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Background: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20–1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01–1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59–0.67) to 0.65 (95% CI, 0.62–0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=−4.82×10 −3 per year [95% CI, −6.49×10 −3 to −3.14×10 −3 ]; P =1.82×10 −8 ), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86–0.98]; P =0.0041). Conclusions: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH.

Summary DeepPheWAS is an R package for phenome-wide association studies that creates clinically curated composite phenotypes and integrates quantitative phenotypes from primary care data, longitudinal trajectories of quantitative measures, disease progression and drug response phenotypes. Tools are provided for efficient analysis of association with any genetic input, under any genetic model, with optional sex-stratified analysis, and for developing novel phenotypes. Availability and implementation The DeepPheWAS R package is freely available under GNU general public licence v3.0 from at https://github.com/Richard-Packer/DeepPheWAS. Supplementary information Supplementary data are available at Bioinformatics online.

Chronic Obstructive Pulmonary Disease (COPD) has a simple physiological diagnostic criterion but a wide range of clinical characteristics. The mechanisms underlying this variability in COPD phenotypes are unclear. To investigate the potential contribution of genetic variants to phenotypic heterogeneity, we examined the association of genome-wide associated lung function, COPD, and asthma variants with other phenotypes using phenome-wide association results derived in the UK Biobank. Our clustering analysis of the variants-phenotypes association matrix identified three clusters of genetic variants with different effects on white blood cell counts, height, and body mass index (BMI). To assess the potential clinical and molecular effects of these groups of variants, we investigated the association between cluster-specific genetic risk scores and phenotypes in the COPDGene cohort. We observed differences in steroid use, BMI, lymphocyte counts, chronic bronchitis, and differential gene and protein expression across the three genetic risk scores. Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

RATIONALE: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. OBJECTIVE: To identify and validate molecular determinants of IPF survival. METHODS: A staged genome-wide association study (GWAS) was performed using paired genomic and survival data. Stage I cases were drawn from centers across the US and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplant-free survival (TFS). Stage I variants with nominal significance (p

Genome-wide association studies (GWASs) have identified regions associated with chronic obstructive pulmonary disease (COPD). GWASs of other diseases have shown an approximately 10-fold overrepresentation of nonsynonymous variants, despite limited exonic coverage on genotyping arrays. We hypothesized that a large-scale analysis of coding variants could discover novel genetic associations with COPD, including rare variants with large effect sizes. We performed a meta-analysis of exome arrays from 218,399 controls and 33,851 moderate-to-severe COPD cases. All exome-wide significant associations were present in regions previously identified by GWAS. We did not identify any novel rare coding variants with large effect sizes. Within GWAS regions on chromosomes 5q, 6p, and 15q, four coding variants were conditionally significant ( P < 0.00015) when adjusting for lead GWAS single-nucleotide polymorphisms A common gasdermin B ( GSDMB) splice variant (rs11078928) previously associated with a decreased risk for asthma was nominally associated with a decreased risk for COPD [minor allele frequency (MAF) = 0.46, P = 1.8e-4]. Two stop variants in coiled-coil α-helical rod protein 1 ( CCHCR1), a gene involved in regulating cell proliferation, were associated with COPD (both P < 0.0001). The SERPINA1 Z allele was associated with a random-effects odds ratio of 1.43 for COPD (95% confidence interval = 1.17–1.74), though with marked heterogeneity across studies. Overall, COPD-associated exonic variants were identified in genes involved in DNA methylation, cell-matrix interactions, cell proliferation, and cell death. In conclusion, we performed the largest exome array meta-analysis of COPD to date and identified potential functional coding variants. Future studies are needed to identify rarer variants and further define the role of coding variants in COPD pathogenesis.

SummaryACE inhibitors (ACEIs) are commonly prescribed for hypertension, a global risk factor for cardiovascular disease. Their primary side effect is a dry cough which affects 5-35% of users. As clinical guidelines recommend switching those experiencing cough to an angiotensin-II receptor blocker, we have used this switch as a proxy for ACEI-induced cough. Through a two-stage multi-ancestry genome-wide association study, including up to 7,030 cases and 39,921 controls, we identify five independent genome-wide significant associations implicating six protein-coding genes, including INHBC, KCNIP4, NTSR1 and PREP which encode proteins involved in the nervous system. We also observe genetic overlap between ACEI-induced cough and chronic dry cough through genetic correlation and phenome-wide association studies. In line with existing hypotheses, our findings suggest a neurological basis for the pathology of ACEI-induced cough, particularly the role of proinflammatory mediators in sensory airway sensitivity and cough reflex modulation, and shared biological mechanisms with chronic dry cough.

Lung function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry GWAS meta-analysis of lung function to date, comprising 580,869 participants, 1020 independent association signals identified 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score (GRS) showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies (PheWAS) for selected associated variants, and trait and pathway-specific GRS to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

RationaleIdiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. Novel therapies and prognostic biomarkers are needed.ObjectiveTo identify and validate molecular determinants of IPF survival.MethodsA staged genome-wide association study (GWAS) was performed using paired genomic and survival data. Stage I cases were drawn from centers across the US and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplant-free survival (TFS). Stage I variants with nominal significance (p−5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (p−8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance.Main ResultsAfter quality controls, 1481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of proprotein convertase subtilisin/kexin type 6 (PCSK6) reaching genome-wide significance (HR 4.11; 95%CI 2.54-6.67; p=9.45×10−9). PCSK6 protein was highly expressed in IPF lung parenchyma and negatively correlated with survival. Peripheral blood PCSK6 gene expression and plasma concentration were associated with reduced transplant-free survival.ConclusionsWe identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein may serve as prognostic biomarker in IPF and potential therapeutic target.

Background: Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone.Research Question: What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma?Study Design and Methods: We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P < 5 × 10–6) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2).Results: We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P < 5 × 10–8) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent.Interpretation: We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.

IntroductionIdiopathic pulmonary fibrosis (IPF) is a rare lung disease characterised by progressive scarring in the alveoli. IPF can be defined in population studies using electronic healthcare records (EHR) but recent genetic studies of IPF using EHR have shown an attenuation of effect size for known genetic risk factors when compared to clinically-derived datasets, suggesting misclassification of cases.MethodsWe used EHR (ICD-10, Read (2 & 3)) and questionnaire data to define IPF cases in UK Biobank, and evaluated these definitions using association results for the largest genetic risk variant for IPF (rs35705950-T, MUC5B). We further evaluated the impact of exclusions based on co-occurring codes for non-IPF pulmonary fibrosis and restricting codes according to changes in diagnostic practice.ResultsOdds ratio (OR) estimates for rs35705950-T associations with IPF defined using EHR and questionnaire data in UK Biobank were significant and ranged from 2.06 to 3.09 which was lower than those reported using clinically-derived IPF datasets (95% confidence intervals: 3.74, 6.66). Code-based exclusions of cases gave slightly closer effect estimates to those previously reported, but sample sizes were substantially reduced.DiscussionWe show that none of the UK Biobank IPF codes replicate the effect size for the association of rs35705950-T on IPF risk when using clinically-derived IPF datasets. Further code-based exclusions also did not lead to effect estimates closer to those expected. Whilst the apparent increased sample sizes available for IPF from general population cohorts may be of benefit, future studies should take these limitations of the case definition into account.Key MessagesWhat is already known on this topicUK Biobank is a very large prospective cohort that can be utilised to increase sample sizes for studies of rare diseases such as idiopathic pulmonary fibrosis (IPF). However, effect size estimates for genetic risk factors for IPF in UK Biobank and other general population cohorts, when defining cases using electronic healthcare records (EHR), are smaller than those estimated from clinically-derived IPF datasets.What this study addsUsing Hospital Episode Statistics (HES) data, primary care data, death registry data and self-report data in UK Biobank, we used the association rs35705950-T, the largest genetic risk factor for IPF, to evaluate code-based definitions of IPF. We show that none of the available IPF coding replicates the effect size for rs35705950-T on IPF risk that is observed in clinically-derived IPF datasets.How this study might affect research, practice or policyResearch using large general population cohorts and datasets for observational studies of IPF should take these limitations of EHR definitions of IPF into consideration.

Treatment-resistant depression (TRD) is a major contributor to the disability caused by major depressive disorder (MDD). Primary care electronic health records provide an easily accessible approach to investigate TRD clinical and genetic characteristics. MDD defined from primary care records in UK Biobank (UKB) and EXCEED studies was compared with other measures of depression and tested for association with MDD polygenic risk score (PRS). Using prescribing records, TRD was defined from at least two switches between antidepressant drugs, each prescribed for at least 6 weeks. Clinical-demographic characteristics, SNP-based heritability (h2SNP) and genetic overlap with psychiatric and non-psychiatric traits were compared in TRD and non-TRD MDD cases. In 230,096 and 8926 UKB and EXCEED participants with primary care data, respectively, the prevalence of MDD was 8.7% and 14.2%, of which 13.2% and 13.5% was TRD, respectively. In both cohorts, MDD defined from primary care records was strongly associated with MDD PRS, and in UKB it showed overlap of 71–88% with other MDD definitions. In UKB, TRD vs healthy controls and non-TRD vs healthy controls h2SNP was comparable (0.25 [SE = 0.04] and 0.19 [SE = 0.02], respectively). TRD vs non-TRD was positively associated with the PRS of attention deficit hyperactivity disorder, with lower socio-economic status, obesity, higher neuroticism and other unfavourable clinical characteristics. This study demonstrated that MDD and TRD can be reliably defined using primary care records and provides the first large scale population assessment of the genetic, clinical and demographic characteristics of TRD.

Background: Asthma is a complex disease with multiple phenotypes that may differ in disease pathobiology and treatment response. IL33 single nucleotide polymorphisms (SNPs) have been reproducibly associated with asthma. IL33 levels are elevated in sputum and bronchial biopsies of patients with asthma. The functional consequences of IL33 asthma SNPs remain unknown. Objective: This study sought to determine whether IL33 SNPs associate with asthma-related phenotypes and with IL33 expression in lung or bronchial epithelium. This study investigated the effect of increased IL33 expression on human bronchial epithelial cell (HBEC) function. Methods: Association between IL33 SNPs (Chr9: 5,815,786-6,657,983) and asthma phenotypes (Lifelines/DAG [Dutch Asthma GWAS]/GASP [Genetics of Asthma Severity & Phenotypes] cohorts) and between SNPs and expression (lung tissue, bronchial brushes, HBECs) was done using regression modeling. Lentiviral overexpression was used to study IL33 effects on HBECs. Results: We found that 161 SNPs spanning the IL33 region associated with 1 or more asthma phenotypes after correction for multiple testing. We report a main independent signal tagged by rs992969 associating with blood eosinophil levels, asthma, and eosinophilic asthma. A second, independent signal tagged by rs4008366 presented modest association with eosinophilic asthma. Neither signal associated with FEV 1, FEV 1/forced vital capacity, atopy, and age of asthma onset. The 2 IL33 signals are expression quantitative loci in bronchial brushes and cultured HBECs, but not in lung tissue. IL33 overexpression in vitro resulted in reduced viability and reactive oxygen species–capturing of HBECs, without influencing epithelial cell count, metabolic activity, or barrier function. Conclusions: We identify IL33 as an epithelial susceptibility gene for eosinophilia and asthma, provide mechanistic insight, and implicate targeting of the IL33 pathway specifically in eosinophilic asthma.

Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008–2010) and SpiroMeta Consortium (multiple countries, 1947–2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.

Background Healthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs. Methods and findings We conducted a cross-sectional analysis using data from the baseline questionnaire of the United Kingdom Research study into Ethnicity and Coronavirus Disease 2019 (COVID-19) Outcomes in Healthcare workers (UK-REACH) cohort study, administered between December 2020 and March 2021. We used logistic regression to examine associations of demographic, household, and occupational risk factors with SARS-CoV-2 infection (defined by polymerase chain reaction (PCR), serology, or suspected COVID-19) in a diverse group of HCWs. The primary exposure of interest was self-reported ethnicity. Among 10,772 HCWs who worked during the first UK national lockdown in March 2020, the median age was 45 (interquartile range [IQR] 35 to 54), 75.1% were female and 29.6% were from ethnic minority groups. A total of 2,496 (23.2%) reported previous SARS-CoV-2 infection. The fully adjusted model contained the following dependent variables: demographic factors (age, sex, ethnicity, migration status, deprivation, religiosity), household factors (living with key workers, shared spaces in accommodation, number of people in household), health factors (presence/absence of diabetes or immunosuppression, smoking history, shielding status, SARS-CoV-2 vaccination status), the extent of social mixing outside of the household, and occupational factors (job role, the area in which a participant worked, use of public transport to work, exposure to confirmed suspected COVID-19 patients, personal protective equipment [PPE] access, aerosol generating procedure exposure, night shift pattern, and the UK region of workplace). After adjustment, demographic and household factors associated with increased odds of infection included younger age, living with other key workers, and higher religiosity. Important occupational risk factors associated with increased odds of infection included attending to a higher number of COVID-19 positive patients (aOR 2.59, 95% CI 2.11 to 3.18 for ≥21 patients per week versus none), working in a nursing or midwifery role (1.30, 1.11 to 1.53, compared to doctors), reporting a lack of access to PPE (1.29, 1.17 to 1.43), and working in an ambulance (2.00, 1.56 to 2.58) or hospital inpatient setting (1.55, 1.38 to 1.75). Those who worked in intensive care units were less likely to have been infected (0.76, 0.64 to 0.92) than those who did not. Black HCWs were more likely to have been infected than their White colleagues, an effect which attenuated after adjustment for other known risk factors. This study is limited by self-selection bias and the cross sectional nature of the study means we cannot infer the direction of causality. Conclusions We identified key sociodemographic and occupational risk factors associated with SARS-CoV-2 infection among UK HCWs, and have determined factors that might contribute to a disproportionate odds of infection in HCWs from Black ethnic groups. These findings demonstrate the importance of social and occupational factors in driving ethnic disparities in COVID-19 outcomes, and should inform policies, including targeted vaccination strategies and risk assessments aimed at protecting HCWs in future waves of the COVID-19 pandemic. Trial registration The study was prospectively registered at ISRCTN (reference number: ISRCTN11811602).

Key Features of the UK-REACH Cohort (Profile in a nutshell)The UK-REACH Cohort was established to understand why ethnic minority healthcare workers (HCWs) are at risk of poorer outcomes from COVID-19 when compared to their white ethnic counterparts in the United Kingdom (UK). Through study design, it contains a uniquely high percentage of participants from ethnic minority backgrounds about whom a wide range of qualitative and quantitative data has been collected.A total of 17891 HCWs aged 16-89 years (mean age: 44) have been recruited from across the UK via all major healthcare regulators, individual National Health Service (NHS) hospital trusts and UK HCW membership bodies who advertised the study to their registrants/staff to encourage participation in the study.Data available include linked healthcare records for 25 years from the date of consent and consent to obtain genomic sequencing data collected via saliva. Online questionnaires include information on demographics, COVID-19 exposures at work and home, redeployment in the workforce due to COVID-19, mental health measures, workforce attrition, and opinions on COVID-19 vaccines, with baseline (n=15 119), 6 (n=5632) and 12-month follow-up data captured.Request data access and collaborations by following documentation found at https://www.uk-reach.org/main/data_sharing.

BackgroundSeveral countries now have mandatory SARS-CoV-2/COVID-19 vaccination for healthcare workers (HCWs) or the general population. HCWs’ views on this are largely unknown.MethodsWe administered an online questionnaire to 17891 United Kingdom (UK) HCWs in Spring 2021 as part of the United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH) nationwide prospective cohort study. We categorised responses to a free-text question “What should society do if people don’t get vaccinated against COVID-19?” using content analysis. We collapsed categories into a binary variable: favours mandatory vaccination or not and used logistic regression to calculate its demographic predictors, and occupational, health and attitudinal predictors adjusted for demographics.FindingsOf 5633 questionnaire respondents, 3235 answered the freetext question; 18% (n=578) of those favoured mandatory vaccination but the most frequent suggestion was education (32%, n=1047). Older HCWs, HCWs vaccinated against influenza (OR 1.48; 95%CI 1.10 – 1.99, vs none) and with more positive vaccination attitudes generally (OR 1.10; 95%CI 1.06 – 1.14) were more likely to favour mandatory vaccination (OR 1.26; 95%CI 1.17 – 1.37, per decade increase), whereas female HCWs (OR= 0.80, 95%CI 0.65 – 0.99, vs male), Black HCWs (OR= 0.48, 95%CI 0.26 – 0.87, vs White), those hesitant about COVID-19 vaccination (OR= 0.56; 95%CI 0.43 – 0.71, vs not hesitant), in an Allied Health Profession (OR 0.67; 95%CI 0.51 – 0.88, vs Medical), or who trusted their organisation (OR 0.78; 95%CI 0.63 – 0.96) were less likely to.InterpretationOnly one in six of the HCWs in this large, diverse, UK-wide sample favoured mandatory vaccination. Building trust, educating and supporting HCWs who are hesitant about vaccination may be more acceptable, effective and equitable.FundingMRC-UK Research and Innovation grant (MR/V027549/1) and the Department of Health and Social Care via the National Institute for Health Research.

Whether smoking-associated DNA methylation has a causal effect on lung function has not been thoroughly evaluated. We first investigated the causal effects of 474 smoking-associated CpGs on forced expiratory volume in 1 s (FEV1) in UK Biobank (n = 321,047) by using two-sample Mendelian randomization (MR) and then replicated this investigation in the SpiroMeta Consortium (n = 79,055). Second, we used two-step MR to investigate whether DNA methylation mediates the effect of smoking on FEV1. Lastly, we evaluated the presence of horizontal pleiotropy and assessed whether there is any evidence for shared causal genetic variants between lung function, DNA methylation, and gene expression by using a multiple-trait colocalization (“moloc”) framework. We found evidence of a possible causal effect for DNA methylation on FEV1 at 18 CpGs (p < 1.2 × 10−4). Replication analysis supported a causal effect at three CpGs (cg21201401 [LIME1 and ZGPAT], cg19758448 [PGAP3], and cg12616487 [EML3 and AHNAK] [p < 0.0028]). DNA methylation did not clearly mediate the effect of smoking on FEV1, although DNA methylation at some sites might influence lung function via effects on smoking. By using “moloc”, we found evidence of shared causal variants between lung function, gene expression, and DNA methylation. These findings highlight potential therapeutic targets for improving lung function and possibly smoking cessation, although larger, tissue-specific datasets are required to confirm these results.

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC 1

IntroductionHealthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs.MethodsWe conducted a cross-sectional analysis using data from the United Kingdom Research study into Ethnicity And COVID-19 Outcomes in Healthcare workers (UK-REACH) cohort study. We used logistic regression to examine associations of demographic, household and occupational predictor variables with SARS-CoV-2 infection (defined by PCR, serology or suspected COVID-19) in a diverse group of HCWs.Results2,496 of the 10,772 HCWs (23.2%) who worked during the first UK national lockdown in March 2020 reported previous SARS-CoV-2 infection. In an adjusted model, demographic and household factors associated with increased odds of infection included younger age, living with other key workers and higher religiosity. Important occupational risk factors associated with increased odds of infection included attending to a higher number of COVID-19 positive patients (aOR 2.49, 95%CI 2.03–3.05 for ≥21 patients per week vs none), working in a nursing or midwifery role (1.35, 1.15– 1.58, compared to doctors), reporting a lack of access to personal protective equipment (1.27, 1.15 – 1.41) and working in an ambulance (1.95, 1.52–2.50) or hospital inpatient setting (1.54, 1.37 – 1.74). Those who worked in Intensive Care Units were less likely to have been infected (0.76, 0.63–0.90) than those who did not. Black HCWs were more likely to have been infected than their White colleagues, an effect which attenuated after adjustment for other known predictors.ConclusionsWe identified key sociodemographic and occupational risk factors associated with SARS-CoV-2 infection amongst UK HCWs, and have determined factors that might contribute to a disproportionate odds of infection in HCWs from Black ethnic groups. These findings demonstrate the importance of social and occupational factors in driving ethnic disparities in COVID-19 outcomes, and should inform policies, including targeted vaccination strategies and risk assessments aimed at protecting HCWs in future waves of the COVID-19 pandemic.Trial registrationISRCTN 11811602

BackgroundVaccination is key to successful prevention of COVID-19 particularly nosocomial acquired infection in health care workers (HCWs). ‘Vaccine hesitancy’ is common in the population and in HCWs, and like COVID-19 itself, hesitancy is more frequent in ethnic minority groups. UK-REACH (United Kingdom Research study into Ethnicity and COVID-19 outcomes) is a large-scale study of COVID-19 in UK HCWs from diverse ethnic backgrounds, which includes measures of vaccine hesitancy. The present study explores predictors of vaccine hesitancy using a ‘phenomic approach’, considering several hundred questionnaire-based measures.MethodsUK-REACH includes a questionnaire study encompassing 12,431 HCWs who were recruited from December 2020 to March 2021 and completed a lengthy online questionnaire (785 raw items; 392 derived measures; 260 final measures). Ethnicity was classified using the Office for National Statistics’ five (ONS5) and eighteen (ONS18) categories. Missing data were handled by multiple imputation. Variable selection used theislassopackage inR, which provides standard errors so that results from imputations could be combined using Rubin’s rules. The data were modelled using path analysis, so that predictors, and predictors of predictors could be assessed. Significance testing used the Bayesian approach of Kass and Raftery, a ‘very strong’ Bayes Factor of 150, N=12,431, and a Bonferroni correction giving a criterion of p−8for the main regression, and p−10for variables in the path analysis.ResultsAt the first step of the phenomic analysis, six variables were direct predictors of greater vaccine hesitancy: Lower pro-vaccination attitudes; no flu vaccination in 2019-20; pregnancy; higher COVID-19 conspiracy beliefs; younger age; and lower optimism the roll-out of population vaccination. Overall 44 lower variables in total were direct or indirect predictors of hesitancy, with the remaining 215 variables in the phenomic analysis not independently predicting vaccine hesitancy. Key variables for predicting hesitancy were belief in conspiracy theories of COVID-19 infection, and a low belief in vaccines in general. Conspiracy beliefs had two main sets of influences:Higher Fatalism, which was influenced a) by high external and chance locus of control and higher need for closure, which in turn were associated with neuroticism, conscientiousness, extraversion and agreeableness; and b) by religion being important in everyday life, and being Muslim.receiving information via social media, not having higher education, and perceiving greater risks to self, the latter being influenced by higher concerns about spreading COVID, greater exposure to COVID-19, and financial concerns.There were indirect effects of ethnicity, mediated by religion. Religion was more important for Pakistani and African HCWs, and less important for White and Chinese groups. Lower age had a direct effect on hesitancy, and age and female sex also had several indirect effects on hesitancy.ConclusionsThe phenomic approach, coupled with a path analysis revealed a complex network of social, cognitive, and behavioural influences on SARS-Cov-2 vaccine hesitancy from 44 measures, 6 direct and 38 indirect, with the remaining 215 measures not having direct or indirect effects on hesitancy. It is likely that issues of trust underpin many associations with hesitancy. Understanding such a network of influences may help in tailoring interventions to address vaccine concerns and facilitate uptake in more hesistant groups.FundingUKMRI-MRC and NIHR

Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV1), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were significantly associated with FEV1. This study investigates the utility of assessing gene-by-smoking interactions and underscores their effects on potential pulmonary function.