Genetic liability estimated from large-scale family data improves genetic prediction, risk score profiling, and gene mapping for major depression.

Large biobank samples provide an opportunity to integrate broad phenotyping, familial records, and molecular genetics data to study complex traits and diseases. We introduce Pearson-Aitken Family Genetic Risk Scores (PA-FGRS), a method for estimating disease liability from patterns of diagnoses in extended, age-censored genealogical records. We then apply the method to study a paradigmatic complex disorder, major depressive disorder (MDD), using the iPSYCH2015 case-cohort study of 30,949 MDD cases, 39,655 random population controls, and more than 2 million relatives. We show that combining PA-FGRS liabilities estimated from family records with molecular genotypes of probands improves three lines of inquiry. Incorporating PA-FGRS liabilities improves classification of MDD over and above polygenic scores, identifies robust genetic contributions to clinical heterogeneity in MDD associated with comorbidity, recurrence, and severity and can improve the power of genome-wide association studies. Our method is flexible and easy to use, and our study approaches are generalizable to other datasets and other complex traits and diseases.

Developmental language disorder - heritability and genetic correlations with other disorders affecting language.

Developmental language disorder (DLD) is a neurodevelopmental disorder primarily affecting language in the absence of a known biomedical condition, which may have a large impact on a person's life and mental health. Family-based studies indicate a strong genetic component in DLD, but genetic studies of DLD are scarce. In this study we estimated the heritability of DLD and its genetic correlations with related disorders and traits in sample of >25,000 individuals from the Danish Blood Donor Study for whom we had both genotype data and questionnaire data on language disorder and language support. We estimated SNP-based heritabilities for DLD and genetic correlations with disorders which may involve spoken language deficits and traits related to spoken language. We found significant heritability estimates for DLD ranging from ∼27 % to ∼52 %, depending on the method used. We found no significant evidence for genetic correlation with the investigated disorders or traits, although the strongest effect was observed for a negative genetic correlation between DLD and nonword repetition ability. To our knowledge, this study reports the first significant heritability estimate for DLD from molecular genetic data.

Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform.

Alzheimer's disease (AD) is a complex genetic disease, and variants identified through genome-wide association studies (GWAS) explain only part of its heritability. Epistasis has been proposed as a major contributor to this 'missing heritability', however, many current methods are limited to only modelling additive effects. We use VariantSpark, a machine learning approach to GWAS, and BitEpi, a tool for epistasis detection, to identify AD associated variants and interactions across two independent cohorts, ADNI and UK Biobank. By incorporating significant epistatic interactions, we captured 10.41% more phenotypic variance than logistic regression (LR). We validate the well-established AD loci, APOE, and identify two novel genome-wide significant AD associated loci in both cohorts, SH3BP4 and SASH1, which are also in significant epistatic interactions with APOE. We show that the SH3BP4 SNP has a modulating effect on the known pathogenic APOE SNP, demonstrating a possible protective mechanism against AD. SASH1 is involved in a triplet interaction with pathogenic APOE SNP and ACOT11, where the SASH1 SNP lowered the pathogenic interaction effect between ACOT11 and APOE. Finally, we demonstrate that VariantSpark detects disease associations with 80% fewer controls than LR, unlocking discoveries in well annotated but smaller cohorts.

Locus-resolution analysis of L1 regulation and retrotransposition potential in mouse embryonic development.

Mice harbor ∼2800 intact copies of the retrotransposon Long Interspersed Element 1 (L1). The in vivo retrotransposition capacity of an L1 copy is defined by both its sequence integrity and epigenetic status, including DNA methylation of the monomeric units constituting young mouse L1 promoters. Locus-specific L1 methylation dynamics during development may therefore elucidate and explain spatiotemporal niches of endogenous retrotransposition but remain unresolved. Here, we interrogate the retrotransposition efficiency and epigenetic fate of source (donor) L1s, identified as mobile in vivo. We show that promoter monomer loss consistently attenuates the relative retrotransposition potential of their offspring (daughter) L1 insertions. We also observe that most donor/daughter L1 pairs are efficiently methylated upon differentiation in vivo and in vitro. We use Oxford Nanopore Technologies (ONT) long-read sequencing to resolve L1 methylation genome-wide and at individual L1 loci, revealing a distinctive "smile" pattern in methylation levels across the L1 promoter region. Using Pacific Biosciences (PacBio) SMRT sequencing of L1 5' RACE products, we then examine DNA methylation dynamics at the mouse L1 promoter in parallel with transcription start site (TSS) distribution at locus-specific resolution. Together, our results offer a novel perspective on the interplay between epigenetic repression, L1 evolution, and genome stability.

Thresholding Gini variable importance with a single-trained random forest: An empirical Bayes approach.

Random forests (RFs) are a widely used modelling tool capable of feature selection via a variable importance measure (VIM), however, a threshold is needed to control for false positives. In the absence of a good understanding of the characteristics of VIMs, many current approaches attempt to select features associated to the response by training multiple RFs to generate statistical power via a permutation null, by employing recursive feature elimination, or through a combination of both. However, for high-dimensional datasets these approaches become computationally infeasible. In this paper, we present RFlocalfdr, a statistical approach, built on the empirical Bayes argument of Efron, for thresholding mean decrease in impurity (MDI) importances. It identifies features significantly associated with the response while controlling the false positive rate. Using synthetic data and real-world data in health, we demonstrate that RFlocalfdr has equivalent accuracy to currently published approaches, while being orders of magnitude faster. We show that RFlocalfdr can successfully threshold a dataset of 106 datapoints, establishing its usability for large-scale datasets, like genomics. Furthermore, RFlocalfdr is compatible with any RF implementation that returns a VIM and counts, making it a versatile feature selection tool that reduces false discoveries.

The identification of distinct protective and susceptibility mechanisms for hip osteoarthritis: findings from a genome-wide association study meta-analysis of minimum joint space width and Mendelian randomisation cluster analyses.

BACKGROUND: Hip minimum joint space width (mJSW) provides a proxy for cartilage thickness. This study aimed to conduct a genome-wide association study (GWAS) of mJSW to (i) identify new genetic determinants of mJSW and (ii) identify which mJSW loci convey hip osteoarthritis (HOA) risk and would therefore be of therapeutic interest. METHODS: GWAS meta-analysis of hip mJSW derived from plain X-rays and DXA was performed, stratified by sex and adjusted for age and ancestry principal components. Mendelian randomisation (MR) and cluster analyses were used to examine causal effect of mJSW on HOA. FINDINGS: 50,745 individuals were included in the meta-analysis. 42 SNPs, which mapped to 39 loci, were identified. Mendelian randomisation (MR) revealed little evidence of a causal effect of mJSW on HOA (ORIVW 0.98 [95% CI 0.82-1.18]). However, MR-Clust analysis suggested the null MR estimates reflected the net effect of two distinct causal mechanisms cancelling each other out, one of which was protective, whereas the other increased HOA susceptibility. For the latter mechanism, all loci were positively associated with height, suggesting mechanisms leading to greater height and mJSW increase the risk of HOA in later life. INTERPRETATIONS: One group of mJSW loci reduce HOA risk via increased mJSW, suggesting possible utility as targets for chondroprotective therapies. The second group of mJSW loci increased HOA risk, despite increasing mJSW, but were also positively related to height, suggesting they contribute to HOA risk via a growth-related mechanism. FUNDING: Primarily funded by the Medical Research Council and Wellcome Trust.

Genetic impact of blood C-reactive protein levels on chronic spinal & widespread pain.

PURPOSE: Causal mechanisms underlying systemic inflammation in spinal & widespread pain remain an intractable experimental challenge. Here we examined whether: (i) associations between blood C-reactive protein (CRP) and chronic back, neck/shoulder & widespread pain can be explained by shared underlying genetic variants; and (ii) higher CRP levels causally contribute to these conditions. METHODS: Using genome-wide association studies (GWAS) of chronic back, neck/shoulder & widespread pain (N = 6063-79,089 cases; N = 239,125 controls) and GWAS summary statistics for blood CRP (Pan-UK Biobank N = 400,094 & PAGE consortium N = 28,520), we employed cross-trait bivariate linkage disequilibrium score regression to determine genetic correlations (rG) between these chronic pain phenotypes and CRP levels (FDR < 5%). Latent causal variable (LCV) and generalised summary data-based Mendelian randomisation (GSMR) analyses examined putative causal associations between chronic pain & CRP (FDR < 5%). RESULTS: Higher CRP levels were genetically correlated with chronic back, neck/shoulder & widespread pain (rG range 0.26-0.36; P ≤ 8.07E-9; 3/6 trait pairs). Although genetic causal proportions (GCP) did not explain this finding (GCP range - 0.32-0.08; P ≥ 0.02), GSMR demonstrated putative causal effects of higher CRP levels contributing to each pain type (beta range 0.027-0.166; P ≤ 9.82E-03; 3 trait pairs) as well as neck/shoulder pain effects on CRP levels (beta [S.E.] 0.030 [0.021]; P = 6.97E-04). CONCLUSION: This genetic evidence for higher CRP levels in chronic spinal (back, neck/shoulder) & widespread pain warrants further large-scale multimodal & prospective longitudinal studies to accelerate the identification of novel translational targets and more effective therapeutic strategies.

Mendelian randomization study of maternal coffee consumption and its influence on birthweight, stillbirth, miscarriage, gestational age and pre-term birth.

BACKGROUND: Coffee consumption has been associated with several adverse pregnancy outcomes, although data from randomized-controlled trials are lacking. We investigate whether there is a causal relationship between coffee consumption and miscarriage, stillbirth, birthweight, gestational age and pre-term birth using Mendelian randomization (MR). METHODS: A two-sample MR study was performed using summary results data from a genome-wide association meta-analysis of coffee consumption (N = 91 462) from the Coffee and Caffeine Genetics Consortium. Outcomes included self-reported miscarriage (N = 49 996 cases and 174 109 controls from a large meta-analysis); the number of stillbirths [N = 60 453 from UK Biobank (UKBB)]; gestational age and pre-term birth (N = 43 568 from the 23andMe, Inc cohort) and birthweight (N = 297 356 reporting own birthweight and N = 210 248 reporting offspring's birthweight from UKBB and the Early Growth Genetics Consortium). Additionally, a one-sample genetic risk score (GRS) analysis of coffee consumption in UKBB women (N up to 194 196) and the Avon Longitudinal Study of Parents and Children (N up to 6845 mothers and 4510 children) and its relationship with offspring outcomes was performed. RESULTS: Both the two-sample MR and one-sample GRS analyses showed no change in risk of sporadic miscarriages, stillbirths, pre-term birth or effect on gestational age connected to coffee consumption. Although both analyses showed an association between increased coffee consumption and higher birthweight, the magnitude of the effect was inconsistent. CONCLUSION: Our results suggest that coffee consumption during pregnancy might not itself contribute to adverse outcomes such as stillbirth, sporadic miscarriages and pre-term birth or lower gestational age or birthweight of the offspring.

A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits.

The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.

A metabolic associated fatty liver disease risk variant in MBOAT7 regulates toll like receptor induced outcomes.

The breakdown of toll-like receptor (TLR) tolerance results in tissue damage, and hyperactivation of the TLRs and subsequent inflammatory consequences have been implicated as risk factors for more severe forms of disease and poor outcomes from various diseases including COVID-19 and metabolic (dysfunction) associated fatty liver disease (MAFLD). Here we provide evidence that membrane bound O-acyltransferase domain containing 7 (MBOAT7) is a negative regulator of TLR signalling. MBOAT7 deficiency in macrophages as observed in patients with MAFLD and in COVID-19, alters membrane phospholipid composition. We demonstrate that this is associated with a redistribution of arachidonic acid toward proinflammatory eicosanoids, induction of endoplasmic reticulum stress, mitochondrial dysfunction, and remodelling of the accessible inflammatory-related chromatin landscape culminating in macrophage inflammatory responses to TLRs. Activation of MBOAT7 reverses these effects. These outcomes are further modulated by the MBOAT7 rs8736 (T) MAFLD risk variant. Our findings suggest that MBOAT7 can potentially be explored as a therapeutic target for diseases associated with dysregulation of the TLR signalling cascade.

A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci.

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR-Alu (SVA) elements, a class of great ape-specific transposable elements with gene-regulatory roles, which represents a major source of structural variability in the human population. We highlight the presence of structurally variable SVAs (SV-SVAs) in neurological disease-associated loci, and we further associate SV-SVAs to disease-associated SNPs and differential gene expression using luciferase assays and expression quantitative trait loci data. Finally, we genetically deleted SV-SVAs in the BIN1 and CD2AP Alzheimer's disease-associated risk loci and in the BCKDK Parkinson's disease-associated risk locus and assessed multiple aspects of their gene-regulatory influence in a human neuronal context. Together, this study reveals a novel layer of genetic variation in transposable elements that may contribute to identification of the structural variants that are the actual drivers of disease associations of GWAS loci.

Regenerating zebrafish scales express a subset of evolutionary conserved genes involved in human skeletal disease.

BACKGROUND: Scales are mineralised exoskeletal structures that are part of the dermal skeleton. Scales have been mostly lost during evolution of terrestrial vertebrates whilst bony fish have retained a mineralised dermal skeleton in the form of fin rays and scales. Each scale is a mineralised collagen plate that is decorated with both matrix-building and resorbing cells. When removed, an ontogenetic scale is quickly replaced following differentiation of the scale pocket-lining cells that regenerate a scale. Processes promoting de novo matrix formation and mineralisation initiated during scale regeneration are poorly understood. Therefore, we performed transcriptomic analysis to determine gene networks and their pathways involved in dermal scale regeneration. RESULTS: We defined the transcriptomic profiles of ontogenetic and regenerating scales of zebrafish and identified 604 differentially expressed genes (DEGs). These were enriched for extracellular matrix, ossification, and cell adhesion pathways, but not in enamel or dentin formation processes indicating that scales are reminiscent to bone. Hypergeometric tests involving monogenetic skeletal disorders showed that DEGs were strongly enriched for human orthologues that are mutated in low bone mass and abnormal bone mineralisation diseases (P< 2× 10-3). The DEGs were also enriched for human orthologues associated with polygenetic skeletal traits, including height (P< 6× 10-4), and estimated bone mineral density (eBMD, P< 2× 10-5). Zebrafish mutants of two human orthologues that were robustly associated with height (COL11A2, P=6× 10-24) or eBMD (SPP1, P=6× 10-20) showed both exo- and endo- skeletal abnormalities as predicted by our genetic association analyses; col11a2Y228X/Y228X mutants showed exoskeletal and endoskeletal features consistent with abnormal growth, whereas spp1P160X/P160X mutants predominantly showed mineralisation defects. CONCLUSION: We show that scales have a strong osteogenic expression profile comparable to other elements of the dermal skeleton, enriched in genes that favour collagen matrix growth. Despite the many differences between scale and endoskeletal developmental processes, we also show that zebrafish scales express an evolutionarily conserved sub-population of genes that are relevant to human skeletal disease.

Osteoclasts recycle via osteomorphs during RANKL-stimulated bone resorption.

Osteoclasts are large multinucleated bone-resorbing cells formed by the fusion of monocyte/macrophage-derived precursors that are thought to undergo apoptosis once resorption is complete. Here, by intravital imaging, we reveal that RANKL-stimulated osteoclasts have an alternative cell fate in which they fission into daughter cells called osteomorphs. Inhibiting RANKL blocked this cellular recycling and resulted in osteomorph accumulation. Single-cell RNA sequencing showed that osteomorphs are transcriptionally distinct from osteoclasts and macrophages and express a number of non-canonical osteoclast genes that are associated with structural and functional bone phenotypes when deleted in mice. Furthermore, genetic variation in human orthologs of osteomorph genes causes monogenic skeletal disorders and associates with bone mineral density, a polygenetic skeletal trait. Thus, osteoclasts recycle via osteomorphs, a cell type involved in the regulation of bone resorption that may be targeted for the treatment of skeletal diseases.

Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs.

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating "virtual" mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.

Identification of susceptibility variants to benign childhood epilepsy with centro-temporal spikes (BECTS) in Chinese Han population.

BACKGROUND: Benign Childhood Epilepsy with Centro-temporal Spikes (BECTS) is the most common form of idiopathic epilepsy in children, accounting for up to 23% of pediatric epilepsy. The pathogenesis of BECTS is unknown, but it is thought that genetic factors play a role in susceptibility to the disease. METHODS: To investigate the role of common genetic variants in BECTS pathogenesis, a 2-stage genome-wide association study (GWAS) was performed in 1,800 Chinese Han BECTS patients, and 7,090 healthy controls. Genetic findings were used in a Mendelian Randomization study in the UK Biobank dataset to investigate the potential role of smoking in BECTS. FINDINGS: Definitive evidence of a role for common-variant heritability was demonstrated, with heritability of BECTS of >10% observed even with conservative disease prevalence assumptions. Although no individual locus achieved genome-wide significance, twelve loci achieved suggestive evidence of association (5 × 10-8

LINE-1 Evasion of Epigenetic Repression in Humans.

Epigenetic silencing defends against LINE-1 (L1) retrotransposition in mammalian cells. However, the mechanisms that repress young L1 families and how L1 escapes to cause somatic genome mosaicism in the brain remain unclear. Here we report that a conserved Yin Yang 1 (YY1) transcription factor binding site mediates L1 promoter DNA methylation in pluripotent and differentiated cells. By analyzing 24 hippocampal neurons with three distinct single-cell genomic approaches, we characterized and validated a somatic L1 insertion bearing a 3' transduction. The source (donor) L1 for this insertion was slightly 5' truncated, lacked the YY1 binding site, and was highly mobile when tested in vitro. Locus-specific bisulfite sequencing revealed that the donor L1 and other young L1s with mutated YY1 binding sites were hypomethylated in embryonic stem cells, during neurodifferentiation, and in liver and brain tissue. These results explain how L1 can evade repression and retrotranspose in the human body.