Prediction of functional regulatory elements of bipolar disorder via data integration analysis

• Main Authors: Aamir Fahira, Jinmai Zhang, Jian Xuemin, Zhiqiang Li, Yongyong Shi
• Format: Article
• Language: English
• Published: Elsevier 2020-12-01
• Series: Journal of Affective Disorders Reports
• Subjects: Bipolar disorder; Proxy SNPs; Annotation; Gene expression analysis; Protein-protein interactions
• Online Access: http://www.sciencedirect.com/science/article/pii/S2666915320300159

Genome-wide association studies identified more than 30 loci for bipolar disorder (BP). These SNPs mostly lie in the non-coding region which makes it hard to determine the specific functional association. We conducted a multi-approach analysis for functional annotation of BP-associated SNPs, SNPs were retrieved from the Stahl Eli A et al. BP-GWAS data. 1000 genomes data was used to fetch the proxy SNPs for the BP-GWAS associated SNPs. These SNPs were functionally prioritized via RegulomeDB. Whereas, highly functional SNPs were mapped to expression data, including eQTL, mQTL, and miRNA. Moreover, gene enrichment analysis, over-representation analysis, Protein-protein interaction (PPI), and miRNA-gene interaction analysis were carried out. Overall 184 SNPs were prioritized via RegulomeDB. Whereas 95 SNPs were associated with mQTL (DNA methylation quantitative trait loci P-value < 5 × 10−8) which influence the expression of 8 genes, while 67 SNPs were associated with 24 genes (eQTL, P-value < 5 × 10−8). Similarly, the 12 functional SNPs were associated with miRNA binding 3′utr region which affects the gene expression of MAU2, HAPLN4, TFAP2B, UBE2Q2P1, FADS1, and ZNF592. Gene ontology (GO) analysis shows that the predicted genes were highly enriched in the BPD. Moreover, prioritized SNPs were involved in fatty acid metabolism. This study demonstrates an in-depth view of the BP associated SNPs along with proxy SNPs. We found that these proxy SNPs involved in the BP-associated gene expression and miRNA and miRNA-gene interactions, these findings may help the researchers to understand the mechanism behind BP GWAS-associated SNPs.