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Conduct problems in children and adolescents affect individuals, families, and their environment. The aetiology of conduct problems involves a combination of genetic and environmental risk factors, many of which are inherently linked to parental characteristics given parents’ central role in children’s lives across development. It is important to disentangle to what extent links between parental characteristics and children’s behaviour are due to transmission of genetic risk or due to environmentally mediated genetic influences on offspring behaviour (i.e., genetic nurture). We used 31,346 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 12 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Among genotyped trios, maternal reports of conduct problems at age 8 years were available for 15,516 children. We found significant genetic transmission effects on conduct problems for 11 out of 12 PGS (strongest positive association: PGS for smoking, β = 0.07 95% confidence interval = [0.05, 0.08]; strongest negative association: PGS for education, β = –0.04, 95% confidence interval = [¬–0.06, –0.02]). Conversely, we did not find strong evidence for genetic nurture effects for child conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics like psychiatric conditions or risk behaviours and child conduct problems. Our results may also indicate that genetic nurture is of limited aetiological importance for conduct problems—though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers having experienced childhood maltreatment (CM). OXTR DNA methylation and gene expression was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon 3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, very high mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study characterized the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to guide future studies in their choice of CpG sites.

Antenatal synthetic glucocorticoid (sGC) treatment is a potent modifier of the hypothalamic-pituitary-adrenal (HPA) axis. In this context, epigenetic modifications are discussed as potential regulators explaining how prenatal exposure to GCs might translate into persistent changes of HPA axis “functioning”. The purpose of this study was to investigate whether DNA methylation and gene expression profiles of stress-associated genes (NR3C1; FKBP5; SLC6A4) may mediate the persistent effects of sGC on cortisol stress reactivity that have been previously observed. In addition, hair cortisol concentrations (hairC) were investigated as a valid biomarker of long-term HPA axis activity. This cross-sectional study comprised 108 term-born children and adolescents, including individuals with antenatal GC treatment and controls. From whole blood, DNA methylation was analyzed by targeted deep bisulfite sequencing. Relative mRNA expression was determined by RT-qPCR experiments and qBase analysis. Acute stress reactivity was assessed by the Trier Social Stress Test (TSST) measuring salivary cortisol by ELISA and hairC concentrations were determined from hair samples by liquid chromatography coupled with tandem mass spectrometry. First, no differences in DNA methylation and mRNA expression levels of the stress-associated genes between individuals treated with antenatal sGC compared to controls were found. Second, DNA methylation and mRNA expression levels were neither associated with cortisol stress reactivity nor with hairC. These findings do not corroborate the belief that DNA methylation and mRNA expression profiles of stress-associated genes (NR3C1; FKBP5; SLC6A4) play a key mediating role of the persistent effects of sGC on HPA axis functioning.

DNA methylation analysis is increasingly used in stress research. Available methods are expensive, laborious and often limited by either the analysis of short CpG stretches or low assay sensitivity. Here, we present a cost-efficient next generation sequencing-based strategy for the simultaneous investigation of multiple candidate genes in large cohorts. To illustrate the method, we present analysis of four candidate genes commonly assessed in psychoneuroendocrine research: Glucocorticoid receptor (NR3C1), Serotonin transporter (SLC6A4), FKBP Prolyl isomerase 5 (FKBP5), and the Oxytocin receptor (OXTR).DNA methylation standards and DNA of a female and male donor were bisulfite treated in three independent trials and were used to generate sequencing libraries for 42 CpGs from the NR3C1 1F promoter region, 83 CpGs of the SLC6A4 5’ regulatory region, 5 CpGs located in FKBP5 intron 7, and additional 12 CpGs located in a potential enhancer element in intron 3 of the OXTR. In addition, DNA of 45 patients with borderline personality disorder (BPD) and 45 healthy controls was assayed. Multiplex libraries of all samples were sequenced on a MiSeq system and analyzed for mean methylation values of all CpG sites using amplikyzer2 software.Results indicated excellent accuracy of the assays when investigating replicates generated from the same bisulfite converted DNA, and very high linearity (R2> 0.9) of the assays shown by the analysis of differentially methylated DNA standards. Comparing DNA methylation between BPD and healthy controls revealed no biologically relevant differences.The technical approach as described here facilitates targeted DNA methylation analysis and represents a highly sensitive, cost-efficient and high throughput tool to close the gap between coverage and precision in epigenetic research of stress-associated phenotypes.

Adverse childhood experiences such as maltreatment or neglect are associated with mental health problems in adulthood. Changes in the regulation of the psychological and physiological stress reaction, mediated via epigenetic modifications, are discussed as potential mechanisms. This study aimed to replicate the role of DNA methylation of the KITLG gene in mediating the association between childhood adversity and stress-induced cortisol reactivity in a sample of adults reporting childhood adversity and a matched control group (N=60). DNA was extracted from purified CD14+ monocytes and genome-wide DNA methylation was assessed with the 450k BeadChip for targeted replication and exploratory analyses. As previously reported, childhood adversity was associated with significantly lower cortisol reactivity to stress. We could neither replicate the association between KITLG DNA methylation and cortisol stress reactivity nor the association with childhood adversity. Moreover, DNA methylation of the target CpG (cg27512205) was not associated with KITLG mRNA expression in monocytes. Exploratory analyses of array-wide DNA methylation patterns showed no significant results for individual sites after correction for multiple testing – neither in association with childhood trauma nor with adult cortisol stress reactivity. The analysis of differentially methylated regions (DMRs) revealed two significant regions which both mapped to non-coding genes in the association with cortisol stress reactivity. The mediating role of DNA methylation of the KITLG locus in the association between childhood adversity and cortisol stress reactivity could not be replicated in monocytes. In addition to differences in investigated tissue, reasons for non-replication might include differences between samples in age, ethnicity, trauma severity, and cortisol reactivity.

Genetic influences are ubiquitous as virtually all phenotypes and most exposures typically classified as environmental have been found to be heritable. A polygenic score summarises the associations between millions of genetic variants and an outcome in a single value for each individual. Ever lowering costs have enabled the genotyping of many samples relevant to child psychology and psychiatry research, including cohort studies, leading to the proliferation of polygenic score studies. It is tempting to assume that associations detected between polygenic scores and phenotypes in those studies only reflect genetic effects. However, such associations can reflect many pathways (e.g. via environmental mediation) and biases.Here, we provide a comprehensive overview of the many reasons why associations between polygenic scores, environmental exposures, and phenotypes exist. We include formal representations of common analyses in polygenic score studies using structural equation modelling. We derive biases, provide illustrative empirical examples and, when possible, mention steps that can be taken to alleviate those biases.Structural equation models and derivations show the many complexities arising from jointly modelling polygenic scores with environmental exposures and phenotypes. Counter-intuitive examples include that: (a) associations between polygenic scores and phenotypes may exist even in the absence of direct genetic effects; (b) associations between child polygenic scores and environmental exposures can exist in the absence of evocative/active gene-environment correlations; and (c) adjusting an exposure-outcome association for a polygenic score can increase rather than decrease bias.Strikingly, using polygenic scores may, in some cases, lead to more bias than not using them. Appropriately conducting and interpreting polygenic score studies thus requires researchers in child psychology and psychiatry and beyond to be versed in both epidemiological and genetic methods or build on interdisciplinary collaborations.