A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Self-selection in epidemiological studies may introduce selection bias and influence the validity of study results. To evaluate potential bias due to self-selection in a large prospective pregnancy cohort in Norway, the authors studied differences in prevalence estimates and association measures between study participants and all women giving birth in Norway. Women who agreed to participate in the Norwegian Mother and Child Cohort Study (43.5% of invited; n = 73 579) were compared with all women giving birth in Norway (n = 398 849) using data from the population-based Medical Birth Registry of Norway in 2000-2006. Bias in the prevalence of 23 exposure and outcome variables was measured as the ratio of relative frequencies, whereas bias in exposure-outcome associations of eight relationships was measured as the ratio of odds ratios. Statistically significant relative differences in prevalence estimates between the cohort participants and the total population were found for all variables, except for maternal epilepsy, chronic hypertension and pre-eclampsia. There was a strong under-representation of the youngest women (<25 years), those living alone, mothers with more than two previous births and with previous stillbirths (relative deviation 30-45%). In addition, smokers, women with stillbirths and neonatal death were markedly under-represented in the cohort (relative deviation 22-43%), while multivitamin and folic acid supplement users were over-represented (relative deviation 31-43%). Despite this, no statistically relative differences in association measures were found between participants and the total population regarding the eight exposure-outcome associations. Using data from the Medical Birth Registry of Norway, this study suggests that prevalence estimates of exposures and outcomes, but not estimates of exposure-outcome associations are biased due to self-selection in the Norwegian Mother and Child Cohort Study.

Familial correlations in birth weight and gestational age have been explained by fetal and maternal genetic factors, mainly in studies on offspring of twins. The aim of the present intergenerational study was to estimate and compare fetal and maternal genetic effects and shared sibling environmental effects on birth weight and gestational age and also on crown-heel length and head circumference. The authors used path analysis and maximum likelihood principles to estimate these effects and, at the same time, to adjust for covariates. Parent-offspring data were obtained from the Medical Birth Registry of Norway from 1967 to 2004. For the analysis of birth weight and crown-heel length, 101,748 families were included; for gestational age, 91,617 families; and for head circumference, 77,044 families. Assuming no cultural transmission and random mating, the authors found that fetal genetic factors explained 31% of the normal variation in birth weight and birth length, 27% of the variation in head circumference, and 11% of the variation in gestational age. Maternal genetic factors explained 22% of the variation in birth weight, 19% of the variation in birth length and head circumference, and 14% of the variation in gestational age. Relative to the proportion of explained variation, fetal genes were most important for birth length and head circumference.

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Percentiles for birthweight by gestational age are presented for clinical use, based on a current period 1987-98, covering 20-44 completed gestational weeks. In the final standards we excluded stillbirths, infants born with malformations and cesarean sections. Birthweights in the Scandinavian populations are high and standards from other populations may not be representative, especially for the term weeks. Also, the secular changes demonstrated in this study indicate that old birthweight by gestational age standards need revision, especially due to changes in obstetrical routines influencing preterm data.

Elevated tHcy concentration is associated with common pregnancy complications and adverse pregnancy outcomes.

BackgroundWe explored the association between gestational age and cord blood DNA methylation at birth and whether DNA methylation could be effective in predicting gestational age due to limitations with the presently used methods. We used data from the Norwegian Mother and Child Birth Cohort study (MoBa) with Illumina HumanMethylation450 data measured for 1753 newborns in two batches: MoBa 1, n = 1068; and MoBa 2, n = 685. Gestational age was computed using both ultrasound and the last menstrual period. We evaluated associations between DNA methylation and gestational age and developed a statistical model for predicting gestational age using MoBa 1 for training and MoBa 2 for predictions. The prediction model was additionally used to compare ultrasound and last menstrual period-based gestational age predictions. Furthermore, both CpGs and associated genes detected in the training models were compared to those detected in a published prediction model for chronological age.ResultsThere were 5474 CpGs associated with ultrasound gestational age after adjustment for a set of covariates, including estimated cell type proportions, and Bonferroni-correction for multiple testing. Our model predicted ultrasound gestational age more accurately than it predicted last menstrual period gestational age.ConclusionsDNA methylation at birth appears to be a good predictor of gestational age. Ultrasound gestational age is more strongly associated with methylation than last menstrual period gestational age. The CpGs linked with our gestational age prediction model, and their associated genes, differed substantially from the corresponding CpGs and genes associated with a chronological age prediction model.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1063-4) contains supplementary material, which is available to authorized users.