We report FAM63B methylation to be significantly associated with BD, thus replicating the same finding recently published for SZ , with consistency in genomic position (same CpG sites) and direction (lower methylation in cases) across both studies. This is of interest in the light of phenotypic overlap between BD and SZ , with relatives to BD patients having increased risk for developing SZ, schizoaffective disorder or major depression [19, 20]. It has also been shown that the two disorders share common genetic risk variants, with a SNP co-heritability estimate of 0.15 . The discovery of shared epigenetic risk loci across the two diseases, with differential methylation at the same sites and in the same direction in the same tissue, as in the case of FAM63B, may help progress the understanding of the shared etiology.
Interestingly, a large recent genome-wide association study (GWAS) meta-analysis of SZ identified association with FAM63B SNP, rs793571, as the most associated finding in this gene (p value = 4.54 × 10−6) . Rs793571 is positioned in intron 7 of FAM63B (~5 kb from exon 9) and could potentially affect methylation levels of the 18 bp region of interest. In our data, rs793571 was however not an mQTL for the two CpG sites and thus unlikely to be involved in the methylation differences in the 18 bp region of interest in blood, at least in our sample.
In general, we do not find strong local mQTLs for the two investigated CpG sites in blood. In human fetal brain, a recent study characterized systematically mQTLs and found no Bonferroni-corrected mQTLs for FAM63B ; however, larger samples sizes across different tissues may reveal robust mQTLs for FAM63B. The present literature and data does in our opinion not imply that methylation of this gene is strongly driven by genotypes of known common SNPs, suggesting that methylation differences at these sites are not readably picked up by GWAS. In the near future, dense genotyping coupled with DNA methylation and expression levels across different tissue and cell types from projects like PsychENCODE  will help to resolve whether the differences are driven by genetic variation or if they represent independent epigenetic signal.
The strength of the study was the use of the same tissue and analysis of the exact same CpG sites, as identified as the top differentially methylated sites in the large EWAS of SZ . Also, we used a relatively large sample of bipolar cases and controls, with genotypes available for the majority of participants.
A limitation of this study is the possible confounder of age. Because the BD cases in our study were slightly older than controls, we analyzed the controls and cases separately and found no effect of age on methylation at this locus. Also, because the FAM63B hypomethylation was initially identified in a large EWAS study of SZ , and replicated in an independent sample, while adjusting for age, we find it unlikely that the hypomethylation in our study is driven by this covariate.
A second limitation is the possible confounder of blood cell composition on methylation that we were not able to correct for because of the candidate-gene approach in this study. This limitation is not specific to our study. While we acknowledge that cell heterogeneity may explain some of the variation in the entire dataset (also among controls), it becomes a confounder only if cell composition is systematically different in cases. If cell composition is a confounder, it must be shared between BD and SZ.
Thirdly, medication could influence the methylation levels of FAM63B. Interestingly, the use of mood-stabilizing medication has been shown to influence the DNA methylation patterns in blood in a recent study by Houtepen and co-workers , using primarily the Infinium HumanMethylation27 to measure methylation levels. This array does not cover sites in FAM63B, so the effect of medication on FAM63B methylation in BD (and SZ) remains to be determined. It would be of great interest in the future to collect medication information (drug type, dosage and patient response). This not only would permit correction for possible medication effects in methylation data but also would also allow separation of the BD patients into pharmacological subphenotypes that could provide a link between methylation signatures and medication response.
The biological function of FAM63B is currently not well described. The gene is expressed across most tissues, with highest expression in the cerebellar hemisphere and cerebellum according to the genotype-tissue expression (GTEx) portal  (Additional file 8: Figure S4). In the BioGPS reference panel of normal human tissues , high FAM63B expression was specifically apparent in the pineal body (Additional file 9: Figure S5), a small endocrine gland positioned in the center of the brain. Interestingly, the pineal body is known to be involved in producing and releasing melatonin which is involved in the circadian clock . Disruption of the circadian clock has been linked to the etiology of multiple psychiatric disorders . In the future, inclusion of information on diurnal mood variation and sleeping patterns of investigated individuals could allow for investigation of possible correlations between DNA methylation levels of FAM63B and the circadian clock.
In conclusion, we have identified FAM63B hypomethylation in BD. Our data supports that FAM63B is a shared epigenetic risk gene for BD and SZ.