Genetics of chronic respiratory disease.

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma and interstitial lung diseases are frequently occurring disorders with a polygenic basis that account for a large global burden of morbidity and mortality. Recent large-scale genetic epidemiology studies have identified associations between genetic variation and individual respiratory diseases and linked specific genetic variants to quantitative traits related to lung function. These associations have improved our understanding of the genetic basis and mechanisms underlying common lung diseases. Moreover, examining the overlap between genetic associations of different respiratory conditions, along with evidence for gene-environment interactions, has yielded additional biological insights into affected molecular pathways. This genetic information could inform the assessment of respiratory disease risk and contribute to stratified treatment approaches.

Indian Ocean salinity build-up primes deglacial ocean circulation recovery.

The Indian Ocean provides a source of salt for North Atlantic deep-water convection sites, via the Agulhas Leakage, and may thus drive changes in the ocean's overturning circulation1-3. However, little is known about the salt content variability of Indian Ocean and Agulhas Leakage waters during past glacial cycles and how this may influence circulation. Here we show that the glacial Indian Ocean surface salt budget was notably different from the modern, responding dynamically to changes in sea level. Indian Ocean surface salinity increased during glacial intensification, peaking in glacial maxima. We find that this is due to rapid land exposure in the Indonesian archipelago induced by glacial sea-level lowering, and we suggest a mechanistic link via reduced input of relatively fresh Indonesian Throughflow waters into the Indian Ocean. Using climate model results, we show that the release of this glacial Indian Ocean salinity via the Agulhas Leakage during deglaciation can directly impact the Atlantic Meridional Overturning Circulation and global climate.

Antarctic icebergs reorganize ocean circulation during Pleistocene glacials.

The dominant feature of large-scale mass transfer in the modern ocean is the Atlantic meridional overturning circulation (AMOC). The geometry and vigour of this circulation influences global climate on various timescales. Palaeoceanographic evidence suggests that during glacial periods of the past 1.5 million years the AMOC had markedly different features from today1; in the Atlantic basin, deep waters of Southern Ocean origin increased in volume while above them the core of the North Atlantic Deep Water (NADW) shoaled2. An absence of evidence on the origin of this phenomenon means that the sequence of events leading to global glacial conditions remains unclear. Here we present multi-proxy evidence showing that northward shifts in Antarctic iceberg melt in the Indian-Atlantic Southern Ocean (0-50° E) systematically preceded deep-water mass reorganizations by one to two thousand years during Pleistocene-era glaciations. With the aid of iceberg-trajectory model experiments, we demonstrate that such a shift in iceberg trajectories during glacial periods can result in a considerable redistribution of freshwater in the Southern Ocean. We suggest that this, in concert with increased sea-ice cover, enabled positive buoyancy anomalies to 'escape' into the upper limb of the AMOC, providing a teleconnection between surface Southern Ocean conditions and the formation of NADW. The magnitude and pacing of this mechanism evolved substantially across the mid-Pleistocene transition, and the coeval increase in magnitude of the 'southern escape' and deep circulation perturbations implicate this mechanism as a key feedback in the transition to the '100-kyr world', in which glacial-interglacial cycles occur at roughly 100,000-year periods.

Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods.

Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern. They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta. Phylogenetic methods provide the "gold standard" for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges provide a motivation to develop complementary methods that can incorporate all of the genetic data available without down-sampling to extract meaningful information rapidly and with minimal curation. In this paper, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies. While not serving as a substitute for current phylogenetic analyses, the proposed methods can be used as a complementary, and fully automatable, approach to identify and confirm new emerging variants.

Template switching enables chemical probing of native RNA structures.

RNAs are often studied in non-native sequence contexts to facilitate structural studies. However, seemingly innocuous changes to an RNA sequence may perturb the native structure and generate inaccurate or ambiguous structural models. To facilitate the investigation of native RNA secondary structure by selective 2' hydroxyl acylation analyzed by primer extension (SHAPE), we engineered an approach that couples minimal enzymatic steps to RNA chemical probing and mutational profiling (MaP) reverse transcription (RT) methods - a process we call template switching and mutational profiling (Switch-MaP). In Switch-MaP, RT templates and additional library sequences are added post-probing through ligation and template switching, capturing reactivities for every nucleotide. For a candidate SAM-I riboswitch, we compared RNA structure models generated by the Switch-MaP approach to those of traditional primer-based MaP, including RNAs with or without appended structure cassettes. Primer-based MaP masked reactivity data in the 5' and 3' ends of the RNA, producing ambiguous ensembles inconsistent with the conserved SAM-I riboswitch secondary structure. Structure cassettes enabled unambiguous modeling of an aptamer-only construct but introduced non-native interactions in the full length riboswitch. In contrast, Switch-MaP provided reactivity data for all nucleotides in each RNA and enabled unambiguous modeling of secondary structure, consistent with the conserved SAM-I fold. Switch-MaP is a straightforward alternative approach to primer-based and cassette-based chemical probing methods that precludes primer masking and the formation of alternative secondary structures due to non-native sequence elements.

Structure of pre-miR-31 reveals an active role in Dicer-TRBP complex processing.

As an essential posttranscriptional regulator of gene expression, microRNA (miRNA) levels must be strictly maintained. The biogenesis of many miRNAs is mediated by trans-acting protein partners through a variety of mechanisms, including remodeling of the RNA structure. miR-31 functions as an oncogene in numerous cancers, and interestingly, its biogenesis is not known to be regulated by protein-binding partners. Therefore, the intrinsic structural properties of the precursor element of miR-31 (pre-miR-31) can provide a mechanism by which its biogenesis is regulated. We determined the solution structure of pre-miR-31 to investigate the role of distinct structural elements in regulating processing by the Dicer-TRBP complex. We found that the presence or absence of mismatches within the helical stem does not strongly influence Dicer-TRBP processing of the pre-miRNAs. However, both the apical loop size and structure at the Dicing site are key elements for discrimination by the Dicer-TRBP complex. Interestingly, our NMR-derived structure reveals the presence of a triplet of base pairs that link the Dicer cleavage site and the apical loop. Mutational analysis in this region suggests that the stability of the junction region strongly influences processing by the Dicer-TRBP complex. Our results enrich our understanding of the active role that RNA structure plays in regulating miRNA biogenesis, which has direct implications for the control of gene expression.

A beta-Poisson model for infectious disease transmission.

Outbreaks of emerging and zoonotic infections represent a substantial threat to human health and well-being. These outbreaks tend to be characterised by highly stochastic transmission dynamics with intense variation in transmission potential between cases. The negative binomial distribution is commonly used as a model for transmission in the early stages of an epidemic as it has a natural interpretation as the convolution of a Poisson contact process and a gamma-distributed infectivity. In this study we expand upon the negative binomial model by introducing a beta-Poisson mixture model in which infectious individuals make contacts at the points of a Poisson process and then transmit infection along these contacts with a beta-distributed probability. We show that the negative binomial distribution is a limit case of this model, as is the zero-inflated Poisson distribution obtained by combining a Poisson-distributed contact process with an additional failure probability. We assess the beta-Poisson model's applicability by fitting it to secondary case distributions (the distribution of the number of subsequent cases generated by a single case) estimated from outbreaks covering a range of pathogens and geographical settings. We find that while the beta-Poisson mixture can achieve a closer to fit to data than the negative binomial distribution, it is consistently outperformed by the negative binomial in terms of Akaike Information Criterion, making it a suboptimal choice on parsimonious grounds. The beta-Poisson performs similarly to the negative binomial model in its ability to capture features of the secondary case distribution such as overdispersion, prevalence of superspreaders, and the probability of a case generating zero subsequent cases. Despite this possible shortcoming, the beta-Poisson distribution may still be of interest in the context of intervention modelling since its structure allows for the simulation of measures which change contact structures while leaving individual-level infectivity unchanged, and vice-versa.

Functional Validation of SAM Riboswitch Element A from Listeria monocytogenes.

SreA is one of seven candidate S-adenosyl methionine (SAM) class I riboswitches identified in Listeria monocytogenes, a saprophyte and opportunistic foodborne pathogen. SreA precedes genes encoding a methionine ATP-binding cassette (ABC) transporter, which imports methionine and is presumed to regulate transcription of its downstream genes in a SAM-dependent manner. The proposed role of SreA in controlling the transcription of genes encoding an ABC transporter complex may have important implications for how the bacteria senses and responds to the availability of the metabolite SAM in the diverse environments in which L. monocytogenes persists. Here we validate SreA as a functional SAM-I riboswitch through ligand binding studies, structure characterization, and transcription termination assays. We determined that SreA has both a structure and SAM binding properties similar to those of other well-characterized SAM-I riboswitches. Despite the apparent structural similarities to previously described SAM-I riboswitches, SreA induces transcription termination in response to comparatively lower (nanomolar) ligand concentrations. Furthermore, SreA is a leaky riboswitch that permits some transcription of the downstream gene even in the presence of millimolar SAM, suggesting that L. monocytogenes may "dampen" the expression of genes for methionine import but likely does not turn them "OFF".

Genome-wide association study of preserved ratio impaired spirometry (PRISm).

BACKGROUND: Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≥0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities. METHODS: We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed. RESULTS: 22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits. CONCLUSION: This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.

Epithelial Interleukin-1 Receptor-Like-1 Activation Is Contingent on Interleukin-33 Isoforms and Asthma-Related Receptor Variation.

INTRODUCTION: The interleukin-33/interleukin-1 receptor-like-1 (IL-33/IL1RL1) signalling pathway is implicated in asthma pathogenesis, with IL1RL1 nonsynonymous genetic polymorphisms associated with disease risk. We aimed to determine these variants' effect on IL1RL1 signalling induced by different IL33 isoforms thought to be elevated in the asthmatic airway. METHOD: In a project funded by GSK plc, which has developed an IL-33 receptor inhibitor for asthma treatment, human embryonic kidney 293 (HEK293) cells expressing secreted embryonic alkaline phosphatase (SEAP) driven by a nuclear factor kappa-beta (NF-κB) promoter, were transiently transfected with IL1RL1, containing one of four extracellular and Toll/interleukin 1 receptor (TIR) domain haplotypes. Cells were stimulated with seven different splice and proteolytic-generated IL-33 isoforms (0.001-50 ng/mL) for 24 h. Supernatant SEAP activity and interleukin-8 (IL-8) levels were determined. Primary human bronchial epithelial cells (HBECs) representing different genotype carriers were stimulated with IL-33112-270 (50 ng/mL) and induced IL-8 mRNA expression measured. RESULTS: HEK293 cells carrying both asthma extracellular and TIR domain IL1RL1 risk haplotypes presented maximal IL33-driven signalling, with minimal signalling after IL-33 activation in other protective haplotypes. All IL-33 isoforms activated IL1RL1 but with differing magnitudes. Proteolytically cleaved IL3395-270 and IL33106-270 had the greatest effect and the IL33113-270, and Exon 3,4 deletion isoform exhibited the lowest. The effect of extracellular and TIR domain genetic variants on receptor signalling was replicated in primary HBECs. Maximal IL1RL1 signalling was observed in cells carrying both extracellular and TIR signalling domain risk haplotypes. CONCLUSIONS: Overall, our study suggests asthma patients carrying the extracellular and TIR domain risk haplotype and have a lung microenvironment that promotes elevated levels of cleaved IL33, particularly where IL3395-270 and IL33106-270 may be more amenable to IL33/IL1RL1 targeting.

Free-Breathing Functional Pulmonary Proton MRI: A Novel Approach Using Voxel-Wise Lung Ventilation (VOLVE) Assessment in Healthy Volunteers and Patients With Chronic Obstructive Pulmonary Disease.

BACKGROUND: In respiratory medicine, there is a need for sensitive measures of regional lung function that can be performed using standard imaging technology, without the need for inhaled or intravenous contrast agents. PURPOSE: To describe VOxel-wise Lung VEntilation (VOLVE), a new method for quantifying regional lung ventilation (V) and perfusion (Q) using free-breathing proton MRI, and to evaluate VOLVE in healthy never-smokers, healthy people with smoking history, and people with chronic obstructive pulmonary disease (COPD). STUDY TYPE: Prospective pilot. POPULATION: Twelve healthy never-smoker participants (age 30.3 ± 12.5 years, five male), four healthy participants with smoking history (>10 pack-years) (age 42.5 ± 18.3 years, one male), and 12 participants with COPD (age 62.8 ± 11.1 years, seven male). FIELD STRENGTH/SEQUENCE: Single-slice free-breathing two-dimensional fast field echo sequence at 3 T. ASSESSMENT: A novel postprocessing was developed to evaluate the MR signal changes in the lung parenchyma using a linear regression-based approach, which makes use of all the data in the time series for maximum sensitivity. V/Q-weighted maps were produced by computing the cross-correlation, lag and gradient between the respiratory/cardiac phase time course and lung parenchyma signal time courses. A comparison of histogram median and skewness values and spirometry was performed. STATISTICAL TESTS: Kruskal-Wallis tests with Dunn's multiple comparison tests to compare VOLVE metrics between groups; Spearman correlation to assess the correlation between MRI and spirometry-derived parameters; and Bland-Altman analysis and coefficient of variation to evaluate repeatability were used. A P-value <0.05 was considered significant. RESULTS: Significant differences between the groups were found for ventilation between healthy never-smoker and COPD groups (median XCCV, LagV, and GradV) and perfusion (median XCCQ, LagQ, and GradQ). Minimal bias and no significant differences between intravisit scans were found (P range = 0.12-0.97). DATA CONCLUSION: This preliminary study showed that VOLVE has potential to provide metrics of function quantification. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

DYNamic Assessment of Multi-Organ level dysfunction in patients recovering from COVID-19: DYNAMO COVID-19.

We evaluated the impacts of COVID-19 on multi-organ and metabolic function in patients following severe hospitalised infection compared to controls. Patients (n = 21) without previous diabetes, cardiovascular or cerebrovascular disease were recruited 5-7 months post-discharge alongside controls (n = 10) with similar age, sex and body mass. Perceived fatigue was estimated (Fatigue Severity Scale) and the following were conducted: oral glucose tolerance (OGTT) alongside whole-body fuel oxidation, validated magnetic resonance imaging and spectroscopy during resting and supine controlled exercise, dual-energy X-ray absorptiometry, short physical performance battery (SPPB), intra-muscular electromyography, quadriceps strength and fatigability, and daily step-count. There was a greater insulin response (incremental area under the curve, median (inter-quartile range)) during the OGTT in patients [18,289 (12,497-27,448) mIU/min/L] versus controls [8655 (7948-11,040) mIU/min/L], P < 0.001. Blood glucose response and fasting and post-prandial fuel oxidation rates were not different. This greater insulin resistance was not explained by differences in systemic inflammation or whole-body/regional adiposity, but step-count (P = 0.07) and SPPB scores (P = 0.004) were lower in patients. Liver volume was 28% greater in patients than controls, and fat fraction adjusted liver T1, a measure of inflammation, was raised in patients. Patients displayed greater perceived fatigue scores, though leg muscle volume, strength, force-loss, motor unit properties and post-exercise muscle phosphocreatine resynthesis were comparable. Further, cardiac and cerebral architecture and function (at rest and on exercise) were not different. In this cross-sectional study, individuals without known previous morbidity who survived severe COVID-19 exhibited greater insulin resistance, pointing to a need for physical function intervention in recovery.

Risk factors for SARS-CoV-2 infection at a UK electricity-generating company: a test-negative design case-control study.

OBJECTIVES: Identify workplace risk factors for SARS-CoV-2 infection, using data collected by a UK electricity-generating company. METHODS: Using a test-negative design case-control study, we estimated the OR of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage and site COVID-19 weekly risk rating, adjusting for age, test date and test type. RESULTS: From an original 80 077 COVID-19 tests, there were 70 646 included in the final analysis. Most exclusions were due to being visitor tests (5030) or tests after an individual first tested positive (2968).Women were less likely to test positive than men (OR=0.71; 95% CI 0.58 to 0.86). Test reason was strongly associated with positivity and although not a cause of infection itself, due to differing test regimes by area, it was a strong confounder for other variables. Compared with routine tests, tests due to symptoms were highest risk (94.99; 78.29 to 115.24), followed by close contact (16.73; 13.80 to 20.29) and broader-defined work contact 2.66 (1.99 to 3.56). After adjustment, we found little difference in risk by job category, but some differences by site with three sites showing substantially lower risks, and one site showing higher risks in the final model. CONCLUSIONS: In general, infection risk was not associated with job category. Vulnerable individuals were at slightly lower risk, tests during outages were higher risk, vaccination showed no evidence of an effect on testing positive, and site COVID-19 risk rating did not show an ordered trend in positivity rates.

Anomalously weak Labrador Sea convection and Atlantic overturning during the past 150 years.

The Atlantic meridional overturning circulation (AMOC) is a system of ocean currents that has an essential role in Earth's climate, redistributing heat and influencing the carbon cycle1, 2. The AMOC has been shown to be weakening in recent years 1 ; this decline may reflect decadal-scale variability in convection in the Labrador Sea, but short observational datasets preclude a longer-term perspective on the modern state and variability of Labrador Sea convection and the AMOC1, 3-5. Here we provide several lines of palaeo-oceanographic evidence that Labrador Sea deep convection and the AMOC have been anomalously weak over the past 150 years or so (since the end of the Little Ice Age, LIA, approximately AD 1850) compared with the preceding 1,500 years. Our palaeoclimate reconstructions indicate that the transition occurred either as a predominantly abrupt shift towards the end of the LIA, or as a more gradual, continued decline over the past 150 years; this ambiguity probably arises from non-AMOC influences on the various proxies or from the different sensitivities of these proxies to individual components of the AMOC. We suggest that enhanced freshwater fluxes from the Arctic and Nordic seas towards the end of the LIA-sourced from melting glaciers and thickened sea ice that developed earlier in the LIA-weakened Labrador Sea convection and the AMOC. The lack of a subsequent recovery may have resulted from hysteresis or from twentieth-century melting of the Greenland Ice Sheet 6 . Our results suggest that recent decadal variability in Labrador Sea convection and the AMOC has occurred during an atypical, weak background state. Future work should aim to constrain the roles of internal climate variability and early anthropogenic forcing in the AMOC weakening described here.

Residual Lung Abnormalities after COVID-19 Hospitalization: Interim Analysis of the UKILD Post-COVID-19 Study.

Rationale: Shared symptoms and genetic architecture between coronavirus disease (COVID-19) and lung fibrosis suggest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to progressive lung damage. Objectives: The UK Interstitial Lung Disease Consortium (UKILD) post-COVID-19 study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 on the basis of risk strata. Methods: The PHOSP-COVID-19 (Post-Hospitalization COVID-19) study was used to capture routine and research follow-up within 240 days from discharge. Thoracic computed tomography linked by PHOSP-COVID-19 identifiers was scored for the percentage of residual lung abnormalities (ground-glass opacities and reticulations). Risk factors in linked computed tomography were estimated with Bayesian binomial regression, and risk strata were generated. Numbers within strata were used to estimate posthospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol-driven research follow-up. Measurements and Main Results: The interim cohort comprised 3,700 people. Of 209 subjects with linked computed tomography (median, 119 d; interquartile range, 83-155), 166 people (79.4%) had more than 10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (risk ratio [RR], 1.21; 95% credible interval [CrI], 1.05-1.40), percent predicted DlCO less than 80% (RR, 1.25; 95% CrI, 1.00-1.56), and severe admission requiring ventilation support (RR, 1.27; 95% CrI, 1.07-1.55). In the remaining 3,491 people, moderate to very high risk of residual lung abnormalities was classified at 7.8%, and posthospitalization prevalence was estimated at 8.5% (95% CrI, 7.6-9.5), rising to 11.7% (95% CrI, 10.3-13.1) in the sensitivity analysis. Conclusions: Residual lung abnormalities were estimated in up to 11% of people discharged after COVID-19-related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

Mendelian randomisation of eosinophils and other cell types in relation to lung function and disease.

RATIONALE: Eosinophils are associated with airway inflammation in respiratory disease. Eosinophil production and survival is controlled partly by interleukin-5: anti-interleukin-5 agents reduce asthma and response correlates with baseline eosinophil counts. However, whether raised eosinophils are causally related to chronic obstructive pulmonary disease (COPD) and other respiratory phenotypes is not well understood. OBJECTIVES: We investigated causality between eosinophils and: lung function, acute exacerbations of COPD, asthma-COPD overlap (ACO), moderate-to-severe asthma and respiratory infections. METHODS: We performed Mendelian randomisation (MR) using 151 variants from genome-wide association studies of blood eosinophils in UK Biobank/INTERVAL, and respiratory traits in UK Biobank/SpiroMeta, using methods relying on different assumptions for validity. We performed multivariable analyses using eight cell types where there was possible evidence of causation by eosinophils. MEASUREMENTS AND MAIN RESULTS: Causal estimates derived from individual variants were highly heterogeneous, which may arise from pleiotropy. The average effect of raising eosinophils was to increase risk of ACO (weighted median OR per SD eosinophils, 1.44 (95%CI 1.19 to 1.74)), and moderate-severe asthma (weighted median OR 1.50 (95%CI 1.23 to 1.83)), and to reduce forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) and FEV1 (weighted median estimator, SD FEV1/FVC: -0.054 (95% CI -0.078 to -0.029), effect only prominent in individuals with asthma). CONCLUSIONS: Broad consistency across MR methods may suggest causation by eosinophils (although of uncertain magnitude), yet heterogeneity necessitates caution: other important mechanisms may be responsible for the impairment of respiratory health by these eosinophil-raising variants. These results could suggest that anti-IL5 agents (designed to lower eosinophils) may be valuable in treating other respiratory conditions, including people with overlapping features of asthma and COPD.

Genome-wide association study of chronic sputum production implicates loci involved in mucus production and infection.

BACKGROUND: Chronic sputum production impacts on quality of life and is a feature of many respiratory diseases. Identification of the genetic variants associated with chronic sputum production in a disease agnostic sample could improve understanding of its causes and identify new molecular targets for treatment. METHODS: We conducted a genome-wide association study (GWAS) of chronic sputum production in UK Biobank. Signals meeting genome-wide significance (p<5×10-8) were investigated in additional independent studies, were fine-mapped and putative causal genes identified by gene expression analysis. GWASs of respiratory traits were interrogated to identify whether the signals were driven by existing respiratory disease among the cases and variants were further investigated for wider pleiotropic effects using phenome-wide association studies (PheWASs). RESULTS: From a GWAS of 9714 cases and 48 471 controls, we identified six novel genome-wide significant signals for chronic sputum production including signals in the human leukocyte antigen (HLA) locus, chromosome 11 mucin locus (containing MUC2, MUC5AC and MUC5B) and FUT2 locus. The four common variant associations were supported by independent studies with a combined sample size of up to 2203 cases and 17 627 controls. The mucin locus signal had previously been reported for association with moderate-to-severe asthma. The HLA signal was fine-mapped to an amino acid change of threonine to arginine (frequency 36.8%) in HLA-DRB1 (HLA-DRB1*03:147). The signal near FUT2 was associated with expression of several genes including FUT2, for which the direction of effect was tissue dependent. Our PheWAS identified a wide range of associations including blood cell traits, liver biomarkers, infections, gastrointestinal and thyroid-associated diseases, and respiratory disease. CONCLUSIONS: Novel signals at the FUT2 and mucin loci suggest that mucin fucosylation may be a driver of chronic sputum production even in the absence of diagnosed respiratory disease and provide genetic support for this pathway as a target for therapeutic intervention.

Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential.

Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Simplified within-host and Dose-response Models of SARS-CoV-2.

Understanding the mechanistic dynamics of transmission is key to designing more targeted and effective interventions to limit the spread of infectious diseases. A well-described within-host model allows explicit simulation of how infectiousness changes over time at an individual level. This can then be coupled with dose-response models to investigate the impact of timing on transmission. We collected and compared a range of within-host models used in previous studies and identified a minimally-complex model that provides suitable within-host dynamics while keeping a reduced number of parameters to allow inference and limit unidentifiability issues. Furthermore, non-dimensionalised models were developed to further overcome the uncertainty in estimates of the size of the susceptible cell population, a common problem in many of these approaches. We will discuss these models, and their fit to data from the human challenge study (see Killingley et al. (2022)) for SARS-CoV-2 and the model selection results, which has been performed using ABC-SMC. The parameter posteriors have then used to simulate viral-load based infectiousness profiles via a range of dose-response models, which illustrate the large variability of the periods of infection window observed for COVID-19.