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Background: The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period., Objective: To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19., Methods: Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR)., Results: RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64., Conclusions: Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data., Competing Interests: The authors have declared that no competing interests exist.

Background: Genome-wide association studies have identified novel genetic associations for asthma, but without taking into account the role of active tobacco smoking. This study aimed to identify novel genes that interact with ever active tobacco smoking in adult onset asthma., Methods: We performed a genome-wide interaction analysis in six studies participating in the GABRIEL consortium following two meta-analyses approaches based on 1) the overall interaction effect and 2) the genetic effect in subjects with and without smoking exposure. We performed a discovery meta-analysis including 4,057 subjects of European descent and replicated our findings in an independent cohort (LifeLines Cohort Study), including 12,475 subjects., Results: First approach: 50 SNPs were selected based on an overall interaction effect at p<10-4. The most pronounced interaction effect was observed for rs9969775 on chromosome 9 (discovery meta-analysis: ORint = 0.50, p = 7.63*10-5, replication: ORint = 0.65, p = 0.02). Second approach: 35 SNPs were selected based on the overall genetic effect in exposed subjects (p <10-4). The most pronounced genetic effect was observed for rs5011804 on chromosome 12 (discovery meta-analysis ORint = 1.50, p = 1.21*10-4; replication: ORint = 1.40, p = 0.03)., Conclusions: Using two genome-wide interaction approaches, we identified novel polymorphisms in non-annotated intergenic regions on chromosomes 9 and 12, that showed suggestive evidence for interaction with active tobacco smoking in the onset of adult asthma.

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development., Competing Interests: Dr. BM Psaty serves on the DSMB for a clinical trial of a device funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Steno Diabetes Center and Synlab Holding Deutschland GmbH provided support in the form of salaries for authors T.S.A. and W.M. respectively, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Objective: Allergic conjunctivitis (AC) is a common condition, especially in childhood. The extent to which it occurs concurrently with or independently from allergic rhinitis (AR) has not been well described., Aim: To examine the inter-relationship between rhinitis and conjunctivitis and the epidemiological risk factors for these conditions in a rural UK population., Methods: Cross-sectional study of rural school children (aged 5-11 years). Parental questionnaires were used to diagnose allergic outcomes (including conjunctivitis, rhinitis and rhinoconjunctivitis), and to collect data on atopic history, demographic and environmental exposures. Odds ratios of allergic outcome by exposure were examined adjusted for age, sex, breastfeeding, family history of allergy, number of older and younger siblings., Results: Prevalence of conjunctivitis was 17.5%, rhinitis 15.1% and rhinoconjunctivitis 13.0%. Seasonality of symptoms varied by condition: 64.7% of those with conjunctivitis had seasonal symptoms (April-Sept only), 46.7% of those with rhinitis and 92.2% of those with rhinoconjunctivitis. Living on a farm consistently reduced the risk of conjunctivitis (odds ratio 0.47, 95%CI 0.29-0.79, p = 0.004), rhinitis (OR 0.57, 95%CI 0.33-1.01, p = 0.05) and rhinoconjunctivitis (OR 0.57, 95%CI 0.32-1.03, p = 0.06). Exposure to farm animals (particularly in early life), current consumption of unpasteurised milk and playing in a barn or stable significantly reduced the risk of all three conditions., Conclusion: More children had parent-reported conjunctivitis than rhinitis. The majority of children with either condition also reported symptoms with the other condition. Farmers' children have less eye and/or nasal symptoms. A number of farming variables linked with the farm microbial environment are likely to be mediating the protective effect.

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8). This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

Background: Childhood obesity and asthma are increasing worldwide. A possible link between the two conditions has been postulated., Methods: Cross-sectional studies of stratified random samples of 8-12-year-old children (n = 10 652) (16 centres in affluent and 8 centres in non-affluent countries) used the standardized methodology of ISAAC Phase Two. Respiratory and allergic symptoms were ascertained by parental questionnaires. Tests for allergic disease were performed. Height and weight were measured, and overweight and obesity were defined according to international definitions. Prevalence rates and prevalence odds ratios were calculated., Results: Overweight (odds ratio = 1.14, 95%-confidence interval: 0.98; 1.33) and obesity (odds ratio = 1.67, 95%-confidence interval: 1.25; 2.21) were related to wheeze. The relationship was stronger in affluent than in non-affluent centres. Similar results were found for cough and phlegm, rhinitis and eczema but the associations were mostly driven by children with wheeze. There was a clear association of overweight and obesity with airways obstruction (change in FEV1/FVC, -0.90, 95%-confidence interval: -1.33%; -0.47%, for overweight and -2.46%, 95%-confidence interval: -3.84%; -1.07%, for obesity) whereas the results for the other objective markers, including atopy, were null., Conclusions: Our data from a large international child population confirm that there is a strong relation of body mass index with wheeze especially in affluent countries. Moreover, body mass index is associated with an objective marker of airways obstruction (FEV1/FVC) but no other objective markers of respiratory and allergic disorders.

Background: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function., Methods: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis., Results: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively., Conclusions: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function.

The aim is to examine the association of lifecourse socioeconomic position (SEP) on circulating levels of D-dimer. Data from the 1958 British birth cohort were used, social class was determined at three stages of respondents' life: at birth, at 23 and at 42 years. A cumulative indicator score of SEP (CIS) was calculated ranging from 0 (always in the highest social class) to 9 (always in the lowest social class). In men and women, associations were observed between CIS and D-dimer (P<0.05). Thus, the respondents in more disadvantaged social classes had elevated levels of D-dimer compared to respondents in less disadvantaged social class. In multivariate analyses, the association of disadvantaged social position with D-dimer was largely explained by fibrinogen, C-reactive protein and von Willebrand Factor in women, and additionally by smoking, alcohol consumption and physical activity in men. Socioeconomic circumstances across the lifecourse at various stages also contribute independently to raised levels of D-dimer in middle age in women only. Risk exposure related to SEP accumulates across life and contributes to raised levels of D-dimer. The association of haemostatic markers and social differences in health may be mediated by inflammatory and other markers.

[This corrects the article DOI: 10.1371/journal.pone.0044008.].

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies., Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations., Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5 x 10(-8)) and three variants reported as suggestive (P<5× 10(-7)). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever., Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4 × 10(-9)). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (P(Stage1+Stage2) = 1.1x10(-9)), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (P(Stage1+Stage2) = 1.1x10(-8)), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status., Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.

Rationale: Lung function measures are heritable traits that predict population morbidity and mortality and are essential for the diagnosis of chronic obstructive pulmonary disease (COPD). Variations in many genes have been reported to affect these traits, but attempts at replication have provided conflicting results. Recently, we undertook a meta-analysis of Genome Wide Association Study (GWAS) results for lung function measures in 20,288 individuals from the general population (the SpiroMeta consortium)., Objectives: To comprehensively analyse previously reported genetic associations with lung function measures, and to investigate whether single nucleotide polymorphisms (SNPs) in these genomic regions are associated with lung function in a large population sample., Methods: We analysed association for SNPs tagging 130 genes and 48 intergenic regions (+/-10 kb), after conducting a systematic review of the literature in the PubMed database for genetic association studies reporting lung function associations., Results: The analysis included 16,936 genotyped and imputed SNPs. No loci showed overall significant association for FEV(1) or FEV(1)/FVC traits using a carefully defined significance threshold of 1.3×10(-5). The most significant loci associated with FEV(1) include SNPs tagging MACROD2 (P = 6.81×10(-5)), CNTN5 (P = 4.37×10(-4)), and TRPV4 (P = 1.58×10(-3)). Among ever-smokers, SERPINA1 showed the most significant association with FEV(1) (P = 8.41×10(-5)), followed by PDE4D (P = 1.22×10(-4)). The strongest association with FEV(1)/FVC ratio was observed with ABCC1 (P = 4.38×10(-4)), and ESR1 (P = 5.42×10(-4)) among ever-smokers., Conclusions: Polymorphisms spanning previously associated lung function genes did not show strong evidence for association with lung function measures in the SpiroMeta consortium population. Common SERPINA1 polymorphisms may affect FEV(1) among smokers in the general population.