Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa

Correction: Volume: 23 Issue: 9 DOI: 10.1038/mp.2017.202 Published: SEP 2018Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P = 9.89 x 10(-6)), and rs7700147, an intergenic variant (P = 2.93 x 10(-5)). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes.Peer reviewe

The Familial Clustering of Age at Menarche in Extended Twin Families

The timing of puberty is complex, possibly involving many genetic factors that may interact with environmental influences. Familial resemblance for age at menarche was studied in a sample of 4,995 female twins, 1,296 sisters, 2,946 mothers and 635 female spouses of male twins. They had indicated their age at menarche as part of a larger longitudinal survey. We assessed assortative mating for age at menarche, gene–environment interaction effects and estimated the heritability of individual differences in pubertal timing. There was significant evidence of gene–environment interaction, accounting for 1.5% of the variance. There was no indication of consistent mate assortment on age at menarche. Individual differences in age at menarche are highly heritable, with additive genetic factors explaining at least 70% of the true variation. An additional 1.5% of the variation can be explained by a genotype–environment interaction effect where environmental factors are more important in individuals genetically predisposed for late menarche

Associations of Sleep Duration and Screen Time with Incidence of Overweight in European Children: The IDEFICS/I.Family Cohort

Introduction: Over the past decades, children have been increasingly using screen devices, while at the same time their sleep duration has decreased. Both behaviors have been associated with excess weight, and it is possible they act as mutually reinforcing behaviors for weight gain. The aim of the study was to explore independent, prospective associations of screen time and sleep duration with incident overweight in a sample of European children. Methods: Data from 4, 285 children of the IDEFICS/I.Family cohort who were followed up from 2009/2010 to 2013/2014 were analyzed. Hours per day of screen time and of sleep duration were reported by parents at baseline. Logistic regression analyses were carried out in separate and mutually adjusted models controlled for sex, age, European country region, parental level of education, and baseline BMI z-scores. Results: Among normal weight children at baseline (N = 3, 734), separate models suggest that every hour increase in screen time and every hour decrease in sleep duration were associated with higher odds of the child becoming overweight or obese at follow-up (OR = 1.16, 95% CI: 1.02-1.32 and OR = 1.23, 95% CI: 1.05-1.43, respectively). In the mutually adjusted model, both associations were attenuated slightly (screen time OR = 1.13, 95% CI: 0.99-1.28; sleep duration OR = 1.20, 95% CI: 1.03-1.40), being consistently somewhat stronger for sleep duration. Discussion/Conclusion: Both screen time and sleep duration increased the incidence of overweight or obesity by 13-20%. Interventions that include an emphasis on adequate sleep and minimal screen time are needed to establish their causal role in the prevention of overweight and obesity among European children. © 2021 The Author(s). Published by S. Karger AG, Basel

Ketone body 3-hydroxybutyrate as a biomarker of aggression

Human aggression is a complex behaviour, the biological underpinnings of which remain poorly known. To gain insights into aggression biology, we studied relationships with aggression of 11 low-molecular-weight metabolites (amino acids, ketone bodies), processed using H-1 nuclear magnetic resonance spectroscopy. We used a discovery sample of young adults and an independent adult replication sample. We studied 725 young adults from a population-based Finnish twin cohort born 1983-1987, with aggression levels rated in adolescence (ages 12, 14, 17) by multiple raters and blood plasma samples at age 22. Linear regression models specified metabolites as the response variable and aggression ratings as predictor variables, and included several potential confounders. All metabolites showed low correlations with aggression, with only one-3-hydroxybutyrate, a ketone body produced during fasting-showing significant (negative) associations with aggression. Effect sizes for different raters were generally similar in magnitude, while teacher-rated (age 12) and self-rated (age 14) aggression were both significant predictors of 3-hydroxybutyrate in multi-rater models. In an independent replication sample of 960 adults from the Netherlands Twin Register, higher aggression (self-rated) was also related to lower levels of 3-hydroxybutyrate. These exploratory epidemiologic results warrant further studies on the role of ketone metabolism in aggression.Peer reviewe

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs. Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.Peer reviewe