key: cord-0257570-29fbqgyw
authors: Allen, R. J.; Oldham, J. M.; Jenkins, D. A.; Leavy, O. C.; Guillen-Guio, B.; Melbourne, C. A.; Ma, S.-F.; Jou, J.; Kim, J. S.; CleanUP-IPF Investigators of the Pulmonary Trials Cooperative,; Fahy, W. A.; Oballa, E.; Hubbard, R. B.; Navaratnam, V.; Braybrooke, R.; Saini, G.; Roach, K. M.; Tobin, M. D.; Hirani, N.; Whyte, M. K.; Kaminski, N.; Zhang, Y.; Martinez, F. J.; Linderholm, A. L.; Adegunsoye, A.; Strek, M. E.; Maher, T. M.; Molyneaux, P. L.; Flores, C.; Noth, I.; Jenkins, R. G.; Wain, L. V.
title: Genome-wide analysis of longitudinal lung function and gas transfer in individuals with idiopathic pulmonary fibrosis
date: 2022-03-30
journal: nan
DOI: 10.1101/2022.03.28.22272832
sha: a9fc7721f70cde15be176a357f5bfaa3ca53307c
doc_id: 257570
cord_uid: 29fbqgyw

Background: Idiopathic pulmonary fibrosis (IPF) is an incurable disease characterised by progressive scarring of the lungs. This leads to the lungs becoming stiffer, reducing lung capacity, and impeding gas transfer. We aimed to identify genetic variants associated with either declining lung capacity or gas transfer after diagnosis of IPF. Methods: We performed a genome-wide meta-analysis of longitudinal measures of forced vital capacity (FVC) and diffusing capacity for lung of carbon monoxide (DLco) in individuals diagnosed with IPF from three studies. Suggestively significant variants were investigated further in an additional study. Variants were defined as significantly associated if they had a meta-analysis p<5x10-8, had consistent direction of effects across all studies and were nominally significant (p<0.05) in each study. Findings: 1,048 individuals with measures of longitudinal FVC and 729 individuals with longitudinal measures of DLco passed quality control. In total, 4,560 measures of FVC and 2,795 measures of DLco and over 7 million genetic variants were included in the analysis. One variant located in an antisense RNA gene for Protein Kinase N2 (PKN2) showed a genome-wide significant association with FVC decline (-140 ml/year per risk allele, 95% CI [-180, -100], p=9.14x10-12). Interpretation: These results identify a possible druggable target involved in promoting IPF disease progression. Funding: Action for Pulmonary Fibrosis, Medical Research Council, Wellcome Trust, National Institute of Health/National Heart, Lung and Blood Institute

Idiopathic pulmonary fibrosis (IPF) is a devastating disease where the lungs become scarred, this scarring leads to a reduced lung capacity, poorer rates of gas transfer and is eventually fatal. However, disease progression is highly variable and it is not clear why this is. To date, genome-wide association studies (GWAS) have identified 20 genetic loci associated with susceptibility to IPF. These genetic loci implicate genes involved with host defence, regulation of TGFβ signalling, telomere maintenance, cell-cell adhesion and spindle assembly as important biological processes involved in the pathogenesis of IPF. The GWAS variant with the strongest effect on disease risk is found in the promoter region of the MUC5B gene (rs35705950). Generally, the variants associated with IPF susceptibility show little or no association with disease progression, apart from the risk allele at rs35705950 which has been reported as having an association with improved survival times.

Although genetic variants associated with disease risk have been widely studied, little has been reported to investigate the effect of genetics on progression of IPF. Here we present a GWAS of progressive IPF by identifying genetic variants associated longitudinal measures of lung health after diagnosis of IPF. We identify a genetic locus associated with a more rapid decline in lung capacity that lies in the RNA antisense gene of PKN2.

The novel genetic locus associated with a more rapid decline in lung capacity in individuals with IPF implicates a Rho/RAC effector protein. Effective treatments for IPF are desperately needed. There are currently PKN2 inhibitors under development meaning this analysis highlights a potential therapeutic target for IPF. We also show the genetic determinants of IPF progression appear to be distinct from those that drive IPF susceptibility.

Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease characterised by an aberrant response to lung injury leading to the deposit of scar tissue in the lung alveoli. IPF has a prevalence of around 50 per 100,000 individuals and is more common in men, the elderly and those of European ancestry.

As the disease progresses, the scarring spreads throughout the lung. This scarring makes the lungs stiffer, making it more difficult to breathe and leading to reduced lung capacity. The scar tissue also impedes gas transfer in and out of the bloodstream. This decrease in lung health leads to a poorer quality of life and eventually death with half of individuals dying within 3 to 5 years of diagnosis. Two measures of lung health are commonly used to monitor disease progression in individuals with IPF. These are forced vital capacity (FVC, i.e. the total volume of air that can be expired measured through spirometry) and the diffusing capacity for lung of carbon monoxide (DLco, i.e. a measure of how much gas can pass between the air sacs and bloodstream).

Generally, both FVC and DLco decline over time in individuals with IPF. However, rates of lung function decline are highly variable between individuals with some individuals experiencing rapid decline and shorter survival times, while others experience relatively stable lung function and live for many years after diagnosis 1 .

There are many known genetic and environmental risk factors for IPF. Studies of sporadic and familial IPF have identified genetic risk factors that implicate host defence (such as mucus and pulmonary surfactant regulation), signalling (particularly regulation of TGFβ signalling), cell-cell adhesion (such as desmoplakin which plays a role in structural integrity of the epithelium), telomere maintenance (with IPF cases having shorter telomeres than age-matched controls), and spindle assembly as important processes in disease risk [2] [3] [4] [5] [6] [7] .

Drug targets with supporting genetic evidence are twice as likely to be successful during drug development 8 . Little is known about genetic determinants of disease progression and identifying targets that modify disease process, rather than predisposing to disease, might yield therapeutic benefit.

We aimed to identify biological processes involved in disease progression by performing the first genome-wide association study (GWAS) of lung function and gas transfer decline in individuals with IPF.

For this study we utilised a two-stage design. Firstly, variants from across the genome were tested for their association with longitudinal FVC and DLco separately in discovery GWASs. Variants showing evidence of being associated with rate of change of FVC or DLco in the discovery GWAS were then analysed in an independent analysis and variants reaching genome-wide significance (with support from all studies) were reported. Full summary statistics for the FVC and DLco genomewide meta-analyses can be accessed from https://github.com/genomicsITER/PFgenetics.

For the discovery GWAS, we utilised longitudinal measures of FVC and DLco from IPF cases from three previously described studies (named as US, UK, UUS). is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The US study 4 (referred to as the "Chicago study" in some previous IPF GWAS) had three study centres that collected longitudinal data, namely the UC (University of Chicago), UPMC (University of Pittsburgh Medical Centre) and COMET (Correlating Outcomes with biochemical Markers to Estimate Time-progression) centres. The COMET study did not record DLco. Individuals were genotyped using the Affymetrix 6.0 SNP array. The UK study 9 had four centres that collected longitudinal data, namely the Brompton, PROFILE (Prospective Study of Fibrosis in the Lung Endpoints), Edinburgh and TLF (Trent Lung Function) centres. Individuals were genotyped using the Affymetrix UK BiLEVE array.

Six centres in the UUS study 5 collected longitudinal data, namely ACE (AntiCoagulant Effectiveness in Idiopathic Pulmonary Fibrosis), Brompton, Chicago, Nottingham, PANTHER (Prednisone, Azathioprine, and N-Acetylcysteine for Pulmonary Fibrosis), and UCD (University of California, Davis) centres. The ACE and PANTHER trials did not record DLco. Individuals were genotyped using the Affymetrix UK Biobank array.

For the follow-up stage, the CleanUP-IPF (Study of Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in Idiopathic Pulmonary Fibrosis) study 10 was used. As CleanUP-IPF individuals were followed-up for a shorter time period than in the other three studies (up to three measures of FVC and DLco over two years), the CleanUP-IPF study was selected for the follow-up analyses and was not included in the discovery GWAS. Individuals were genotyped using the Affymetrix UK Biobank array (Supplement).

All studies were imputed using the Haplotype Reference Consortium 11 , had appropriate ethics approval and diagnosed cases using ATS/ERS guidelines 12, 13 .

For quality control, we excluded individuals who failed Affymetrix genotyping quality measures, were not IPF cases, where their genetic sex did not match their recorded sex at birth, were heterozygosity outliers, non-European ancestry based on genetic principal components, duplicates and up to 2 nd degree related individuals. We only included individuals with at least two longitudinal measures. Where duplicates or related individuals were identified, the individual with the more complete phenotype data was kept (where this was the same, the individual from the smaller study was kept).

In our analysis we took enrolment to the study as a proxy for time of diagnosis. Some historical measures of FVC and DLco were available, however we excluded measures that were more than a year before enrolment. As most centres only recorded longitudinal measures for 3-5 years, to reduce biases in fitting longitudinal models with sparse data at later time points, we only included FVC and DLco measures taken within 3 years of enrolment. We only included variants with a minor allele frequency (MAF) greater than 1%.

We performed genome-wide analyses using a longitudinal linear mixed model with random slope and intercept with a (Time×SNP) interaction term and adjusting for age, sex, the first 10 genetic principal components (to account for population stratification) and study centre, as follows:

. CC-BY 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Where e and u are normally distributed random variables for level 1 and level 2 respectively. SNP was the genetic dosage for that variant (i.e. equal to 0 for individuals with two copies of the reference allele, 1 for heterozygotes and 2 for individuals with two copies of the effect allele), Time was the time in years after enrolment that the measure was taken, Sex was coded as 1 for males and 0 for females, PC1 to PC10 were the first 10 genetic principal components (included to adjust for population stratification) and Centre was a categorical variable for each study centre. Age was treated as a time varying covariate and centred on 72 (the median age of individuals at baseline). As we are interested in whether the genetic variant effects the rate of change of FVC or DLco, our effect estimate of interest is γ11.

The genome-wide discovery analysis was performed in each of the three studies (US, UK and UUS) separately and results were meta-analysed across studies using a fixed effect inverse variance weighted meta-analysis using the METAL software 14 . Genomic-control was applied to the metaanalysis results where λ>1. Only variants that were included in at least two of the studies were included in the meta-analysis.

Independent variants were followed-up in the CleanUP-IPF study if they reached a suggestive significance threshold in the discovery meta-analysis (p<5×10 −6 ), had consistent direction of effects and reached nominal significance (p<0.05) in each of the contributing GWAS studies. Conditional analyses were performed using GCTA-COJO to identify if there were multiple independent association signals at each association locus (Supplement).

Variants were defined as significantly associated with FVC or DLco if they were genome-wide significant when meta-analysing across all studies (p<5×10 −8 ), had consistent direction of effects and reached nominal significance (p<0.05) in each of the contributing studies.

Credible sets were calculated for each associated risk signal to generate a set of variants that were 95% certain to contain the true causal variant (under the assumption there is only one causal variant and that we have measured it, Supplement).

To identify putative causal genes from association signals we performed the following analyses to prioritise genes of interest:

1. Nearest gene: The nearest gene is often found to be the gene of interest an association signal 15 , we therefore included nearest gene as part of our gene prioritisation analyses. 2. Annotation: To determine the functional annotation of the variants in the credible sets we used VEP 16 .

To determine if the association signals were associated with gene expression, we investigated whether the variants in the credible sets were associated with gene expression using publicly available eQTL resources; eQTLgen 17 is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Variants in the credible set were investigated for whether they had been previously reported as associated with any other trait in previous GWAS (Supplement). We also investigated whether these variants showed an association with changes in lung function in the general population (Supplement) and investigated the effect these variants had on IPF susceptibility in a GWAS of 4,125 IPF cases vs 20,464 controls 7 . Variants previously reported as associated with IPF susceptibility were investigated for their effect on FVC and DLco decline.

Finally, the combined effect of multiple variants in a gene and enrichment in biological pathways was tested using Vegas2 24 (Supplement).

To investigate variants associated with either FVC or DLco decline further, we performed the following sensitivity analyses: 1. Short-term progression: We repeated the longitudinal mixed model analysis only including data within 1-year of diagnosis. 2. Clinical utility: To assess the clinical utility of associated variants we calculated the 1-year trend of FVC for each individual (in terms of %change) and classified individuals as "progressive" if they had a 1 year decline in FVC≥10% or died within the first year. We then fit a logistic regression model to test the association between the genetic variant and this binary trait (Supplement). 3. Non-linear effects: We investigated non-linear effects for time by allowing for polynomial time and interaction effects (Supplement). 4. Baseline lung function: We tested whether the variant was associated with the first measure of FVC or DLco using a linear regression model (Supplement). 5. Effect in general population: Using 32,013 unrelated European individuals in UK Biobank, we tested whether the variant was associated with a decline of FVC, forced expiratory volume in 1 second (FEV1) or is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted March 30, 2022. ; https://doi.org/10.1101/2022.03.28.22272832 doi: medRxiv preprint 7. Age at baseline: To investigate whether the variant was associated with age at baseline using a linear regression model (Supplement). 8. Treatment response: Longitudinal analyses were performed allowing for an interaction between treatment, genetic variant and time (Supplement). Analyses were performed using the CleanUp-IPF study and the effect of associated genetic variants on nintedanib, pirfenidone and anti-microbial therapy response were investigated.

In all circumstances, sensitivity analyses were performed in the UK, UUS, US and CleanUP-IPF studies separately and then meta-analysed across studies.

The funding source had no role in the analysis, writing of the publication or decision to submit for publication.

There Table 1 , Supplementary Figures 2 and 3 ). is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted March 30, 2022. ; https://doi.org/10.1101/2022.03.28.22272832 doi: medRxiv preprint There were 7,611,174 variants included in the FVC longitudinal analysis and 7,536,843 variants in the DLco longitudinal analysis (Figure 1 and Supplementary Figure 4) . There were 24 independent variants in the FVC analysis and 30 independent variants in the DLco analysis reaching suggestive significance that were investigated further in the CleanUP-IPF dataset (Supplementary Table 1 Figure  5) . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint One variant, rs115982800, met genome-wide significance (p=3.68×10 −8 ) in the discovery GWAS meta-analysis with consistent direction of effects and nominal significance (p<0.05) in all discovery cohorts (Figure 2) . This variant was also significant in CleanUP-IPF (p=0.007) with a consistent effect. Following meta-analysis of the discovery GWAS and CleanUP-IPF, this variant was associated with an annual FVC decline of 140ml/year per copy of the risk allele A (95% CI [−180, −100], p=9.14×10 −12 , Supplementary Figure 6) . The credible set for this association signal contained seven genetic variants with three highly correlated variants accounting for 25.7% of the posterior probability each (Supplementary Table 2 ). All of these variants were located on chromosome 1 upstream of the Protein Kinase N2 gene (PKN2) in introns of the antisense-RNA PKN2-AS1 (Figure 3) . One of the three variants in the credible set with high posterior probability (rs115590681) was located in an open chromatin region. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Sensitivity analyses showed that the association with rs115982800 remained when restricting measurements to one year after diagnosis and showed an association with clinically defined "progressive IPF" (Supplementary Figure 7) . There was evidence of non-linear effects in the UUS study only (Supplementary Figure 7) . The variant rs115982800 showed no association with survival times, however incorporating survival as part of a joint model did reduce the estimated effect of rs115982800 on longitudinal FVC (Supplementary Figures 7 and 8) . The variant showed no association with baseline FVC, baseline DLco or with age at baseline (Supplementary Figure 7) . There was no evidence of a treatment interaction between rs115982800 and response to nintedanib, pirfenidone or anti-microbial therapy (Supplementary Table 3) , however the rs115982800 variant does show an association with Dothiepin medication in UK Biobank. The variant shows no association with IPF risk or with lung function decline in UK Biobank (Supplementary Table 4) .

Given that the genome-wide significant association signal may be involved in long-distance gene regulation through an open chromatin, we performed gene-prioritisation on all genes within 3Mb of the sentinel variant. PKN2 was the nearest gene and the location of the association signal in an antisense-RNA gene for PKN2 implicated PKN2 as a gene of interest. The fragment of DNA that contains the longitudinal FVC association signal appears to physically interact with many other parts of the DNA across multiple tissues and cell-types (Supplementary Figure 9) . Both PKN2 and GBP5 are included on a diagnostic panel of 44 autoinflammatory diseases (which includes interstitial lung disease autoinflammatory disorders) but are not directly linked to a specific ILD (Supplementary Table 5 ). Rare variants in both PKN2 (% predicted FEV1) and LMO4 (FEV1 and FVC) show a suggestive association (p<5×10 −6 ) with lung function and rare variants in HFM1 show an association with IGF-1 levels (which is known to promote pulmonary fibrosis) (Supplementary Table 5 ). The FVC association signal did not colocalise with expression of any genes and no genes showed a relevant phenotype when knocked out in mice models (Supplementary Figure 10 and Supplementary Table  5 ). Collectively, PKN2 had the strongest evidence of being the gene that this association signal acts through (Supplementary Figure 11) .

Variants previously reported as associated with IPF risk did not show an association with FVC or DLco decline (Supplementary Table 6 ).

When utilising the genome-wide summary statistics, no genes or pathways were found to be significantly enriched in genetic associations with FVC or DLco decline after Bonferroni corrections for multiple testing (Supplementary Tables 7 and 8 and Supplementary Figure 12) . The gene TMEM105 showed a borderline significant association with FVC decline in the gene-based analysis, however this gene includes variants in the FVC decline association signal on chromosome 17 that was not supported in the analysis in CleanUP-IPF (Supplementary Table 1 ). "GO:0051302_regulation_of_cell_division" was the only pathway term with empirical p<10 −4 in the FVC or DLco analysis (genes in this pathway were enriched with DLco decline, p=8.80×10 −5 ). This pathway contained 271 genes, many known to be associated with IPF risk including growth factor regulating genes (especially for TGFβ signalling), spindle assembly genes and WNT signalling (Supplementary Table 8 ).

By performing the first genome-wide association study of decline in lung health in individuals diagnosed with IPF, we have identified a genetic variant associated with declining lung capacity in individuals with IPF which lies within an antisense RNA for PKN2. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted March 30, 2022. ; https://doi.org/10.1101/2022.03.28.22272832 doi: medRxiv preprint PKN2 (Protein Kinase N2), which had the strongest evidence of being the causal gene for the association signal, is a Rho/RAC effector protein known to regulate cell cycle progression, actin cytoskeleton assembly, cell migration, cell adhesion, tumour cell invasion and transcription activation signalling processes 26 . RhoA is associated with IPF susceptibility through regulating TGFβ signalling and other RhoGEFs for RhoA have been implicated in GWAS of IPF risk (for example AKAP13) 9 . Protein analyses have shown PKN2 is linked to fibrotic processes in chronic atrial fibrillation 27 . IPF is a chronic lung disease characterised by fibroblast proliferation, activation and differentiation into myofibroblasts. Recent studies have shown mouse embryonic fibroblasts to depend on PKN2 for proliferation, growth and motility 28 , and cancer associated fibroblasts to depend on PKN2 for activation, differentiation and motility 29 . In addition, PKN2 has been suggested to play critical roles in actin stress fibre formation in NIH3T3 cells 30 . PKN2 inhibitors are currently in development for cancer therapy 31 and the PKN2 inhibitor Fostamatinib has been suggested as a drug repurposing candidate for the treatment of acute respiratory distress syndrome in severe COVID-19 patients 32 .

The variant we identified as associated with FVC decline also shows an association with Dothiepin medication. Dothiepin is an anti-depressant that has previous been reported as a potential risk factor for IPF 33 .

There are a number of strengths to this study. Firstly, the identified association signal shows a consistent association and effect size estimate across four independent studies, suggesting this variant is robustly associated with FVC decline in individuals with IPF. Secondly, sensitivity analyses showed that the signal remained when restricting FVC measurements to the first year after diagnosis and the variant also showed an association with clinically defined "progressive IPF". Thirdly, by applying a mixed model, we were able to maximise the power of the analysis by incorporating over 5,000 measures of FVC and 3,000 measures of DLco. We assumed a linear mixed effects model as we were not aiming to model lung function trajectories in IPF individuals, rather we were interested in genetic variants associated with declining FVC and DLco. Although it is unlikely that FVC or DLco trajectories follow a linear trend, assuming linearity simplifies the model (increasing power and aiding model convergence) while still being able to distinguish between individuals with a generally declining trend against those with a relatively stable disease. Sensitivity analyses did show a nominal association with non-linear effects though the effect size was small and a significant non-linear effect was only observed in one study.

There are also limitations to the analysis. Firstly, our model assumes non-informative dropout which is unlikely to be true, especially for DLco. Sensitivity analyses showed that although rs115982800 is not associated with survival times, incorporating censoring due to death through a joint model does remove the association with longitudinal FVC meaning censoring due to death may have some effect on the analysis. The joint model coefficients are estimated together and it is possible the effect of the variant is being distributed across the longitudinal and time-to-event parts of the model. This is especially true given the complexity of the joint model and if rs115982800 explains little of the variance. Furthermore, rs115982800 showed consistent effect size estimates across all four studies with varying levels of censoring, including the CleanUP-IPF study where there was very little censoring, suggesting this association is not purely caused by informative dropout. Secondly, the credible set included a variant lying in an open chromatin region and multiple regions were significant in the Hi-C analyses. This suggests the signal could be involved in regulating a large number of genes in a tissue or cell-specific manner. Thirdly, to reduce confounding we only included . CC-BY 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint European individuals meaning we may miss genetic variants associated with progressive IPF. The rs115982800_A allele is low frequency in most populations and rare in African or Asian populations 34 . Finally, although we have maximised the available power of the analysis by incorporating multiple measurements, larger studies are needed to detect variants with smaller effect sizes or for rarer variants associated with lung function decline in individuals with IPF. The smaller sample size analysis means there was lower statistical power in the DLco analysis, which may explain why no association signals were identified.

In summary, by utilising thousands of lung health measures in individuals we have shown a genetic association with worsening lung capacity in IPF. These results highlight the role of protein kinase N2 in disease progression and may aid the development of new and desperately needed treatments. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint 

L Wain reports research funding from GlaxoSmithKline and Orion Pharma, and consultancy for Galapagos (all outside of the submitted work). J Oldham reports personal fees from Boehringer Ingelheim, Genentech, United Therapeutics, AmMax Bio and Lupin pharmaceuticals unrelated to the submitted work. G Jenkins is a trustee of Action for Pulmonary Fibrosis and reports personal fees from Astra Zeneca, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Chiesi, Daewoong, Galapagos, Galecto, GlaxoSmithKline, Heptares, NuMedii, PatientMPower, Pliant, Promedior, Redx, Resolution Therapeutics, Roche, Veracyte and Vicore. A Adegunsoye reports personal fees from Boehringer Ingelheim, and Genentech, unrelated to the submitted work. N Kaminski served as a consultant to Boehringer Ingelheim, Third Rock, Pliant, Samumed, NuMedii, TheraVance, Indalo, LifeMax, Three Lake Partners, Optikira, Astra Zeneca, Rohbar, Astra-Zeneca, CSL-Behring, Galapagos and Thyron over the last 3 years; reports Equity in Pliant and Thyron; grants from Veracyte and Boehringer Ingelheim; non-financial support from MiRagen and Astra Zeneca and has IP on novel biomarkers and therapeutics in IPF licensed to Biotech. W Fahy and E Oballa are employees of GlaxoSmithKline.

This research was conducted using previously published work with appropriate ethics approval. The PROFILE study (which provided samples for the UK and UUS studies) had institutional ethics approval at the University of Nottingham (NCT01134822 -ethics reference 10/H0402/2) and Royal Brompton and Harefield NHS Foundation Trust (NCT01110694 -ethics reference 10/H0720/12 is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint 

Full summary statistics for the FVC and DLco genome-wide meta-analyses can be accessed from https://github.com/genomicsITER/PFgenetics. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted March 30, 2022. ; https://doi.org/10.1101/2022.03.28.22272832 doi: medRxiv preprint

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