A methylome-wide mQTL analysis reveals associations of methylation sites with GAD1 and HDAC3 SNPs and a general psychiatric risk score.

Ciuculete DM, Boström AE, Voisin S, Philipps H, Titova OE, Bandstein M, Nikontovic L, Williams MJ, Mwinyi J, Schiöth HB

Transl Psychiatry 7 (1) e1002 [2017-01-17; online 2017-01-17]

Genome-wide association studies have identified a number of single-nucleotide polymorphisms (SNPs) that are associated with psychiatric diseases. Increasing body of evidence suggests a complex connection of SNPs and the transcriptional and epigenetic regulation of gene expression, which is poorly understood. In the current study, we investigated the interplay between genetic risk variants, shifts in methylation and mRNA levels in whole blood from 223 adolescents distinguished by a risk for developing psychiatric disorders. We analyzed 37 SNPs previously associated with psychiatric diseases in relation to genome-wide DNA methylation levels using linear models, with Bonferroni correction and adjusting for cell-type composition. Associations between DNA methylation, mRNA levels and psychiatric disease risk evaluated by the Development and Well-Being Assessment (DAWBA) score were identified by robust linear models, Pearson's correlations and binary regression models. We detected five SNPs (in HCRTR1, GAD1, HADC3 and FKBP5) that were associated with eight CpG sites, validating five of these SNP-CpG pairs. Three of these CpG sites, that is, cg01089319 (GAD1), cg01089249 (GAD1) and cg24137543 (DIAPH1), manifest in significant gene expression changes and overlap with active regulatory regions in chromatin states of brain tissues. Importantly, methylation levels at cg01089319 were associated with the DAWBA score in the discovery group. These results show how distinct SNPs linked with psychiatric diseases are associated with epigenetic shifts with relevance for gene expression. Our findings give a novel insight on how genetic variants may modulate risks for the development of psychiatric diseases.

Bioinformatics Compute and Storage [Service]

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

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PubMed 28094813

DOI 10.1038/tp.2016.275

Crossref 10.1038/tp.2016.275


pmc PMC5545735