Pathway Analysis Using Information from Allele-Specific Gene Methylation in Genome-Wide Association Studies for Bipolar Disorder

Abstract

Bipolar disorder (BPD) is a complex psychiatric trait with high heritability. Despite efforts through conducting genome-wide association (GWA) studies, the success of identifying susceptibility loci for BPD has been limited, which is partially attributed to the complex nature of its pathogenesis. Pathway-based analytic strategy is a powerful tool to explore joint effects of gene sets within specific biological pathways. Additionally, to incorporate other aspects of genomic data into pathway analysis may further enhance our understanding for the underlying mechanisms for BPD. Patterns of DNA methylation play important roles in regulating gene expression and function. A commonly observed phenomenon, allele-specific methylation (ASM) describes the associations between genetic variants and DNA methylation patterns. The present study aimed to identify biological pathways that are involve in the pathogenesis of BPD while incorporating brain specific ASM information in pathway analysis using two large-scale GWA datasets in Caucasian populations. A weighting scheme was adopted to take ASM information into consideration for each pathway. After multiple testing corrections, we identified 88 and 15 enriched pathways for their biological relevance for BPD in the Genetic Association Information Network (GAIN) and the Wellcome Trust Case Control Consortium dataset, respectively. Many of these pathways were significant only when applying the weighting scheme. Three ion channel related pathways were consistently identified in both datasets. Results in the GAIN dataset also suggest for the roles of extracellular matrix in brain for BPD. Findings from Gene Ontology (GO) analysis exhibited functional enrichment among genes of non-GO pathways in activity of gated channel, transporter, and neurotransmitter receptor. We demonstrated that integrating different data sources with pathway analysis provides an avenue to identify promising and novel biological pathways for exploring the underlying molecular mechanisms for bipolar disorder. Further basic research can be conducted to target the biological mechanisms for the identified genes and pathways.

Building a genetic risk model for bipolar disorder from genome-wide association data with random forest algorithm

“…Similarly, we found a number of significant pathways for the identified genes. These pathway results are quite consistent with pathways findings in previous GWA studies for bipolar disorder4041.…”

In silico analysis of regulatory and structural motifs of the ovine HSP90AA1 gene

“…2). These results confirm that the allele-specific methylation is also a tissue-specific event, and therefore, the different patterns observed could play an important role in the gene expression regulation (Chuang et al 2013). Additional information could be provided by the CpGs at positions −772, −746, −718, −696, −678, and −671 preceding the rs397514116 (g.660G > C) and the CpG at position −633.…”

Exploring Genetic Variation that Influences Brain Methylation in Attention-Deficit/Hyperactivity Disorder

“…Investigating SNPs that display allele-specific methylation could help identify risk variants for common diseases, including neuropsychiatric disorders 18 , as shown by recent studies of BD and schizophrenia 9,19 . The present study investigated the possible contribution of ASM to ADHD using data from the largest GWAS meta-analysis performed to date in ADHD 4 .…”