Critical illness in COVID-19 is both an extreme disease phenotype and a relatively homogeneous clinical definition; it includes patients with hypoxaemic respiratory failure⁵ with acute lung injury⁶, and excludes many patients with non-pulmonary clinical presentations⁷, who are known to have divergent responses to therapy⁸. In the UK, individuals in the critically ill group are younger, less likely to have significant comorbidity and more severely affected than a general hospitalized cohort⁵, characteristics which may amplify observed genetic effects. In addition, as development of critical illness is in itself a key clinical end-point for therapeutic trials⁸, using critical illness as a phenotype in genetic studies enables the detection of directly therapeutically relevant genetic effects¹.

Using microarray genotyping in 2,244 cases, we previously discovered that critical COVID-19 is associated with genetic variation in the host immune response to viral infection (OAS1, IFNAR2 and TYK2) and the inflammasome regulator DPP9¹. In collaboration with international groups, we extended these findings to include a variant near TAC4 (rs77534576)³. Several variants have been associated with milder phenotypes, including the ABO blood-type locus², a pleiotropic inversion in chr17q21.31⁹ and associations in five additional loci, including the T lymphocyte-associated transcription factor, FOXP4³. An enrichment of rare loss-of-function variants in candidate interferon signalling genes has been reported⁴, but this has yet to be replicated at genome-wide significance thresholds^10,11.

In partnership with Genomics England, we performed whole-genome sequencing (WGS) to improve the resolution and deepen the fine-mapping of significant signals and thereby provide further biological insight into critical COVID-19. Here we present results from a cohort of 7,491 critically ill patients from 224 intensive care units, compared with 48,400 control individuals, describing the discovery and validation of 23 gene loci for susceptibility to critical COVID-19 (Extended Data Fig. 1).

After quality control procedures, we used a logistic mixed model regression, implemented in SAIGE¹², to perform association analyses with unrelated individuals (critically ill cases, n = 7,491; controls, n = 48,400 (100,000 Genomes Project (100k) cohort, n = 46,770; mild COVID-19, n = 1,630) (Methods, Supplementary Table 2). A total of 1,339 of these cases were included in the primary analysis for our previous report¹. Genome-wide association studies (GWASs) were performed separately for genetic ancestry groups (n_cases/n_controls: European (EUR) 5,989/42,891; South Asian (SAS) 788/3,793; African (AFR) 440/1,350; East Asian (EAS) 274/366), and combined by inverse-variance-weighted fixed effects meta-analysis using METAL (Methods). We established the independence of signals using GCTA-cojo, and we validated this with conditional analysis using individual-level data with SAIGE (Methods, Supplementary Table 6). To reduce the risk of spurious associations arising from genotyping or pipeline errors, we required supporting evidence from variants in linkage disequilibrium (LD) for all genome-wide-significant variants: observed z-scores for each variant were compared with imputed z-scores for the same variant, with discrepant values being excluded (see Methods, Supplementary Fig. 2).

In population-specific analyses, we discovered 22 independent genome-wide-significant associations in the EUR ancestry group (Fig. 1, Supplementary Fig. 11, Table 1) at a \(P\) value threshold adjusted for multiple testing (2.2 × 10⁻⁰⁸; Supplementary Table 5). In multi-ancestry meta-analysis, we identified an additional three independent genome-wide-significant association signals (Fig. 1, Table 1).

To assess the sensitivity of our results to mismatches of demographic characteristics between cases and controls (Supplementary Figs. 9, 10), we performed an age-, sex- and body mass index (BMI)-matched case–control analysis (Supplementary Figs. 18–21). As there is a theoretical risk of mismatch between cases and 100,000 Genomes Project participants in risk factors for exposure (for example, shielding behaviour) or susceptibility to critical COVID-19 (for example, immunosuppression), we performed a sensitivity analysis using only the cohort with mild COVID-19 (see above; Supplementary Table 10). In both of these analyses, allele frequencies and directions of effect were concordant for all lead signals.

We inferred credible sets of variants using Bayesian fine-mapping with susieR¹³, by analysing the GWAS summaries of 17 regions of genomic length 3 Mb that were flanking groups of lead signals. We obtained 22 independent credible sets of variants for EUR and an additional 2 from the trans-ancestry meta-analysis with a posterior inclusion probability greater than 0.95 (Extended Data Table 1, Supplementary Information). Fine-mapping of the association signals revealed putative causal variants for both previously reported and novel association signals (see Supplementary Information, Extended Data Table 1). In 12 out of the 24 fine-mapped signals, the credible sets included 5 or fewer variants, and for 8 signals we detected variants with predicted missense or worse consequence across each credible set (Extended Data Table 1). We were able to fine-map multiple independent signals at previously identified loci (Fig. 3, Extended Data Figs. 2, 4). For example, the signal in the 3p21.31 region², was fine-mapped into two independent associations, with the credible set for the first refined to a single variant in the 5′ untranslated region (UTR) of SLC6A20 (chr3:45796521:G:T, rs2271616, odds ratio (OR): 1.29, 95% confidence interval (CI):1.21–1.37), and the second credible set including multiple variants in downstream and intronic regions of LZTFL1 (Fig. 3). Among the novel signals, at 3q24 and 9p21.3 we detected missense variants that affect PLSCR1 and IFNA10, respectively (chr3:146517122:G:A, rs343320, p.His262Tyr, OR: 1.24, 95% CI: 1.15–1.33, CADD: 22.6; chr9:21206606:C:G, rs28368148, p.Trp164Cys, OR:1.74, 95% CI: 1.45–2.09, CADD: 23.9). Both are predicted to be deleterious by the Combined Annotation Dependent Depletion (CADD) tool¹⁴. Structural predictions for these variants suggest functional effects (Extended Data Fig. 5). We assessed whether the main signals of this study were underlain by rarer variants with a lower minor allele frequency (MAF) (less than 0.02%) than our GWAS default threshold (less than 0.5%), by including rarer variant summaries when fine-mapping, but no additional variants were added to the main credible sets (Supplementary Table 9).

Consistent with our expectation that genetic susceptibility has a stronger role in younger individuals, age-stratified analysis (individuals of younger than 60 years old versus individuals of 60 years old or above) in the EUR group revealed a signal in the 3p21.31 region with a significantly stronger effect in the younger age group (chr3:45801750:G:A, rs13071258, OR: 3.34, 95% CI: 2.98–3.75 versus OR: 2.1, 95% CI 1.88–2.34), which is in strong LD (r² = 0.947) with the main GWAS signal indexed by rs73064425. Sex-specific analysis did not reveal significant effects (Supplementary Fig. 17).

For replication, we performed a meta-analysis of summary statistics generously shared by 23andMe and the COVID-19 Host Genetics Initiative (HGI) data freeze 6 (B2). As a previous analysis of GenOMICC¹ contributes a substantial part of the signal at each locus in HGI v.6, and leave-one-out analyses were not available, we removed the signal from GenOMICC cases in HGI v.6 using mathematical subtraction to ensure independence (Methods). Using LD clumping to find variants genotyped in both the discovery and replication studies, we required P < 0.002 (0.05/25) and concordant direction of effect (Table 1, Supplementary Table 8) for replication. We interrogated two variants that failed replication in this set in a second GWAS meta-analysis of hospitalized patients with COVID-19 from UK Biobank, AncestryDNA, Penn Medicine Biobank and Geisinger Health Systems, which included a total of 9,937 individuals who were hospitalized with COVID-19 and 1,059,390 control individuals. This led to a further successful replicated finding, in IFNA10 (Table 1).

We replicated 23 of the 25 significant associations that were identified in the population-specific and/or multi-ancestry GWASs. One of the non-replicated signals (rs4424872) corresponds to a rare variant that may not be well represented in the replication datasets—which are dominated by single-nucleotide polymorphism (SNP) genotyping data—but which also had significant heterogeneity among ancestries. The second non-replicated signal is within the human leukocyte antigen (HLA) locus, which has complex LD (see below).

The lead variant in the HLA region, rs9271609, lies upstream of the HLA-DQA1 and HLA-DRB1 genes. To investigate the contribution of specific HLA alleles to the observed association in the HLA region, we imputed HLA alleles at a four-digit (two-field) level using HIBAG¹⁵. The only allele that reached genome-wide significance was HLA-DRB1*04:01 (OR: 0.80, 95% CI: 0.75–0.86, P = 1.6 × 10⁻¹⁰ in EUR), which has a stronger \(P\) value than the lead SNP in the region (OR: 0.88, 95% CI: 0.84–0.92, P = 3.3 × 10⁻⁹ in EUR) and is a better fit to the data (Akaike information criterion (AIC): AIC_DRB1*04:01 = 30,241.34; AIC_leadSNP = 30,252.93) (Extended Data Fig. 6). HLA-DRB1*04:01 has been previously reported to confer protection against severe disease in a small cohort of European ancestry¹⁶.

To assess the contribution of rare variants to critical illness, we performed gene-based analysis using SKAT-O as implemented in SAIGE-GENE¹⁷ on a subset of 12,982 individuals from our cohort (7,491 individuals with critical COVID-19 and 5,391 control individuals), for which the genome-sequencing data were processed with the same alignment and variant calling pipeline. We tested the burden of rare (MAF < 0.5%) variants considering the predicted variant consequence type (tested variant counts provided in the Supplementary Information). We assessed burden using a strict definition for damaging variants (high-confidence putative loss-of-function (pLoF) variants as identified by LOFTEE¹⁸) and a lenient definition (pLoF plus missense variants with CADD ≥ 10)¹⁴, but found no significant associations at a gene-wide-significance level. Moreover, all individual rare variants included in the tests had P values greater than 10⁻⁵.

Consistent with other recent work¹¹, we did not find any significant gene burden test associations among the 13 genes previously reported from an interferon-pathway-focused study⁴ (tests for all genes had P > 0.05; Supplementary Information), and we did not replicate the reported association^19,20,21 in TLR7 (EUR P = 0.30 for pLoF and P = 0.075 for missense variants).

To infer the effect of genetically determined variation in gene expression on disease susceptibility, we performed a transcriptome-wide association study (TWAS) using gene expression data (GTEx v.8; ref. ²²) for two disease-relevant tissues: lung and whole blood. We found significant associations between critical COVID-19 and predicted expression in lung (14 genes) and blood (6 genes) (Supplementary Fig. 23) and in an all-tissue meta-analysis (GTEx v.8; 51 genes) (Supplementary Fig. 24). Expression signals for 16 genes significantly colocalized with susceptibility (Fig. 2). As the LD structure of the HLA is complex, we only assessed colocalization for the significant association, HLA-DRB1. Although it was not significant in our TWAS analysis, expression quantitative trait loci (eQTLs) in the proximity of the association significantly colocalize with the GWAS signal for both blood and lung (both PP_H4 > 0.8; Supplementary Information).

We repeated the TWAS analysis using models of intron excision rate from GTEx v.8 to obtain a splicing TWAS, which revealed significant signals in lung (16 genes) and whole blood (9 genes), and in an all-tissue meta-analysis (33 genes); 11 of these had strongly colocalizing splicing signals (Supplementary Information).

We performed generalized summary-data-based Mendelian randomization (GSMR)²³ in a replicated outcome study design using the protein quantitative trait loci (pQTLs) from the INTERVAL study²⁴. GSMR incorporates information from multiple independent SNPs and provides stronger evidence of a causal relationship than single-SNP-based approaches. Of 16 proteome-wide-significant associations in this study, 8 were replicated in an external dataset at a Bonferroni-corrected P value threshold of P < 0.0031 (P < 0.05/16; Extended Data Table 2, Extended Data Fig. 7) .

We report 23 replicated genetic associations with critical COVID-19, which were discovered in only 7,491 cases. This demonstrates the efficiency of the design of the GenOMICC study, an open-source²⁵ international research programme (https://genomicc.org) that focuses on extreme phenotypes: patients with life-threatening infectious disease, sepsis, pancreatitis and other critical illness phenotypes. GenOMICC detects greater heritability and stronger effect sizes than other study designs across all variants (Supplementary Figs. 22, 14). In COVID-19, critical illness is not only an extreme susceptibility phenotype, but also a more homogeneous one: we have shown previously that critically ill patients with COVID-19 are more likely to have the primary disease process—hypoxaemic respiratory failure⁵—and that patients in this group have a divergent response to immunosuppressive therapy compared to other hospitalized patients⁸. We detect distinct signals at several of the associated loci, in some cases implicating different biological mechanisms.

Five of the variants associated with critical COVID-19 have direct roles in interferon signalling and broadly concordant predicted biological effects. These include a probable destabilizing amino acid substitution in a ligand, IFNA10 (Trp164Cys, Extended Data Fig. 5), and—as we reported previously¹—reduced expression of a subunit of its receptor IFNAR2 (Fig. 2). IFNAR2 signals through a kinase that is encoded by TYK2¹. Although the lead variant in TYK2 in WGS is a protein-coding variant with reduced STAT1 phosphorylation activity²⁶, it is also associated with significantly increased expression of TYK2 (Fig. 2, Methods). Fine-mapping reveals a significant association with an independent missense variant in IL10RB, a receptor for type III (lambda) interferons (rs8178521; Table 1). Finally, we detected a lead risk variant in phospholipid scramblase 1 (chr3:146517122:G:A, rs343320; PLSCR1) which disrupts a nuclear localization signal that is important for the antiviral effect of interferons²⁷ (Extended Data Fig. 5). PLSCR1 controls the replication of other RNA viruses, including vesicular stomatitis virus, encephalomyocarditis virus and influenza A virus^27,28.

Although our genome-wide gene-based association tests did not replicate any findings from a previous pathway-specific study of rare deleterious variants⁴, our results provide robust evidence implicating reduced interferon signalling in susceptibility to critical COVID-19. Notably, systemic administration of interferon in two large clinical trials, albeit late in disease, did not reduce mortality^29,30.

We found significant associations in genes that are implicated in lymphopoesis and in the differentiation of myeloid cells. BCL11A is essential for B and T lymphopoiesis³¹ and promotes the differentiation of plasmacytoid dendritic cells³². TAC4, reported previously³, encodes a regulator of B cell lymphopoesis³³ and antibody production³⁴, and promotes the survival of dendritic cells³⁵. Finally, although the strongest fine-mapping signal at 5q31.1 (chr5:131995059:C:T, rs56162149) is in an intron of ACSL6 with significant effects on expression (Supplementary Information), the credible set includes a missense variant in CSF2 (encoding granulocyte–macrophage colony stimulating factor; GM-CSF) of uncertain significance (chr5:132075767:T:C; Extended Data Table 1). We have previously shown that GM-CSF is strongly up-regulated in critical COVID-19³⁶, and it is already under investigation as a target for therapy³⁷. Mendelian randomization results are consistent with a direct link between the plasma levels of a closely related cytokine receptor subunit, IL3RA, and critical COVID-19 (Extended Data Table 2).

Fine-mapping, colocalization and TWAS analyses provide evidence for increased expression of MUC1 as the mediator of the association with rs41264915 (Supplementary Table 12). This suggests that mucins could have a therapeutically important role in the development of critical illness in COVID-19.

Mendelian randomization provides genetic evidence in support of a causal role for coagulation factors (F8) and platelet activation (PDGFRL) in critical COVID-19 (Extended Data Table 2, Extended Data Fig. 7), consistent with autopsy⁶, proteomic³⁸ and therapeutic³⁹ evidence. Perhaps more importantly, we identify specific and closely related intercellular adhesion molecules that have known roles in the recruitment of inflammatory cells to sites of inflammation, including E-selectin (SELE), intercellular adhesion molecule 5 (ICAM5) and DC-SIGN (dendritic-cell-specific ICAM3-grabbing non-integrin; CD209), which may provide additional therapeutic targets. DC-SIGN (CD209) mediates pathogen endocytosis and antigen presentation, and is known to be involved in multiple viral infections, including SARS-CoV and influenza A virus. It has affinity for SARS-CoV-2^40,41.

Our previous report of an association between the OAS gene cluster and severe disease was robustly replicated in an external cohort¹, but does not meet genome-wide significance in the present analysis (Supplementary Table 7). This may indicate a change in the observed effect size because any effect that is detected in GWASs is more likely to have been sampled from the larger end of the range of possible effect sizes —the ‘winner’s curse’. Alternatively, it may indicate either a change in the population of patients (cases or controls) or a change in the pathogen. For example it is possible that—as with the other coronaviruses that are known to infect humans⁴²—more recent variants of SARS-CoV-2 have evolved to overcome this host antiviral defence mechanism.

In contrast to microarray genotyping, WGS is a rapidly evolving and relatively new technology for GWASs, with relatively few sources of population controls. We selected a control cohort from the 100,000 Genomes Project, which was sequenced and analysed using a different platform and bioinformatics pipeline compared with the case cohort (Extended Data Fig. 1). However, to minimize the risk of false-positive associations due to technical artifacts, extensive quality measures were used (Methods). In brief, we masked low-quality genotypes, filtered for genotype signal using a low threshold for missingness and performed a control–control relative allele frequency filter using a subset of samples processed with both bioinformatics pipelines. Finally, we required all significant associations to be supported by local variants in LD, which may be excessively stringent (Methods). Although this approach may remove some true associations, our priority is to maximize confidence in the reported signals. Of 25 variants that meet this requirement, 23 are externally replicated, and the remaining 2 may be true associations that are yet to be replicated owing to a lack of coverage or power in the replication datasets.

The design of our study incorporates genetic signals for every stage in the disease progression into a single phenotype. This includes establishment of infection, viral replication, inflammatory lung injury and hypoxaemic respiratory failure. Although we can have considerable confidence that the replicated associations with critical COVID-19 we report are robust, we cannot determine at which stage in the disease process, or in which tissue, the relevant biological mechanisms are active.

These genetic associations identify biological mechanisms that may underlie the development of life-threatening COVID-19, several of which may be amenable to therapeutic targeting. Furthermore, we demonstrate the value of WGS for fine-mapping loci in a complex trait. In the context of the ongoing global pandemic, translation to clinical practice is an urgent priority. As with our previous work, biological and molecular studies—and, where appropriate, large-scale randomized trials—will be essential before our findings can be translated into clinical practice.

Ethics

GenOMICC study: GenOMICC was approved by the following research ethics committees: Scotland ‘A’ Research Ethics Committee (15/SS/0110) and Coventry and Warwickshire Research Ethics Committee (England, Wales and Northern Ireland) (19/WM/0247). Current and previous versions of the study protocol are available at https://genomicc.org/protocol/. 100,000 Genomes project: the 100,000 Genomes project was approved by the East of England—Cambridge Central Research Ethics Committee (REF 20/EE/0035). Only individuals from the 100,000 Genomes project for whom WGS data were available and who consented for their data to be used for research purposes were included in the analyses. UK Biobank study: ethical approval for the UK Biobank was previously obtained from the North West Centre for Research Ethics Committee (11/NW/0382). The work described herein was approved by UK Biobank under application number 26041. Geisinger Health Systems (GHS) study: approval for DiscovEHR analyses was provided by the GHS Institutional Review Board under project number 2006-0258. AncestryDNA study: all data for this research project were from individuals who provided prior informed consent to participate in AncestryDNA’s Human Diversity Project, as reviewed and approved by our external institutional review board, Advarra (formerly Quorum). All data were de-identified before use. Penn Medicine Biobank study: appropriate consent was obtained from each participant regarding the storage of biological specimens, genetic sequencing and genotyping, and access to all available EHR data. This study was approved by the institutional review board of the University of Pennsylvania and complied with the principles set out in the Declaration of Helsinki. Informed consent was obtained for all study participants. 23andMe study: participants in this study were recruited from the customer base of 23andMe, a personal genetics company. All individuals included in the analyses provided informed consent and answered surveys online according to the 23andMe protocol for research in humans, which was reviewed and approved by Ethical and Independent Review Services, a private institutional review board (http://www.eandireview.com).

Recruitment of cases (patients with COVID-19)

Patients were recruited to the GenOMICC study in 224 UK intensive care units (https://genomicc.org). All individuals had confirmed COVID-19 according to local clinical testing and were deemed, in the view of the treating clinician, to require continuous cardiorespiratory monitoring. In UK practice this kind of monitoring is undertaken in high-dependency or intensive care units.

Recruitment of control individuals

Mild or asymptomatic control individuals

Participants were recruited to the mild COVID-19 cohort on the basis of having experienced mild (non-hospitalized) or asymptomatic COVID-19. Participants volunteered to take part in the study via a microsite and were required to self-report the details of a positive COVID-19 test. Volunteers were prioritized for genome sequencing on the basis of demographic matching with the critical COVID-19 cohort considering self-reported ancestry, sex, age and location within the UK. We refer to this cohort as the COVID-19 mild cohort.

Control individuals from the 100,000 Genomes project

Participants were enrolled in the 100,000 Genomes Project from families with a broad range of rare diseases, cancers and infection by 13 regional NHS Genomic Medicine Centres across England and in Northern Ireland, Scotland and Wales. For this analysis, participants for whom a positive SARS-CoV-2 test had been recorded as of March 2021 were not included owing to uncertainty in the severity of COVID-19 symptoms. Only participants for whom genome sequencing was performed from blood-derived DNA were included and participants with haematological malignancies were excluded to avoid potential tumour contamination.

DNA extraction

For severe cases of COVID-19 and mild cohort controls, DNA was extracted from whole blood either manually using a Nucleon Kit (Cytiva) and resuspended in 1 ml TE buffer pH 7.5 (10 mM Tris-Cl pH 7.5, 1 mM EDTA pH 8.0), or automated on the Chemagic 360 platform using the Chemagic DNA blood kit (PerkinElmer) and re-suspended in 400 μl elution buffer. The yield of the DNA was measured using Qubit and normalized to 50 ng μl⁻¹ before sequencing. For the 100,000 Genomes Project samples, DNA was extracted from whole blood at designated extraction centres following sample handling guidance provided by Genomics England and NHS England.

WGS

Sequencing libraries were generated using the Illumina TruSeq DNA PCR-Free High Throughput Sample Preparation kit and sequenced with 150-bp paired-end reads in a single lane of an Illumina Hiseq X instrument (for 100,000 Genomes Project samples) or a NovaSeq instrument (for the COVID-19 critical and mild cohorts).

Sequencing data quality control

All genome sequencing data were required to meet minimum quality metrics and quality control measures were applied for all genomes as part of the bioinformatics pipeline. The minimum data requirements for all genomes were: more than 85 × 10⁻⁹ bases with Q ≥ 30 and at least 95% of the autosomal genome covered at 15× or higher calculated from reads with mapping quality greater than 10 after removing duplicate reads and overlapping bases, after adaptor and quality trimming. Assessment of germline cross-sample contamination was performed using VerifyBamID and samples with more than 3% contamination were excluded. Sex checks were performed to confirm that the sex reported for a participant was concordant with the sex inferred from the genomic data.

WGS alignment and variant calling

COVID-19 cohorts

For the critical and mild COVID-19 cohorts, sequencing data alignment and variant calling were performed with Genomics England pipeline 2.0, which uses the DRAGEN software (v.3.2.22). Alignment was performed to genome reference GRCh38 including decoy contigs and alternative haplotypes (ALT contigs), with ALT-aware mapping and variant calling to improve specificity.

100,000 Genomes Project cohort

All genomes from the 100,000 Genomes Project cohort were analysed with the Illumina North Star Version 4 Whole Genome Sequencing Workflow (NSV4, v.2.6.53.23); which comprises the iSAAC Aligner (v.03.16.02.19) and Starling Small Variant Caller (v.2.4.7). Samples were aligned to the Homo Sapiens NCBI GRCh38 assembly with decoys.

A subset of the genomes from the cancer program of the 100,000 Genomes Project were reprocessed (alignment and variant calling) using the same pipeline used for the COVID-19 cohorts (DRAGEN v.3.2.22) for equity of alignment and variant calling.

Aggregation

Aggregation was conducted separately for the samples analysed with Genomics England pipeline 2.0 (severe cohort, mild cohort, cancer-realigned 100,000 Genomes Project) and those analysed with the Illumina North Star Version 4 pipeline (100,000 Genomes Project).

For the first three, the WGS data were aggregated from single-sample gVCF files to multi-sample VCF files using GVCFGenotyper (GG) v.3.8.1, which accepts gVCF files generated by the DRAGEN pipeline as input. GG outputs multi-allelic variants (several ALT variants per position on the same row), and for downstream analyses the output was decomposed to bi-allelic variants per row using the software vt v.0.57721. We refer to the aggregate as aggCOVID_vX, in which X is the specific freeze.The analysis in this manuscript uses data from freeze v.4.2 and the respective aggregate is referred to as aggCOVID_v4.2.

Aggregation for the 100,000 Genomes Project cohort was performed using Illumina’s gvcfgenotyper v.2019.02.26, merged with bcftools v.1.10.2 and normalized with vt v.0.57721.

Sample quality control

Samples that failed any of the following four BAM-level quality control filters: freemix contamination > 3%, mean autosomal coverage < 25×, per cent mapped reads < 90% or per cent chimeric reads > 5% were excluded from the analysis.

In addition, a set of VCF-level quality control filters were applied after aggregation on all autosomal bi-allelic single-nucleotide variants (SNVs) (akin to gnomAD v.3.1)¹⁸. Samples were filtered out on the basis of the residuals of eleven quality control metrics (calculated using bcftools) after regressing out the effects of sequencing platform and the first three ancestry assignment principal components (PCs) (including all linear, quadratic and interaction terms) taken from the sample projections onto the SNP loadings from the individuals of 1000 Genomes Project phase 3 (1KGP3). Samples were removed that were four median absolute deviations (MADs) above or below the median for the following metrics: ratio of heterozygous to homozygous, ratio of insertions to deletions, ratio of transitions to transversions, total deletions, total insertions, total heterozygous SNPs, total homozygous SNPs, total transitions and total transversions. For the number of total singletons (SNPs), samples were removed that were more than 8 MADs above the median. For the ratio of heterozygous to homozygous alternative SNPs, samples were removed that were more than 4 MADs above the median.

After quality control, 79,803 individuals were included in the analysis with the breakdown according to cohort shown in Supplementary Table 2.

Selection of high-quality independent SNPs

We selected high-quality independent variants for inferring kinship coefficients, performing PCA, assigning ancestry and for the conditioning on the genetic relatedness matrix by the logistic mixed model of SAIGE and SAIGE-GENE. To avoid capturing platform and/or analysis pipeline effects for these analyses, we performed very stringent variant quality control as described below.

High-quality common SNPs

We started with autosomal, bi-allelic SNPs which had a frequency of higher than 5% in aggV2 (100,000 Genomes Project participant aggregate) and in the 1KGP3. We then restricted to variants that had missingness < 1%, median genotype quality control > 30, median depth (DP) ≥ 30 and at least 90% of heterozygote genotypes passing an ABratio binomial test with P value > 10⁻² for aggV2 participants. We also excluded variants in complex regions from the list available in https://genome.sph.umich.edu/wiki/Regions_of_high_linkage_disequilibrium_(LD) (lifted over for GRCh38), and variants where the REF/ALT combination was CG or AT (C/G, G/C, A/T, T/A). We also removed all SNPs that were out of Hardy–Weinberg equilibrium (HWE) in any of the AFR, EAS, EUR or SAS super-populations of aggV2, with a P value cut-off of P_HWE < 10⁻⁵. We then LD-pruned using PLINK v.1.9 with r² = 0.1 and in 500-kb windows. This resulted in a total of 63,523 high-quality sites from aggV2.

We then extracted these high-quality sites from the aggCOVID_v4.2 aggregate and further applied variant quality filters (missingness < 1%, median quality control > 30, median depth ≥ 30 and at least 90% of heterozygote genotypes passing an ABratio binomial test with P value > 10⁻²), per batch of sequencing platform (that is, HiseqX, NovaSeq6000).

After applying variant filters in aggV2 and aggCOVID_v4.2, we merged the genomic data from the two aggregates for the intersection of the variants, which resulted in a final total of 58,925 sites.

High-quality rare SNPs

We selected high-quality rare (MAF < 0.005) bi-allelic SNPs to be used with SAIGE for aggregate variant testing (AVT) analysis. To create this set, we applied the same variant quality control procedure as with the common variants: We selected variants that had missingness < 1%, median quality control > 30, median depth ≥ 30 and at least 90% of heterozygote genotypes passing an ABratio binomial test with P value > 10⁻² per batch of sequencing and genotyping platform (that is, HiSeq + NSV4, HiSeq + Pipeline 2.0, NovaSeq + Pipeline 2.0). We then subsetted those to the following groups of minor allele count (MAC) and MAF categories: MAC 1, 2, 3, 4, 5, 6–10, 11–20, MAC 20–MAF 0.001, MAF 0.001–0.005.

Relatedness, ancestry and principal components

Kinship

We calculated kinship coefficients among all pairs of samples using the software PLINK v.2.0 and its implementation of the KING robust algorithm. We used a kinship cut-off of <0.0442 to select unrelated individuals with argument “–king-cutoff”.

Genetic ancestry prediction

To infer the ancestry of each individual, we performed principal component analysis (PCA) on unrelated 1KGP3 individuals with GCTA v.1.93.1_beta software using high-quality common SNPs⁴³, and inferred the first 20 PCs. We calculated loadings for each SNP, which we used to project aggV2 and aggCOVID_v4.2 individuals onto the 1KGP3 PCs. We then trained a random forest algorithm from the R package randomForest with the first 10 1KGP3 PCs as features and the super-population ancestry of each individual as labels. These were ‘AFR’ for individuals of African ancestry, ‘AMR’ for individuals of American ancestry, ‘EAS’ for individuals of East Asian ancestry, ‘EUR’ for individuals of European ancestry and ‘SAS’ for individuals of South Asian ancestry. We used 500 trees for the training. We then used the trained model to assign a probability of belonging to a certain super-population class for each individual in our cohorts. We assigned individuals to a super-population when class probability ≥ 0.8. Individuals for whom no class had probability ≥ 0.8 were labelled as ‘unassigned’ and were not included in the analyses.

PCA

After labelling each individual with predicted genetic ancestry, we calculated ancestry-specific PCs using GCTA v.1.93.1_beta⁴³. We computed 20 PCs for each of the ancestries that were used in the association analyses (AFR, EAS, EUR and SAS).

Variant quality control

Variant quality control was performed to ensure high quality of variants and to minimize batch effects due to using samples from different sequencing platforms (NovaSeq6000 and HiseqX) and different variant callers (Strelka2 and DRAGEN). We first masked low-quality genotypes setting them to missing, merged aggregate files and then performed additional variant quality control separately for the two major types of association analyses, GWAS and AVT, which concerned common and rare variants, respectively.

Masking

Before any analysis, we masked low-quality genotypes using the bcftools setGT module. Genotypes with DP < 10, genotype quality (GQ) < 20 and heterozygote genotypes failing an ABratio binomial test with P value < 10⁻³ were set to missing.

We then converted the masked VCF files to PLINK and bgen format using PLINK v.2.0.

Merging of aggregate samples

Merging of aggV2 and aggCOVID_v4.2 samples was done using PLINK files with masked genotypes and the merge function of PLINK v.1.9⁴⁴. for variants that were found in both aggregates.

GWAS analyses

Variant quality control

We restricted all GWAS analyses to common variants applying the following filters using PLINK v.1.9: MAF > 0 in both cases and controls, MAF > 0.5% and MAC > 20, missingness < 2%, differential missingness between cases and controls, mid-P value < 10⁻⁵, HWE deviations on unrelated controls, mid-P value < 10⁻⁶. Multi-allelic variants were in addition required to have MAF > 0.1% in both aggV2 and aggCOVID_v4.2.

Control–control quality control filter

100,000 Genomes Project aggV2 samples that were aligned and genotype called with the Illumina North Star version 4 pipeline represented the majority of control samples in our GWAS analyses, whereas all of the cases were aligned and called with Genomics England pipeline 2.0 (Supplementary Table 1). Therefore, the alignment and genotyping pipelines partially match the case–control status, which necessitates additional filtering for adjusting for between-pipeline differences in alignment and variant calling. To control for potential batch effects, we used the overlap of 3,954 samples from the Genomics England 100,000 Genomes Project participants that were aligned and called with both pipelines. For each variant, we computed and compared between platforms the inferred allele frequency for the population samples. We then filtered out all variants that had >1% relative difference in allele frequency between platforms. The relative difference was computed on a per-population basis for EUR (n = 3,157), SAS (n = 373), AFR (n = 354) and EAS (n = 81).

Model

We used a two-step logistic mixed model regression approach as implemented in SAIGE v.0.44.5 for single-variant association analyses. In step 1, SAIGE fits the null mixed model and covariates. In step 2, single-variant association tests are performed with the saddlepoint approximation (SPA) correction to calibrate unbalanced case–control ratios. We used the high-quality common variant sites for fitting the null model and sex, age, age², age-by-sex and 20 PCs as covariates in step 1. The PCs were computed separately by predicted genetic ancestry (that is, EUR-specific, AFR-specific and so on), to capture subtle structure effects.

Analyses

All analyses were done on unrelated individuals with a pairwise kinship coefficient < 0.0442. We conducted GWAS analyses per predicted genetic ancestry, for all populations for which we had more than 100 cases and more than 100 controls (AFR, EAS, EUR and SAS).

Multiple testing correction

As our study is testing variants that were directly sequenced by WGS and not imputed, we calculated the P value significance threshold by estimating the effective number of tests. After selecting the final filtered set of tested variants for each population, we LD-pruned in a window of 250 kb and r² = 0.8 with PLINK 1.9. We then computed the Bonferroni-corrected P value threshold as 0.05 divided by the number of LD-pruned variants tested in the GWAS. The P value thresholds that were used for declaring statistical significance are provided in Supplementary Table 5.

LD-clumping

We used PLINK v.1.9 to do clumping of variants that were genome-wide significant for each analysis with P1 set to per-population P value from Supplementary Table 5, P2 = 0.01, clump distance 1,500 kb and r² = 0.1.

Conditional analysis and signal independence

To find the set of independent variants in the per-population analyses, we performed a step-wise conditional analysis with the GWAS summary statistics for each population using GCTA 1.9.3 –cojo-slct function⁴³. The parameters for the function were pval = 2.2 × 10⁻⁸, a distance of 10,000 kb and a colinear threshold of 0.9 (ref. ⁴⁵). For establishing independence of multi-ancestry meta-analysis signals from per-population discovered signals, we performed LD-clumping using the meta-analysis summaries and identified signals with no overlap with the LD-clumped results from the per-population analyses. In addition to the GCTA-cojo analysis, we also performed confirmatory individual-level conditional analysis as implemented in SAIGE. For every lead variant signal (including the multi-ancestry meta-analysis signals), we conditioned on the lead variants of all other signals identified as independent by GCTA-cojo and located on the same chromosome with option –condition of SAIGE (Supplementary Table 6).

Fine-mapping

We performed fine-mapping for genome-wide-significant signals using theR package SusieR v.0.11.42¹³. For each genome-wide-significant variant locus, we selected the variants 1.5 Mbp on each side and computed the correlation matrix among them with PLINK v.1.9. We then ran the susieR summary-statistics-based function susie_rss and provided the summary z scores from SAIGE (that is, effect size divided by its standard error) and the correlation matrix computed with the same samples that were used for the corresponding GWAS. We required coverage ≥``{=html}0.95 for each identified credible set and minimum and median absolute correlation coefficients (purity) of r = 0.1 and 0.5, respectively.

Functional annotation of credible sets

We annotated all variants included in each credible set identified by SusieR using the online Variant Effect Predictor (VEP) v.104 and selected the worst consequence across GENCODE basic transcripts (Supplementary Information). We also ranked each variant within each credible set according to the predicted consequence and the ranking was based on the table provided by Ensembl: https://www.ensembl.org/info/genome/variation/prediction/predicted_data.html.

Multi-ancestry meta-analysis

We performed a meta-analysis across all ancestries using an inverse-variance weighting method and control for population stratification for each separate analysis in the METAL software⁴⁶. The meta-analysed variants were filtered for variants with heterogeneity P value P < 2.22 × 10⁻⁸ and variants that are not present in at least half of the individuals. We used the meta R package to plot forest plots of the clumped multi-ancestry meta-analysis variants⁴⁷.

LD-based validation of lead GWAS signals

To quantify the support for genome-wide-significant signals from nearby variants in LD, we assessed the internal consistency of GWAS results of the lead variants and their surroundings. To this end, we compared observed z-scores at lead variants with the expected z-scores based on those observed at neighbouring variants. Specifically, we computed the observed z-score for a variant i as \({s}_{i}=\hat{\beta }/{\hat{\sigma }}_{\hat{\beta }}\) and, following a previous approach⁴⁸, the imputed z-score at a target variant t as

where \({{\bf{s}}}_{P}\) are the observed z-scores at a set P of predictor variants, \({{\boldsymbol{\Sigma }}}_{x,y}\) is the empirical correlation matrix of dosage coded genotypes computed on the GWAS sample between the variants in x and y, and λ is a regularization parameter set to 10⁻⁵. The set P of predictor variants consisted of all variants within 100 kb of the target variant with a genotype correlation with the target variant greater than 0.25. This approach is similar to one proposed recently⁴⁹.

Stratified analysis

We performed sex-specific analysis (male and female individuals separately) as well as analysis stratified by age (that is, participants of younger than 60 years old and 60 years old or above) for the EUR ancestry group. To compare the effect of variants within groups for the age- and sex-stratified analysis we first adjusted the effect and error of each variant for the standard deviation of the trait in each stratified group and then used the following t-statistic, as in previous studies^50,51

where b₁ is the adjusted effect for group 1, b₂ is the adjusted effect for group 2, se₁ and se₂ are the adjusted standard errors for groups 1 and 2, respectively, and r is the Spearman rank correlation between groups across all genetic variants.

Replication

To generate a replication set, we conducted a meta-analysis of data from 23andMe, together with a meta-analysis of the COVID-19 HGI data freeze 6 (hospitalized COVID versus population) GWAS (B2 analysis), including all genetic ancestries. Although the HGI programme included an analysis designed to mirror the GenOMICC study (analysis ‘A2’), most of these cases come from GenOMICC and are already included in the discovery cohort. We therefore used the broader hospitalized phenotype (‘B2’) for replication.

To account for signal due to sample overlap we performed a mathematical subtraction from HGI v.6 B2, of the GenOMICC GWAS of European genetic ancestry. Publicly available HGI data were downloaded from https://www.covid19hg.org/results/r6/. The subtraction was performed using the MetaSubtract package (v.1.60) for R (v.4.0.2) after removing variants with the same genomic position and using the lambda.cohorts with genomic inflation calculated on the GenOMICC summary statistics.

We calculated a multi-ancestry meta-analysis for the three ancestries with summary statistics in 23andMe—African, Latino and European—using variants that passed the 23andMe ancestry quality control, with imputation score > 0.6 and with MAF > 0.005, before performing a final meta-analysis of 23andMe and HGI B2 without GenOMICC to create the final replication set. Meta-analysis was performed using METAL⁴⁶, with the inverse-variance weighting method (STDERR mode) and genomic control ON. We considered that a hit was replicated if the direction of effect in the GenOMICC-subtracted HGI summary statistics was the same as in our GWAS, and the P value was significant after Bonferroni correction for the number of attempted replications (pval < 0.05/25). If the main hit was not present in the HGI–23andMe meta-analysis or if the hit was not replicating, we looked for replication in variants in high LD with the top variant (r² > 0.9), which helped replicate two regions.

To attempt additional replication of two associations, we performed a multi-ancestry meta-analysis across five continental ancestry groups in the UK Biobank, AncestryDNA, Penn Medicine Biobank and GHS, totalling 9,937 hospitalized cases of COVID-19 and 1,059,390 controls (COVID-19 negative or unknown). Hospitalization status (positive, negative or unknown) was determined on the basis of COVID-19-related ICD10 codes U071, U072, U073 in variable ‘diag_icd10’ (table ‘hesin_diag’) in the UK Biobank study; self-reported hospitalization due to COVID-19 in the AncestryDNA study; and medical records in the GHS and Penn Medicine Biobank studies. Association analyses in each study were performed using the genome-wide Firth logistic regression test implemented in REGENIE. In this implementation, Firth’s approach is applied when the P value from a standard logistic regression score test is less than 0.05. We included in step 1 of REGENIE (that is, prediction of individual trait values based on the genetic data) directly genotyped variants with MAF > 1%, missingness < 10%, HWE test P > 1 × 10⁻¹⁵ and LD-pruning (1,000 variant windows, 100 variant sliding windows and r² < 0.9). The association model used in step 2 of REGENIE included as covariates age, age², sex, age-by-sex, and the first 10 ancestry-informative PCs derived from the analysis of a stricter set of LD-pruned (50 variant windows, 5 variant sliding windows and r² < 0.5) common variants from the array (imputed for the GHS study) data. Within each study, association analyses were performed separately for five different continental ancestries defined on the basis of the array data: African (AFR), Hispanic or Latin American (HLA), East Asian (EAS), European (EUR) and South Asian (SAS). Results were subsequently meta-analysed across studies and ancestries using an inverse-variance-weighted fixed-effects meta-analysis.

HLA imputation and association analysis

HLA types were imputed at two-field (four-digit) resolution for all samples within aggV2 and aggCOVID_v4.2 for the following seven loci: HLA-A, HLA-C, HLA-B, HLA-DRB1, HLA-DQA1, HLA-DQB1 and HLA-DPB1, using the HIBAG package in R¹⁵. At the time of writing, HLA types were also imputed for \(\mathop{8}\limits^{ \sim }\) 2% of samples using HLA*LA⁵². Inferred HLA alleles between HIBAG and HLA*LA were more than 96% identical at four-digit resolution. HLA association analysis was run under an additive model using SAIGE, in an identical manner to the SNV GWAS. The multi-sample VCF of aggregated HLA type calls from HIBAG was used as input in cases in which any allele call with posterior probability (T) < 0.5 were set to missing.

AVT

AVT on aggCOVID_v4.2 was performed using SKAT-O as implemented in SAIGE-GENE v.0.44.5¹⁷ on all protein-coding genes. Variant and sample quality control for the preparation and masking of the aggregate files have been described elsewhere. We further excluded SNPs with differential missingness between cases and controls (mid-P value < 10⁻⁵) or a site-wide missingness above 5%. Only bi-allelic SNPs with MAF < 0.5% were included.

We filtered the variants to include in the AVT by applying two functional annotation filters: a putative loss of function (pLoF) filter, in which only variants that are annotated by LOFTEE¹⁸ as high-confidence loss of function were included; and a more lenient (missense) filter, in which variants that have a consequence of missense or worse as annotated by VEP, with a CADD_PHRED score of ≥10, were also included. All variants were annotated using VEP v99. SAIGE-GENE was run with the same covariates used in the single variant analysis: sex, age, age², age-by-sex and 20 (population-specific) PCs generated from common variants (MAF ≥ 5%).

We ran the tests separately by genetically predicted ancestry, as well as across all four ancestries as a mega-analysis. We considered a gene-wide-significant threshold on the basis of the genes tested per ancestry, correcting for the two masks (pLoF and missense; Supplementary Table 14).

Post-GWAS analysis

TWASs

We performed TWASs in the MetaXcan framework and the GTEx v.8 eQTL and splicing quantitative trait loci (sQTL) MASHR-M models available for download in http://predictdb.org/. We first calculated, using the European summary statistics, individual TWASs for whole blood and lung with the S-PrediXcan function^53,54. Then we performed a metaTWAS including data from all tissues to increase statistical power using s-MultiXcan⁵⁵. We applied the Bonferroni correction to the results to choose significant genes and introns for each analysis.

Colocalization analysis

Significant genes from the TWAS, splicing TWAS, metaTWAS and splicing metaTWAS, as well as genes for which one of the top variants was a significant eQTL or sQTL, were selected for a colocalization analysis using the coloc R package⁵⁶. We chose the lead SNPs from the European ancestry GWAS summary statistics and a region of ±200 kb around each SNP to do the colocalization with the identified genes in the region. GTEx v.8 whole-blood and lung tissue summary statistics and eqtlGen (which has blood eQTL summary statistics for more than 30,000 individuals) were used for the analysis^22,57. We first performed a sensitivity analysis of the posterior probability of colocalization (PP_H4) on the prior probability of colocalization (P₁₂), going from P₁₂ = 10⁻⁸ to P₁₂ = 10⁻⁴, with the default threshold being P₁₂ = 10⁻⁵. eQTL signal and GWAS signals were deemed to colocalize if these two criteria were met: (1) at P₁₂ = 5 × 10⁻⁵ the probability of colocalization PP_H4 > 0.5; and (2) at P₁₂ = 10⁻⁵ the probability of independent signal (PP_H3) was not the main hypothesis (PP_H3 < 0.5). These criteria were chosen to allow eQTLs with weaker P values, owing to lack of power in GTEx v.8, to be colocalized with the signal when the main hypothesis using small priors was that there was not any signal in the eQTL data.

As the chromosome 3-associated interval is larger than 200 kb, we performed additional colocalization including a region up to 500 kb, but no further colocalizations were found.

Mendelian randomization

We performed GSMR²³ in a replicated outcome study design. As exposures, we used the pQTLs from the INTERVAL study²⁴. We used the 1000 Genomes Project imputed data of the Health and Retirement Study (HRS) (n = 8,557) as the LD reference data required for GSMR analysis. The HRS data are available from dbGap (accession number: phs000428).

GSMR was undertaken using all exposures for which we were able to identify two or more independent SNPs associated with the exposure (P value(exposure) < 5 × 10⁻⁸; LD clumping ±1 Mb, r² < 0.05; HEIDI-outlier filtering test, for the removal of SNPs with evidence of horizontal pleiotropy, was performed at the default threshold value of 0.01). Using GSMR, we identified those proteins implicated in determining COVID-19 severity in the new GenOMICC results (following genomic-control correction for inflation) at a false discovery rate (FDR) of less than 0.05, and attempted replication in the GWAS of ‘Hospitalized COVID versus population’ (phenotype B2) of the COVID-19 HGI (ref. ⁵⁸) having excluded the previous GenOMICC results. We achieved this by mathematically removing the contribution of GenOMICC¹ from the meta-analysis. We considered as replicated those results that passed a Bonferroni-corrected P value threshold, correcting for the total number of replication tests attempted (that is, the number of observations from the discovery set with FDR < 0.05).

Heritability

For the SNP-based narrow-sense heritabilities of severe COVID-19 and HGI COVID phenotypes, both high-definition likelihood (HDL) and LD score regression (LDSC)⁵⁹ methods were applied. The HGI summary statistics were based on the GWAS analysis of all available samples, in which the majority were European populations (see https://www.covid19hg.org/results/r6/). The munge_sumstats.py procedure in the LDSC software was used to harmonize the summary statistics, and in LDSC, the reference panel was built using the 1000 Genome European samples with SNPs that have MAF > 0.05. As both HDL and LDSC are based on GWAS summary z-score statistics, the estimated heritabilities are thus on the observed scale.

Enrichment analysis

Enrichment analysis was performed to identify ontologies in which discovery genes were overrepresented. Using the XGR algorithm (http://galahad.well.ox.ac.uk/XGR)⁶⁰, 19 genes identified through lead variant proximity, credible variant sets, mutation consequence and TWAS analyses were tested for enrichment in disease ontology⁶¹, gene ontologies (biological process, molecular function and cellular component)⁶² and KEGG⁶³ and Reactome⁶⁴ pathways using default settings. This generated a P value and FDR for overrepresentation of genes within each of the ontologies (Supplementary Table 15).

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this paper.

All data are available through https://genomicc.org/data. This includes downloadable summary data tables and instructions for applying to access individual-level data. Individual-level genome sequence data for the COVID-19 severe and mild cohorts can be analysed by qualified researchers in the UK Outbreak Data Analysis Platform at the University of Edinburgh by application at https://genomicc.org/data. Genomic data for the 100,000 Genomes Project participants and a subset of COVID-19 cases are also available through the Genomics England research environment, which can be accessed by application at https://www.genomicsengland.co.uk/join-a-gecip-domain. The full GWAS summary statistics for the 23andMe discovery dataset are available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. More information and access to the data are provided at https://research.23andMe.com/dataset-access/.

Code to calculate the imputation of P values based on LD SNPs is available at https://github.com/baillielab/GenOMICC_GWAS.

We thank the patients and their loved ones who volunteered to contribute to this study at one of the most difficult times in their lives, and the research staff in every intensive care unit who recruited patients at personal risk under challenging conditions. GenOMICC was funded by the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council (MRC), UKRI, Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (J.K.B., 223164/Z/21/Z) a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. WGS was performed by Illumina at Illumina Laboratory Services and was overseen by Genomics England. We would like to thank all at Genomics England who have contributed to the sequencing, clinical and genomic data analysis. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref. MC_PC_20029). A.D.B. would like to acknowledge funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z) and the Edinburgh Clinical Academic Track (ECAT) programme. We thank the research participants and employees of 23andMe for making this work possible. Genomics England and the 100,000 Genomes Project were funded by the National Institute for Health Research, the Wellcome Trust, the MRC, Cancer Research UK, the DHSC and NHS England. We are grateful for the support from S. Hill and the team in NHS England and the 13 Genomic Medicine Centres that delivered the 100,000 Genomes Project, which provided most of the control genome sequences for this study. We thank the participants in the 100,000 Genomes Project, who made this study possible, and the Genomics England Participant Panel for their strategic advice, involvement and engagement. We acknowledge NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre, who provided life-course longitudinal clinical data on the participants. This work forms part of the portfolio of research of the National Institute for Health Research Barts Biomedical Research Centre. Mark Caulfield is an NIHR Senior Investigator. This study owes a great deal to the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. Additional replication was conducted using the UK Biobank Resource (project 26041). The Penn Medicine BioBank is funded by a gift from the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health under CTSA award number UL1TR001878; and the Perelman School of Medicine at the University of Pennsylvania. We thank the AncestryDNA customers who voluntarily contributed information in the COVID-19 survey. HRS (dbGaP accession: phs000428.v1.p1): HRS was supported by the National Institute on Aging (NIA U01AG009740). The genotyping was funded separately by the National Institute on Aging (RC2 AG036495, RC4 AG039029). Genotyping was conducted by the NIH Center for Inherited Disease Research (CIDR) at Johns Hopkins University. Genotyping quality control and final preparation of the data were performed by the Genetics Coordinating Center at the University of Washington. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by the NCI, NHGRI, NHLBI, NIDA, NIMH and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 22 August 2021 (GTEx Analysis Release v.8 (dbGaP Accession phs000424.v8.p2). We thank the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available at https://www.covid19hg.org/acknowledgements. The views expressed are those of the authors and not necessarily those of the DHSC, NHS, Department for International Development (DID), NIHR, MRC, Wellcome Trust or Public Health England.

1. These authors contributed equally: Athanasios Kousathanas, Erola Pairo-Castineira

2. These authors jointly supervised this work: Sara Clohisey Hendry, Loukas Moutsianas, Andy Law, Mark J. Caulfield, J. Kenneth Baillie

Authors and Affiliations

1. Genomics England, London, UK

   Athanasios Kousathanas, Alex Stuckey, Christopher A. Odhams, Susan Walker, Daniel Rhodes, Afshan Siddiq, Peter Goddard, Sally Donovan, Tala Zainy, Fiona Maleady-Crowe, Linda Todd, Shahla Salehi, Greg Elgar, Georgia Chan, Prabhu Arumugam, Christine Patch, Augusto Rendon, Tom A. Fowler, Richard H. Scott, Loukas Moutsianas & Mark J. Caulfield

2. Roslin Institute, University of Edinburgh, Edinburgh, UK

   Erola Pairo-Castineira, Konrad Rawlik, Clark D. Russell, Jonathan Millar, Fiona Griffiths, Wilna Oosthuyzen, Bo Wang, Marie Zechner, Nick Parkinson, Albert Tenesa, Sara Clohisey Hendry, Andy Law & J. Kenneth Baillie

3. MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK

   Erola Pairo-Castineira, Lucija Klaric, Albert Tenesa, Chris P. Ponting, Veronique Vitart, James F. Wilson, Andrew D. Bretherick & J. Kenneth Baillie

4. Centre for Inflammation Research, The Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

   Clark D. Russell & J. Kenneth Baillie

5. Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

   Tomas Malinauskas, Katherine S. Elliott & Julian Knight

6. Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia

   Yang Wu

7. Biostatistics Group, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China

   Xia Shen

8. Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK

   Xia Shen, Albert Tenesa & James F. Wilson

9. Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK

   Kirstie Morrice, Angie Fawkes & Lee Murphy

10. Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK

    Sean Keating, Timothy Walsh & J. Kenneth Baillie

11. Department of Critical Care Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, Ontario, Canada

    David Maslove

12. Clinical Research Centre at St Vincent’s University Hospital, University College Dublin, Dublin, Ireland

    Alistair Nichol

13. NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK

    Malcolm G. Semple

14. Respiratory Medicine and Institute in the Park, Alder Hey Children’s Hospital and University of Liverpool, Liverpool, UK

    Malcolm G. Semple

15. Illumina Cambridge, Great Abington, UK

    David Bentley & Clare Kingsley

16. Regeneron Genetics Center, Tarrytown, NY, USA

    Jack A. Kosmicki, Julie E. Horowitz, Aris Baras, Goncalo R. Abecasis & Manuel A. R. Ferreira

17. Geisinger, Danville, PA, USA

    Anne Justice, Tooraj Mirshahi & Matthew Oetjens

18. Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Daniel J. Rader, Marylyn D. Ritchie & Anurag Verma

19. Test and Trace, the Health Security Agency, Department of Health and Social Care, London, UK

    Tom A. Fowler

20. Department of Intensive Care Medicine, Guy’s and St Thomas’ NHS Foundation Trust, London, UK

    Manu Shankar-Hari

21. Department of Medicine, University of Cambridge, Cambridge, UK

    Charlotte Summers

22. William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK

    Charles Hinds

23. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

    Peter Horby

24. Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China

    Lowell Ling

25. Wellcome–Wolfson Institute for Experimental Medicine, Queen’s University Belfast, Belfast, UK

    Danny McAuley

26. Department of Intensive Care Medicine, Royal Victoria Hospital, Belfast, UK

    Danny McAuley

27. UCL Centre for Human Health and Performance, London, UK

    Hugh Montgomery

28. National Heart and Lung Institute, Imperial College London, London, UK

    Peter J. M. Openshaw

29. Imperial College Healthcare NHS Trust: London, London, UK

    Peter J. M. Openshaw

30. Imperial College, London, UK

    Paul Elliott

31. Intensive Care National Audit and Research Centre, London, UK

    Kathy Rowan

32. School of Life Sciences, Westlake University, Hangzhou, China

    Jian Yang

33. Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China

    Jian Yang

34. Great Ormond Street Hospital, London, UK

    Richard H. Scott

35. William Harvey Research Institute, Queen Mary University of London, London, UK

    Mark J. Caulfield

36. Roslin Institute, University of Edinburgh, Edinburgh, UK

    J. Kenneth Baillie, Sara Clohisey Hendry, Johnny Millar, Ruth Armstrong, Ceilia Boz, Adam Brown, Judy Coyle, Louise Cullum, Nicky Day, Esther Duncan, Paul Finernan, Max Head Fourman, James Furniss, Bernadette Gallagher, Ailsa Golightly, Fiona Griffiths, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Hanning Mal, Ellie Mcmaster, Jen Meikle, Mybaya Hellen, Wilna Oosthuyzen, Nick Parkinson, Trevor Paterson, Andrew Stenhouse, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Tony Wackett, Mairi Ward, Jane Weaver & Marie Zechner

37. Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK

    J. Kenneth Baillie & Timothy Walsh

38. Royal Hospital for Children, Glasgow, UK

    Colin Begg & Barry Milligan

39. William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK

    Charles Hinds

40. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

    Peter Horby

41. Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

    Julian Knight

42. Prince of Wales Hospital, Hong Kong, China

    Lowell Ling

43. Department of Critical Care Medicine, Queen’s University and Kingston Health Sciences Centre, Kingston, Ontario, Canada

    David Maslove

44. Wellcome–Wolfson Institute for Experimental Medicine, Queen’s University Belfast, Belfast, UK

    Danny McAuley

45. Department of Intensive Care Medicine, Royal Victoria Hospital, Belfast, UK

    Danny McAuley

46. UCL Centre for Human Health and Performance, London, UK

    Hugh Montgomery

47. Clinical Research Centre at St Vincent’s University Hospital, University College Dublin, Dublin, Ireland

    Alistair Nichol

48. National Heart and Lung Institute, Imperial College London, London, UK

    Peter J. M. Openshaw

49. Imperial College Healthcare NHS Trust: London, London, UK

    Peter J. M. Openshaw

50. Heart Institute, University of São Paulo, São Paulo, Brazil

    Alexandre C. Pereira

51. MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK

    Chris P. Ponting

52. Intensive Care National Audit and Research Centre, London, UK

    Kathy Rowan

53. NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK

    Malcolm G. Semple, Shona C. Moore & Lance Turtle

54. Respiratory Medicine and Institute in the Park, Alder Hey Children’s Hospital and University of Liverpool, Liverpool, UK

    Malcolm G. Semple

55. Department of Intensive Care Medicine, Guy’s and St Thomas’ NHS Foundation Trust, London, UK

    Manu Shankar-Hari

56. Department of Medicine, University of Cambridge, Cambridge, UK

    Charlotte Summers

57. NIHR Clinical Research Network (CRN), Hammersmith Hospital, London, UK

    Latha Aravindan, Sukamal Das, Sheena Murphy & Mihaela Das

58. Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

    Heather Biggs, Anita Furlong & Katherine Schon

59. Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK

    Richard Clark, Audrey Coutts, Lorna Donnelly, Angie Fawkes, Tammy Gilchrist, Katarzyna Hafezi, Louise Macgillivray, Alan Maclean, Sarah McCafferty, Kirstie Morrice, Lee Murphy & Nicola Wrobel

60. Biostatistics Group, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China

    Chenqing Zheng & Jiantao Chen

61. Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands

    Maaike Swets

62. Guys and St Thomas’ Hospital, London, UK

    Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Manu Shankar-Hari & Christopher Whitton

63. Barts Health NHS Trust, London, UK

    Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak & Olivier Zongo

64. James Cook University Hospital, Middlesbrough, UK

    Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett & Evie Headlam

65. Royal Stoke University Hospital, Stoke-on-Trent, UK

    Nageswar Bandla, Minnie Gellamucho, Michelle Davies & Christopher Thompson

66. North Middlesex University Hospital NHS Trust, London, UK

    Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Alasdair Frater, Malik Saleem, David Carter, Samuel Jenkins, Zoe Lamond & Alanna Wall

67. North Middlesex University Hospital NHS Trust, London, UK

    Rohit Kumar

68. The Royal Liverpool University Hospital, Liverpool, UK

    Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A. C. Waite, Victoria Waugh, Ingeborg D. Welters & Karen Williams

69. King’s College Hospital, London, UK

    Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O’Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith & Abigail Knighton

70. Charing Cross Hospital, St Mary’s Hospital and Hammersmith Hospital, London, UK

    David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias & Maie Templeton

71. Nottingham University Hospital, Nottingham, UK

    Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei & Angela Andrew

72. John Radcliffe Hospital, Oxford, UK

    Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie & Jean Wilson

73. Kingston Hospital, Kingston-upon-Thames, UK

    David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera & Jonathan Fox

74. Kingston Hospital, Kingston-upon-Thames, UK

    Denise O’Connor

75. Royal Infirmary of Edinburgh, Edinburgh, UK

    Gillian Andrew, J. Kenneth Baillie, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton & Sophie Birch

76. Queen Alexandra Hospital, Portsmouth, UK

    Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose & Angela Nown

77. Morriston Hospital, Swansea, UK

    Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams & Sophie Arnold

78. Addenbrooke’s Hospital, Cambridge, UK

    Petra Polgarova, Katerina Stroud, Charlotte Summers, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney & Kay Elston

79. BHRUT (Barking Havering)—Queen’s Hospital and King George Hospital, Romford, UK

    Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong & Aparna George

80. Royal Sussex County Hospital, Brighton, UK

    Laura Ortiz-Ruiz de Gordoa, Emily Peasgood & Claire Phillips

81. Queen Elizabeth Hospital, Birmingham, UK

    Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson & James Scriven

82. Queen Elizabeth Hospital, Woolwich, London, UK

    Amy Collins, Waqas Khaliq & Estefania Treus Gude

83. St George’s Hospital, London, UK

    Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun & Kamal Patel

84. Stepping Hill Hospital, Stockport, UK

    Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt & Ahmed Zaki

85. Countess of Chester Hospital, Chester, UK

    Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury & Clare Smedley

86. Royal Blackburn Teaching Hospital, Blackburn, UK

    Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves & Rachel Bolton

87. The Tunbridge Wells Hospital and Maidstone Hospital, Tunbridge Wells, UK

    Miriam Davey, David Golden & Rebecca Seaman

88. Royal Gwent Hospital, Newport, UK

    Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, Owen Richards & Yusuf Cheema

89. Pinderfields General Hospital, Wakefield, UK

    Hollie Brooke, Sarah Buckley, Jose Cebrian Suarez, Ruth Charlesworth, Karen Hansson, John Norris, Alice Poole, Alastair Rose, Rajdeep Sandhu, Brendan Sloan, Elizabeth Smithson, Muthu Thirumaran, Veronica Wagstaff & Alexandra Metcalfe

90. Royal Berkshire NHS Foundation Trust, Reading, UK

    Mark Brunton, Jess Caterson, Holly Coles, Matthew Frise, Sabi Gurung Rai, Nicola Jacques, Liza Keating, Emma Tilney, Shauna Bartley & Parminder Bhuie

91. Broomfield Hospital, Chelmsford, UK

    Sian Gibson, Amanda Lyle, Fiona McNeela, Jayachandran Radhakrishnan & Alistair Hughes

92. Northumbria Healthcare NHS Foundation Trust, North Shields, UK

    Bryan Yates, Jessica Reynolds, Helen Campbell, Maria Thompsom, Steve Dodds & Stacey Duffy

93. Whiston Hospital, Prescot, UK

    Sandra Greer, Karen Shuker & Ascanio Tridente

94. Croydon University Hospital, Croydon, UK

    Reena Khade, Ashok Sundar & George Tsinaslanidis

95. York Hospital, York, UK

    Isobel Birkinshaw, Joseph Carter, Kate Howard, Joanne Ingham, Rosie Joy, Harriet Pearson, Samantha Roche & Zoe Scott

96. Heartlands Hospital, Birmingham, UK

    Hollie Bancroft, Mary Bellamy, Margaret Carmody, Jacqueline Daglish, Faye Moore, Joanne Rhodes, Mirriam Sangombe, Salma Kadiri & James Scriven

97. Ashford and St Peter’s Hospital, Chertsey, UK

    Maria Croft, Ian White, Victoria Frost & Maia Aquino

98. Barnet Hospital, London, UK

    Rajeev Jha, Vinodh Krishnamurthy, Lai Lim & Li Lim

99. East Surrey Hospital, Redhill, UK

    Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech & Sallyanne Trotman

100. Ninewells Hospital, Dundee, UK

     Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman & Clare Whyte

101. Worthing Hospital, Worthing, UK

     Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm & Jordi Margalef

102. St Richard’s Hospital, Chichester, UK

     Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm & Jordi Margalef

103. Southampton General Hospital, Southampton, UK

     Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts & Karen Salmon

104. The Alexandra Hospital, Redditch and Worcester Royal Hospital, Worcester, UK

     Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton & Alex McCurdy

105. Sandwell General Hospital and City Hospital, Birmingham, UK

     Cecilia Ahmed, Balvinder Baines, Sarah Clamp, Julie Colley, Risna Haq, Anne Hayes, Jonathan Hulme, Samia Hussain, Sibet Joseph, Rita Kumar, Zahira Maqsood & Manjit Purewal

106. Blackpool Victoria Hospital, Blackpool, UK

     Leonie Benham, Zena Bradshaw, Joanna Brown, Melanie Caswell, Jason Cupitt, Sarah Melling, Stephen Preston, Nicola Slawson, Emma Stoddard & Scott Warden

107. Royal Glamorgan Hospital, Pontyclun, UK

     Bethan Deacon, Ceri Lynch, Carla Pothecary, Lisa Roche, Gwenllian Sera Howe, Jayaprakash Singh, Keri Turner, Hannah Ellis & Natalie Stroud

108. The Royal Oldham Hospital, Manchester, UK

     Jodie Hunt, Joy Dearden, Emma Dobson, Andy Drummond, Michelle Mulcahy, Sheila Munt, Grainne O’Connor, Jennifer Philbin, Chloe Rishton, Redmond Tully & Sarah Winnard

109. Glasgow Royal Infirmary, Glasgow, UK

     Susanne Cathcart, Katharine Duffy, Alex Puxty, Kathryn Puxty, Lynne Turner, Jane Ireland & Gary Semple

110. St James’s University Hospital and Leeds General Infirmary, Leeds, UK

     Kate Long, Simon Whiteley, Elizabeth Wilby & Bethan Ogg

111. University Hospital North Durham, Durham, UK

     Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell & Ellen Brown

112. Darlington Memorial Hospital, Darlington, UK

     Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell & Ellen Brown

113. Fairfield General Hospital, Bury, UK

     Julie Melville, Jay Naisbitt, Rosane Joseph, Maria Lazo, Olivia Walton & Alan Neal

114. Wythenshawe Hospital, Manchester, UK

     Peter Alexander, Schvearn Allen, Joanne Bradley-Potts, Craig Brantwood, Jasmine Egan, Timothy Felton, Grace Padden, Luke Ward, Stuart Moss & Susannah Glasgow

115. Royal Alexandra Hospital, Paisley, UK

     Lynn Abel, Michael Brett, Brian Digby, Lisa Gemmell, James Hornsby, Patrick MacGoey, Pauline O’Neil, Richard Price, Natalie Rodden, Kevin Rooney, Radha Sundaram & Nicola Thomson

116. Good Hope Hospital, Birmingham, UK

     Bridget Hopkins, James Scriven, Laura Thrasyvoulou & Heather Willis

117. Tameside General Hospital, Ashton-under-Lyne, UK

     Martyn Clark, Martina Coulding, Edward Jude, Jacqueline McCormick, Oliver Mercer, Darsh Potla, Hafiz Rehman, Heather Savill & Victoria Turner

118. Royal Derby Hospital, Derby, UK

     Charlotte Downes, Kathleen Holding, Katie Riches, Mary Hilton, Mel Hayman, Deepak Subramanian & Priya Daniel

119. Medway Maritime Hospital, Gillingham, UK

     Oluronke Adanini, Nikhil Bhatia, Maines Msiska & Rebecca Collins

120. Royal Victoria Infirmary, Newcastle-upon-Tyne, UK

     Ian Clement, Bijal Patel, A. Gulati, Carole Hays, K. Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett & Philip Robinson

121. Poole Hospital, Poole, UK

     Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams & Yasmin Death

122. Bedford Hospital, Bedford, UK

     Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari & Brice Djeugam

123. Queens Hospital Burton, Burton-on-Trent, UK

     Gillian Bell, Katy English, Amro Katary & Louise Wilcox

124. North Manchester General Hospital, Manchester, UK

     Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T. Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper & Joanne Rothwell

125. Aberdeen Royal Infirmary, Aberdeen, UK

     Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper & Adriana Botello

126. Derriford Hospital, Plymouth, UK

     Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe & Kayleigh Spencer

127. Manchester Royal Infirmary, Manchester, UK

     Craig Brandwood, Lara Smith, Richard Clark, Katie Birchall, Laurel Kolakaluri, Deborah Baines & Anila Sukumaran

128. Salford Royal Hospital, Manchester, UK

     Elena Apetri, Cathrine Basikolo, Bethan Blackledge, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Jade Harris, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Melanie Taylor, Vicky Thomas, Danielle Walker, Angiy Michael & Matthew Collis

129. William Harvey Hospital, Ashford, UK

     Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston & James Rand

130. Queen Elizabeth University Hospital, Glasgow, UK

     Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim & Gordan McCreath

131. Bradford Royal Infirmary, Bradford, UK

     Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood & Michael Bentley

132. Bristol Royal Infirmary, Bristol, UK

     Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster & Georgia Efford

133. Norfolk and Norwich University Hospital (NNUH), Norwich, UK

     Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell & Katie Stammers

134. Queen Elizabeth Hospital Gateshead, Gateshead, UK

     Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson & Helen Wild

135. Sunderland Royal Hospital, Sunderland, UK

     Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson & Jordan Jarmain

136. Aintree University Hospital, Liverpool, UK

     Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding & Peter Harding

137. Hull Royal Infirmary, Hull, UK

     Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson & Elizabeth Stones

138. Hull Royal Infirmary, Hull, UK

     Llucia Carbral-Ortega

139. University College Hospital, London, UK

     Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes & Deborah Smyth

140. Royal Devon and Exeter Hospital, Exeter, UK

     Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn & Kizzy Baines

141. The Royal Papworth Hospital, Cambridge, UK

     Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke & Julie Zamikula

142. Ipswich Hospital, Ipswich, UK

     Bally Purewal, Vanessa Rivers & Stephanie Bell

143. Southmead Hospital, Bristol, UK

     Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith & Deanna Stephens

144. Milton Keynes University Hospital, Milton Keynes, UK

     Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren & Sara-Beth Sutherland

145. Royal Hampshire County Hospital, Winchester, UK

     Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson & Caroline Wrey Brown

146. Great Ormond St Hospital and UCL Great Ormond St Institute of Child Health NIHR Biomedical Research Centre, London, UK

     Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A. L. Jones, Tara McHugh, Hamza Meghari, Lauran O’Neill, Mark J. Peters, Samiran Ray & Ana Luisa Tomas

147. Stoke Mandeville Hospital, Aylesbury, UK

     Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt & Danielle Thornton

148. University Hospital of Wales, Cardiff, UK

     Jade Cole, Michelle Davies, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas & Angharad Williams

149. Basingstoke and North Hampshire Hospital, Basingstoke, UK

     Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright & Maria Alvarez Corral

150. Arrowe Park Hospital, Wirral, UK

     Reni Jacob, Cathy Jones & Craig Denmade

151. Chesterfield Royal Hospital Foundation Trust, Chesterfield, UK

     Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson & Amanda Whileman

152. Musgrove Park Hospital, Taunton, UK

     Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton & Marius Vaida

153. Peterborough City Hospital, Peterborough, UK

     Deborah Butcher, Susie O’Sullivan & Nicola Butterworth-Cowin

154. Hinchingbrooke Hospital, Huntingdon, UK

     Deborah Butcher, Susie O’Sullivan & Nicola Butterworth-Cowin

155. Royal Hallamshire Hospital and Northern General Hospital, Sheffield, UK

     Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. Mills, Ajay Raithatha, Matthew Wiles, Jayne Willson, Helen Newell, Alison Lye, Lorenza Nwafor, Claire Jarman, Sarah Rowland-Jones, David Foote, Joby Cole, Roger Thompson, James Watson, Lisa Hesseldon, Irene Macharia, Luke Chetam, Jacqui Smith, Amber Ford, Samantha Anderson, Kathryn Birchall, Kay Housley, Sara Walker, Leanne Milner, Helena Hanratty, Helen Trower, Patrick Phillips, Simon Oxspring & Ben Donne

156. Dumfries and Galloway Royal Infirmary, Dumfries, UK

     Catherine Jardine, Dewi Williams & Alasdair Hay

157. Royal Bolton Hospital, Bolton, UK

     Rebecca Flanagan, Gareth Hughes, Scott Latham, Emma McKenna, Jennifer Anderson, Robert Hull & Kat Rhead

158. Lister Hospital, Stevenage, UK

     Carina Cruz & Natalie Pattison

159. Craigavon Area Hospital, Craigavon, UK

     Rob Charnock, Denise McFarland & Denise Cosgrove

160. Southport and Formby District General Hospital, Ormskirk, UK

     Ashar Ahmed, Anna Morris, Srinivas Jakkula & Arvind Nune

161. Calderdale Royal Hospital, Halifax, UK

     Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq & Sarah Hanley

162. Huddersfield Royal Infirmary, Huddersfield, UK

     Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq & Sarah Hanley

163. Prince Charles Hospital, Merthyr Tydfil, UK

     Bethan Deacon, Meg Hibbert, Carla Pothecary, Dariusz Tetla, Christopher Woodford, Latha Durga & Gareth Kennard-Holden

164. Royal Bournemouth Hospital, Bournemouth, UK

     Debbie Branney, Jordan Frankham, Sally Pitts & Nigel White

165. Royal Preston Hospital, Preston, UK

     Shondipon Laha, Mark Verlander & Alexandra Williams

166. Whittington Hospital, London, UK

     Abdelhakim Altabaibeh, Ana Alvaro, Kayleigh Gilbert, Louise Ma, Loreta Mostoles, Chetan Parmar, Kathryn Simpson, Champa Jetha, Lauren Booker & Anezka Pratley

167. Princess Royal Hospital, Telford and Royal Shrewsbury Hospital, Shrewsbury, UK

     Colene Adams, Anita Agasou, Tracie Arden, Amy Bowes, Pauline Boyle, Mandy Beekes, Heather Button, Nigel Capps, Mandy Carnahan, Anne Carter, Danielle Childs, Denise Donaldson, Kelly Hard, Fran Hurford, Yasmin Hussain, Ayesha Javaid, James Jones, Sanal Jose, Michael Leigh, Terry Martin, Helen Millward, Nichola Motherwell, Rachel Rikunenko, Jo Stickley, Julie Summers, Louise Ting, Helen Tivenan, Louise Tonks & Rebecca Wilcox

168. Princess Royal Hospital, Haywards Heath, UK

     Denise Skinner, Jane Gaylard, Dee Mullan & Julie Newman

169. Macclesfield District General Hospital, Macclesfield, UK

     Maureen Holland, Natalie Keenan, Marc Lyons, Helen Wassall, Chris Marsh, Mervin Mahenthran, Emma Carter & Thomas Kong

170. Royal Surrey County Hospital, Guildford, UK

     Helen Blackman, Ben Creagh-Brown, Sinead Donlon, Natalia Michalak-Glinska, Sheila Mtuwa, Veronika Pristopan, Armorel Salberg, Eleanor Smith, Sarah Stone, Charles Piercy, Jerik Verula, Dorota Burda, Rugia Montaser, Lesley Harden, Irving Mayangao, Cheryl Marriott, Paul Bradley & Celia Harris

171. Hereford County Hospital, Hereford, UK

     Susan Anderson, Eleanor Andrews, Janine Birch, Emma Collins, Kate Hammerton & Ryan O’Leary

172. University Hospital of North Tees, Stockton-on-Tees, UK

     Michele Clark & Sarah Purvis

173. Lincoln County Hospital, Lincoln, UK

     Russell Barber, Claire Hewitt, Annette Hilldrith, Karen Jackson-Lawrence, Sarah Shepardson, Maryanne Wills, Susan Butler, Silvia Tavares, Amy Cunningham, Julia Hindale & Sarwat Arif

174. Royal Cornwall Hospital, Truro, UK

     Sarah Bean, Karen Burt & Michael Spivey

175. Royal United Hospital, Bath, UK

     Carrie Demetriou, Charlotte Eckbad, Sarah Hierons, Lucy Howie, Sarah Mitchard, Lidia Ramos, Alfredo Serrano-Ruiz, Katie White & Fiona Kelly

176. Royal Brompton Hospital, London, UK

     Daniele Cristiano, Natalie Dormand, Zohreh Farzad, Mahitha Gummadi, Kamal Liyanage, Brijesh Patel, Sara Salmi, Geraldine Sloane, Vicky Thwaites, Mathew Varghese & Anelise C. Zborowski

177. University Hospital Crosshouse, Kilmarnock, UK

     John Allan, Tim Geary, Gordon Houston, Alistair Meikle & Peter O’Brien

178. Basildon Hospital, Basildon, UK

     Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches & Mark Vertue

179. Glan Clwyd Hospital, Bodelwyddan, UK

     Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joanne Lewis & Stephanie Rees

180. West Middlesex Hospital, Isleworth, UK

     Metod Oblak, Monica Popescu & Mini Thankachen

181. Royal Lancaster Infirmary, Lancaster, UK

     Andrew Higham, Kerry Simpson & Jayne Craig

182. Western General Hospital, Edinburgh, UK

     Rosie Baruah, Sheila Morris, Susie Ferguson & Amy Shepherd

183. Chelsea and Westminster NHS Foundation Trust, London, UK

     Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins & Jaime Carungcong

184. The Queen Elizabeth Hospital, King’s Lynn, UK

     Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage & Matthew White

185. King’s Mill Hospital, Nottingham, UK

     Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton & Inez Wynter

186. Watford General Hospital, Watford, UK

     Siobhain Carmody & Valerie Joan Page

187. University Hospital Wishaw, Wishaw, UK

     Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D’Sylva & Kathryn Norman

188. Forth Valley Royal Hospital, Falkirk, UK

     Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch & Dhaneesha Senaratne

189. George Eliot Hospital NHS Trust, Nuneaton, UK

     Michaela Hill, Thogulava Kannan & Laura Wild

190. Barnsley Hospital, Barnsley, UK

     Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson & Gemma Wray

191. The Great Western Hospital, Swindon, UK

     Helen Langton, Rachel Prout, Malcolm Watters & Catherine Novis

192. Harefield Hospital, London, UK

     Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Vicky Thwaites & Kanta Mahay

193. Rotherham General Hospital, Rotherham, UK

     Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham & Rachel Walker

194. Ysbyty Gwynedd, Bangor, UK

     Ellen Knights, Alicia Price, Alice Thomas & Chris Thorpe

195. Diana Princess of Wales Hospital, Grimsby, UK

     Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard & Rachael Stead

196. Russell’s Hall Hospital, Dudley, UK

     Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith & Janet Imeson-Wood

197. St Mary’s Hospital, Newport, UK

     Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins & Liz Nicol

198. University Hospital Lewisham, London, UK

     Waqas Khaliq, Rosie Reece-Anthony & Mark Birt

199. Colchester General Hospital, Colchester, UK

     Alison Ghosh & Emma Williams

200. Queen Elizabeth the Queen Mother Hospital, Margate, UK

     Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki & Sharon Turney

201. Royal Albert Edward Infirmary, Wigan, UK

     Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn & Natalia Waddington

202. Victoria Hospital, Kirkcaldy, UK

     Tina Coventry, Susan Fowler, Michael MacMahon & Amanda McGregor

203. Eastbourne District General Hospital, Eastbourne, UK

     Anne Cowley & Judith Highgate

204. Conquest Hospital, St Leonards-on-Sea, UK

     Anne Cowley & Judith Highgate

205. Cumberland Infirmary, Carlisle, UK

     Alison Brown, Jane Gregory, Susan O’Connell, Tim Smith & Luigi Barberis

206. New Cross Hospital, Wolverhampton, UK

     Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell & Elizabeth Radford

207. The Princess Alexandra Hospital, Harlow, UK

     Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White & Amy Easthope

208. Salisbury District Hospital, Salisbury, UK

     Phil Donnison, Fiona Trim & Beena Eapen

209. Dorset County Hospital, Dorchester, UK

     Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams & Barbara Winter-Goodwin

210. University College Dublin, St Vincent’s University Hospital, Dublin, Ireland

     Ailstair Nichol, Kathy Brickell, Michelle Smyth & Lorna Murphy

211. Glangwili General Hospital, Carmarthen, UK

     Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj & Craig Sell

212. Gloucestershire Royal Hospital, Gloucester, UK

     Paula Hilltout, Jayne Evitts, Amanda Tyler & Joanne Waldron

213. Yeovil Hospital, Yeovil, UK

     Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood & Clare Buckley

214. Leicester Royal Infirmary, Leicester, UK

     Peter Barry, Neil Flint, Patel Rekha & Dawn Hales

215. Royal Manchester Children’s Hospital, Manchester, UK

     Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall & Gayathri Subramanian

216. Royal Victoria Hospital, Belfast, UK

     Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins & Bernadette King

217. Wrexham Maelor Hospital, Wrexham, UK

     Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon & Claire Watkins

218. Walsall Manor Hospital, Walsall, UK

     Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga & Emma Virgilio

219. Darent Valley Hospital, Dartford, UK

     Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant & Madeleine Anderson

220. Warrington General Hospital, Warrington, UK

     Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle & Bijoy Mathew

221. Warwick Hospital, Warwick, UK

     Ben Attwood & Penny Parsons

222. University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK

     Geraldine Ward & Pamela Bremmer

223. University Hospital Monklands, Airdrie, UK

     West Joe, Baird Tracy & Ruddy Jim

224. Princess of Wales Hospital, Llantrisant, UK

     Ellie Davies, Lisa Roche & Sonia Sathe

225. Northwick Park Hospital, London, UK

     Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran & Anisha Sukha

226. Raigmore Hospital, Inverness, UK

     Rachael Campbell, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O’Hara, Laura Okeefe & Clare Bradley

227. Royal Free Hospital, London, UK

     Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou & Mark De Neef

228. Scunthorpe General Hospital, Scunthorpe, UK

     Kathy Dent, Elizabeth Horsley, Muhammad Nauman Akhtar, Sandra Pearson, Dorota Potoczna & Sue Spencer

229. West Cumberland Hospital, Whitehaven, UK

     Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Tim Smith, Rachel Mutch & Luigi Barberis

230. Airedale General Hospital, Keighley, UK

     Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland & Sophie Packham

231. Birmingham Children’s Hospital, Birmingham, UK

     Rehana Bi, Barney Scholefield & Lydia Ashton

232. Liverpool Heart and Chest Hospital, Liverpool, UK

     Linsha George, Sophie Twiss & David Wright

233. Pilgrim Hospital, Lincoln, UK

     Manish Chablani, Amy Kirkby & Kimberley Netherton

234. Prince Philip Hospital, Llanelli, UK

     Kim Davies, Linda O’Brien, Zohra Omar, Igor Otahal, Emma Perkins, Tracy Lewis & Isobel Sutherland

235. Furness General Hospital, Barrow-in-Furness, UK

     Karen Burns & Andrew Higham

236. Scarborough General Hospital, Scarborough, UK

     Ben Chandler, Kerry Elliott, Janine Mallinson & Alison Turnbull

237. Southend University Hospital, Westcliff-on-Sea, UK

     Prisca Gondo, Bernard Hadebe, Abdul Kayani & Bridgett Masunda

238. Alder Hey Children’s Hospital, Liverpool, UK

     Taya Anderson, Dan Hawcutt, Laura O’Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones & Rachael Dore

239. Torbay Hospital, Torquay, UK

     Matthew Halkes, Pauline Mercer & Lorraine Thornton

240. Borders General Hospital, Melrose, UK

     Joy Dawson, Sweyn Garrioch, Melanie Tolson & Jonathan Aldridge

241. Kent and Canterbury Hospital, Canterbury, UK

     Ritoo Kapoor, David Loader & Karen Castle

242. West Suffolk Hospital, Bury St Edmunds, UK

     Sally Humphreys & Ruth Tampsett

243. James Paget University Hospital NHS Trust, Great Yarmouth, UK

     Katherine Mackintosh, Amanda Ayers, Wendy Harrison & Julie North

244. The Christie NHS Foundation Trust, Manchester, UK

     Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley & Andrew Fagan

245. The Royal Marsden Hospital, London, UK

     Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham & Benjamin Thomas

246. University Hospital Hairmyres, East Kilbride, UK

     Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon & Austin Rattray

247. Withybush General Hospital, Haverfordwest, Wales, UK

     Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks & Michelle Edwards

248. Ealing Hospital, Southall, UK

     Victoria Parris, Sheena Quaid & Ekaterina Watson

249. North Devon District Hospital, Barnstaple, UK

     Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay & Katie Adams

250. St John’s Hospital Livingston, Livingston, UK

     Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie & Miranda Odam

251. Northampton General Hospital NHS Trust, Northampton, UK

     Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis & Alex Lyon

252. Harrogate and District NHS Foundation Trust, Harrogate, UK

     Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson & Sarah Marsh

253. National Hospital for Neurology and Neurosurgery, London, UK

     David Brealey, John Hardy, Henry Houlden, Eleanor Moncur, Eamon Raith, Ambreen Tariq & Arianna Tucci

254. Bronglais General Hospital, Aberystwyth, UK

     Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench & Rebecca Wolf-Roberts

255. Golden Jubilee National Hospital, Clydebank, UK

     Val Irvine & Benjamin Shelley

256. Homerton University Hospital Foundation NHS Trust, London, UK

     Amy Easthope, Claire Gorman, Abhinav Gupta, Elizabeth Timlick & Rebecca Brady

257. Sheffield Children’s Hospital, Sheffield, UK

     Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter & Alex Howlett

258. The Royal Alexandra Children’s Hospital, Brighton, UK

     Katy Fidler, Emma Tagliavini & Kevin Donnelly

259. 23andMe, Sunnyvale, CA, USA

     Janie F. Shelton, Anjali J. Shastri, Chelsea Ye, Catherine H. Weldon, Teresa Filshtein-Sonmez, Daniella Coker, Antony Symons, Stella Aslibekyan & Adam Auton

260. Human Genetics R&D and Target Sciences R&D, GSK Medicines Research Centre, Stevenage, UK

     Jorge Esparza-Gordillo

261. Yale University, New Haven, CT, USA

     Gita A. Pathak & Renato Polimanti

262. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland

     Juha Karjalainen, Mattia Cordioli, Matti Pirinen, Mari E. K. Niemi, Kati Donner, Katja Kivinen, Aarno Palotie, Samuli Ripatti, Sanni Ruotsalainen, Mari Kaunisto, Sara Pigazzini, Mark J. Daly & Andrea Ganna

263. Broad Institute of MIT and Harvard, Cambridge, MA, USA

     Christine Stevens, Masahiro Kanai, Kumar Veerapen, Huy Nguyen, Matthew Solomonson, Rachel G. Liao, Amy Trankiem, Mary K. Balaconis, Lindokuhle Nkambul, Samuli Ripatti, Lindokuhle Nkambule, Lindokuhle Nkambule, Lindo Nkambul, Konrad J. Karczewski, Elizabeth G. Atkinson, Kristin Tsuo, Nikolas Baya, Patrick Turley, Rahul Gupta, Raymond K. Walters, Duncan S. Palmer, Gopal Sarma, Nathan Cheng, Wenhan Lu, Sam Bryant, Claire Churchhouse, Caroline Cusick, Jacqueline I. Goldstein, Daniel King, Cotton Seed, Hilary Finucane, Alicia R. Martin, F. Kyle Satterstrom, Mark J. Daly, Benjamin M. Neale & Andrea Ganna

264. Icahn School of Medicine at Mount Sinai, New York, NY, USA

     Shea J. Andrews, Nadia Harerimana, Laura G. Sloofman, Alexander W. Charney, Noam D. Beckmann, Eric E. Schadt, Daniel M. Jordan, Ryan C. Thompson, Kyle Gettler, Noura S. Abul-Husn, Steven Ascolillo, Joseph D. Buxbaum, Kumardeep Chaudhary, Judy H. Cho, Yuval Itan, Eimear E. Kenny, Gillian M. Belbin, Stuart C. Sealfon, Robert P. Sebra, Irene Salib, Brett L. Collins, Tess Levy, Bari Britvan, Katherine Keller, Lara Tang, Michael Peruggia, Liam L. Hiester, Kristi Niblo, Alexandra Aksentijevich, Alexander Labkowsky, Avrohom Karp, Menachem Zlatopolsky, Michael Preuss, Ruth J. F. Loos, Girish N. Nadkarni, Ron Do, Clive Hoggart, Sam Choi, Slayton J. Underwood, Paul O’Reilly, Laura M. Huckins & Marissa Zyndorf

265. University of Michigan, Ann Arbor, MI, USA

     Brooke Wolford, Cristen Willer, Albert V. Smith, Andrew P. Boughton, Kevin W. Li, Jonathon LeFaive, Aubrey Annis, Sebastian Zöllner, Jiongming Wang & Andrew Beck

266. Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, Bialystok, Poland

     Karolina Chwialkowska

267. Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK

     Caroline Hayward, Anne Richmond, Archie Campbell, Chloe Fawns-Ritchie, David J. Porteous, Paul R. H. J. Timmers, James F. Wilson, Albert Tenesa & Shona M. Kerr

268. University of Texas Health, Houston, TX, USA

     Marcela Morris & Joseph B. McCormick

269. Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

     Joseph T. Glessner, Xiao Chang, Hakon Hakonarson, Joseph R. Glessner & Hakon Hakonarson

270. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

     Joseph T. Glessner & Hakon Hakonarson

271. Vanderbilt University Medical Center, Nashville, TN, USA

     Douglas M. Shaw, Hannah Polikowski, Lauren E. Petty, Hung-Hsin Chen, Zhu Wanying & Jennifer Below

272. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

     Kari North

273. Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK

     Albert Tenesa & Kenton D’Mellow

274. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA

     Lindokuhle Nkambul, Wei Zhou, Lindokuhle Nkambule & Lindo Nkambul

275. Genolier Innovation Network and Hub, Swiss Medical Network, Genolier Healthcare Campus, Genolier, Switzerland

     Kathrin Aprile von Hohenstaufen

276. Department of Pediatrics, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Ali Sobh

277. Department of Clinical Pathology, Faculty of Medicine, Tanta University, Tanta, Egypt

     Madonna M. Eltoukhy & Attia A. S. Mohamed

278. Department of Anaethesia and Critical Care, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Amr M. Yassen

279. Department of Surgery, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Mohamed A. F. Hegazy & Amr Samir

280. Department of Internal Medicine, Faculty of Medicine, Tanta University, Tanta, Egypt

     Kamal Okasha

281. Faculty of Science, Tanta University, Tanta, Egypt

     Mohammed A. Eid

282. Chest Department, Faculty of Medicine, Tanta University, Tanta, Egypt

     Hanteera S. Moahmed, Walaa M. El-Lawaty & Mohamed S. Torky

283. Department of Clinical Pathology, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Doaa Shahin, Yasser M. El-Sherbiny & Jehan J. El-Jawhari

284. Department of Biosciences, School of Science and Technology, Nottingham Trent University, Nottingham, UK

     Yasser M. El-Sherbiny & Jehan J. El-Jawhari

285. Chest Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Tamer A. Elhadidy

286. Anesthesia, Surgical Intensive Care and Pain Management Department, Faculty of Medicine, Tanta University, Tanta, Egypt

     Mohamed S. Abd Elghafar

287. Department of Medical Biochemistry, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Marwa H. Elnagdy

288. Department of Tropical Medicine, Faculty of Medicine, Mansoura University, Mansoura, Egypt

     Mahmoud Abdel-Aziz

289. Pediatric and Neonatology, Kafr El-Zayat General Hospital, Kafr El-Zayat, Egypt

     Walid T. Khafaga

290. Pediatrics Department, Faculty of Medicine, Tanta University, Tanta, Egypt

     Mohamed R. El-shanshory

291. Department of Health Sciences, University of Leicester, Leicester, UK

     Chiara Batini, Paul H. Lee, Nick Shrine, Alexander T. Williams, Martin D. Tobin, Anna L. Guyatt, Catherine John, Richard J. Packer, Altaf Ali, Xueyang Wang, Louise V. Wain, Laura D. Venn, Catherine E. Bee & Emma L. Adams

292. Leicester NIHR Biomedical Research Centre, Leicester, UK

     Martin D. Tobin

293. Department of Respiratory Sciences, University of Leicester, Leicester, UK

     Robert C. Free

294. University of Leicester, Leicester, UK

     Edward J. Hollox

295. Digestive Oncology Research Center, Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

     Ahmadreza Niavarani & Bahareh Sharififard

296. Department of Pulmonology, School of Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

     Rasoul Aliannejad & Zeinab Naderpour

297. Department of Critical Care Medicine, Noorafshar Hospital, Tehran, Iran

     Ali Amirsavadkouhi

298. Department of Emergency Intensive Care Unit, School of Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

     Hengameh Ansari Tadi

299. Department of Anesthesiology, School of Medicine, Amir Alam Hospital, Tehran University of Medical Sciences, Tehran, Iran

     Afshar Etemadi Aleagha

300. Department of Pulmonology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

     Saeideh Ahmadi

301. Department of Pathology, Parseh Pathobiology and Genetics Laboratory, Tehran, Iran

     Seyed Behrooz Mohseni Moghaddam

302. Department of Microbiology, Health and Family Research Center, NIOC Hospital, Tehran, Iran

     Alireza Adamsara

303. Department of Emergency Medicine, School of Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

     Morteza Saeedi

304. Department of Anesthesiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

     Hamed Abdollahi

305. Department of Pathology, Faculty of Medicine, Tehran Azad University, Tehran, Iran

     Abdolmajid Hosseini

306. Clinical Pharmacokinetics and Pharmacogenomics Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Pajaree Chariyavilaskul, Monpat Chamnanphon & Thitima B. Suttichet

307. Department of Pharmacology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Pajaree Chariyavilaskul

308. Department of Pathology, Faculty of Medicine, Nakornnayok, Srinakharinwirot University, Bangkok, Thailand

     Monpat Chamnanphon

309. Center of Excellence for Medical Genomics, Medical Genomics Cluster, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Vorasuk Shotelersuk, Chureerat Phokaew & Wanna Chetruengchai

310. Excellence Center for Genomics and Precision Medicine, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand

     Vorasuk Shotelersuk, Chureerat Phokaew & Wanna Chetruengchai

311. Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand

     Monnat Pongpanich

312. Omics Sciences and Bioinfomatics Center, Faculty of Science, Chulalongkorn University, Bangkok, Thailand

     Monnat Pongpanich

313. Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Chureerat Phokaew

314. Thai Red Cross Emerging Infectious Diseases Clinical Centre, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

     Watsamon Jantarabenjakul, Opass Putchareon & Pattama Torvorapanit

315. Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Watsamon Jantarabenjakul & Thanyawee Puthanakit

316. Division of Infectious Diseases, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Opass Putchareon, Pattama Torvorapanit & Voraphoj Nilaratanakul

317. Center of Excellence in Pediatric Infectious Diseases and Vaccines, Chulalongkorn University, Bangkok, Thailand

     Thanyawee Puthanakit & Pintip Suchartlikitwong

318. Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Pintip Suchartlikitwong

319. Immunology Division, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Nattiya Hirankarn & Pimpayao Sodsai

320. Center of Excellence in Immunology and Immune-mediated Diseases, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand

     Nattiya Hirankarn & Pimpayao Sodsai

321. Healthcare-associated Infection Research Group STAR (Special Task Force for Activating Research), Chulalongkorn University, Bangkok, Thailand

     Voraphoj Nilaratanakul

322. K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

     Ben M. Brumpton, Kristian Hveem & Bjørn Olav Åsvold

323. HUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Levanger, Norway

     Ben M. Brumpton, Kristian Hveem & Bjørn Olav Åsvold

324. Clinic of Medicine, St Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway

     Ben M. Brumpton & Bjørn Olav Åsvold

325. Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA

     Cristen Willer

326. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

     Cristen Willer

327. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA

     Wei Zhou

328. Gemini Center for Sepsis Research, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

     Tormod Rogne & Erik Solligard

329. Department of Chronic Disease Epidemiology and Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA

     Tormod Rogne

330. Clinic of Anaesthesia and Intensive Care, St Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway

     Tormod Rogne & Erik Solligard

331. Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia

     Malak Abedalthagafi, Fawz Al Harthi, Ebtehal Alsolm, Leen Abu Safieh, Albandary M. Alowayn, Fatimah Alqubaishi, Amal Al Mutairi, Hadeel AlBardis, Sara Alotaibi & Mohammad S. Fawzy

332. Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Manal Alaamery, Mansour Almutairi & Salam Massadeh

333. Saudi Human Genome Project (SHGP), King Abdulaziz City for Science and Technology (KACST), Satellite Lab at King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Manal Alaamery, Mansour Almutairi & Salam Massadeh

334. The Liver Transplant Unit, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia

     Saleh Alqahtani

335. The Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, MD, USA

     Saleh Alqahtani

336. Department of Pathology, College of Medicine, King Saud University, Riyadh, Saudi Arabia

     Duna Barakeh & Rana Hasanato

337. Titus Family Department of Clinical Pharmacy, USC School of Pharmacy, University of Southern California, Los Angeles, CA, USA

     Serghei Mangul

338. College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia

     Abdulraheem Alshareef & Bandar A. Suliman

339. Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Mona Sawaji

340. KACST-BWH Centre of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia

     Nora Aljawini, Nour Albesher, Sarah Alkwai, Moneera Alswailm & Iman Almohammed

341. Ministry of the National Guard Health Affairs, King Abdullah International Medical Research Center and King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia

     Yaseen M. Arabi & Ebrahim S. Mahmoud

342. Ohud Hospital, Ministry of Health, Madinah, Saudi Arabia

     Amin K. Khattab, Roaa T. Halawani, Ziab Z. Alahmadey, Jehad K. Albakri & Walaa A. Felemban

343. Pediatric Infectious Diseases, Children’s Specialized Hospital, King Fahad Medical City, Riyadh, Saudi Arabia

     Laila Al-Awdah

344. The Saudi Biobank, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Jahad Alghamdi

345. Developmental Medicine Department, King Abdullah International Medical Research Center and King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Deema AlZahrani, Nouf AlDhawi, Faisal Almalki, Maha Albeladi & Anoud Albader

346. Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences and King Abdullah International Medical Research Center, Riyadh, Saudi Arabia

     Sameera AlJohani

347. Laboratory Department, Security Forces Hospital, General Directorate of Medical Services, Ministry of Interior, Riyadh, Saudi Arabia

     Hani Al-Afghani

348. Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia

     May Alrashed

349. King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia

     Eman Barhoush

350. Life Science and Environmental Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia

     Abdulaziz AlMalik

351. Department of Developmental Medicine, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia

     Bader Alghamdi

352. Titus Family Department of Clinical Pharmacy, USC School of Pharmacy University of Southern California, Los Angeles, CA, USA

     Junghyun Jung

353. Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway

     Yunsung Lee & Per Magnus

354. Department of Method Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway

     Lill-Iren S. Trogstad

355. Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway

     Øyvind Helgeland & Jennifer R. Harris

356. Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK

     Massimo Mangino, Tim D. Spector & Emma Duncan

357. NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UK

     Massimo Mangino

358. Vanda Pharmaceuticals, London, UK

     Sandra P. Smieszek, Bartlomiej P. Przychodzen, Christos Polymeropoulos, Vasilios Polymeropoulos & Mihael H. Polymeropoulos

359. Stroke Pharmacogenomics and Genetics, Biomedical Research Institute Sant Pau, Sant Pau Hospital, Barcelona, Spain

     Israel Fernandez-Cadenas, Laia Llucià-Carol, Natalia Cullell, Elena Muiño & Jara Cárcel-Márquez

360. Institute of Biomedicine of Valencia (IBV), National Spanish Research Council (CSIC), València, Spain

     Jordi Perez-Tur

361. Network Center for Biomedical Research on Neurodegenerative Diseases (CIBERNED), València, Spain

     Jordi Perez-Tur

362. Neurology and Genetic Mixed Unit, La Fe Health Research Institute, València, Spain

     Jordi Perez-Tur

363. Institute for Biomedical Research of Barcelona (IIBB), National Spanish Research Council (CSIC), Barcelona, Spain

     Laia Llucià-Carol & Anna M. Planas

364. Department of Neurology, Hospital Universitari MútuaTerrassa, Fundació Docència i Recerca MútuaTerrassa, Terrassa, Spain

     Natalia Cullell

365. Department of Molecular and Cell Biology, Centro Nacional de Biotecnología (CNB-CSIC), Campus Universidad Autónoma de Madrid, Madrid, Spain

     Marta L. DeDiego

366. Instituto de Física de Cantabria (IFCA-CSIC), Santander, Spain

     Lara Lloret Iglesias

367. Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

     Anna M. Planas

368. Hospital Clínic, Barcelona, Spain

     Alex Soriano, Veronica Rico, Daiana Agüero, Josep L. Bedini, Carlos Domingo & Veronica Robles

369. Hospital Clínic, IDIBAPS, School of Medicine, University of Barcelona, Barcelona, Spain

     Francisco Lozano

370. IDIBAPS, Barcelona, Spain

     Francisca Ruiz-Jaén

371. IIBB-CSIC, Barcelona, Spain

     Leonardo Márquez

372. Servicio de Salud del Principado de Asturias, Oviedo, Spain

     Juan Gomez, Eliecer Coto, Guillermo M. Albaiceta & Marta García-Clemente

373. Hospital Mutua de Terrassa, Terrassa, Spain

     David Dalmau, Maria J. Arranz, Beatriz Dietl & Alex Serra-Llovich

374. Hospital Valle Hebrón, Barcelona, Spain

     Pere Soler, Roger Colobrán, Andrea Martín-Nalda & Alba Parra Martínez

375. Instituto de Biomedicina y Genética Molecular (IBGM), CSIC-Universidad de Valladolid, Valladolid, Spain

     David Bernardo, Aida Fiz-López, Elisa Arribas & Paloma de la Cal-Sabater

376. Hospital Clínico Universitario de Valladolid (SACYL), Valladolid, Spain

     Silvia Rojo

377. University Hospital of Albacete, Albacete, Spain

     Tomás Segura, Esther González-Villa & Gemma Serrano-Heras

378. Department of Neurology, Biomedical Research Institute Sant Pau (IIB Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

     Joan Martí-Fàbregas & Elena Jiménez-Xarrié

379. Hospital Universitario Ramon y Cajal, IRYCIS, Madrid, Spain

     Alicia de Felipe Mimbrera, Jaime Masjuan & Sebastian García-Madrona

380. Institute of Biomedicine of Seville (IBiS), Hospital Universitario Virgen del Rocío, CSIC and University of Seville, Seville, Spain

     Anna Domínguez-Mayoral, Joan Montaner Villalonga & Paloma Menéndez-Valladares

381. Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain

     Anna Domínguez-Mayoral, Joan Montaner Villalonga & Paloma Menéndez-Valladares

382. Brigham and Women’s Hospital, Boston, MA, USA

     Daniel I. Chasman, Julie E. Buring, Paul M. Ridker, Giulianini Franco, Howard D. Sesso, JoAnn E. Manson, Scott T. Weiss, Elizabeth W. Karlson & Ann E. Woolley

383. Harvard Medical School, Boston, MA, USA

     Daniel I. Chasman, Julie E. Buring, Paul M. Ridker, Howard D. Sesso & JoAnn E. Manson

384. Division of Human Genetics, Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

     Joseph R. Glessner & Hakon Hakonarson

385. Faculty of Medicine, University of Iceland, Reykjavik, Iceland

     Hakon Hakonarson

386. Erasmus MC, Rotterdam, The Netherlands

     Carolina Medina-Gomez, Andre G. Uitterlinden & M. Arfan Ikram

387. Finnish Institute for Health and Welfare (THL), Helsinki, Finland

     Kati Kristiansson, Sami Koskelainen & Markus Perola

388. University of Helsinki, Faculty of Medicine, Clinical and Molecular Metabolism Research Program, Helsinki, Finland

     Markus Perola

389. Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland

     Samuli Ripatti

390. Department of Human Genetics, McGill University, Montréal, Québec, Canada

     Tomoko Nakanishi, Guillaume Butler-Laporte, Vincenzo Forgetta, David R. Morrison, Biswarup Ghosh, Laetitia Laurent, Alexandre Belisle, Danielle Henry, Tala Abdullah, Olumide Adeleye, Noor Mamlouk, Nofar Kimchi, Zaman Afrasiabi, Nardin Rezk, Branka Vulesevic, Meriem Bouab, Charlotte Guzman, Louis Petitjean, Chris Tselios, Xiaoqing Xue, Erwin Schurr, Jonathan Afilalo, Marc Afilalo, Maureen Oliveira, Bluma Brenner, Pierre Lepage, Jiannis Ragoussis, Daniel Auld, Nathalie Brassard, Madeleine Durand, Michaël Chassé, Daniel E. Kaufmann, G. Mark Lathrop, Vincent Mooser, J. Brent Richards, Rui Li & Darin Adra

391. Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada

     Tomoko Nakanishi & Guillaume Butler-Laporte

392. Kyoto–McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan

     Tomoko Nakanishi

393. Research Fellow, Japan Society for the Promotion of Science, Kyoto, Japan

     Tomoko Nakanishi

394. University of Liege, Liege, Belgium

     Souad Rahmouni, Michel Georges, Benoit Misset, Gilles Darcis, Julien Guiot, Samira Azarzar & Yasmine Belhaj

395. CHU of Liege, Liege, Belgium

     Michel Moutschen, Benoit Misset, Gilles Darcis, Julien Guiot, Julien Guntz, Samira Azarzar, Olivier Malaise, Pascale Huynen, Christelle Meuris, Marie Thys, Jessica Jacques, Philippe Léonard, Frederic Frippiat, Jean-Baptiste Giot, Anne-Sophie Sauvage, Christian von Frenckell & Bernard Lambermont

396. 5BHUL (Liege Biobank), CHU of Liege, Liege, Belgium

     Stéphanie Gofflot & Yves Beguin

397. CHC Mont-Legia, Liege, Belgium

     Sabine Claassen

398. University of Colorado Anschutz Medical Campus, Aurora, CO, USA

     Michelle Daya, Jonathan Shortt, Nicholas Rafaels, Stephen J. Wicks, Kristy Crooks, Kathleen C. Barnes, Christopher R. Gignoux & Sameer Chavan

399. Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia

     Triin Laisk, Kristi Läll, Maarja Lepamets, Reedik Mägi, Tõnu Esko, Ene Reimann, Lili Milani, Helene Alavere, Kristjan Metsalu, Mairo Puusepp & Andres Metspalu

400. University of Tartu, Tartu, Estonia

     Paul Naaber

401. Kuressaare Hospital, Kuressaare, Estonia

     Edward Laane & Jaana Pesukova

402. Tartu University Hospital, Tartu, Estonia

     Edward Laane, Joel Starkopf, Anu Tamm & Anne Kallaste

403. Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia

     Pärt Peterson & Kai Kisand

404. West Tallinn Central Hospital, Tallinn, Estonia

     Jekaterina Tabri, Raili Allos & Kati Hensen

405. Estonian Health Insurance Fund, Tallinn, Estonia

     Inge Ringmets

406. Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland

     Pierre-Yves Bochud, Stéphanie Bibert & Noémie Boillat

407. Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland

     Carlo Rivolta, Mathieu Quinodoz & Dhryata Kamdar

408. Department of Ophthalmology, University of Basel, Basel, Switzerland

     Carlo Rivolta, Mathieu Quinodoz & Dhryata Kamdar

409. Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland

     Semira Gonseth Nussle

410. Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland

     Werner Albrich

411. Division of Intensive Care, Geneva University Hospitals and the University of Geneva Faculty of Medicine, Geneva, Switzerland

     Noémie Suh

412. Infectious Disease Service, Department of Internal Medicine, Geneva University Hospital, Geneva, Switzerland

     Dionysios Neofytos

413. Clinique de Médecine et Spécialités, Infectiologie, HFR-Fribourg, Fribourg, Switzerland

     Véronique Erard

414. Infectious Diseases Division, University Hospital Centre of the canton of Vaud, Hospital of Valais, Sion, Switzerland

     Cathy Voide

415. GCAT-Genomes for Life, Germans Trias i Pujol Health Sciences Research Institute (IGTP), Badalona, Spain

     Rafael de Cid, Iván Galván-Femenía, Natalia Blay, Anna Carreras, Beatriz Cortés, Xavier Farré & Lauro Sumoy

416. Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, Consortium for Biomedical Research in Epidemiology and Public Health and University of Barcelona, Barcelona, Spain

     Victor Moreno

417. Massachusetts General Hospital, Boston, MA, USA

     Josep Maria Mercader, Jordan W. Smoller, Yen-Chen Anne Feng, Shawn N. Murphy, James B. Meigs, Emma F. Perez, Konrad J. Karczewski, Elizabeth G. Atkinson, Kristin Tsuo, Nikolas Baya, Patrick Turley, Rahul Gupta, Raymond K. Walters, Duncan S. Palmer, Gopal Sarma, Nathan Cheng, Wenhan Lu, Sam Bryant, Claire Churchhouse, Jacqueline I. Goldstein, Daniel King, Cotton Seed, Hilary Finucane, Alicia R. Martin & F. Kyle Satterstrom

418. Life and Medical Sciences, Barcelona Supercomputing Center–Centro Nacional de Supercomputación (BSC-CNS), Barcelona, Spain

     Marta Guindo-Martinez & David Torrents

419. ISGlobal, Barcelona, Spain

     Manolis Kogevinas, Judith Garcia-Aymerich, Gemma Castaño-Vinyals & Carlota Dobaño

420. IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain

     Manolis Kogevinas & Gemma Castaño-Vinyals

421. Universitat Pompeu Fabra (UPF), Barcelona, Spain

     Manolis Kogevinas, Judith Garcia-Aymerich & Gemma Castaño-Vinyals

422. CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain

     Manolis Kogevinas, Judith Garcia-Aymerich, Gemma Castaño-Vinyals & Carlota Dobaño

423. Medical Genetics, University of Siena, Siena, Italy

     Alessandra Renieri, Francesca Mari, Chiara Fallerini, Sergio Daga, Margherita Baldassarri, Francesca Fava, Elisa Frullanti, Floriana Valentino, Gabriella Doddato, Annarita Giliberti, Mirella Bruttini, Susanna Croci, Ilaria Meloni, Giada Beligni, Laura Di Sarno, Maria Palmieri, Miriam Lucia Carriero, Diana Alaverdian & Mirjam Lista

424. Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Siena, Italy

     Alessandra Renieri, Francesca Mari, Francesca Fava, Rossella Tita, Sara Amitrano, Mirella Bruttini, Maria Antonietta Mencarelli, Caterina Lo Rizzo & Anna Maria Pinto

425. Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy

     Alessandra Renieri, Francesca Mari, Chiara Fallerini, Sergio Daga, Elisa Benetti, Margherita Baldassarri, Francesca Fava, Elisa Frullanti, Floriana Valentino, Gabriella Doddato, Annarita Giliberti, Mirella Bruttini, Susanna Croci, Ilaria Meloni, Giada Beligni, Laura Di Sarno, Maria Palmieri, Miriam Lucia Carriero, Diana Alaverdian, Simone Furini, Francesca Montagnani, Kristina Zguro, Katia Capitani, Francesco Bianchi, Mario Tumbarello & Mirjam Lista

426. Infectious Diseases Clinic, Department of Medicine 2, Azienda Ospedaliera di Perugia and University of Perugia, Santa Maria Hospital, Perugia, Italy

     Andrea Tommasi, Daniela Francisci & Elisabetta Schiaroli

427. Department of Anesthesia and Intensive Care, University of Modena and Reggio Emilia, Modena, Italy

     Stefano Busani, Massimo Girardis & Sophie Venturelli

428. Division of Infectious Diseases and Immunology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

     Raffaele Bruno, Marco Vecchia, Stefania Mantovani & Mario Umberto Mondelli

429. Department of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy

     Raffaele Bruno & Mario Umberto Mondelli

430. U.O.C. Medicina, ASST Nord Milano, Ospedale Bassini, Milan, Italy

     Mary Ann Belli, Sandro Mancarella & Luisa Tavecchia

431. Department of Mathematics, University of Pavia, Pavia, Italy

     Nicola Picchiotti

432. University of Siena, DIISM-SAILAB, Siena, Italy

     Nicola Picchiotti, Marco Gori & Marco Tanfoni

433. Independent researcher, Milan, Italy

     Maurizio Sanarico & Chiara Gabbi

434. Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

     Serena Ludovisi

435. Department of Infectious and Tropical Diseases, University of Brescia and ASST Spedali Civili Hospital, Brescia, Italy

     Francesco Castelli, Eugenia Quiros-Roldan & Melania Degli Antoni

436. Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy

     Isabella Zanella

437. Clinical Chemistry Laboratory, Cytogenetics and Molecular Genetics Section, Diagnostic Department, ASST Spedali Civili di Brescia, Brescia, Italy

     Isabella Zanella

438. Chirurgia Vascolare, Ospedale Maggiore di Crema, Crema, Italy

     Massimo Vaghi

439. III Infectious Diseases Unit, ASST-FBF-Sacco, Milan, Italy

     Stefano Rusconi & Agostino Riva

440. Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy

     Stefano Rusconi, Matteo Siano, Arianna Gabrieli & Agostino Riva

441. Department of Specialized and Internal Medicine, Tropical and Infectious Diseases Unit, Azienda Ospedaliera Universitaria Senese, Siena, Italy

     Francesca Montagnani, Massimiliano Fabbiani, Barbara Rossetti & Ilaria Rancan

442. HIV/AIDS Department, National Institute for Infectious Diseases Lazzaro Spallanzani, IRCCS, Rome, Italy

     Arianna Emiliozzi, Andrea Antinori & Alessandra Vergori

443. Unit of Respiratory Diseases and Lung Transplantation, Department of Internal and Specialist Medicine, University of Siena, Siena, Italy

     Elena Bargagli, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli & David Bennett

444. Unit of Intensive Care Medicine. Departments of Emergency and Urgency, Medicine, Surgery and Neurosciences, Siena University Hospital, Siena, Italy

     Federico Anedda, Simona Marcantonio, Sabino Scolletta & Federico Franchi

445. Unit of Diagnostic Imaging, Departments of Medical, Surgical and Neurosciences and Radiological Sciences, University of Siena, Siena, Italy

     Maria Antonietta Mazzei & Susanna Guerrini

446. Rheumatology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, Siena, Italy

     Edoardo Conticini, Luca Cantarini & Bruno Frediani

447. Infectious Diseases Unit, Department of Specialized and Internal Medicine, San Donato Hospital Arezzo, Arezzo, Italy

     Danilo Tacconi & Chiara Spertilli

448. Anesthesia Unit, Department of Emergency, San Donato Hospital, Arezzo, Italy

     Marco Feri & Alice Donati

449. Pneumology Unit and UTIP, Department of Specialized and Internal Medicine, San Donato Hospital, Arezzo, Italy

     Raffaele Scala & Luca Guidelli

450. Anesthesia Unit, Department of Emergency, Misericordia Hospital, Grosseto, Italy

     Genni Spargi & Marta Corridi

451. Infectious Diseases Unit, Department of Specialized and Internal Medicine, Misericordia Hospital, Grosseto, Italy

     Cesira Nencioni & Leonardo Croci

452. Department of Preventive Medicine, Azienda USL Toscana Sud Est, Tuscany, Italy

     Maria Bandini, Paolo Piacentini, Elena Desanctis, Silvia Cappelli & Davide Romani

453. Clinical Chemical Analysis Laboratory, Misericordia Hospital, Grosseto, Italy

     Gian Piero Caldarelli

454. Territorial Scientific Technician Department, Azienda USL Toscana Sud Est, Arezzo, Italy

     Anna Canaccini, Agnese Verzuri & Valentina Anemoli

455. Clinical Chemical Analysis Laboratory, San Donato Hospital, Arezzo, Italy

     Agostino Ognibene, Alessandro Pancrazzi & Maria Lorubbio

456. Department of Health Sciences, Clinic of Infectious Diseases, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy

     Antonella D’Arminio Monforte & Federica Gaia Miraglia

457. Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, Modena, Italy

     Andrea Cossarizza

458. Infectious Diseases Clinic, Santa Maria Hospital, University of Perugia, Perugia, Italy

     Daniela Francisci, Elisabetta Schiaroli & Francesco Paciosi

459. Department of Infectious Diseases, Treviso Hospital, Treviso, Italy

     Pier Giorgio Scotton & Francesca Andretta

460. Clinical Infectious Diseases, Mestre Hospital, Venezia, Italy

     Sandro Panese

461. Infectious Diseases Clinic, Belluno, Italy

     Renzo Scaggiante & Francesca Gatti

462. Department of Molecular Medicine, University of Padova, Padua, Italy

     Saverio Giuseppe Parisi & Stefano Baratti

463. Medical Genetics and Laboratory of Medical Genetics Unit, A.O.R.N. Antonio Cardarelli Hospital, Naples, Italy

     Matteo Della Monica & Carmelo Piscopo

464. Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy

     Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon & Giuseppe Merla

465. CEINGE Biotecnologie Avanzate, Naples, Italy

     Mario Capasso, Roberta Russo, Immacolata Andolfo & Achille Iolascon

466. IRCCS SDN, Naples, Italy

     Mario Capasso

467. Unit of Respiratory Physiopathology, AORN dei Colli, Monaldi Hospital, Naples, Italy

     Giuseppe Fiorentino

468. Division of Medical Genetics, Fondazione IRCCS Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

     Massimo Carella & Marco Castori

469. Laboratory of Regulatory and Functional Genomics, Fondazione IRCCS Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

     Giuseppe Merla & Gabriella Maria Squeo

470. Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

     Filippo Aucella

471. Clinical Trial Office, Fondazione IRCCS Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

     Pamela Raggi, Carmen Marciano & Rita Perna

472. Department of Health Sciences, University of Genova, Genova, Italy

     Matteo Bassetti

473. Infectious Diseases Clinic, Policlinico San Martino Hospital, IRCCS for Cancer Research, Genova, Italy

     Matteo Bassetti & Antonio Di Biagio

474. Microbiology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Catholic University of Medicine, Rome, Italy

     Maurizio Sanguinetti, Luca Masucci & Alessandra Guarnaccia

475. Department of Laboratory Sciences and Infectious Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy

     Maurizio Sanguinetti & Luca Masucci

476. Department of Cardiovascular Diseases, University of Siena, Siena, Italy

     Serafina Valente & Oreste De Vivo

477. Otolaryngology Unit, University of Siena, Siena, Italy

     Marco Mandalà, Alessia Giorli & Lorenzo Salerni

478. Department of Internal Medicine, ASST Valtellina e Alto Lario, Sondrio, Italy

     Patrizia Zucchi & Pierpaolo Parravicini

479. Oncologia Medica e Ufficio Flussi Sondrio, Sondrio, Italy

     Elisabetta Menatti

480. First Aid Department, Luigi Curto Hospital, Polla, Salerno, Italy

     Tullio Trotta, Ferdinando Giannattasio & Gabriella Coiro

481. Local Health Unit, Pharmaceutical Department of Grosseto, Toscana Sud Est Local Health Unit, Grosseto, Italy

     Fabio Lena

482. U.O.C. Laboratorio di Genetica Umana, IRCCS Istituto Giannina Gaslini, Genoa, Italy

     Domenico A. Coviello

483. Infectious Diseases Clinics, University of Modena and Reggio Emilia, Modena, Italy

     Cristina Mussini

484. Department of Respiratory Diseases, Azienda Ospedaliera di Cremona, Cremona, Italy

     Enrico Martinelli

485. Department of Cardiovascular, Neural and Metabolic Sciences, Istituto Auxologico Italiano, IRCCS, San Luca Hospital, Milan, Italy

     Lia Crotti & Gianfranco Parati

486. Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy

     Lia Crotti & Gianfranco Parati

487. Laboratory of Cardiovascular Genetics, Istituto Auxologico Italiano, IRCCS, Milan, Italy

     Lia Crotti & Lia Crotti

488. Unit of Infectious Diseases, ASST Papa Giovanni XXIII Hospital, Bergamo, Italy

     Marco Rizzi, Franco Maggiolo & Diego Ripamonti

489. Direzione Scientifica, Istituti Clinici Scientifici Maugeri IRCCS, Pavia, Italy

     Tiziana Bachetti

490. Department of Cardiology, Istituti Clinici Scientifici Maugeri IRCCS, Institute of Montescano, Pavia, Italy

     Maria Teresa La Rovere

491. Department of Cardiac Rehabilitation, Institute of Tradate (VA) and Istituti Clinici Scientifici Maugeri IRCCS, Pavia, Italy

     Simona Sarzi-Braga

492. Department of Cardiology, Istituti Clinici Scientifici Maugeri IRCCS, Institute of Milan, Milan, Italy

     Maurizio Bussotti

493. Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy

     Stefano Ceri & Pietro Pinoli

494. Scuola Normale Superiore, Pisa, Italy

     Francesco Raimondi

495. CNR-Consiglio Nazionale delle Ricerche, Istituto di Biologia e Biotecnologia Agraria (IBBA), Milano, Italy

     Filippo Biscarini & Alessandra Stella

496. Core Research Laboratory, ISPRO, Florence, Italy

     Katia Capitani

497. Fondazione per la Ricerca Ospedale di Bergamo, Bergamo, Italy

     Claudia Suardi

498. Health Management, Azienda USL Toscana Sud Est, Tuscany, Italy

     Simona Dei

499. IRCCS Mondino Foundation, Pavia, Italy

     Sabrina Ravaglia & Ravaglia Sabrina

500. Medical Genetics Unit, Meyer Children’s University Hospital, Florence, Italy

     Rosangela Artuso & Elena Andreucci

501. Allelica, New York, NY, USA

     Giordano Bottà & Paolo Di Domenico

502. Pneumology Unit, Department of Medicine, Misericordia Hospital, Grosseto, Italy

     Antonio Perrella & Francesco Bianchi

503. Intensive Care Unit and Department of Anesthesia, ASST Fatebenefratelli Sacco, Luigi Sacco Hospital, Polo Universitario, University of Milan, Milan, Italy

     Paola Bergomi, Emanuele Catena & Riccardo Colombo

504. Infectious Disease Unit, Hospital of Massa, Massa, Italy

     Antonella Vincenti

505. Department of Clinical Medicine, Public Health, Life and Environment Sciences, University of L’Aquila, L’Aquila, Italy

     Claudio Ferri & Davide Grassi

506. UOSD Laboratorio di Genetica Medica—ASL Viterbo, San Lorenzo, Italy

     Gloria Pessina & Monica Poscente

507. Department of Medical Sciences, Infectious and Tropical Diseases Unit, Azienda Ospedaliera Universitaria Senese, Siena, Italy

     Mario Tumbarello

508. Unit of Infectious Diseases, Santa Maria Annunziata Hospital, Florence, Italy

     Massimo Di Pietro

509. Infectious Disease Unit, Hospital of Lucca, Lucca, Italy

     Sauro Luchi & Paola Petrocelli

510. Infectious Diseases Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy

     Chiara Barbieri, Giusy Tiseo & Marco Falcone

511. Infectious Disease Unit, Santo Stefano Hospital, AUSL Toscana Centro, Prato, Italy

     Donatella Acquilini

512. Clinic of Infectious Diseases, Catholic University of the Sacred Heart, Rome, Italy

     Francesco Vladimiro Segala

513. Department of Diagnostic and Laboratory Medicine, Institute of Biochemistry and Clinical Biochemistry, Fondazione Policlinico Universitario A. Gemelli IRCCS, Catholic University of the Sacred Heart, Rome, Italy

     Silvia Baroni

514. Department of Population Health Sciences, Geisinger Health System, Danville, PA, USA

     Anne E. Justice, Geetha Chittoor & Navya Shilpa Josyula

515. Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA

     Tooraj Mirshahi & Dave J. Carey

516. Regeneron Genetics Center, Tarrytown, NY, USA

     Jack A. Kosmicki, Manuel A. R. Ferreira, Julie E. Horowitz, Michael N. Cantor, Ashish Yadav, Aris Baras & Goncalo R. Abecasis

517. Phenomic Analytics and Clinical Data Core, Geisinger Health System, Danville, PA, USA

     Joseph B. Leader & Matthew C. Gass

518. Queen Mary University of London, London, UK

     David A. van Heel, Karen A. Hunt, Sarah Finer, Bhavi Trivedi & Christopher J. Griffiths

519. Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford, UK

     Dan Mason & John Wright

520. Medical and Population Genomics, Wellcome Sanger Institute, Hinxton, UK

     Qin Qin Huang & Hilary C. Martin

521. School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King’s College London, London, UK

     Richard C. Trembath

522. Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK

     Nicole Soranzo & John Danesh

523. National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK

     Nicole Soranzo, Adam S. Butterworth, John Danesh & Emanuele Di Angelantonio

524. Department of Haematology, University of Cambridge, Cambridge, UK

     Nicole Soranzo

525. British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

     Jing Hua Zhao, Adam S. Butterworth, John Danesh & Emanuele Di Angelantonio

526. British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK

     Adam S. Butterworth, John Danesh & Emanuele Di Angelantonio

527. Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Cambridge, UK

     Adam S. Butterworth, John Danesh & Emanuele Di Angelantonio

528. Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands

     Lude Franke, Marike Boezen, Annique Claringbould, Esteban Lopera, Robert Warmerdam, Irene van Blokland & Anil P. S. Ori

529. Department of Genetics, University Medical Centre Utrecht, Utrecht, The Netherlands

     Patrick Deelen

530. Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

     Judith M. Vonk

531. Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands

     Pauline Lanting

532. Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands

     Anil P. S. Ori

533. Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

     Gina Peloso

534. Center for Population Genomics, MAVERIC, VA Boston Healthcare System, Boston, MA, USA

     Gina Peloso, Jennifer E. Huffman & Christopher J. O’Donnell

535. MAVERIC, VA Boston Healthcare System, Boston, MA, USA

     Yuk-Lam Ho, Kelly Cho & J. Michael Gaziano

536. Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA

     Yan V. Sun

537. Stanford University, Stanford, CA, USA

     Phil Tsao & Binglan Li

538. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

     Michel Nivard, Eco de Geus, Meike Bartels & Jouke Jan Hottenga

539. Broad Institute of MIT and Harvard, Boston, MA, USA

     Robert C. Green & Josep Mercader

540. Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

     Daniel Rader, Anurag Verma, Marylyn D. Ritchie, Shefali S. Verma, Anastasia Lucas & Yuki Bradford

541. Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden

     Hugo Zeberg

542. Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

     Hugo Zeberg & Tomislav Maricic

543. Anaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden

     Robert Frithiof, Michael Hultström, Miklos Lipcsey & Miklos Lipcsey

544. Integrative Physiology, Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden

     Michael Hultström

545. Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Muscatine, IA, USA

     Lindo Nkambul

546. Division Anesthesiology and Intensive Care, CLINTEC, Karolinska Institutet, Stockholm, Sweden

     Nicolas Tardif, Olav Rooyackers & Jonathan Grip

547. Department of Clinical Research and Leadership, George Washington University, Washington, DC, USA

     Shawneequa Callier

548. Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK

     Daniel J. Wilson, Jacob Armstrong, Justine K. Rudkin, Sarah G. Earle, Shang-Kuan Lin & Nicolas Arning

549. Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

     Gavin Band

550. Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK

     Derrick W. Crook

551. Public Health England, Field Service, Addenbrooke’s Hospital, Cambridge, UK

     David H. Wyllie

552. Public Health England, Data and Analytical Services, National Infection Service, London, UK

     Anne Marie O’Connell

553. Genomics PLC, Oxford, UK

     Chris C. A. Spencer & Nils Koelling

554. Genomics England, London, UK

     Mark J. Caulfield, Richard H. Scott, Tom Fowler, Loukas Moutsianas, Athanasios Kousathanas, Dorota Pasko, Susan Walker, Augusto Rendon, Alex Stuckey, Christopher A. Odhams, Daniel Rhodes, Georgia Chan & Prabhu Arumugam

555. Ancestry, Lehi, UT, USA

     Catherine A. Ball, Eurie L. Hong, Kristin Rand, Ahna Girshick, Harendra Guturu, Asher Haug Baltzell, Genevieve Roberts, Danny Park, Marie Coignet, Shannon McCurdy, Spencer Knight, Raghavendran Partha, Brooke Rhead, Miao Zhang, Nathan Berkowitz, Michael Gaddis, Keith Noto, Luong Ruiz & Milos Pavlovic

Consortia

Contributions

A.K., E.P.-C., K. Rawlik, A. Stuckey, C.A.O., S.W., T. Malinauskas, Y.W., X.S., K.S.E., B.W., D.R., L.K., M.Z., N.P., J.A.K., J.E.H., A.B., G.R.A., M.A.R.F., A.J., T. Mirshahi, M.O., D.J.R., M.D.R., A.V., J.Y., A.D.B., S.C.H., L. Moutsianas, A.L. and J.K.B. contributed to data analysis. A.K., E.P.-C., K. Rawlik, A. Stuckey, C.A.O., S.W., C.D.R., J.M., A.R., S.C.H., L. Moutsianas and A.L. contributed to bioinformatics. A.K., E.P.-C., K. Rawlik, C.D.R., J.M., D.M., A.N., M.G.S., S.C.H., L. Moutsianas, M.J.C. and J.K.B. contributed to writing and reviewing the manuscript. E.P.-C., K. Rawlik, K.M., S.K., A.F., L. Murphy, K. Rowan, C.P.P., V.V., J.F.W., S.C.H., A.L., M.J.C. and J.K.B. contributed to design. S.W., F.G., W.O., P.G. and S.D. contributed to project management. F.G., W.O., K.M., S.K., P.G., S.D., D.M., A.N., M.G.S., S.S., J.K., T.A.F., M.S.-H., C.S., C.H., P.H., L.L., D. McAuley, H.M., P.J.O., P.E., T.W., A.T., A.F., L. Murphy, K. Rowan, C.P.P., R.H.S., S.C.H. and A.L. contributed to oversight. F.G., W.O., F.M.-C. and J.K.B. contributed to ethics and governance. K.M., A. Siddiq, A.F. and L. Murphy contributed to sample handling and sequencing. A. Siddiq contributed to data collection. T.Z. contributed to sample handing. T.Z., G.E., C.P., D.B. and C.K. contributed to sequencing. L.T. contributed to the recruitment of controls. G.C., P.A., K. Rowan and A.L. contributed to clinical data management. K. Rowan, C.P.P., S.C.H. and J.K.B. contributed to conception. K. Rowan, C.P.P., V.V. and J.F.W. contributed to reviewing the manuscript. M.J.C. and J.K.B. contributed to scientific leadership.

Corresponding authors

Correspondence to Mark J. Caulfield or J. Kenneth Baillie.

Competing interests

J.A.K., J.E.H., A.B., G.R.A. and M.A.R.F. are current employees and/or stockholders of Regeneron Genetics Center or Regeneron Pharmaceuticals. Genomics England is a wholly owned Department of Health and Social Care company created in 2013 to work with the NHS to introduce advanced genomic technologies and analytics into healthcare. All Genomics England affiliated authors are, or were, salaried by Genomics England during this programme. All other authors declare that they have no competing interests relating to this work.

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