Cargando…
Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging
Expression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression a...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026054/ https://www.ncbi.nlm.nih.gov/pubmed/32066731 http://dx.doi.org/10.1038/s41398-020-0724-y |
_version_ | 1783498609216454656 |
---|---|
author | Barbu, Miruna C. Spiliopoulou, Athina Colombo, Marco McKeigue, Paul Clarke, Toni-Kim Howard, David M. Adams, Mark J. Shen, Xueyi Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. |
author_facet | Barbu, Miruna C. Spiliopoulou, Athina Colombo, Marco McKeigue, Paul Clarke, Toni-Kim Howard, David M. Adams, Mark J. Shen, Xueyi Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. |
author_sort | Barbu, Miruna C. |
collection | PubMed |
description | Expression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity. Using large-scale eQTL mapping studies, we computed 6457 gene expression scores (eQTL scores) using genome-wide genotype data in UK Biobank, where each score represents a genetic proxy measure of gene expression. These scores were then tested for associations with two diffusion tensor imaging measures, fractional anisotropy (N(FA) = 14,518) and mean diffusivity (N(MD) = 14,485), representing white matter structural integrity. We found FDR-corrected significant associations between 8 eQTL scores and structural connectivity phenotypes, including global and regional measures (β(absolute) FA = 0.0339–0.0453; MD = 0.0308–0.0381) and individual tracts (β(absolute) FA = 0.0320–0.0561; MD = 0.0295–0.0480). The loci within these eQTL scores have been reported to regulate expression of genes involved in various brain-related processes and disorders, such as neurite outgrowth and Parkinson’s disease (DCAKD, SLC35A4, SEC14L4, SRA1, NMT1, CPNE1, PLEKHM1, UBE3C). Our findings indicate that eQTL scores are associated with measures of in vivo brain connectivity and provide novel information not previously found by conventional genome-wide association studies. Although the role of expression of these genes regarding white matter microstructural integrity is not yet clear, these results suggest it may be possible, in future, to map potential trait- and disease-associated eQTL to in vivo brain connectivity and better understand the mechanisms of psychiatric disorders and brain traits, and their associated imaging findings. |
format | Online Article Text |
id | pubmed-7026054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70260542020-03-03 Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging Barbu, Miruna C. Spiliopoulou, Athina Colombo, Marco McKeigue, Paul Clarke, Toni-Kim Howard, David M. Adams, Mark J. Shen, Xueyi Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. Transl Psychiatry Article Expression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity. Using large-scale eQTL mapping studies, we computed 6457 gene expression scores (eQTL scores) using genome-wide genotype data in UK Biobank, where each score represents a genetic proxy measure of gene expression. These scores were then tested for associations with two diffusion tensor imaging measures, fractional anisotropy (N(FA) = 14,518) and mean diffusivity (N(MD) = 14,485), representing white matter structural integrity. We found FDR-corrected significant associations between 8 eQTL scores and structural connectivity phenotypes, including global and regional measures (β(absolute) FA = 0.0339–0.0453; MD = 0.0308–0.0381) and individual tracts (β(absolute) FA = 0.0320–0.0561; MD = 0.0295–0.0480). The loci within these eQTL scores have been reported to regulate expression of genes involved in various brain-related processes and disorders, such as neurite outgrowth and Parkinson’s disease (DCAKD, SLC35A4, SEC14L4, SRA1, NMT1, CPNE1, PLEKHM1, UBE3C). Our findings indicate that eQTL scores are associated with measures of in vivo brain connectivity and provide novel information not previously found by conventional genome-wide association studies. Although the role of expression of these genes regarding white matter microstructural integrity is not yet clear, these results suggest it may be possible, in future, to map potential trait- and disease-associated eQTL to in vivo brain connectivity and better understand the mechanisms of psychiatric disorders and brain traits, and their associated imaging findings. Nature Publishing Group UK 2020-02-04 /pmc/articles/PMC7026054/ /pubmed/32066731 http://dx.doi.org/10.1038/s41398-020-0724-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Barbu, Miruna C. Spiliopoulou, Athina Colombo, Marco McKeigue, Paul Clarke, Toni-Kim Howard, David M. Adams, Mark J. Shen, Xueyi Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title | Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title_full | Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title_fullStr | Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title_full_unstemmed | Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title_short | Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging |
title_sort | expression quantitative trait loci-derived scores and white matter microstructure in uk biobank: a novel approach to integrating genetics and neuroimaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026054/ https://www.ncbi.nlm.nih.gov/pubmed/32066731 http://dx.doi.org/10.1038/s41398-020-0724-y |
work_keys_str_mv | AT barbumirunac expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT spiliopoulouathina expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT colombomarco expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT mckeiguepaul expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT clarketonikim expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT howarddavidm expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT adamsmarkj expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT shenxueyi expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT lawriestephenm expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT mcintoshandrewm expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging AT whalleyheatherc expressionquantitativetraitlociderivedscoresandwhitemattermicrostructureinukbiobankanovelapproachtointegratinggeneticsandneuroimaging |