Genetic influences on nicotinic α5 receptor (CHRNA5) CpG methylation and mRNA expression in brain and adipose tissue

The CHRNA5/CHRNA3/CHRNB4 Nicotinic Receptor Regulome: Genomic Architecture, Regulatory Variants, and Clinical Associations

Functionally related genes often cluster into a genome region under coordinated regulation, forming a local regulome. To understand regulation of the CHRNA5/CHRNA3/CHRNB4 nicotinic receptor gene cluster, we integrate large-scale RNA expression data (brain and peripheral) from GTEx (Genotype Tissue Expression), clinical associations (GRASP), and linkage disequilibrium data (1000 Genomes) to find candidate SNPs representing independent regulatory variants. CHRNA3, CHRNA5, CHRNB4 mRNAs, and a well-expressed CHRNA5 antisense RNA (RP11-650L12.2) are co-expressed in many human tissues, suggesting common regulatory elements. The CHRNA5 enhancer haplotype tagged by rs880395 not only increases CHRNA5 mRNA expression in all tissues, but also enhances RP11-650L12.2 and CHRNA3 expression, suggesting DNA looping to multiple promoters. However, in nucleus accumbens and putamen, but not other brain regions, CHRNA3 expression associates uniquely with a haplotype tagged by rs1948 (located in the CHRNB4 3'UTR). Haplotype/diplotype analysis of rs880395 and rs1948 plus rs16969968 (a nonsynonymous CHRNA5 risk variant) in GWAS (COGEND, UW-TTURC, SAGE) yields a nicotine dependence risk profile only partially captured by rs16969968 alone. An example of local gene clusters, this nicotinic regulome is controlled by complex genetic variation, with broad implications for interpreting GWAS.

Replicated Risk Nicotinic Cholinergic Receptor Genes for Nicotine Dependence

It has been hypothesized that the nicotinic acetylcholine receptors (nAChRs) play important roles in nicotine dependence (ND) and influence the number of cigarettes smoked per day (CPD) in smokers. We compiled the associations between nicotinic cholinergic receptor genes (CHRNs) and ND/CPD that were replicated across different studies, reviewed the expression of these risk genes in human/mouse brains, and verified their expression using independent samples of both human and mouse brains. The potential functions of the replicated risk variants were examined using cis-eQTL analysis or predicted using a series of bioinformatics analyses. We found replicated and significant associations for ND/CPD at 19 SNPs in six genes in three genomic regions (CHRNB3-A6, CHRNA5-A3-B4 and CHRNA4). These six risk genes are expressed in at least 18 distinct areas of the human/mouse brain, with verification in our independent human and mouse brain samples. The risk variants might influence the transcription, expression and splicing of the risk genes, alter RNA secondary or protein structure. We conclude that the replicated associations between CHRNB3-A6, CHRNA5-A3-B4,CHRNA4 and ND/CPD are very robust. More research is needed to examine how these genetic variants contribute to the risk for ND/CPD.