Jean-Charles Lambert
Marcos Romualdo Costa
author_sort Diego Marques-Coelho
title Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
title_short Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
title_full Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
title_fullStr Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
title_full_unstemmed Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains
title_sort differential transcript usage unravels gene expression alterations in alzheimer’s disease human brains
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/d9b5cd0c8e78499db37977012745cbe4
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