BACKGROUND: The genetic and environmental aetiology of autistic and Attention Deficit Hyperactivity Disorder (ADHD) traits is known to vary spatially, but does this translate into variation in the association of specific common genetic variants?
METHODS: We mapped associations between polygenic scores for autism and ADHD and their respective traits in the Avon Longitudinal Study of Parents and Children (N = 4,255-6,165) across the area surrounding Bristol, UK, and compared them to maps of environments associated with the prevalence of autism and ADHD.
RESULTS: Our results suggest genetic associations vary spatially, with consistent patterns for autistic traits across polygenic scores constructed at different p-value thresholds. Patterns for ADHD traits were more variable across thresholds. We found that the spatial distributions often correlated with known environmental influences.
CONCLUSIONS: These findings shed light on the factors that contribute to the complex interplay between the environment and genetic influences in autistic and ADHD traits.

OBJECTIVE: Few longitudinal studies have investigated the mediating role of inflammation during childhood in associations between prenatal maternal stress and adolescent mental health. The objective of this study was to examine the associations between prenatal maternal stress, concentrations of immune markers at age 9, and symptoms of generalized anxiety disorder (GAD) and depression during adolescence.
METHODS: This study included 3723 mother-child pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Prenatal maternal stress was examined using 55 items measured during pregnancy. Inflammation was assessed using serum concentrations of interleukin-6 (IL-6) and C-reactive protein (CRP) when children were 9 years old. GAD and depression were assessed when children were 16 and 18 years of age, respectively. Analyses comprised of structural equation models.
RESULTS: Prenatal maternal stress was associated with higher concentrations of IL-6 in childhood, and with greater symptoms of depression and GAD in adolescence. However, we did not observe associations between prenatal maternal stress and CRP; also, CRP and IL-6 were not associated with depression and GAD. There was no evidence that CRP and IL-6 mediated the associations between prenatal maternal stress and either GAD or depression.
CONCLUSIONS: Prenatal maternal stress is associated with IL-6 levels in childhood, and with GAD and depression during adolescence. Future studies should examine immune activity at multiple points during development in relation to mental health into adulthood to determine whether inflammation at different points during development could increase risk for mental health problems among children whose mothers experienced significant stressors during pregnancy.

BACKGROUND: Emotional problems (EPs) increase sharply after mid-adolescence. Earlier EPs are associated with poorer long-term outcomes, and their underlying mechanisms may differ to later-onset EPs. Given an established relationship between ADHD, autism, and later depression, we aimed to examine associations between neurodevelopmental conditions and correlates and early adolescent-onset EPs.
METHODS: Adolescents in two UK population cohorts, Avon Longitudinal Study of Parents and Children (ALSPAC) and Millennium Cohort Study (MCS), were included. Individuals scoring >6 on the Strengths and Difficulties Questionnaire (SDQ) emotional problems subscale between ages 11-14 were defined as having early adolescent-onset EP, whilst those scoring >6 for the first time at 16-25 were defined as having later-onset EP. We tested associations between early adolescent-onset EP (total cases = 887, controls = 19,582) and ICD-10/DSM-5 neurodevelopmental conditions and known correlates, including: sex, birth complications, low cognitive ability, special educational needs (SEND), and epilepsy. Analyses were conducted separately in ALSPAC and MCS then meta-analysed.
RESULTS: In the meta-analysis of both cohorts, early adolescent-onset EPs were associated with female sex and greater likelihood of low cognitive ability, SEND, autism, ADHD, and reading difficulties. Compared to later-onset EP, early adolescent-onset EPs were associated with male sex, low cognitive ability, SEND, epilepsy, ASD, ADHD, and reading difficulties.
CONCLUSIONS: A clinical definition of depression/anxiety was available only in ALSPAC, instead we primarily defined EP via questionnaires, which capture a broader phenotype.
CONCLUSIONS: Individuals with early adolescent-onset EP are likely to have a co-occurring neurodevelopmental condition. Clinicians should consider assessing for neurodevelopmental conditions in young adolescents with EPs.

UNASSIGNED: Null mutations within the filaggrin ( FLG) gene are established genetic risk factors for atopic dermatitis. Studies of FLG have typically used sequencing or bespoke genotyping. Large-scale population cohorts with genome-wide imputed data offer powerful genetic analysis opportunities, but bespoke FLG genotyping is often not feasible in such studies. Therefore, we aimed to determine the quality of selected FLG null genotype data extracted from genome-wide imputed sources, focussing on UK population data.
UNASSIGNED: We compared the allele frequencies of three FLG null mutations that could be detected by imputation (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter; commonly referred to as R501X, R2447X and S3247X respectively) in directly genotyped and genome-wide imputed data in the ALSPAC cohort. Logistic regression analysis was used to test the association of atopic dermatitis with imputed and genotyped FLG null mutations in ALSPAC and UK Biobank to investigate the usefulness of imputed FLG data.
UNASSIGNED: The three FLG null mutations appear to be well imputed in datasets that use the Haplotype Reference Consortium (HRC) for imputation (0.3% discordance compared with directly genotyped data). However, a greater proportion of null alleles failed imputation compared to wild-type alleles. Despite the calling of FLG mutations in imputed data being imperfect, they are still strongly associated with atopic dermatitis (p-values between 7x10 -10 and 5x10 -75 in UK Biobank).
UNASSIGNED: HRC imputed data appears to be adequate for UK population-based genetic analysis of selected FLG null mutations (p.Arg501Ter, p.Arg2447Ter and p.Ser3247Ter).

Genetic variants used as instruments for exposures in Mendelian randomisation (MR) analyses may have horizontal pleiotropic effects (i.e., influence outcomes via pathways other than through the exposure), which can undermine the validity of results. We examined the extent of this using smoking behaviours as an example. We first ran a phenome-wide association study in UK Biobank, using a smoking initiation genetic instrument. From the most strongly associated phenotypes, we selected those we considered could either plausibly or not plausibly be caused by smoking. We examined associations between genetic instruments for smoking initiation, smoking heaviness and lifetime smoking and these phenotypes in UK Biobank and the Avon Longitudinal Study of Parents and Children (ALSPAC). We conducted negative control analyses among never smokers, including children. We found evidence that smoking-related genetic instruments were associated with phenotypes not plausibly caused by smoking in UK Biobank and (to a lesser extent) ALSPAC. We observed associations with phenotypes among never smokers. Our results demonstrate that smoking-related genetic risk scores are associated with unexpected phenotypes that are less plausibly downstream of smoking. This may reflect horizontal pleiotropy in these genetic risk scores, and we would encourage researchers to exercise caution this when using these and genetic risk scores for other complex behavioural exposures. We outline approaches that could be taken to consider this and overcome issues caused by potential horizontal pleiotropy, for example, in genetically informed causal inference analyses (e.g., MR) it is important to consider negative control outcomes and triangulation approaches, to avoid arriving at incorrect conclusions.

BACKGROUND: Infections during pregnancy have been robustly associated with adverse mental and physical health outcomes in offspring, yet the underlying molecular pathways remain largely unknown. Here, we examined whether exposure to common infections in utero associates with DNA methylation (DNAm) patterns at birth and whether this in turn relates to offspring health outcomes in the general population.
METHODS: Using data from 2,367 children from the Dutch population-based Generation R Study, we first performed an epigenome-wide association study to identify differentially methylated sites and regions at birth associated with prenatal infection exposure. We also examined the influence of infection timing by using self-reported cumulative infection scores for each trimester. Second, we sought to develop an aggregate methylation profile score (MPS) based on cord blood DNAm as an epigenetic proxy of prenatal infection exposure and tested whether this MPS prospectively associates with offspring health outcomes, including psychiatric symptoms, BMI, and asthma at ages 13-16 years. Third, we investigated whether prenatal infection exposure associates with offspring epigenetic age acceleration - a marker of biological aging. Across all analysis steps, we tested whether our findings replicate in 864 participants from an independent population-based cohort (ALSPAC, UK).
RESULTS: We observed no differentially methylated sites or regions in cord blood in relation to prenatal infection exposure, after multiple testing correction. 33 DNAm sites showed suggestive associations (p < 5e10 - 5; of which one was also nominally associated in ALSPAC), indicating potential links to genes associated with immune, neurodevelopmental, and cardiovascular pathways. While the MPS of prenatal infections associated with maternal reports of infections in the internal hold out sample in the Generation R Study (R2incremental = 0.049), it did not replicate in ALSPAC (R2incremental = 0.001), and it did not prospectively associate with offspring health outcomes in either cohort. Moreover, we observed no association between prenatal exposure to infections and epigenetic age acceleration across cohorts and clocks.
CONCLUSIONS: In contrast to prior studies, which reported DNAm differences in offspring exposed to severe infections in utero, we do not find evidence for associations between self-reported clinically evident common infections during pregnancy and DNAm or epigenetic aging in cord blood within the general pediatric population. Future studies are needed to establish whether associations exist but are too subtle to be statistically meaningful with present sample sizes, whether they replicate in a cohort with a more similar infection score as our discovery cohort, whether they occur in different tissues than cord blood, and whether other biological pathways may be more relevant for mediating the effect of prenatal common infection exposure on downstream offspring health outcomes.

Longitudinal data on religious/spiritual beliefs and behaviors (RSBB) are essential for understanding both how religion shapes our lives and the factors determining religiosity. Despite this importance, there are few longitudinal studies with detailed and repeated RSBB data. Using data spanning nearly 30 years from the parental generation of the Avon Longitudinal Study of Parents and Children (ALSPAC) based in the Southwest of England, we describe individual-level changes in various aspects of self-reported RSBB (religious belief, affiliation, and attendance, among others) measured on four occasions (pregnancy, plus 5, 9, and 28 years post-partum; approx. 3600 mothers and 1200 partners have data at all four time-points). Although RSBBs were generally consistent over time, a shift towards non-religiosity was observed; exceptions included Roman Catholic affiliation, which was remarkably stable over three decades, and religious attendance, which increased from pregnancy to 5 years, before declining at 28 years. Most changes in RSBB were minor, e.g., between \"yes\" and \"not sure\" regarding religious belief, rather than between \"yes\" and \"no.\" We also provide a simple illustrative example of how these longitudinal data can be analyzed. In addition to describing these longitudinal patterns, this paper will help inform future research using ALSPAC\'s longitudinal RSBB data.

UNASSIGNED: Autism and autistic traits have been associated with greater risk of childhood trauma and adulthood psychopathology. However, the role that childhood trauma plays in the association between autism, autistic traits and depression in adulthood is poorly understood.
UNASSIGNED: We used a UK-based birth cohort with phenotype and genotype data on autism, autistic traits, childhood trauma and depression in up to 9,659 individuals prospectively followed up from birth until age 28 years. Using mixed-effects growth-curve models, we assessed trajectories of depression symptoms over time according to the presence or absence of autism/ autistic traits and explored whether these differed by trauma exposure. We further investigated the association between autism/ autistic traits and depression in adulthood using confounder-adjusted logistic regression models and undertook mediation analyses to investigate the relationship with childhood trauma.
UNASSIGNED: All autism variables demonstrated increased depressive symptom trajectories between ages 10-28 years. Social communication difficulties (SCDs) were the most strongly associated with a depression diagnosis in adulthood (age 24 OR= 2.15; 95%CIs: 1.22-3.76). Trauma and autistic traits combined to further increase depression symptom scores. Mediation analyses provided evidence for direct pathways between autistic traits and increased risk of depression alongside indirect pathways through increased risk of trauma.
UNASSIGNED: Autism/ autistic traits increase the odds of experiencing childhood trauma and of being diagnosed with depression at age 18 and 24. Depressive symptom trajectories emergent in childhood persist into adulthood. The combined effect of SCDs and childhood trauma is greater than the individual exposures, suggesting worse depression symptomatology following trauma in individuals with SCDs.

Selection bias is a common concern in epidemiologic studies. In the literature, selection bias is often viewed as a missing data problem. Popular approaches to adjust for bias due to missing data, such as inverse probability weighting, rely on the assumption that data are missing at random and can yield biased results if this assumption is violated. In observational studies with outcome data missing not at random, Heckman\'s sample selection model can be used to adjust for bias due to missing data. In this paper, we review Heckman\'s method and a similar approach proposed by Tchetgen Tchetgen and Wirth (2017). We then discuss how to apply these methods to Mendelian randomization analyses using individual-level data, with missing data for either the exposure or outcome or both. We explore whether genetic variants associated with participation can be used as instruments for selection. We then describe how to obtain missingness-adjusted Wald ratio, two-stage least squares and inverse variance weighted estimates. The two methods are evaluated and compared in simulations, with results suggesting that they can both mitigate selection bias but may yield parameter estimates with large standard errors in some settings. In an illustrative real-data application, we investigate the effects of body mass index on smoking using data from the Avon Longitudinal Study of Parents and Children.

Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example. Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC. Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase. Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.
To inform policy and improve clinical practice, it is important that researchers who study people\'s health find out which traits might increase the risk of illness. However, it can be difficult to know which traits should be looked at. In this study, we wanted to look for traits that might increase the risk of painful and heavy periods, using data about the switches that turn our genes on and off. There are some people in the Children of the 90s study that have data on gene switches. We compared all the switches between those with and without painful or heavy periods. For painful periods, we found links with seven switches and for heavy periods, we found two. We then used another data source, called the EWAS Catalog, to see which traits were associated with these switches. The traits we found included body size, smoking and child abuse. Finally, when using data on traits from the wider Children of the 90s group, we found that smoking and more difficult childhoods were some of the traits related to painful and heavy periods. A good thing about this approach is that we could find new traits that might increase the risk of painful or heavy periods; these should be looked at in future studies.