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

Genome-Wide Association Study of Susceptibility to Idiopathic Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a complex lung disease characterised by scarring of the lung that is believed to result from an atypical response to injury of the epithelium. Genome-wide association studies have reported signals of association implicating multiple pathways including host defence, telomere maintenance, signalling and cell-cell adhesion. Objectives: To improve our understanding of factors that increase IPF susceptibility by identifying previously unreported genetic associations. Methods and measurements: We conducted genome-wide analyses across three independent studies and meta-analysed these results to generate the largest genome-wide association study of IPF to date (2,668 IPF cases and 8,591 controls). We performed replication in two independent studies (1,456 IPF cases and 11,874 controls) and functional analyses (including statistical fine-mapping, investigations into gene expression and testing for enrichment of IPF susceptibility signals in regulatory regions) to determine putatively causal genes. Polygenic risk scores were used to assess the collective effect of variants not reported as associated with IPF. Main results: We identified and replicated three new genome-wide significant (P<5×10−8) signals of association with IPF susceptibility (associated with altered gene expression of KIF15, MAD1L1 and DEPTOR) and confirmed associations at 11 previously reported loci. Polygenic risk score analyses showed that the combined effect of many thousands of as-yet unreported IPF susceptibility variants contribute to IPF susceptibility. Conclusions: The observation that decreased DEPTOR expression associates with increased susceptibility to IPF, supports recent studies demonstrating the importance of mTOR signalling in lung fibrosis. New signals of association implicating KIF15 and MAD1L1 suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility

Association study of human leukocyte antigen (HLA) variants and idiopathic pulmonary fibrosis

IntroductionIdiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF and a prior association of theHLA-DQB1gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Due to the important role that the Human Leukocyte Antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk.MethodsWe performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising a total of 5159 cases and 27 459 controls, including the prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association thresholdp&lt;4.5×10−4and a posterior probability of replication &gt;90% were considered significant. We sought to replicate the previously reportedHLA-DQB1association in the subset of studies independent of the original report.ResultsThe meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. TheHLA-DQB1association was not replicated in the independent IPF studies.ConclusionVariation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF

Additional file 1 of A genome-wide association study of survival in patients with sepsis

Additional file 1. Supplementary methods, figures, and tables.The supplementary methods include a description of the GEN-SEP and MESSI study populations, genotyping and quality control, more details of the genome-wide association study of 28-day sepsis survival and the index event bias assessment, tools for the annotation of the functional effects of the sentinel variants and the gene expression of related genes, the association of polygenic risks of sepsis with the 28-day sepsis survival, the replication of genes from previous sepsis mortality GWAS, and related references. The supplementary figures include a principal component analysis, the quantile-quantile plot of the GWAS, regional plots for the genome-wide significant variants, Kaplan-Meier 28-day survival plots, a manhattan plot of sepsis 28-day survival association study results in the HLA region, a plot of expression of related genes across cell types, a boxplot of SAMD9 gene expression values in GSE54514 and GSE65682, a boxplot of SAMD9 gene expression values in GSE32707, and polygenic risk score (PRS) model fitting. The supplementary tables show the relevant demographic and clinical features of cases and controls used for the GWAS of sepsis risk and for the GEN-SEP patients, the list of previous candidate genes associated with sepsis risk, the prioritized independent SNPs, the index bias event results, the association results with 28-day mortality and the percentage of variation explained by the sentinel SNPs by separate or as part of a PRS, the association results of the sentinel variants from other sepsis mortality GWAS studies, the nominally significant results for the classical HLA alleles and amino acids, and the functional assessment of variants associated with 28-day sepsis survival

New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

Abstract Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function–associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD

Author Correction:New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

Correction to: Nature Genetics https://doi.org/10.1038/s41588-018-0321-7, published online 25 February 2019

Author Correction:New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries (Nature Genetics, (2019), 51, 3, (481-493), 10.1038/s41588-018-0321-7)

Correction to: Nature Geneticshttps://doi.org/10.1038/s41588-018-0321-7, published online 25 February 2019. In the version of the article initially published, unconsented individuals were erroneously included in SPIROMICS consortium results. The analysis has now been repeated with the unconsented individuals removed. The change in the results does not affect the conclusions in the paper. The corrections required to the paper are as follows: In the third paragraph of the “Association with FEV1/FVC and COPD in multiple ancestries” section: “(n = 6,979 cases and 3,915 controls)”, should be “(n = 6,964 cases and 3,904 controls)” and “P = 2.87 × 10–75” should be “P = 2.21 × 10–75”. In the fourth paragraph of the “Association with FEV1/FVC and COPD in multiple ancestries” section: “4.73 (95% CI: [3.79, 5.90]), P = 3.00 × 10−43”, should be “4.71 (95% CI: [3.77, 5.87]), P = 7.24 × 10−43”. In the Fig. 3b table, the SPIROMICS row: “1.54, 1.38, 1.72, 4.47 × 10–14, 988, 537”, should be “1.55, 1.39, 1.74, 6.80 × 10–14, 973, 526”; and the Meta-analysis row: “1.55, 1.48, 1.62, 1.48 × 10–75, 6,979, 3,915”, should be “1.55, 1.48, 1.62, 2.21 × 10–75, 6,964, 3,904”. In the final paragraph of the Discussion: “The 279-variant GRS we constructed was associated with a 4.73-fold increased relative risk…”, should be “The 279-variant GRS we constructed was associated with a 4.71-fold increased relative risk…” In the fifth paragraph of the “Effect of genetic risk score on COPD susceptibility in multiple ancestries” section in the Methods: “SPIROMICS (988 cases, 537 controls)”, should be “SPIROMICS (973 cases, 526 controls)”. In the third paragraph of the “Association with FEV1/FVC and COPD in multiple ancestries” section: “(n = 6,979 cases and 3,915 controls)”, should be “(n = 6,964 cases and 3,904 controls)” and “P = 2.87 × 10–75” should be “P = 2.21 × 10–75”. In the fourth paragraph of the “Association with FEV1/FVC and COPD in multiple ancestries” section: “4.73 (95% CI: [3.79, 5.90]), P = 3.00 × 10−43”, should be “4.71 (95% CI: [3.77, 5.87]), P = 7.24 × 10−43”. In the Fig. 3b table, the SPIROMICS row: “1.54, 1.38, 1.72, 4.47 × 10–14, 988, 537”, should be “1.55, 1.39, 1.74, 6.80 × 10–14, 973, 526”; and the Meta-analysis row: “1.55, 1.48, 1.62, 1.48 × 10–75, 6,979, 3,915”, should be “1.55, 1.48, 1.62, 2.21 × 10–75, 6,964, 3,904”. In the final paragraph of the Discussion: “The 279-variant GRS we constructed was associated with a 4.73-fold increased relative risk…”, should be “The 279-variant GRS we constructed was associated with a 4.71-fold increased relative risk…” In the fifth paragraph of the “Effect of genetic risk score on COPD susceptibility in multiple ancestries” section in the Methods: “SPIROMICS (988 cases, 537 controls)”, should be “SPIROMICS (973 cases, 526 controls)”. The correction is due to 26 unconsented SPIROMICS samples being originally included in the analysis. The analyses that previously included these samples have been rerun with data from these 26 samples removed. Supplementary Information accompanies the online version of this amendment and includes: Updated Supplementary Text and Figures wherein we have changed: On page 23 (description of SPIROMICS cohort) the number of COPD cases has been changed from 988 to 973 and controls from 537 to 526. Supplementary Figure 9 – the forest plots have been updated for the new results for association with 279 variants after reanalysis of SPIROMICS. Supplementary Table 20 – the demographics for SPIROMICS have been updated. Supplementary Table 21 – the results rows for the SPIROMICS and “Meta-analysis of 5 European-ancestry study groups” have been updated. Supplementary Table 22 – The “Meta-analysis of 5 European cohorts” columns have been updated after SPIROMICS reanalysis. Updated Supplementary Tables wherein we have changed: Supplementary Table 29 – columns X–Z (“Meta-analysis of 5 external European-ancestry COPD cohorts (Cases = 6,964; Controls = 3,904)”) after reanalysis of SPIROMICS data. Updated Supplementary Text and Figures wherein we have changed: On page 23 (description of SPIROMICS cohort) the number of COPD cases has been changed from 988 to 973 and controls from 537 to 526. Supplementary Figure 9 – the forest plots have been updated for the new results for association with 279 variants after reanalysis of SPIROMICS. Supplementary Table 20 – the demographics for SPIROMICS have been updated. Supplementary Table 21 – the results rows for the SPIROMICS and “Meta-analysis of 5 European-ancestry study groups” have been updated. Supplementary Table 22 – The “Meta-analysis of 5 European cohorts” columns have been updated after SPIROMICS reanalysis. Updated Supplementary Tables wherein we have changed: Supplementary Table 29 – columns X–Z (“Meta-analysis of 5 external European-ancestry COPD cohorts (Cases = 6,964; Controls = 3,904)”) after reanalysis of SPIROMICS data