Alhusaini S, Whelan CD, Sisodiya SM, Thompson PM. Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy.
NEUROIMAGE-CLINICAL 2016;
12:526-534. [PMID:
27672556 PMCID:
PMC5030372 DOI:
10.1016/j.nicl.2016.09.005]
[Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Revised: 07/21/2016] [Accepted: 09/05/2016] [Indexed: 12/18/2022]
Abstract
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.
QMRI traits have the potential to serve as robust intermediate phenotypes for brain-related disorders.
Hippocampal volume is the most promising neuroimaging endophenotype for MTLE + HS.
Imaging genomics holds great promise in advancing epilepsy genetic research.
Studies are encouraged to explore the validity of QMRI traits as endophenotypes for epilepsy.
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