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Genomic and neuroimaging approaches to bipolar disorder
BACKGROUND: To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and v...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867895/ https://www.ncbi.nlm.nih.gov/pubmed/35101157 http://dx.doi.org/10.1192/bjo.2021.1082 |
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author | Oraki Kohshour, Mojtaba Papiol, Sergi Ching, Christopher R. K. Schulze, Thomas G. |
author_facet | Oraki Kohshour, Mojtaba Papiol, Sergi Ching, Christopher R. K. Schulze, Thomas G. |
author_sort | Oraki Kohshour, Mojtaba |
collection | PubMed |
description | BACKGROUND: To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder. AIMS: To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies. METHOD: We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings. RESULTS: ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder. CONCLUSIONS: The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder. |
format | Online Article Text |
id | pubmed-8867895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88678952022-03-10 Genomic and neuroimaging approaches to bipolar disorder Oraki Kohshour, Mojtaba Papiol, Sergi Ching, Christopher R. K. Schulze, Thomas G. BJPsych Open Review BACKGROUND: To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder. AIMS: To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies. METHOD: We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings. RESULTS: ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder. CONCLUSIONS: The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder. Cambridge University Press 2022-02-01 /pmc/articles/PMC8867895/ /pubmed/35101157 http://dx.doi.org/10.1192/bjo.2021.1082 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Review Oraki Kohshour, Mojtaba Papiol, Sergi Ching, Christopher R. K. Schulze, Thomas G. Genomic and neuroimaging approaches to bipolar disorder |
title | Genomic and neuroimaging approaches to bipolar disorder |
title_full | Genomic and neuroimaging approaches to bipolar disorder |
title_fullStr | Genomic and neuroimaging approaches to bipolar disorder |
title_full_unstemmed | Genomic and neuroimaging approaches to bipolar disorder |
title_short | Genomic and neuroimaging approaches to bipolar disorder |
title_sort | genomic and neuroimaging approaches to bipolar disorder |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867895/ https://www.ncbi.nlm.nih.gov/pubmed/35101157 http://dx.doi.org/10.1192/bjo.2021.1082 |
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