Multilocus analysis of hormonal, neurotransmitter, inflammatory pathways and genome‐wide associated variants in migraine susceptibility. (2nd April 2014)

• Record Type: Journal Article
• Authors: Ghosh, J.; Pradhan, S.; Mittal, B.
• Is Part Of: European journal of neurology. Volume 21:Number 7(2014:Jul.)
• Page Start: 1011
• Page End: 1020
• Publication Date: 2014-04-02
• Subjects: Neurology -- Periodicals; Nervous system -- Diseases -- Periodicals; 616.8
• DOI: 10.1111/ene.12427
• Languages: English
• ISSNs: 1351-5101

Abstract

<abstract abstract-type="main" id="ene12427-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="ene12427-sec-0001" sec-type="section"> <title>Background and purpose</title> <p>Migraine pathophysiology involves a complex interplay of processes wherein the hormonal, neurotransmitter and inflammatory pathways interact to influence the migraine phenotype. However, all studies pertaining to the role of genetic variants in migraine have been restricted to a specific pathway and none of the studies has looked into inter‐pathway genetic analysis. Our aim was to combine all the genetic variants from our previously reported studies to conduct higher order gene–gene interaction analysis using different multi‐analytical approaches.</p> </sec> <sec id="ene12427-sec-0002" sec-type="section"> <title>Methods</title> <p>The study group included 324 migraine patients and 134 healthy controls. The study included 20 polymorphisms from hormonal, neurotransmitter, inflammatory and genome‐wide associated variants from our published reports. Univariate and multivariate analyses were carried out by logistic regression. Classification and regression tree (CART) analysis was performed to build a decision tree via recursive partitioning. The high order genetic interactions associated with migraine risk were analyzed using multifactor dimensionality reduction (MDR).</p> </sec> <sec id="ene12427-sec-0003" sec-type="section"> <title>Results</title> <p>Univariate analysis revealed significant associations of polymorphisms in <italic>CYP19A1</italic>, <italic> ESR1</italic>, <italic> TNFA</italic> and <italic>PRDM16</italic> genes with migraine susceptibility. Multiple regression analysis found significant results for four markers in <italic>CYP19A1</italic>, <italic> TNFA</italic>, <italic> ESR1</italic> and <italic>LRP1</italic> genes. In CART, the most prominent splitting variable was <italic>CYP19A1</italic> polymorphism followed by <italic>TNFA</italic>, <italic> ESR1</italic> and <italic>PRDM16</italic> markers. The MDR analysis identified markers of <italic>CYP19A1</italic>, <italic> CYP19A1</italic>‐ <italic>TNFA</italic>, <italic> CYP19A1</italic>‐ <italic>ESR1</italic>‐ <italic>TNFA</italic> and <italic>CYP19A1</italic>‐ <italic>ESR1</italic>‐ <italic>TRPM8</italic>‐ <italic>PRDM16</italic> as best models for one, two, three and four factors, respectively.</p> </sec> <sec id="ene12427-sec-0004" sec-type="section"> <title>Conclusions</title> <p>The present study suggests interactions amongst hormonal, inflammatory and genome‐wide associated variants but not with neurotransmitter pathway variants in migraine susceptibility.</p> </sec> </abstract>