Cargando…

Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease

BACKGROUND: Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive. METHODS: To elucidate mol...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Minghui, Roussos, Panos, McKenzie, Andrew, Zhou, Xianxiao, Kajiwara, Yuji, Brennand, Kristen J., De Luca, Gabriele C., Crary, John F., Casaccia, Patrizia, Buxbaum, Joseph D., Ehrlich, Michelle, Gandy, Sam, Goate, Alison, Katsel, Pavel, Schadt, Eric, Haroutunian, Vahram, Zhang, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088659/
https://www.ncbi.nlm.nih.gov/pubmed/27799057
http://dx.doi.org/10.1186/s13073-016-0355-3
_version_ 1782464140164464640
author Wang, Minghui
Roussos, Panos
McKenzie, Andrew
Zhou, Xianxiao
Kajiwara, Yuji
Brennand, Kristen J.
De Luca, Gabriele C.
Crary, John F.
Casaccia, Patrizia
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Goate, Alison
Katsel, Pavel
Schadt, Eric
Haroutunian, Vahram
Zhang, Bin
author_facet Wang, Minghui
Roussos, Panos
McKenzie, Andrew
Zhou, Xianxiao
Kajiwara, Yuji
Brennand, Kristen J.
De Luca, Gabriele C.
Crary, John F.
Casaccia, Patrizia
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Goate, Alison
Katsel, Pavel
Schadt, Eric
Haroutunian, Vahram
Zhang, Bin
author_sort Wang, Minghui
collection PubMed
description BACKGROUND: Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive. METHODS: To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44,692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits. RESULTS: The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities. CONCLUSIONS: This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0355-3) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5088659
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-50886592016-11-07 Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease Wang, Minghui Roussos, Panos McKenzie, Andrew Zhou, Xianxiao Kajiwara, Yuji Brennand, Kristen J. De Luca, Gabriele C. Crary, John F. Casaccia, Patrizia Buxbaum, Joseph D. Ehrlich, Michelle Gandy, Sam Goate, Alison Katsel, Pavel Schadt, Eric Haroutunian, Vahram Zhang, Bin Genome Med Research BACKGROUND: Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive. METHODS: To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44,692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits. RESULTS: The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities. CONCLUSIONS: This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0355-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-01 /pmc/articles/PMC5088659/ /pubmed/27799057 http://dx.doi.org/10.1186/s13073-016-0355-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wang, Minghui
Roussos, Panos
McKenzie, Andrew
Zhou, Xianxiao
Kajiwara, Yuji
Brennand, Kristen J.
De Luca, Gabriele C.
Crary, John F.
Casaccia, Patrizia
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Goate, Alison
Katsel, Pavel
Schadt, Eric
Haroutunian, Vahram
Zhang, Bin
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title_full Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title_fullStr Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title_full_unstemmed Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title_short Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
title_sort integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to alzheimer’s disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088659/
https://www.ncbi.nlm.nih.gov/pubmed/27799057
http://dx.doi.org/10.1186/s13073-016-0355-3
work_keys_str_mv AT wangminghui integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT roussospanos integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT mckenzieandrew integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT zhouxianxiao integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT kajiwarayuji integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT brennandkristenj integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT delucagabrielec integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT craryjohnf integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT casacciapatrizia integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT buxbaumjosephd integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT ehrlichmichelle integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT gandysam integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT goatealison integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT katselpavel integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT schadteric integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT haroutunianvahram integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease
AT zhangbin integrativenetworkanalysisofnineteenbrainregionsidentifiesmolecularsignaturesandnetworksunderlyingselectiveregionalvulnerabilitytoalzheimersdisease