Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n=321,223) and offspring birth weight (n=230,069 mothers), we identified 190 independent association signals (129 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic effects, and then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of those alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Epigenetic misregulation is consistent with various non-Mendelian features of schizophrenia and bipolar disorder. To date, however, few studies have investigated the role of DNA methylation in major psychosis, and none have taken a genome-wide epigenomic approach. In this study we used CpG-island microarrays to identify DNA-methylation changes in the frontal cortex and germline associated with schizophrenia and bipolar disorder. In the frontal cortex we find evidence for psychosis-associated DNA-methylation differences in numerous loci, including several involved in glutamatergic and GABAergic neurotransmission, brain development, and other processes functionally linked to disease etiology. DNA-methylation changes in a significant proportion of these loci correspond to reported changes of steady-state mRNA level associated with psychosis. Gene-ontology analysis highlighted epigenetic disruption to loci involved in mitochondrial function, brain development, and stress response. Methylome network analysis uncovered decreased epigenetic modularity in both the brain and the germline of affected individuals, suggesting that systemic epigenetic dysfunction may be associated with major psychosis. We also report evidence for a strong correlation between DNA methylation in the MEK1 gene promoter region and lifetime antipsychotic use in schizophrenia patients. Finally, we observe that frontal-cortex DNA methylation in the BDNF gene is correlated with genotype at a nearby nonsynonymous SNP that has been previously associated with major psychosis. Our data are consistent with the epigenetic theory of major psychosis and suggest that DNA-methylation changes are important to the etiology of schizophrenia and bipolar disorder.

OBJECTIVETo characterize physiologic subtypes of gestational diabetes mellitus (GDM).RESEARCH DESIGN AND METHODSInsulin sensitivity and secretion were estimated in 809 women at 24–30 weeks' gestation, using oral glucose tolerance test–based indices. In women with GDM (8.3%), defects in insulin sensitivity or secretion were defined below the 25th percentile in women with normal glucose tolerance (NGT). GDM subtypes were defined based on the defect(s) present.RESULTSRelative to women with NGT, women with predominant insulin sensitivity defects (51% of GDM) had higher BMI and fasting glucose, larger infants (birth weight z score 0.57 [−0.01 to 1.37] vs. 0.03 [−0.53 to 0.52], P = 0.001), and greater risk of GDM-associated adverse outcomes (57.6 vs. 28.2%, P = 0.003); differences were independent of BMI. Women with predominant insulin secretion defects (30% of GDM) had BMI, fasting glucose, infant birth weights, and risk of adverse outcomes similar to those in women with NGT.CONCLUSIONSHeterogeneity of physiologic processes underlying hyperglycemia exists among women with GDM. GDM with impaired insulin sensitivity confers a greater risk of adverse outcomes.