Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of genes important to bone biology in general, and particularly for identifying components unique to intramembranous ossification, which cannot be captured at other skeletal sites. We assessed genetic determinants of SK-BMD in 43,800 individuals, identifying 59 genome-wide significant loci (4 novel), explaining 12.5% of its variance. Pathway and enrichment analyses of the association signals resulted in clustering within gene-sets involved in regulating the development of the skeleton; overexpressed in the musculoskeletal system; and enriched in enhancer and transcribed regions in osteoblasts. From the four novel loci (mapping to ZIC1, PRKAR1A, ATP6V1C1, GLRX3), two (ZIC1 and PRKAR1A) have previously been related to craniofacial developmental defects. Functional validation of skull development in zebrafish revealed abnormal cranial bone initiation that culminated in ectopic sutures and reduced BMD in mutated zic1 and atp6v1c1 fish and asymmetric bone growth and elevated BMD in mutated prkar1a fish. We confirmed a role of ZIC1 loss-of-function in suture patterning and discovered ATP6V1C1 gene associated with suture development. In light of the evidence presented suggesting that SK-BMD is genetically related to craniofacial abnormalities, our study opens new avenues to the understanding of the pathophysiology of craniofacial defects and towards the effective pharmacological treatment of bone diseases.

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5,019 blood samples collected at multiple time-points from birth to late adolescence from 2,348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs).Evidence for nonlinear change and inter-individual variation in nonlinear trajectories was somewhat less common (11% and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. By contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions.These findings depict a methylome undergoing widespread and often nonlinear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

103Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our 104 understanding of the functional relevance of the phenomenon remains limited. Because obesity is the main 105 risk factor for T2D and a driver of methylation from previous study, we aimed to explore the effect of DNA 106 methylation in the early phases of T2D pathology while accounting for body mass index (BMI). We performed 107 a blood-based epigenome-wide association study (EWAS) of fasting glucose and insulin among 4,808 non-108 diabetic European individuals and replicated the findings in an independent sample consisting of 11,750 non-109 diabetic subjects. We integrated blood-based in silico cross-omics databases comprising genomics, 110 epigenomics and transcriptomics collected by BIOS project of the Biobanking and BioMolecular resources 111 Research Infrastructure of the Netherlands (BBMRI-NL), the Meta-Analyses of Glucose and Insulin-related 112 traits Consortium (MAGIC), the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, and 113 the tissue-specific Genotype-Tissue Expression (GTEx) project. We identified and replicated nine novel 114 differentially methylated sites in whole blood (P-value < 1.27 × 10 -7 ): sites in LETM1, RBM20, IRS2, MAN2A2 115 genes and 1q25.3 region were associated with fasting insulin; sites in FCRL6, SLAMF1, APOBEC3H genes and 116 15q26.1 region were associated with fasting glucose. The association between SLAMF1, APOBEC3H and 117 15q26.1 methylation sites and glucose emerged only when accounted for BMI. Follow-up in silico cross-omics 118 analyses indicate that the cis-acting meQTLs near SLAMF1 and SLAMF1 expression are involved in glucose level 119 regulation. Moreover, our data suggest that differential methylation in FCRL6 may affect glucose level and the 120 risk of T2D by regulating FCLR6 expression in the liver. In conclusion, the present study provided nine new DNA 121 methylation sites associated with glycemia homeostasis and also provided new insights of glycemia related loci 122 into the genetics, epigenetics and transcriptomics pathways based on the integration of cross-omics data in 123 silico. 124 125 146 Results 147 1. Blood-based epigenome-wide association analysis of glycemic traits 148The discovery phase was based on four European cohorts (Supplementary Table 1). The meta-analysis 149 revealed DNA methylation in 28 unique CpG sites associated with fasting glucose (11 CpG sites, n = 4,808) 150 and/or insulin (20 CpG sites, n = 4,740) at epigenome-wide significance (P-value < 1.27 × 10 -7 ) in either the 151 baseline model without body mass index (BMI) adjustment or in the second model with BMI adjustment. Of 152 these 28 CpG sites, 15 were novel (Table 1) while 13 were identified by earlier EWAS studies of either T2D or 153 related traits, including glucose, insulin, hemoglobin A1c (HbA1c), homeostatic model assessment-insulin

Background: DNA methylation is an epigenetic mechanism involved in human development. Numerous epigenome-wide association studies (EWAS) have investigated the associations of DNA methylation at single CpG sites with childhood outcomes. However, the overall contribution of DNA methylation across the genome (R2Methylation) towards childhood phenotypes is unknown. An estimate of R2Methylation would provide context regarding the importance of DNA methylation explaining variance in health outcomes. Methods: We estimated the variance explained by epigenome-wide cord blood methylation (R2Methylation) for five childhood phenotypes: gestational age, birth weight, and body mass index (BMI), IQ and ADHD symptoms at school age. We adapted a genome-based restricted maximum likelihood (GREML) approach with cross-validation (CV) to DNA methylation data and applied it in two population-based birth cohorts: ALSPAC (n=775) and Generation R (n=1382). Results: Using information from >470,000 autosomal probes we estimated that DNA methylation at birth explains 45% (SDCV = 0.07) of gestational age variance and 16% (SDCV = 0.05) of birth weight variance. The R2Methylation estimates for BMI, IQ and ADHD symptoms at school age estimates were near 0% across almost all cross-validation iterations. Conclusions: The results suggest that cord blood methylation explains a moderate to large degree of variance in gestational age and birth weight, in line with the success of previous EWAS in identifying numerous CpG sites associated with these phenotypes. In contrast, we could not obtain a reliable estimate for school-age BMI, IQ and ADHD symptoms. This may reflect a null bias due to insufficient sample size to detect variance explained in more weakly associated phenotypes, although the true R2Methylation for these phenotypes is likely below that of gestational age and birth weight when using DNA methylation at birth.