Polygenic risk for schizophrenia and season of birth within the UK Biobank cohort

Background: There is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this ‘season of birth’ effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon. Methods: Here we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth. Results: Neither genetic measure was associated with season or month of birth within the UKBB sample. Conclusions: As our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure

Large-scale genomics: a paradigm shift in psychiatry?

The past decade has been one of unprecedented discovery in psychiatry. Large-scale genomic studies have identified hundreds of molecular risk factors and illuminated the genetic architectures of major psychiatric conditions. And yet with this knowledge has come a realization that these disorders are highly polygenic and that there is widespread pleiotropy of the risk alleles involved. These findings confirm long-held suspicions that our diagnostic categories do not describe biologically distinct conditions, and they pose fundamental challenges for the approaches to disease modeling that have helped us understand simpler Mendelian disorders. While progress has been immense, when and how will the promised impacts on clinical care be delivered

Pooled DNA genotyping on Affymetrix SNP genotyping arrays

BACKGROUND: Genotyping technology has advanced such that genome-wide association studies of complex diseases based upon dense marker maps are now technically feasible. However, the cost of such projects remains high. Pooled DNA genotyping offers the possibility of applying the same technologies at a fraction of the cost, and there is some evidence that certain ultra-high throughput platforms also perform with an acceptable accuracy. However, thus far, this conclusion is based upon published data concerning only a small number of SNPs. RESULTS: In the current study we prepared DNA pools from the parents and from the offspring of 30 parent-child trios that have been extensively genotyped by the HapMap project. We analysed the two pools with Affymetrix 10 K Xba 142 2.0 Arrays. The availability of the HapMap data allowed us to validate the performance of 6843 SNPs for which we had both complete individual and pooled genotyping data. Pooled analyses averaged over 5–6 microarrays resulted in highly reproducible results. Moreover, the accuracy of estimating differences in allele frequency between pools using this ultra-high throughput system was comparable with previous reports of pooling based upon lower throughput platforms, with an average error for the predicted allelic frequencies differences between the two pools of 1.37% and with 95% of SNPs showing an error of < 3.2%. CONCLUSION: Genotyping thousands of SNPs with DNA pooling using Affymetrix microarrays produces highly accurate results and can be used for genome-wide association studies

Pilot study to establish a prospective neonatal cohort: Study of Preterm Infants and Neurodevelopmental Genes (SPRING).

BACKGROUND: Genetic risk variants and preterm birth are early and potent risk factors for later neuropsychiatric disorders. To understand the interrelationships between these factors, a large-scale genetic study of very preterm (VPT, <32 weeks gestation) infants with prospective follow-up is required. In this paper, we describe a streamlined study approach, using efficient processes for biological and clinical data collection, to feasibly establish such a cohort. METHODS: We sought to recruit 500 VPT families within a 1 year period from neonatal units. Treating clinical teams recruited eligible participants, obtained parent consent, collected blood samples and posted specimens to the research laboratory. We extracted all clinical data from the National Neonatal Research Database, an existing UK resource that captures daily patient-level data on all VPT infants. RESULTS: Between May 2017 and June 2018, we established a cohort of 848 VPT infants and their parents from 60 English neonatal units. The study population (median (IQR), gestation: 28.9 (26-30) weeks; birth weight: 1120 (886-1420) g) represented 18.9% of eligible infants born at the study sites during the recruitment period (n=4491). From the subset of 521 complete family trios, we successfully completed genotyping for 510 (97.9%) trios. Of the original 883 infants whose parents consented to participate, the parents of 796 (90.1%) infants agreed to future data linkage and 794 (89.9%) agreed to be recalled. CONCLUSION: We demonstrate the feasibility and acceptability of streamlined strategies for genetic, neonatal and longitudinal data collection and provide a template for future cost-effective and efficient cohort development

POLARIS: polygenic LD-adjusted risk score approach for set-based analysis of GWAS data

Polygenic risk scores (PRSs) are a method to summarise the additive trait variance captured by a set of SNPs, and can increase the power of set-based analyses by leveraging public GWAS datasets. PRS aims to assess the genetic liability to some phenotype on the basis of polygenic risk for the same or di�erent phenotype estimated from independent data. We propose the application of PRSs as a set-based method with an additional component of adjustment for linkage disequilibrium (LD), with potential extension of the PRS approach to analyse biologically meaningful SNP sets. We call this method POLARIS: POlygenic Ld-Adjusted RIsk Score. POLARIS identi�es the LD-structure of SNPs using spectral decomposition of the SNP correlation matrix and replaces the individuals' SNP allele counts with LD-adjusted dosages. Using a raw genotype dataset together with SNP e�ect sizes from a second independent dataset, POLARIS can be used for set-based analysis. MAGMA is an alternative set-based approach employing principal component analysis to account for LD between markers in a raw genotype dataset. We used simulations, both with simple constructed and real LD-structure, to compare the power of these methods. POLARIS shows more power than MAGMA applied to the raw genotype dataset only, but less or comparable power to combined analysis of both datasets. POLARIS has the advantages that it produces a risk score per person per set using all available SNPs, and aims to increase power by leveraging the e�ect sizes from the discovery set in a self-contained test of association in the test dataset

Methylomic trajectories across human fetal brain development

Open access articleEpigenetic processes play a key role in orchestrating transcriptional regulation during development. The importance of DNA methylation in fetal brain development is highlighted by the dynamic expression of de novo DNA methyltransferases during the perinatal period and neurodevelopmental deficits associated with mutations in the methyl-CpG binding protein 2 (MECP2) gene. However, our knowledge about the temporal changes to the epigenome during fetal brain development has, to date, been limited. We quantified genome-wide patterns of DNA methylation at ∼ 400,000 sites in 179 human fetal brain samples (100 male, 79 female) spanning 23 to 184 d post-conception. We identified highly significant changes in DNA methylation across fetal brain development at >7% of sites, with an enrichment of loci becoming hypomethylated with fetal age. Sites associated with developmental changes in DNA methylation during fetal brain development were significantly underrepresented in promoter regulatory regions but significantly overrepresented in regions flanking CpG islands (shores and shelves) and gene bodies. Highly significant differences in DNA methylation were observed between males and females at a number of autosomal sites, with a small number of regions showing sex-specific DNA methylation trajectories across brain development. Weighted gene comethylation network analysis (WGCNA) revealed discrete modules of comethylated loci associated with fetal age that are significantly enriched for genes involved in neurodevelopmental processes. This is, to our knowledge, the most extensive study of DNA methylation across human fetal brain development to date, confirming the prenatal period as a time of considerable epigenomic plasticity.MRCUniversity of Exeter Medical SchoolWellcome Trus

The impact of schizophrenia and mood disorder risk alleles on emotional problems: investigating change from childhood to middle age

Previous studies find that both schizophrenia and mood disorder risk alleles contribute to adult depression and anxiety. Emotional problems (depression or anxiety) begin in childhood and show strong continuities into adult life; this suggests that symptoms are the manifestation of the same underlying liability across different ages. However, other findings suggest that there are developmental differences in the etiology of emotional problems at different ages. To our knowledge, no study has prospectively examined the impact of psychiatric risk alleles on emotional problems at different ages in the same individuals. Data were analyzed using regression-based analyses in a prospective, population-based UK cohort (the National Child Development Study). Schizophrenia and major depressive disorder (MDD) polygenic risk scores (PRS) were derived from published Psychiatric Genomics Consortium genome-wide association studies. Emotional problems were assessed prospectively at six time points from age 7 to 42 years. Schizophrenia PRS were associated with emotional problems from childhood [age 7, OR 1.09 (1.03–1.15), p = 0.003] to mid-life [age 42, OR 1.10 (1.05–1.17), p < 0.001], while MDD PRS were associated with emotional problems only in adulthood [age 42, OR 1.06 (1.00–1.11), p = 0.034; age 7, OR 1.03 (0.98–1.09), p = 0.228]. Our prospective investigation suggests that early (childhood) emotional problems in the general population share genetic risk with schizophrenia, while later (adult) emotional problems also share genetic risk with MDD. The results suggest that the genetic architecture of depression/anxiety is not static across development

Morphometric analysis of structural MRI using schizophrenia meta-analytic priors distinguish patients from controls in two independent samples and in a sample of individuals with high polygenic risk

Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen’s d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (N(CASE) = 50; N(CONTROL) = 125), a replication sample (N(CASE) = 23; N(CONTROL) = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (N(HIGH-SCZ-PRS) = 95; N(LOW-SCZ-PRS) = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual’s patterns of structural brain-wide alterations