Project description:Rationale: Idiopathic pulmonary fibrosis (IPF) is a complex lung disease characterized 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 defense, telomere maintenance, signaling, and cell-cell adhesion.Objectives: To improve our understanding of factors that increase IPF susceptibility by identifying previously unreported genetic associations.Methods: We conducted genome-wide analyses across three independent studies and meta-analyzed 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.Measurements and 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 signaling in lung fibrosis. New signals of association implicating KIF15 and MAD1L1 suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility.
Project description:We conducted a post hoc analysis to assess the potential impact of GAP (gender, age, physiology) stage on the treatment effect of nintedanib in patients with idiopathic pulmonary fibrosis. Outcomes were compared in patients at GAP stage I versus II/III at baseline in the INPULSIS® trials. At baseline, 500 patients were at GAP stage I (nintedanib 304, placebo 196), 489 were at GAP stage II (nintedanib 296, placebo 193) and 71 were at GAP stage III (nintedanib 38, placebo 33). In nintedanib-treated patients, the annual rate of decline in forced vital capacity (FVC) was similar in patients at GAP stage I and GAP stage II/III at baseline (-110.1 and -116.6 mL·year-1, respectively), and in both subgroups was lower than in placebo-treated patients (-218.5 and -227.6 mL·year-1, respectively) (treatment-by-time-by-subgroup interaction p=0.92). In the nintedanib group, the number of deaths was 43.8% of those predicted based on GAP stage (35 versus 79.9). In the placebo group, the number of deaths was 59.8% of those predicted based on GAP stage (33 versus 55.2). In conclusion, data from the INPULSIS® trials suggest that nintedanib has a similar beneficial effect on the rate of FVC decline in patients at GAP stage I versus II/III at baseline.
Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a devastating disease that probably involves several genetic loci. Several rare genetic variants and one common single nucleotide polymorphism (SNP) of MUC5B have been associated with the disease. Our aim was to identify additional common variants associated with susceptibility and ultimately mortality in IPF.MethodsFirst, we did a three-stage genome-wide association study (GWAS): stage one was a discovery GWAS; and stages two and three were independent case-control studies. DNA samples from European-American patients with IPF meeting standard criteria were obtained from several US centres for each stage. Data for European-American control individuals for stage one were gathered from the database of genotypes and phenotypes; additional control individuals were recruited at the University of Pittsburgh to increase the number. For controls in stages two and three, we gathered data for additional sex-matched European-American control individuals who had been recruited in another study. DNA samples from patients and from control individuals were genotyped to identify SNPs associated with IPF. SNPs identified in stage one were carried forward to stage two, and those that achieved genome-wide significance (p<5 × 10(-8)) in a meta-analysis were carried forward to stage three. Three case series with follow-up data were selected from stages one and two of the GWAS using samples with follow-up data. Mortality analyses were done in these case series to assess the SNPs associated with IPF that had achieved genome-wide significance in the meta-analysis of stages one and two. Finally, we obtained gene-expression profiling data for lungs of patients with IPF from the Lung Genomics Research Consortium and analysed correlation with SNP genotypes.FindingsIn stage one of the GWAS (542 patients with IPF, 542 control individuals matched one-by-one to cases by genetic ancestry estimates), we identified 20 loci. Six SNPs reached genome-wide significance in stage two (544 patients, 687 control individuals): three TOLLIP SNPs (rs111521887, rs5743894, rs5743890) and one MUC5B SNP (rs35705950) at 11p15.5; one MDGA2 SNP (rs7144383) at 14q21.3; and one SPPL2C SNP (rs17690703) at 17q21.31. Stage three (324 patients, 702 control individuals) confirmed the associations for all these SNPs, except for rs7144383. Linkage disequilibrium between the MUC5B SNP (rs35705950) and TOLLIP SNPs (rs111521887 [r(2)=0·07], rs5743894 [r(2)=0·16], and rs5743890 [r(2)=0·01]) was low. 683 patients from the GWAS were included in the mortality analysis. Individuals who developed IPF despite having the protective TOLLIP minor allele of rs5743890 carried an increased mortality risk (meta-analysis with fixed-effect model: hazard ratio 1·72 [95% CI 1·24-2·38]; p=0·0012). TOLLIP expression was decreased by 20% in individuals carrying the minor allele of rs5743890 (p=0·097), 40% in those with the minor allele of rs111521887 (p=3·0 × 10(-4)), and 50% in those with the minor allele of rs5743894 (p=2·93 × 10(-5)) compared with homozygous carriers of common alleles for these SNPs.InterpretationNovel variants in TOLLIP and SPPL2C are associated with IPF susceptibility. One novel variant of TOLLIP, rs5743890, is also associated with mortality. These associations and the reduced expression of TOLLIP in patients with IPF who carry TOLLIP SNPs emphasise the importance of this gene in the disease.FundingNational Institutes of Health; National Heart, Lung, and Blood Institute; Pulmonary Fibrosis Foundation; Coalition for Pulmonary Fibrosis; and Instituto de Salud Carlos III.
Project description:IntroductionThe GAP model was widely used as a simple risk "screening" method for patients with idiopathic pulmonary fibrosis (IPF).ObjectivesWe sought to validate the GAP model in Chinese patients with IPF to evaluate whether it can accurately predict the risk for mortality.MethodsA total of 212 patients with IPF diagnosed at China-Japan Friendship Hospital from 2015 to 2019 were enrolled. The latest follow-up ended in September 2022. Cumulative mortality of each GAP stage was calculated and compared based on Fine-Gray models for survival, and lung transplantation was treated as a competing risk. The performance of the model was evaluated in terms of both discrimination and calibration.ResultsThe cumulative mortality in patients with GAP stage III was significantly higher than that in those with GAP stage I or II (Gray's test p < 0.0001). The Harrell c-index for the GAP calculator was 0.736 (95% CI: 0.667-0.864). The discrimination for the GAP staging system were similar with that for the GAP calculator. The GAP model overestimated the mortality rate at 1- and 2-year in patients classified as GAP stage I (6.90% vs. 1.77% for 1-year, 14.20% vs. 6.78% for 2-year).ConclusionsOur findings indicated that the GAP model overestimated the mortality rate in mild group.
Project description:Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition with poor survival times. We previously published a genome-wide meta-analysis of IPF risk across three studies with independent replication of associated variants in two additional studies. To maximise power and to generate more accurate effect size estimates, we performed a genome-wide meta-analysis across all five studies included in the previous IPF risk genome-wide association studies. We used the distribution of effect sizes across the five studies to assess the replicability of the results and identified five robust novel genetic association signals implicating mTOR (mammalian target of rapamycin) signalling, telomere maintenance and spindle assembly genes in IPF risk.
Project description:Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.
Project description:Idiopathic pulmonary fibrosis (IPF) is a disease related to AT2 cell. We used flow cytometry to analyze the epithelial component of donor and IPF lungs. From the live cells, we first excluded the CD31PosCD45Pos and then selected the EPCAMPos cells for further analysis using the human AT2 cell marker HTll-280 and the surface marker PD-L1. Our data indicate that, the bona fide differentiated AT2 cells (HTll-280High PD-L1Neg), were drastically reduced in the context of IPF. More interestingly, the number of HTll-280Low/Neg PD-L1High was drastically increased, suggesting that HTll-280Low PD-L1High epithelial cells could represent a pool of progenitors linked to the deficient AT2 lineage. The aim of this experiment is further characterization of AT2 and PDL1+ cells in donor and IPF.
Project description:Genetic interactions have been reported to underlie phenotypes in a variety of systems, but the extent to which they contribute to complex disease in humans remains unclear. In principle, genome-wide association studies (GWAS) provide a platform for detecting genetic interactions, but existing methods for identifying them from GWAS data tend to focus on testing individual locus pairs, which undermines statistical power. Importantly, a global genetic network mapped for a model eukaryotic organism revealed that genetic interactions often connect genes between compensatory functional modules in a highly coherent manner. Taking advantage of this expected structure, we developed a computational approach called BridGE that identifies pathways connected by genetic interactions from GWAS data. Applying BridGE broadly, we discover significant interactions in Parkinson's disease, schizophrenia, hypertension, prostate cancer, breast cancer, and type 2 diabetes. Our novel approach provides a general framework for mapping complex genetic networks underlying human disease from genome-wide genotype data.
Project description:The aim of the current study is to find plasma-based biomarker candidates for Idiopathic Pulmonary Fibrosis (IPF). Incidence of IPF seems to be increasing in Europe and there is significant mortality associated with IPF. There are no sensistive biomarkers for IPF and diagnosis is entirely clinical and/or histopathological which is often delayed. Minimally invasive biomarkers of IPF would be expected to aid clinicians perfrom early diagnosis of IPF enabling better management of the disease.