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

Abstract 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 elucid...

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Main Authors: Minghui Wang, Panos Roussos, Andrew McKenzie, Xianxiao Zhou, Yuji Kajiwara, Kristen J. Brennand, Gabriele C. De Luca, John F. Crary, Patrizia Casaccia, Joseph D. Buxbaum, Michelle Ehrlich, Sam Gandy, Alison Goate, Pavel Katsel, Eric Schadt, Vahram Haroutunian, Bin Zhang
Format: Article
Language:English
Published: BMC 2016-11-01
Series:Genome Medicine
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Online Access:http://link.springer.com/article/10.1186/s13073-016-0355-3
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language English
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author Minghui Wang
Panos Roussos
Andrew McKenzie
Xianxiao Zhou
Yuji Kajiwara
Kristen J. Brennand
Gabriele C. De Luca
John F. Crary
Patrizia Casaccia
Joseph D. Buxbaum
Michelle Ehrlich
Sam Gandy
Alison Goate
Pavel Katsel
Eric Schadt
Vahram Haroutunian
Bin Zhang
spellingShingle Minghui Wang
Panos Roussos
Andrew McKenzie
Xianxiao Zhou
Yuji Kajiwara
Kristen J. Brennand
Gabriele C. De Luca
John F. Crary
Patrizia Casaccia
Joseph D. Buxbaum
Michelle Ehrlich
Sam Gandy
Alison Goate
Pavel Katsel
Eric Schadt
Vahram Haroutunian
Bin Zhang
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
Genome Medicine
Alzheimer’s disease
Dementia
Differential expression
Gene co-expression network
Gene module
Systems biology
author_facet Minghui Wang
Panos Roussos
Andrew McKenzie
Xianxiao Zhou
Yuji Kajiwara
Kristen J. Brennand
Gabriele C. De Luca
John F. Crary
Patrizia Casaccia
Joseph D. Buxbaum
Michelle Ehrlich
Sam Gandy
Alison Goate
Pavel Katsel
Eric Schadt
Vahram Haroutunian
Bin Zhang
author_sort Minghui Wang
title 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_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_sort integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to alzheimer’s disease
publisher BMC
series Genome Medicine
issn 1756-994X
publishDate 2016-11-01
description Abstract 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.
topic Alzheimer’s disease
Dementia
Differential expression
Gene co-expression network
Gene module
Systems biology
url http://link.springer.com/article/10.1186/s13073-016-0355-3
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spelling doaj-6f5c9ccb12a04ff398d143576bc62ad42020-11-24T21:39:00ZengBMCGenome Medicine1756-994X2016-11-018112110.1186/s13073-016-0355-3Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s diseaseMinghui Wang0Panos Roussos1Andrew McKenzie2Xianxiao Zhou3Yuji Kajiwara4Kristen J. Brennand5Gabriele C. De Luca6John F. Crary7Patrizia Casaccia8Joseph D. Buxbaum9Michelle Ehrlich10Sam Gandy11Alison Goate12Pavel Katsel13Eric Schadt14Vahram Haroutunian15Bin Zhang16Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDivision of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDivision of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceNuffield Department of Clinical Neurosciences, University of OxfordFriedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDivision of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Pediatrics, Icahn School of Medicine at Mount Sinai, One Gustave L Levy PlacePsychiatry, JJ Peters VA Medical CenterDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDivision of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDivision of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceAbstract 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.http://link.springer.com/article/10.1186/s13073-016-0355-3Alzheimer’s diseaseDementiaDifferential expressionGene co-expression networkGene moduleSystems biology