Osteoporosis is a common disease diagnosed primarily by measurement of bone mineral density (BMD). We undertook a genome-wide association study in 142,487 individuals from the UK Biobank to identify loci associated with BMD estimated by quantitative ultrasound of the heel (“eBMD”). We identified 307 conditionally independent SNPs attaining genome-wide significance at 203 loci, explaining approximately 12% of the phenotypic variance. These included 153 novel loci, and several rare variants with large effect sizes. To investigate underlying mechanisms we undertook: 1) bioinformatic, functional genomic annotation and human osteoblast expression studies; 2) gene function prediction; 3) skeletal phenotyping of 120 knockout mice with deletions of genes adjacent to lead independent SNPs; and 4) analysis of gene expression in mouse osteoblasts, osteocytes and osteoclasts. These studies strongly implicate GPC6 as a novel determinant of BMD and also identify abnormal skeletal phenotypes in knockout mice for a further 100 prioritized genes.

BackgroundSexual dimorphism in DNA methylation levels is a recurrent epigenetic feature in different human cell types and has been implicated in predisposition to disease, such as psychiatric and autoimmune disorders. To elucidate the genetic origins of sex-specific DNA methylation, we examined DNA methylation levels in fibroblast cell lines and blood cells from individuals with different combinations of sex chromosome complements and sex phenotypes focusing on a single autosomal region––the differentially methylated region (DMR) in the promoter of the zona pellucida binding protein 2 (ZPBP2) as a reporter.ResultsOur data show that the presence of the sex determining region Y (SRY) was associated with lower methylation levels, whereas higher X chromosome dosage in the absence of SRY led to an increase in DNA methylation levels at the ZPBP2 DMR. We mapped the X-linked modifier of DNA methylation to the long arm of chromosome X (Xq13-q21) and tested the impact of mutations in the ATRX and RLIM genes, located in this region, on methylation levels. Neither ATRX nor RLIM mutations influenced ZPBP2 methylation in female carriers.ConclusionsWe conclude that sex-specific methylation differences at the autosomal locus result from interaction between a Y-linked factor SRY and at least one X-linked factor that acts in a dose-dependent manner.Electronic supplementary materialThe online version of this article (10.1186/s13293-018-0169-7) contains supplementary material, which is available to authorized users.

5‐hydroxymethylcytosine (5hmC) is a methylation state linked with gene regulation, commonly found in cells of the central nervous system. 5hmC is associated with demethylation of cytosines from 5‐methylcytosine (5mC) to the unmethylated state. The presence of 5hmC can be inferred by a paired experiment involving bisulfite and oxidation‐bisulfite treatments on the same sample, followed by a methylation assay using a platform such as the Illumina Infinium MethylationEPIC BeadChip (EPIC). Existing methods for analysis of the resulting EPIC data are not ideal. Most approaches ignore the correlation between the two experiments and any imprecision associated with DNA damage from the additional treatment. Estimates of 5mC/5hmC levels free from these limitations are desirable to reveal associations between methylation states and phenotypes. We propose a hierarchical Bayesian method called Constrained HYdroxy Methylation Estimation (CHYME) to simultaneously estimate 5mC/5hmC signals as well as any associations between these signals and covariates or phenotypes, while accounting for the potential impact of DNA damage and dependencies induced by the experimental design. Simulations show that CHYME has valid type 1 error and better power than a range of alternative methods, including the popular OxyBS method and linear models on transformed proportions. Other methods we examined suffer from hugely inflated type 1 error for inference on 5hmC proportions. We use CHYME to explore genome‐wide associations between 5mC/5hmC levels and cause of death in postmortem prefrontal cortex brain tissue samples. These analyses indicate that CHYME is a useful tool to reveal phenotypic associations with 5mC/5hmC levels.

IntroductionMaternal mental well being influences offspring development. Research suggests that an interplay between genetic and environmental factors underlies this familial transmission of mental disorders.ObjectivesTo explore an interaction between genetic and environmental factors to predict trajectories of maternal mental well being, and to examine whether these trajectories are associated with epigenetic modifications in mothers and their offspring.MethodWe assessed maternal childhood trauma and rearing experiences, prenatal and postnatal symptoms of depression and stress experience from 6 to 72 months postpartum, and genetic and epigenetic variation in a longitudinal birth-cohort study (n = 262) (Maternal adversity, vulnerability and neurodevelopment project). We used latent class modeling to describe trajectories in maternal depressive symptoms, parenting stress, marital stress and general stress, taking polygenetic risk for major depressive disorder (MDD), a composite score for maternal early life adversities, and prenatal depressive symptoms into account.ResultsGenetic risk for MDD associated with trajectories of maternal well being in the postpartum, conditional on the experience of early life adversities and prenatal symptoms of depression. We will explore whether these trajectories are also linked to DNA methylation patterns in mothers and their offspring. Preliminary analyses suggest that maternal early life adversities associate with offspring DNA methylation age estimates, which is mediated through maternal mental well being and maternal DNA methylation age estimates.ConclusionWe found relevant gene-environment interactions associated with trajectories of maternal well being. Our findings inform research on mechanisms underlying familial transmission of vulnerability for psychopathology and might thus be relevant to prevention and early intervention programs.Disclosure of interestThe authors have not supplied their declaration of competing interest.