Integrating Pharmacodynamic Data to Prioritise Candidate Migraine Genes and Pathways Using a Novel Bioinformatics Workflow
Abstract
Background/Objectives: Migraine is a neurological disorder with a heterogeneous presentation; however, compounds perceived as effective by migraine sufferers are often underrepresented in research. This study adopts a novel exploratory approach to determine whether pharmacodynamic data from such compounds can be used to prioritise candidate migraine-related genes and biological pathways for future investigation, and to generate hypotheses regarding migraine pathophysiology. Methods: A structured internet search identified 181 compounds perceived as effective for migraine, of which 148 had at least one supportive report identified in the PubMed literature. Following DrugBank-based exclusions for insufficient interaction data, 137 compounds remained for analysis. A gene list was extrapolated from compound-protein interactions, followed by analyses identifying significantly enriched tissues and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways. Unique genes from enriched tissue-specific sublists were considered targets of interest, and those not previously directly associated with migraine in the databases and literature searches used were deemed candidate migraine target genes. Results: A total of 32 compounds affected the products of 21 targets of interest. CHRM3, CHRNA4, and SCN2B emerged as prioritised candidate genes that had not previously been directly associated with migraine in the databases examined. Enrichment analysis of the pharmacodynamically derived gene…
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