Stratified analyses refine association between TLR7 rare variants and severe COVID-19.

Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (<60 years) cases with no reported clinical risk factors (n = 378), compared to 0.24% of controls (odds ratio [OR] = 12.3, p = 1.27 × 10-10). Incorporation of the results of either functional assays or protein modeling led to a pronounced increase in effect size (ORmax = 46.5, p = 1.74 × 10-15). Association signals for the X-chromosomal gene TLR7 were also detected in the female-only subgroup, suggesting the existence of additional mechanisms beyond X-linked recessive inheritance in males. Additionally, supporting evidence was generated for a contribution to severe COVID-19 of the previously implicated genes IFNAR2, IFIH1, and TBK1. Our results refine the genetic contribution of rare TLR7 variants to severe COVID-19 and strengthen evidence for the etiological relevance of genes in the interferon signaling pathway.

A compendium of genetic regulatory effects across pig tissues.

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.

Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial infarction outcomes.

There is increasing evidence that the complexity of the retinal vasculature measured as fractal dimension, Df, might offer earlier insights into the progression of coronary artery disease (CAD) before traditional biomarkers can be detected. This association could be partly explained by a common genetic basis; however, the genetic component of Df is poorly understood. We present a genome-wide association study (GWAS) of 38,000 individuals with white British ancestry from the UK Biobank aimed to comprehensively study the genetic component of Df and analyse its relationship with CAD. We replicated 5 Df loci and found 4 additional loci with suggestive significance (P < 1e-05) to contribute to Df variation, which previously were reported in retinal tortuosity and complexity, hypertension, and CAD studies. Significant negative genetic correlation estimates support the inverse relationship between Df and CAD, and between Df and myocardial infarction (MI), one of CAD's fatal outcomes. Fine-mapping of Df loci revealed Notch signalling regulatory variants supporting a shared mechanism with MI outcomes. We developed a predictive model for MI incident cases, recorded over a 10-year period following clinical and ophthalmic evaluation, combining clinical information, Df, and a CAD polygenic risk score. Internal cross-validation demonstrated a considerable improvement in the area under the curve (AUC) of our predictive model (AUC = 0.770 ± 0.001) when comparing with an established risk model, SCORE, (AUC = 0.741 ± 0.002) and extensions thereof leveraging the PRS (AUC = 0.728 ± 0.001). This evidences that Df provides risk information beyond demographic, lifestyle, and genetic risk factors. Our findings shed new light on the genetic basis of Df, unveiling a common control with MI, and highlighting the benefits of its application in individualised MI risk prediction.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Adeno-associated virus 2 infection in children with non-A-E hepatitis.

An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland1 in April 2022 and has now been identified in 35 countries2. Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case-control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation sequencing, PCR with reverse transcription, serology and in situ hybridization, we detected recent infection with AAV2 in plasma and liver samples in 26 out of 32 (81%) cases of hepatitis compared with 5 out of 74 (7%) of samples from unaffected individuals. Furthermore, AAV2 was detected within ballooned hepatocytes alongside a prominent T cell infiltrate in liver biopsy samples. In keeping with a CD4+ T-cell-mediated immune pathology, the human leukocyte antigen (HLA) class II HLA-DRB1*04:01 allele was identified in 25 out of 27 cases (93%) compared with a background frequency of 10 out of 64 (16%; P = 5.49 × 10-12). In summary, we report an outbreak of acute paediatric hepatitis associated with AAV2 infection (most likely acquired as a co-infection with human adenovirus that is usually required as a 'helper virus' to support AAV2 replication) and disease susceptibility related to HLA class II status.

Frequency and Phenotype Associations of Rare Variants in 5 Monogenic Cerebral Small Vessel Disease Genes in 200,000 UK Biobank Participants.

Background and Objectives: Based on previous case reports and disease-based cohorts, a minority of patients with cerebral small vessel disease (cSVD) have a monogenic cause, with many also manifesting extracerebral phenotypes. We investigated the frequency, penetrance, and phenotype associations of putative pathogenic variants in cSVD genes in the UK Biobank (UKB), a large population-based study. Methods: We used a systematic review of previous literature and ClinVar to identify putative pathogenic rare variants in CTSA, TREX1, HTRA1, and COL4A1/2. We mapped phenotypes previously attributed to these variants (phenotypes-of-interest) to disease coding systems used in the UKB's linked health data from UK hospital admissions, death records, and primary care. Among 199,313 exome-sequenced UKB participants, we assessed the following: the proportion of participants carrying ≥1 variant(s); phenotype-of-interest penetrance; and the association between variant carrier status and phenotypes-of-interest using a binary (any phenotype present/absent) and phenotype burden (linear score of the number of phenotypes a participant possessed) approach. Results: Among UKB participants, 0.5% had ≥1 variant(s) in studied genes. Using hospital admission and death records, 4%-20% of variant carriers per gene had an associated phenotype. This increased to 7%-55% when including primary care records. Only COL4A1 variant carrier status was significantly associated with having ≥1 phenotype-of-interest and a higher phenotype score (OR = 1.29, p = 0.006). Discussion: While putative pathogenic rare variants in monogenic cSVD genes occur in 1:200 people in the UKB population, only approximately half of variant carriers have a relevant disease phenotype recorded in their linked health data. We could not replicate most previously reported gene-phenotype associations, suggesting lower penetrance rates, overestimated pathogenicity, and/or limited statistical power.

Comparative transcriptome in large-scale human and cattle populations.

BACKGROUND: Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes. RESULTS: Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues. CONCLUSIONS: In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

A multi-tissue atlas of regulatory variants in cattle.

Characterization of genetic regulatory variants acting on livestock gene expression is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here we build a Cattle Genotype-Tissue Expression atlas (CattleGTEx) as part of the pilot phase of the Farm animal GTEx (FarmGTEx) project for the research community based on 7,180 publicly available RNA-sequencing (RNA-seq) samples. We describe the transcriptomic landscape of more than 100 tissues/cell types and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 23 distinct tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multiomics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.

Genetic Landscape of the ACE2 Coronavirus Receptor.

BACKGROUND: SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood. METHODS: We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data. RESULTS: We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells. CONCLUSIONS: Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.

Whole-genome sequencing reveals host factors underlying critical COVID-19.

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4.

Previous genome-wide association studies revealed multiple common variants involved in eczema but the role of rare variants remains to be elucidated. Here, we investigate the role of rare variants in eczema susceptibility. We meta-analyze 21 study populations including 20,016 eczema cases and 380,433 controls. Rare variants are imputed with high accuracy using large population-based reference panels. We identify rare exonic variants in DUSP1, NOTCH4, and SLC9A4 to be associated with eczema. In DUSP1 and NOTCH4 missense variants are predicted to impact conserved functional domains. In addition, five novel common variants at SATB1-AS1/KCNH8, TRIB1/LINC00861, ZBTB1, TBX21/OSBPL7, and CSF2RB are discovered. While genes prioritized based on rare variants are significantly up-regulated in the skin, common variants point to immune cell function. Over 20% of the single nucleotide variant-based heritability is attributable to rare and low-frequency variants. The identified rare/low-frequency variants located in functional protein domains point to promising targets for novel therapeutic approaches to eczema.

Sex differences in genetic architecture in the UK Biobank.

Males and females present differences in complex traits and in the risk of a wide array of diseases. Genotype by sex (GxS) interactions are thought to account for some of these differences. However, the extent and basis of GxS are poorly understood. In the present study, we provide insights into both the scope and the mechanism of GxS across the genome of about 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits. We also found that, in some cases, sex-agnostic analyses may be missing trait-associated loci and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the differences observed through sex-biased gene expression and gene-level analyses. Our results suggest the need to consider sex-aware analyses for future studies to shed light onto possible sex-specific molecular mechanisms.

Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles.

BACKGROUND: The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS: Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS: We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS: APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

Physician-Confirmed and Administrative Definitions of Stroke in UK Biobank Reflect the Same Underlying Genetic Trait.

BACKGROUND: Stroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation. METHODS: We compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants, we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci. RESULTS: The stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg.81-1) and each other (rg.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definition. CONCLUSIONS: Stroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.

Birth weight associations with DNA methylation differences in an adult population.

The Developmental Origins of Health and Disease (DOHaD) theory predicts that prenatal and early life events shape adult health outcomes. Birth weight is a useful indicator of the foetal experience and has been associated with multiple adult health outcomes. DNA methylation (DNAm) is one plausible mechanism behind the relationship of birth weight to adult health. Through data linkage between Generation Scotland and historic Scottish birth cohorts, and birth records held through the NHS Information and Statistics Division, a sample of 1,757 individuals with available birth weight and DNAm data was derived. Epigenome-wide association studies (EWAS) were performed in two independently generated DNAm subgroups (nSet1 = 1,395, nSet2 = 362), relating adult DNAm from whole blood to birth weight. Meta-analysis yielded one genome-wide significant CpG site (p = 5.97x10-9), cg00966482. There was minimal evidence for attenuation of the effect sizes for the lead loci upon adjustment for numerous potential confounder variables (body mass index, educational attainment, and socioeconomic status). Associations between birth weight and epigenetic measures of biological age were also assessed. Associations between lower birth weight and higher Grim Age acceleration (p(FDR) = 3.6x10-3) and shorter DNAm-derived telomere length (p(FDR) = 1.7x10-3) are described, although results for three other epigenetic clocks were null. Our results provide support for an association between birth weight and DNAm both locally at one CpG site, and globally via biological ageing estimates.

Evidence of horizontal indirect genetic effects in humans.

Indirect genetic effects, the effects of the genotype of one individual on the phenotype of other individuals, are environmental factors associated with human disease and complex trait variation that could help to expand our understanding of the environment linked to complex traits. Here, we study indirect genetic effects in 80,889 human couples of European ancestry for 105 complex traits. Using a linear mixed model approach, we estimate partner indirect heritability and find evidence of partner heritability on ~50% of the analysed traits. Follow-up analysis suggests that in at least ~25% of these traits, the partner heritability is consistent with the existence of indirect genetic effects including a wide variety of traits such as dietary traits, mental health and disease. This shows that the environment linked to complex traits is partially explained by the genotype of other individuals and motivates the need to find new ways of studying the environment.

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice.

Epigenome-wide analyses identify DNA methylation signatures of dementia risk.

INTRODUCTION: Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)-free participants. METHODS: Associations between dementia risk measures (family history, AD genetic risk score [GRS], and dementia risk scores [combining lifestyle, demographic, and genetic factors]) and whole-blood DNA methylation were assessed in discovery and replication samples (n = ~400 to ~5000) from Generation Scotland. RESULTS: AD genetic risk and two dementia risk scores were associated with differential methylation. The GRS associated predominantly with methylation differences in cis but also identified a genomic region implicated in Parkinson disease. Loci associated with dementia risk scores were enriched for those previously associated with body mass index and alcohol consumption. DISCUSSION: Dementia risk measures show widespread association with blood-based methylation, generating several hypotheses for assessment by future studies.