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Imaging Transcriptomics of Brain Disorders
Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9616271/ https://www.ncbi.nlm.nih.gov/pubmed/36324650 http://dx.doi.org/10.1016/j.bpsgos.2021.10.002 |
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author | Arnatkeviciute, Aurina Fulcher, Ben D. Bellgrove, Mark A. Fornito, Alex |
author_facet | Arnatkeviciute, Aurina Fulcher, Ben D. Bellgrove, Mark A. Fornito, Alex |
author_sort | Arnatkeviciute, Aurina |
collection | PubMed |
description | Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes. |
format | Online Article Text |
id | pubmed-9616271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-96162712022-11-01 Imaging Transcriptomics of Brain Disorders Arnatkeviciute, Aurina Fulcher, Ben D. Bellgrove, Mark A. Fornito, Alex Biol Psychiatry Glob Open Sci Review Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes. Elsevier 2021-10-21 /pmc/articles/PMC9616271/ /pubmed/36324650 http://dx.doi.org/10.1016/j.bpsgos.2021.10.002 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Arnatkeviciute, Aurina Fulcher, Ben D. Bellgrove, Mark A. Fornito, Alex Imaging Transcriptomics of Brain Disorders |
title | Imaging Transcriptomics of Brain Disorders |
title_full | Imaging Transcriptomics of Brain Disorders |
title_fullStr | Imaging Transcriptomics of Brain Disorders |
title_full_unstemmed | Imaging Transcriptomics of Brain Disorders |
title_short | Imaging Transcriptomics of Brain Disorders |
title_sort | imaging transcriptomics of brain disorders |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9616271/ https://www.ncbi.nlm.nih.gov/pubmed/36324650 http://dx.doi.org/10.1016/j.bpsgos.2021.10.002 |
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