Abstract
In recent years, genome-wide association studies (GWAS) have made great progress in elucidating the genetic influence on complex traits. An overwhelming number of GWAS signals resides in regulatory elements, therefore most post-GWAS studies focused only on transcriptional regulatory variants. However, recent findings have expanded the spectrum of trait/disease-associated regulatory variants beyond transcriptional level and highlighted the importance of post-transcriptional variants like those in miRNA targetome. The present work integrated genome-wide association data of coronary artery disease (CAD) with population-specific linkage disequilibrium structures from 1000 Genomes Project to map disease associations to miRNA targetome. Moreover, we performed a variety of functional prediction analyses to prioritize disease-associated variants (DAVs) influencing miRNA targetome and in-silico analyses to get insights into their functional significance. In conclusion, although the role of miRNA targetome variations in the development of CAD still has to be fully elucidated, we provided a systematic bioinformatics approach to the miRNA targetome variations in CAD. The results of this study will be valuable for researchers interested in the identification of CAD GWAS signals that may implicate polymorphic miRNA targeting.
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