Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy
Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in differe...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2016-01-01
|
Series: | NeuroImage: Clinical |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158216301620 |
id |
doaj-1c54a767ddb34e22ba3b6e4f71766f1b |
---|---|
record_format |
Article |
spelling |
doaj-1c54a767ddb34e22ba3b6e4f71766f1b2020-11-24T22:07:28ZengElsevierNeuroImage: Clinical2213-15822016-01-0112C52653410.1016/j.nicl.2016.09.005Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsySaud Alhusaini0Christopher D. Whelan1Sanjay M. Sisodiya2Paul M. Thompson3Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, CanadaImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USADepartment of Clinical and Experimental Epilepsy, University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, London, UKImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USAOver the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS) method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy.http://www.sciencedirect.com/science/article/pii/S2213158216301620EndophenotypesEpilepsyImaging genomicsMagnetic resonance imaging |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Saud Alhusaini Christopher D. Whelan Sanjay M. Sisodiya Paul M. Thompson |
spellingShingle |
Saud Alhusaini Christopher D. Whelan Sanjay M. Sisodiya Paul M. Thompson Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy NeuroImage: Clinical Endophenotypes Epilepsy Imaging genomics Magnetic resonance imaging |
author_facet |
Saud Alhusaini Christopher D. Whelan Sanjay M. Sisodiya Paul M. Thompson |
author_sort |
Saud Alhusaini |
title |
Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
title_short |
Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
title_full |
Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
title_fullStr |
Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
title_full_unstemmed |
Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
title_sort |
quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy |
publisher |
Elsevier |
series |
NeuroImage: Clinical |
issn |
2213-1582 |
publishDate |
2016-01-01 |
description |
Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS) method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy. |
topic |
Endophenotypes Epilepsy Imaging genomics Magnetic resonance imaging |
url |
http://www.sciencedirect.com/science/article/pii/S2213158216301620 |
work_keys_str_mv |
AT saudalhusaini quantitativemagneticresonanceimagingtraitsasendophenotypesforgeneticmappinginepilepsy AT christopherdwhelan quantitativemagneticresonanceimagingtraitsasendophenotypesforgeneticmappinginepilepsy AT sanjaymsisodiya quantitativemagneticresonanceimagingtraitsasendophenotypesforgeneticmappinginepilepsy AT paulmthompson quantitativemagneticresonanceimagingtraitsasendophenotypesforgeneticmappinginepilepsy |
_version_ |
1725820252150824960 |