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BackgroundConsiderable clinical heterogeneity in Idiopathic Pulmonary Fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes could allow for a biomarker-driven personalised medicine approach in IPF. To improve our understanding of the pathogenesis of IPF by identifying clinically distinct groups of patients with IPF that could represent distinct disease endotypes.MethodsWe co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier was developed and validated using three additional independent datasets (total 194 IPF cases).FindingsWe identified three clusters of IPF patients with statistically significant differences in lung function (P=0·009) and mortality (P=0·009) between groups. Gene enrichment analysis implicated dysregulation of mitochondrial homeostasis, apoptosis, cell cycle and innate and adaptive immunity in the pathogenesis underlying these groups. We developed and validated a 13-gene cluster classifier that predicted mortality in IPF (high-risk clusters vs low-risk cluster: hazard ratio= 4·25, 95% confidence interval= [2·14, 8·46], P=3·7×10−5).InterpretationWe have identified blood gene expression signatures capable of discerning groups of IPF patients with significant differences in survival. These clusters could be representative of distinct pathophysiological states, which would support the theory of multiple endotypes of IPF. Although more work must be done to confirm the existence of these endotypes, our classifier could be a useful tool in patient stratification and outcome prediction in IPF.FundingL.V.W. holds a GSK/British Lung Foundation Chair in Respiratory Research (C17-1). R.G.J. is supported by a National Institute for Health Research (NIHR) Research Professorship (NIHR reference RP-2017-08-ST2-014). P.L.M. is supported by an Action for Pulmonary Fibrosis Mike Bray fellowship. T.M. Maher is supported by a National Institute for Health Research Clinician Scientist Fellowship (CS-2013-13-017) and a British Lung Foundation Chair in Respiratory Research (C17-3). I.N. is supported by a National Heart, Lung, and Blood Institute (NHLBI) grant (R01HL145266). D.A.S. is supported by NHLBI grants (UG3HL151865, R01HL097163, P01HL092870, X01HL134585 and UH3HL123442) and a United States Department of Defense grant (W81XWH-17-1-0597). The GSE110147 study was supported by the Roche Multi Organ Transplant Academic Enrichment Fund, Lawson Research Institute Internal Research Fund and Western Strategic Support for CIHR Success, Seed Grant. The research was partially supported by the NIHR Leicester Biomedical Research Centre; the views expressed are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR, or the Department of Health.Putting research into contextEvidence before this studyWe searched PubMed Central in February 2020 with the search terms “idiopathic pulmonary fibrosis”, “gene expression” and “cluster analysis” with no restrictions on publication date or language. Previous transcriptomic cluster analyses have found that differences in gene expression can be used to predict disease status, severity and outcome in IPF. A previous transcriptomic prognostic biomarker has been developed that can predict outcome in IPF using blood expression data from 52 genes.Added value of this studyBy utilising new methods of data co-normalisation and machine learning, we were able to combine multiple publicly available datasets and perform one of the largest transcriptomic studies in IPF to-date with a total of 416 IPF cases across the discovery and validation stages. We identified three clusters of patients, one of which appeared to contain, on average, the healthiest subjects with favourable lung function and survival over time. These clusters were defined using expression from groups of genes that were significantly enriched for many different biological pathways and processes, including metabolic changes, apoptosis, cell cycle and immune response, and so could be representative of distinct pathophysiological states. Additionally, we developed a 13-gene expression-based classifier to assign individuals with IPF to one of the clusters and validated this classifier using three additional independent cohort of IPF patients (totalling 194 IPF cases). As the clusters were associated with survival, our classifier could potentially be used to predict outcome in IPF.Implications of all the available evidenceOur findings support the hypothesis that the disease consists of multiple endotypes. The clusters identified in this study could provide some valuable insight into the underlying biological processes that may be driving the considerable clinical heterogeneity in IPF. With further development, our gene expression-based classifier could be a useful tool for patient stratification and outcome prediction in IPF.

Reversion of islet autoimmunity (IA) may point to mechanisms that prevent IA progression. We followed 199 individuals who developed IA during the Diabetes Autoimmunity Study in the Young. Untargeted metabolomics was performed in serum samples following IA. Cox proportional hazards models were used to test whether the metabolites (2,487) predicted IA reversion: two or more consecutive visits negative for all autoantibodies. We conducted a principal components analysis (PCA) of the top metabolites; |hazard ratio (HR) >1.25| and nominal P < 0.01. Phosphatidylcholine (16:0_18:1(9Z)) was the strongest individual metabolite (HR per 1 SD 2.16, false discovery rate (FDR)-adjusted P = 0.0037). Enrichment analysis identified four clusters (FDR P < 0.10) characterized by an overabundance of sphingomyelin (d40:0), phosphatidylcholine (16:0_18:1(9Z)), phosphatidylcholine (30:0), and l-decanoylcarnitine. Overall, 63 metabolites met the criteria for inclusion in the PCA. PC1 (HR 1.4, P < 0.0001), PC2 (HR 0.85, P = 0.0185), and PC4 (HR 1.28, P = 0.0103) were associated with IA reversion. Given the potential influence of diet on the metabolome, we investigated whether nutrients were correlated with PCs. We identified 20 nutrients that were correlated with the PCs (P < 0.05). Total sugar intake was the top nutrient. Overall, we identified an association between phosphatidylcholine, sphingomyelin, and carnitine levels and reversion of IA.

Environmental factors including viruses, diet, and the metabolome have been linked with the appearance of islet autoimmunity (IA) that precedes development of type 1 diabetes (T1D). We measured global DNA methylation (DNAm) and untargeted metabolomics prior to IA and at the time of seroconversion to IA in 92 IA cases and 91 controls from the Diabetes Autoimmunity Study in the Young (DAISY). Causal mediation models were used to identify seven DNAm probe-metabolite pairs in which the metabolite measured at IA mediated the protective effect of the DNAm probe measured prior to IA against IA risk. These pairs included five DNAm probes mediated by histidine (a metabolite known to affect T1D risk), one probe (cg01604946) mediated by phostidyl choline p-32:0 or o-32:1, and one probe (cg00390143) mediated by sphingomyelin d34:2. The top 100 DNAm probes were over-represented in six reactome pathways at the FDR &lt, 0.1 level (q = 0.071), including transport of small molecules and inositol phosphate metabolism. While the causal pathways in our mediation models require further investigation to better understand the biological mechanisms, we identified seven methylation sites that may improve our understanding of epigenetic protection against T1D as mediated by the metabolome.

Idiopathic pulmonary fibrosis (IPF) is an incurable genetic disease that affects 5 million people worldwide. The gain-of-function MUC5B promoter variant rs35705950 is the dominant genetic risk factor for IPF, yet has a low penetrance. This raises the possibility that other genes and transcripts affect the penetrance of MUC5B. Previously, we have shown that the concentration of Muc5b in bronchoalveolar epithelia is directly associated with the extent and persistence of bleomycin-induced lung fibrosis in mice. In this study, we investigated whether bleomycin-induced lung injury is Muc5b dependent in genetically divergent strains of mice. Specifically, mice from the eight Diversity Outbred (DO) founders were phenotyped for Muc5b expression and lung fibrosis 3 wk after intratracheal bleomycin administration. Although we identified strains with low Muc5b expression and minimal lung fibrosis (CAST/EiJ and PWK/PhJ) and strains with high Muc5b expression and extensive lung fibrosis (NZO/H1LtJ and WSB/EiJ), there also were strains that did not demonstrate a clear relationship between Muc5b expression and lung fibrosis (129S1/SvlmJ, NOD/ShiLtJ, and C57BL/6J, A/J). Hierarchical clustering suggests that other factors may work in concert with or potentially independent of Muc5b to promote bleomycin-induced lung injury and fibrosis. This study suggests that these strains and their recombinant inbred crosses may prove helpful in identifying the genes and transcripts that interact with Muc5b and cause lung fibrosis.

Both sarcoidosis and chronic beryllium disease (CBD) are granulomatous diseases with overlapping clinical features, however, their clinical courses differ. CBD may have slow clinical progression and rarely resolves while sarcoidosis has variable progression and may resolve depending on the stage of the disease [1]. These commonalities and differences imply differences in antigen(s), and potentially clearance and persistence. Alveolar macrophages play an important role in this process driving innate [2] and adaptive immune responses [3]. Furthermore, subpopulations of macrophages may promote granulomatous inflammation and resolution of lung injury [4], key aspects of sarcoidosis and CBD. Using single-cell RNA sequencing (scRNA-seq), we explored the common and unique pathways between progressive (SarcP) and remitting (SarcR) sarcoidosis as well as CBD and sarcoidosis, focusing on macrophages and macrophages subpopulations (recruited versus resident). Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Dr. Lindner has nothing to disclose. Conflict of Interest: Dr. Liao has nothing to disclose. Conflict of Interest: Dr. Atif has nothing to disclose. Conflict of Interest: Dr. Mould has nothing to disclose. Conflict of Interest: Dr. Konigsberg has nothing to disclose. Conflict of Interest: Dr. Fu has nothing to disclose. Conflict of Interest: Dr. Davidson has nothing to disclose. Conflict of Interest: Dr. Li has nothing to disclose. Conflict of Interest: Dr. Fontenot reports grants from National Institutes of Health (NIH), during the conduct of the study. Conflict of Interest: Dr. Maier reports grants from National Institutes of Health, during the conduct of the study; grants from National Institutes of Health, grants from University of Cincinnati under a Mallinckrodt Foundation, grants from MNK14344100, grants from ATYR1923-C-002, outside the submitted work; and Dr. Maier is a member of the FSR Scientific Advisory Board. She does not receive any compensation for this activity. Conflict of Interest: Dr. Yang reports grants from NIH, during the conduct of the study and personal fees from Eleven P15, outside the submitted work. In addition, Dr. Yang has a patent Circulating Biomarkers of Preclinical Pulmonary Fibrosis pending.

A subset of patients with hypersensitivity pneumonitis (HP) develop lung fibrosis that is clinically similar to idiopathic pulmonary fibrosis (IPF). To address the aetiological determinants of fibrotic HP, we investigated whether the common IPF genetic risk variants were also relevant in study subjects with fibrotic HP. Our findings indicate that common genetic variants in TERC, DSP, MUC5B and IVD were significantly associated with fibrotic HP. These findings provide support for a shared etiology and pathogenesis between fibrotic HP and IPF.

Background Across complex traits, common variants explain only a modest amount of variance, with SNP-heritability consistently below heritability estimates from close relatives. Here, we examined the contribution of rare variant to tobacco use risk in up to 26,000 individuals of European ancestry in the Trans-Omics for Precision Medicine (TOPMed) program with whole genome sequence (WGS;~30X coverage).Method We grouped about 35 million genetic variants by their minor allele frequencies (MAF) and linkage disequilibrium (LD) and estimated SNP-heritability for age of smoking initiation (N = 14,747), cigarettes smoked per day (N = 15,425), smoking cessation (N = 17,871) and initiation (N = 26,340) using linear mixed model. Rare variant population structure is detected and adjusted for by permutation procedure. We estimated an upper bound for narrow-sense heritability for tobacco use using available pedigrees consisting of close relatives in TOPMed.Results Rare variants with MAF 0.1–0.01%, mostly from non-protein altering region, accounted for 26% of variation in age of initiation and 15% for cessation. Follow-up analysis indicated that about one-third of these rare variants contribtion is potentially confounded with rare variants structure even after adjusting for principal components. After further conservative adjustment of population structure, we estimated SNP-based heritability to be 0.21 (SE = 0.08) for age of initiation, 0.15 (0.06) for cigarettes per day, 0.21 (0.09) for cessation, and 0.24 (0.07) for initiation, 1.8–4.5 times higher than previous SNP-based estimates. Our pedigree-based upper-bound for SNP-based heritability ranged from 0.18–0.35.Conclusion The substantial contribution of rare variants for several smoking phenotypes sheds light on the missing heritability and genetic etiology of tobacco use. It also informs fine-mapping strategies since the majority of the rare variant contribution was located in non-coding regulatory regions.

Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2–4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation. We customized Illumina’s Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls. Epigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g. IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively. In summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections. Viral infections affect the body in many ways, including via changes to the epigenome, the sum of chemical modifications to an individual’s collection of genes that affect gene activity. Here, we analyzed the epigenome in blood samples from people with and without COVID-19 to determine whether we could find changes consistent with SARS-CoV-2 infection. Using a combination of statistical and machine learning techniques, we identify markers of SARS-CoV-2 infection as well as of severity and progression of COVID-19 disease. These signals of disease progression were present from the initial blood draw when first walking into the hospital. Together, these approaches demonstrate the potential of measuring the epigenome for monitoring SARS-CoV-2 status and severity. Konigsberg et al. profile DNA methylation in blood samples from SARS-CoV-2 cases and controls. The authors use machine learning to classify infected vs. non-infected individuals and predict clinical outcomes related to disease severity.

Epigenetic modifications are emerging as important regulatory mechanisms of gene expression in lung disease, given that they are influenced by environmental exposures and genetic variants, and that they regulate immune and fibrotic processes. In this review, we introduce these concepts with a focus on the study of DNA methylation and histone modifications and discuss how they have been applied to lung disease, and how they can be applied to sarcoidosis. This information has implications for other exposure and immunologically mediated lung diseases, such as chronic beryllium disease, hypersensitivity pneumonitis, and asbestosis.

An adverse intrauterine environment is associated with the future risk of obesity and type 2 diabetes. Changes in placental function may underpin the intrauterine origins of adult disease, but longitudinal studies linking placental function with childhood outcomes are rare. Here, we determined the abundance and phosphorylation of protein intermediates involved in insulin signaling, inflammation, cortisol metabolism, protein glycosylation, and mitochondrial biogenesis in placental villus samples from healthy mothers from the Healthy Start cohort. Using MANOVA, we tested the association between placental proteins and offspring adiposity (percent fat mass) at birth (n=109) and infancy (4-6mo, n=104), and adiposity, skinfold thickness, triglycerides, and insulin in children (4-6y, n=66). Placental IGF-1 receptor protein was positively associated with serum triglycerides in children. GSK3β phosphorylation at serine 9, a readout of insulin and growth factor signaling, and the ratio of phosphorylated to total JNK2 were both positively associated with midthigh skinfold thickness in children. Moreover, PGC-1α abundance was positively associated with insulin in children. In conclusion, placental insulin/IGF-1 signaling, PGC-1α, and inflammation pathways were positively associated with metabolic outcomes in 4-6-year-old children, identifying a novel link between placental function and long-term metabolic outcomes.

The G/T transversion rs35705950, located approximately 3 kb upstream of the MUC5B start site, is the cardinal risk factor for idiopathic pulmonary fibrosis (IPF). Here, we investigate the function and chromatin structure of this –3 kb region and provide evidence that it functions as a classically defined enhancer subject to epigenetic programming. We use nascent transcript analysis to show that RNA polymerase II loads within 10 bp of the G/T transversion site, definitively establishing enhancer function for the region. By integrating Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) analysis of fresh and cultured human airway epithelial cells with nuclease sensitivity data, we demonstrate that this region is in accessible chromatin that affects the expression of MUC5B. Through applying paired single-nucleus RNA- and ATAC-seq to frozen tissue from IPF lungs, we extend these findings directly to disease, with results indicating that epigenetic programming of the –3 kb enhancer in IPF occurs in both MUC5B-expressing and nonexpressing lineages. In aggregate, our results indicate that the MUC5B-associated variant rs35705950 resides within an enhancer that is subject to epigenetic remodeling and contributes to pathologic misexpression in IPF.

Molecular patterns and pathways in idiopathic pulmonary fibrosis (IPF) have been extensively investigated but few studies have assimilated multi-omic platforms to provide an integrative understanding of molecular patterns that are relevant in IPF. Herein, we combine coding and non-coding transcriptome, DNA methylome, and proteome from IPF and healthy lung tissue to identify molecules and pathways associated with this disease. RNA sequencing, Illumina MethylationEPIC array, and liquid chromatography-mass spectrometry (LC-MS) proteomic data were collected on lung tissue from 24 IPF cases and 14 control subjects. Significant differential features were identified using linear models adjusting for age and sex, inflation and bias where appropriate. Data Integration Analysis for Biomarker discovery using a Latent component method for Omics studies (DIABLO) was used for integrative multi-omic analysis. We identified 4,643 differentially expressed transcripts aligning to 3,439 genes, 998 differentially abundant proteins, 2,500 differentially methylated regions (DMRs), and 1,269 differentially expressed lncRNAs that were significant after correcting for multiple tests (false discovery rate [FDR]0.8) with MMP7. Therefore, using a systems biology approach, we have identified novel molecular relationships in IPF.

Background: Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent chemicals widely detected in women of reproductive age. Prenatal PFAS exposure is associated with adverse health outcomes in children. We hypothesized that DNA methylation changes may result from prenatal PFAS exposure and may be linked to offspring cardio-metabolic phenotype. Objectives: We estimated associations of prenatal PFAS with DNA methylation in umbilical cord blood. We evaluated associations of methylation at selected sites with neonatal cardio-metabolic indicators. Methods: Among 583 mother–infant pairs in a prospective cohort, five PFAS were quantified in maternal serum (median 27 wk of gestation). Umbilical cord blood DNA methylation was evaluated using the Illumina HumanMethylation450 array. Differentially methylated positions (DMPs) were evaluated at a false discovery rate (FDR)

Background DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits. Methods We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment. Results DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P −7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10−4; adolescence Penrichment = 2.10 × 10−7). Conclusions There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.

Rationale: Chronic hypersensitivity pneumonitis (CHP) is caused by an immune response to antigen inhalation and is characterized by variable histopathological and clinical features. A subset of subjects with CHP have usual interstitial pneumonia and appear to be clinically similar to subjects with idiopathic pulmonary fibrosis (IPF). Objectives: To determine the common and unique molecular features of CHP and IPF. Methods: Transcriptome analysis of lung samples from CHP (n = 82), IPF (n = 103), and unaffected controls (n = 103) was conducted. Differential gene expression was determined adjusting for sex, race, age, and smoking history and using false discovery rate to control for multiple comparisons. Measurements and Main Results: When compared with controls, we identified 413 upregulated and 317 downregulated genes in CHP and 861 upregulated and 322 downregulated genes in IPF. Concordantly upregulated or downregulated genes in CHP and IPF were related to collagen catabolic processes and epithelial development, whereas genes specific to CHP (differentially expressed in CHP when compared with control and not differentially expressed in IPF) were related to chemokine-mediated signaling and immune responsiveness. Using weighted gene coexpression network analysis, we found that among subjects with CHP, genes involved in adaptive immunity or epithelial cell development were associated with improved or reduced lung function, respectively, and that MUC5B expression was associated with epithelial cell development. MUC5B expression was also associated with lung fibrosis and honeycombing. Conclusions: Gene expression analysis of CHP and IPF identified signatures common to CHP and IPF, as well as genes uniquely expressed in CHP. Select modules of gene expression are characterized by distinct clinical and pathological features of CHP.

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive, fatal fibrotic interstitial lung disease. Few circulating biomarkers have been identified to have causal effects on IPF.MethodsTo identify candidate IPF-influencing circulating proteins, we undertook an efficient screen of circulating proteins by applying a two-sample Mendelian randomisation (MR) approach with existing publicly available data. For instruments, we used genetic determinants of circulating proteins which reside cis to the encoded gene (cis-single nucleotide polymorphisms (SNPs)), identified by two genome-wide association studies (GWASs) in European individuals (3301 and 3200 subjects). We then applied MR methods to test if the levels of these circulating proteins influenced IPF susceptibility in the largest IPF GWAS (2668 cases and 8591 controls). We validated the MR results using colocalisation analyses to ensure that both the circulating proteins and IPF shared a common genetic signal.ResultsMR analyses of 834 proteins found that a 1 sd increase in circulating galactoside 3(4)-l-fucosyltransferase (FUT3) and α-(1,3)-fucosyltransferase 5 (FUT5) was associated with a reduced risk of IPF (OR 0.81, 95% CI 0.74–0.88; p=6.3×10−7 and OR 0.76, 95% CI 0.68–0.86; p=1.1×10−5, respectively). Sensitivity analyses including multiple cis-SNPs provided similar estimates both for FUT3 (inverse variance weighted (IVW) OR 0.84, 95% CI 0.78–0.91; p=9.8×10−6 and MR-Egger OR 0.69, 95% CI 0.50–0.97; p=0.03) and FUT5 (IVW OR 0.84, 95% CI 0.77–0.92; p=1.4×10−4 and MR-Egger OR 0.59, 95% CI 0.38–0.90; p=0.01). FUT3 and FUT5 signals colocalised with IPF signals, with posterior probabilities of a shared genetic signal of 99.9% and 97.7%, respectively. Further transcriptomic investigations supported the protective effects of FUT3 for IPF.ConclusionsAn efficient MR scan of 834 circulating proteins provided evidence that genetically increased circulating FUT3 level is associated with reduced risk of IPF.

Objective Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Results We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.

BACKGROUND: Nasal (airway) epithelial methylation profiles have been associated with asthma, but the effects of such profiles on expression of distant cis-genes are largely unknown. RESEARCH QUESTION: To identify genes whose expression is associated with proximal and distal CpG probes (within 1 Mb), and to assess whether and how such genes are differentially expressed in atopic asthma. STUDY DESIGN AND METHODS: Genome-wide expression quantitative trait methylation (eQTM) analysis in nasal epithelium from Puerto Rican subjects (aged 9-20 years) with (n = 219) and without (n = 236) asthma. After the eQTM analysis, a Gene Ontology Enrichment analysis was conducted for the top 500 eQTM genes, and mediation analyses were performed to identify paths from DNA methylation to atopic asthma through gene expression. Asthma was defined as physician-diagnosed asthma and wheeze in the previous year, and atopy was defined as at least one positive IgE to allergens. Atopic asthma was defined as the presence of both atopy and asthma. RESULTS: We identified 16,867 significant methylation-gene expression pairs (false-discovery rate-adjusted P < .01) in nasal epithelium from study participants. Most eQTM methylation probes were distant (average distance, ∼378 kb) from their target genes, and also more likely to be located in enhancer regions of their target genes in lung tissue than control probes. The top 500 eQTM genes were enriched in pathways for immune processes and epithelial integrity and were more likely to have been previously identified as differentially expressed in atopic asthma. In a mediation analysis, we identified 5,934 paths through which methylation markers could affect atopic asthma through gene expression in nasal epithelium. INTERPRETATION: Previous epigenome-wide association studies of asthma have estimated the effects of DNA methylation markers on expression of nearby genes in airway epithelium. Our findings suggest that distant epigenetic regulation of gene expression in airway epithelium plays a role in atopic asthma.

Background: Chronic hypersensitivity pneumonitis (CHP) is caused by an immune response to antigen inhalation and is characterized by progressive pulmonary fibrosis. The histopathological and clinical features of CHP are variable, however, a subset of CHP patients have usual interstitial pneumonia and behave clinically similar to patients with idiopathic pulmonary fibrosis (IPF). To determine the common and unique molecular features of CHP and IPF, we conducted a transcriptome analysis of lung samples from CHP (N=82), IPF (N=103), and unaffected controls (N=103). Methods: Gene expression in lung tissue was determined adjusting for sex, race, age, explant site, and smoking history, and using false discovery rate (FDR) to control for multiple comparisons. Findings: When compared to controls, we identified 413 upregulated and 317 downregulated genes in CHP, and 861 upregulated and 322 downregulated genes in IPF. Concordantly up/down-regulated genes in CHP and IPF were related to collagen catabolic processes and epithelial development, whereas genes specific to CHP were related to chemokine-mediated signaling and immune responsiveness. Using weighted gene co-expression network analysis (WGCNA), we found that among subjects with CHP, genes involved in adaptive immunity or epithelial cell development were associated with improved or reduced lung function respectively, and that MUC5B expression was associated with epithelial cell development. MUC5B expression was also associated with lung fibrosis and honeycombing. Interpretation: Gene expression analysis of CHP and IPF identified signatures common to CHP and IPF, as well as genes uniquely expressed in CHP. Select modules of gene expression are characterized by distinct clinical and pathological features of CHP. Funding Statement: NHLBI (R01-HL097163, P01-HL092870, UH3-HL123442, and DoD W81XWH17-1-0597). Declaration of Interests: None of the authors report conflicts of interest relevant to this study. D.A.S. is the founder and chief scientific officer of Eleven P15, a company focused on the early diagnosis and treatment of pulmonary fibrosis. D.A.S. has an awarded patent (US patent no: 8,673,565) for the treatment and diagnosis of fibrotic lung disease. Ethics Approval Statement: This study conformed to the Declaration of Helsinki and was approved by the Colorado Multiple Institution Board (COMIRB) 15-1147.

High-throughput, "next-generation" sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking, bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field.

Cardiovascular disease (CVD) is the leading cause of death in the U.S. and disproportionately affects African Americans (AAs). Routinely measured circulating red blood cell traits, which are highly heritable and differ by ethnicity, are independent predictors for CVD-related traits including hypertension, stroke, coronary heart disease, and CVD mortality. Many genetic loci associated with red blood cell count (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and red cell distribution width (RDW) have been identified. However, identified genetic variants do not fully explain the heritability of these traits. Epigenetic alterations in DNA methylation likely also explain a portion of red cell trait variance, and detecting methylation quantitative trait loci (meQTLs) can provide critical insight into the development of CVD and CVD health disparities. We performed an epigenome-wide association analysis to identify CpG sites at which DNA methylation levels are associated with red blood cell traits in 1753 participants from the Jackson Heart Study, a population-based cohort of AAs. DNA methylation was measured by the Illumina MethylationEPIC array, interrogating approximately 850,000 CpG sites in peripheral blood mononuclear cells at the baseline exam. Associations were assessed using linear mixed models adjusted for age, sex, cell proportions, genetic ancestry, and experimental batch effects. A Bonferroni-corrected p-value of 9x10 -8 was used to assess statistical significance. We identified many significant differentially methylated CpG sites associated with red blood cell traits. Analysis of RBC, HGB, MCV, MCH, and MCHC revealed a novel highly significant association with a CpG annotated to a non-coding RNA (cg11703701; RBC P = 5.19x10 -22 , HGB P = 1.19x10 -11 , MCV P = 4.69x10 -59 , MCH P = 2.68x10 -67 , MCHC P = 2.32x10 -31 ), as well as a strong signal for a reprogramming-specific differentially methylated region (cg04321267; RBC P = 1.67x10 -16 , HGB P = 3.58x10 -12 , MCV P = 2.12x10 -49 , MCH P = 1.74x10 -57 , MCHC P = 5.91x10 -30 ). Multiple CpGs annotated to genes HBA1 and HBA2 were associated with RBC, MCV, MCH, and MCHC, while ITPKB (cg23740281; HGB P = 4.88x10 -10 , HCT P = 6.20x10 -11 ) and ALDH2 (cg17969951; HGB P = 3.03x10 -11 , HCT P = 8.31x10 -9 ) were significantly associated with both HGB and HCT. Additional CpG sites were significantly associated with HCT ( PLXND1 cg22902177; P = 7.54x10 -11 and ARL1 cg23903357; P = 9.86x10 -11 ) and RDW ( CPNE2 cg09018739; P = 3.03x10 -22 ). These findings shed light on potential hematologic and CVD mechanisms in understudied populations. Future work will explore the role of neighboring SNPs in mediating observed methylation-trait associations, and replicate results in an additional multi-ethnic cohort.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Phthalates are known endocrine disruptors and associated with decreased fecundity, pregnancy loss, and adverse obstetrical outcomes, however the underlying mechanisms remain to be established. Environmental factors can influence gene expression and cell function by modifying epigenetic marks, impacting the developing embryo as well as future generations of offspring. The impact of phthalates on placental gene methylation and expression is largely unknown. We studied the effect of maternal phthalate exposure on the human placental DNA methylome and transcriptome. We determined epigenome-wide DNA methylation marks (Illumina Infinium Human Methylation 850k BeadChip) and gene expression (Agilent whole human genome array) associated with phthalate exposure in first trimester placenta. Integrative genomic analysis of candidate genes was performed to define gene methylation-expression relationships. We identified 39 genes with significantly altered methylation and gene expression in the high phthalate exposure group. Most of these relationships were inversely correlated. This analysis identified epidermal growth factor receptor (EGFR) as a critical candidate gene mediating the effects of phthalates on early placental function. Although additional studies are needed to determine the functional consequences of these changes, our findings are consistent with the model that phthalates impact placental function by modulating the expression of critical placental genes through epigenetic regulation.

PURPOSE OF REVIEW: Epigenetic marks are emerging as mediators of genetics and the environment on complex disease phenotypes, including childhood asthma and allergy. RECENT FINDINGS: Epigenome-wide association studies (EWAS) over the past year have added to the growing body of evidence supporting significant associations of epigenetic regulation of gene expression and asthma and allergy. Studies in children have identified signatures of eosinophils in peripheral blood, Th2 cell transcription factors and cytokines in peripheral blood mononuclear cells, and epithelial dysfunction in the respiratory epithelium. Importantly, studies at birth have begun to decipher the contribution of epigenetic marks to asthma inception. Few studies have also begun to address the contribution of genetics and the environment to these associations. SUMMARY: Next generation of EWAS that will deal with confounders, study the influence of the genetics and environment, and incorporate multiple datasets to provide better interpretation of the findings are on the horizon. Identification of key epigenetic marks that are shaped by genetics and the environment, and impact transcription of specific genes will help us have a better understanding of etiology, heterogeneity and severity of asthma, and will also empower us to develop biologically driven therapeutics and biomarkers for secondary prevention of this disease.

Background Few studies have demonstrated associations between maternal dietary inflammatory index (DII) during pregnancy and offspring asthma and/or wheeze. Objective The study aimed to assess associations between maternal DII during pregnancy and 1) offspring cord sera pro-inflammatory cytokines (interleukin [IL]-1β, IL-4, IL-6, IL-10, tumor necrosis factor-α) and chemokines (IL-8, monocyte chemoattractant protein-1) at birth and 2) offspring asthma and/or wheeze at age 4 years. Design The Healthy Start study is a prospective prebirth longitudinal study that recruited pregnant women in Denver, Colorado and tracked their offspring. Participants and setting This study used data from 1228 mother-child dyads enrolled in the Healthy Start study. Pregnant women were recruited in Denver, Colorado, between 2009 and 2014, and offspring tracked until age 4 years. Main outcome measures Cord sera cytokines and chemokines were analyzed with multiplex panel immunoassays. Offspring diagnosis of asthma and/or wheeze by age 4 years was extracted from electronic medical records. Statistical analyses performed Unadjusted and adjusted linear and logistic regression models were used to assess associations. Covariates included factors such as nulliparity, race/ethnicity, gestational smoking, and maternal history of asthma. Results Unadjusted analysis showed that increasing maternal DII scores were associated with increased odds of child asthma and/or wheeze by 4 years (odds ratio = 1.17; 95% CI: 1.07-1.27), but the association was attenuated and no longer statistically significant in the adjusted model (odds ratio = 1.15; 95% CI: 0.99-1.33). There were no significant associations between DII scores and cord sera cytokine or chemokine levels. Conclusions The study showed that the inflammatory profile of the maternal diet was not associated with cytokines and chemokine levels at birth. The results suggested that a more inflammatory maternal diet was associated with increased odds of offspring asthma and/or wheeze by age 4 years, which could be considered of clinical relevance but the finding was not statistically significant at the .05 level.

Background Previous gene expression studies have identified genes IFNγ, TNFα, RNase 3, CXCL9, and CD55 as potential biomarkers for sarcoidosis and/or chronic beryllium disease (CBD). We hypothesized that differential expression of these genes could function as diagnostic biomarkers for sarcoidosis and CBD, and prognostic biomarkers for sarcoidosis. Study Design/Methods We performed RT-qPCR on whole blood samples from CBD (n = 132), beryllium sensitized (BeS) (n = 109), and sarcoidosis (n = 99) cases and non-diseased controls (n = 97) to determine differential expression of target genes. We then performed logistic regression modeling and generated ROC curves to determine which genes could most accurately differentiate: 1) CBD versus sarcoidosis 2) CBD versus BeS 3) sarcoidosis versus controls 4) non-progressive versus progressive sarcoidosis. Results CD55 and TNFα were significantly upregulated, while CXCL9 was significantly downregulated in CBD compared to sarcoidosis (p 0.05). The ROC curve from the logistic regression model demonstrated high discriminatory ability of the combination of CD55, TNFα, and CXCL9 to distinguish between CBD and sarcoidosis with an AUC of 0.98. CD55 and TNFα were significantly downregulated in sarcoidosis compared to controls (p 0.05). The ROC curve from the model showed a reasonable discriminatory ability of CD55 and TNFα to distinguish between sarcoidosis and controls with an AUC of 0.86. There was no combination of genes that could accurately differentiate between CBD and BeS or sarcoidosis phenotypes. Interpretation CD55, TNFα and CXCL9 expression levels can accurately differentiate between CBD and sarcoidosis, while CD55 and TNFα expression levels can accurately differentiate sarcoidosis and controls.

Asthma prevalence has been on the increase, especially in North America compared with other continents. However, the prevalence of asthma differs worldwide, and in many countries the prevalence is stable or decreasing. This highlights the influence of environmental exposures, such as allergens, air pollution, and the environmental microbiome, on disease etiology and pathogenesis. The epigenome might provide the unifying mechanism that translates the influence of environmental exposures to changes in gene expression, respiratory epithelial function, and immune cell skewing that are hallmarks of asthma. In this review we will introduce the concept of the environmental epigenome in asthmatic patients, summarize previous publications of relevance to this field, and discuss future directions.

Background Given the strong environmental influence on both epigenetic marks and allergic asthma in children, the epigenetic alterations in respiratory epithelia might provide insight into allergic asthma. Objective We sought to identify DNA methylation and gene expression changes associated with childhood allergic persistent asthma. Methods We compared genomic DNA methylation patterns and gene expression in African American children with persistent atopic asthma (n = 36) versus healthy control subjects (n = 36). Results were validated in an independent population of asthmatic children (n = 30) by using a shared healthy control population (n = 36) and in an independent population of white adult atopic asthmatic patients (n = 12) and control subjects (n = 12). Results We identified 186 genes with significant methylation changes, differentially methylated regions or differentially methylated probes, after adjustment for age, sex, race/ethnicity, batch effects, inflation, and multiple comparisons. Genes differentially methylated included those with established roles in asthma and atopy and genes related to extracellular matrix, immunity, cell adhesion, epigenetic regulation, and airflow obstruction. The methylation changes were substantial (median, 9.5%; range, 2.6% to 29.5%). Hypomethylated and hypermethylated genes were associated with increased and decreased gene expression, respectively ( P −6 for differentially methylated regions and P −10 for differentially methylated probes). Quantitative analysis in 53 differentially expressed genes demonstrated that 32 (60%) have significant methylation-expression relationships within 5 kb of the gene. Ten loci selected based on the relevance to asthma, magnitude of methylation change, and methylation-expression relationships were validated in an independent cohort of children with atopic asthma. Sixty-seven of 186 genes also have significant asthma-associated methylation changes in nasal epithelia of adult white asthmatic patients. Conclusions Epigenetic marks in respiratory epithelia are associated with allergic asthma and gene expression changes in inner-city children.

Epigenome-wide studies of methylation in children support a role for epigenetic mechanisms in asthma; however, studies in adults are rare and few have examined non-atopic asthma. We conducted the largest epigenome-wide association study (EWAS) of blood DNA methylation in adults in relation to non-atopic and atopic asthma. We measured DNA methylation in blood using the Illumina MethylationEPIC array among 2286 participants in a case-control study of current adult asthma nested within a United States agricultural cohort. Atopy was defined by serum specific immunoglobulin E (IgE). Participants were categorised as atopy without asthma (n=185), non-atopic asthma (n=673), atopic asthma (n=271), or a reference group of neither atopy nor asthma (n=1157). Analyses were conducted using logistic regression. No associations were observed with atopy without asthma. Numerous cytosine–phosphate–guanine (CpG) sites were differentially methylated in non-atopic asthma (eight at family-wise error rate (FWER) p, Distinct methylation signals are found in non-atopic and atopic asthma. Most are related to gene expression and are replicated in asthma-relevant tissues, confirming the value of blood DNA methylation for identifying novel genes linked in asthma pathogenesis. https://bit.ly/2VnbJg3

DNA methylation may be involved in development of type 1 diabetes (T1D), but previous epigenome-wide association studies were conducted among cases with clinically diagnosed diabetes. Using multiple pre-disease peripheral blood samples on the Illumina 450 K and EPIC platforms, we investigated longitudinal methylation differences between 87 T1D cases and 87 controls from the prospective Diabetes Autoimmunity Study in the Young (DAISY) cohort. Change in methylation with age differed between cases and controls in 10 regions. Average longitudinal methylation differed between cases and controls at two genomic positions and 28 regions. Some methylation differences were detectable and consistent as early as birth, including before and after the onset of preclinical islet autoimmunity. Results map to transcription factors, other protein coding genes, and non-coding regions of the genome with regulatory potential. The identification of methylation differences that predate islet autoimmunity and clinical diagnosis may suggest a role for epigenetics in T1D pathogenesis; however, functional validation is warranted.

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown.1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations was associated with both hematologic cancer incidence2–4 and coronary heart disease prevalence.5 Somatic mutations with leukemogenic potential may confer selective cellular advantages leading to clonal expansion, a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP).6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico-informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer. Aggregates of rare germline loss-of-function variants in CHEK2, a DNA damage repair gene, predisposed to CHIP acquisition. Overall, we observe that germline genetic variation altering hematopoietic stem cell function and the fidelity of DNA-damage repair increase the likelihood of somatic mutations leading to CHIP.

BackgroundRelatives of patients with familial interstitial pneumonia (FIP) are at increased risk for pulmonary fibrosis. We assessed the prevalence and risk factors for preclinical pulmonary fibrosis (PrePF) in first-degree relatives of patients with FIP and determined the utility of deep learning in detecting PrePF on CT.MethodsFirst-degree relatives of patients with FIP over 40 years of age who believed themselves to be unaffected by pulmonary fibrosis underwent CT scans of the chest. Images were visually reviewed, and a deep learning algorithm was used to quantify lung fibrosis. Genotyping for common idiopathic pulmonary fibrosis risk variants in MUC5B and TERT was performed.FindingsIn 494 relatives of patients with FIP from 263 families of patients with FIP, the prevalence of PrePF on visual CT evaluation was 15.6% (95% CI 12.6 to 19.0). Compared with visual CT evaluation, deep learning quantitative CT analysis had 84% sensitivity (95% CI 0.72 to 0.89) and 86% sensitivity (95% CI 0.83 to 0.89) for discriminating subjects with visual PrePF diagnosis. Subjects with PrePF were older (65.9, SD 10.1 years) than subjects without fibrosis (55.8 SD 8.7 years), more likely to be male (49% vs 37%), more likely to have smoked (44% vs 27%) and more likely to have the MUC5B promoter variant rs35705950 (minor allele frequency 0.29 vs 0.21). MUC5B variant carriers had higher quantitative CT fibrosis scores (mean difference of 0.36%), a difference that remains significant when controlling for age and sex.InterpretationPrePF is common in relatives of patients with FIP. Its prevalence increases with age and the presence of a common MUC5B promoter variant. Quantitative CT analysis can detect these imaging abnormalities.

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2–4 and coronary heart disease5—this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

A genetic basis for otitis media is established, however, the role of rare variants in disease etiology is largely unknown. Previously a duplication variant within A2ML1 was identified as a significant risk factor for otitis media in an indigenous Filipino population and in US children. In this report exome and Sanger sequencing was performed using DNA samples from the indigenous Filipino population, Filipino cochlear implantees, US probands, Finnish, and Pakistani families with otitis media. Sixteen novel, damaging A2ML1 variants identified in otitis media patients were rare or low-frequency in population-matched controls. In the indigenous population, both gingivitis and A2ML1 variants including the known duplication variant and the novel splice variant c.4061 + 1 G>C were independently associated with otitis media. Sequencing of salivary RNA samples from indigenous Filipinos demonstrated lower A2ML1 expression according to the carriage of A2ML1 variants. Sequencing of additional salivary RNA samples from US patients with otitis media revealed differentially expressed genes that are highly correlated with A2ML1 expression levels. In particular, RND3 is upregulated in both A2ML1 variant carriers and high-A2ML1 expressors. These findings support a role for A2ML1 in keratinocyte differentiation within the middle ear as part of otitis media pathology and the potential application of ROCK inhibition in otitis media.

EgeUn###, Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 3 102295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence. Copyright © 2019 by the American Thoracic Society, Háskóli Íslands, HI University of Chicago University of Ulsan, UOU Monash University, MU University of Nottingham University of Edinburgh University of Colorado Denver Universitat de Barcelona University of Pittsburgh, Pitt Harvard School of Dental Medicine Massachusetts General Hospital, MGH University of Pennsylvania, Penn University College Cork, UCC City, University of London, City University of California, San Francisco, UCSF School of Medicine, Vanderbilt University Ege Üniversitesi University of Virginia, UV Aarhus Universitetshospital Central Manchester University Hospitals NHS Foundation Trust Columbia University Novartis Sunovion COPD Foundation Pfizer National Heart, Lung, and Blood Institute, NHLBI: R01-HL097163, UH3-HL123442, P01-HL092870 U.S. Department of Defense, DOD: W81XWH-17-1-0597, U01 HL089897, U01 HL089856 AstraZeneca Siemens Foundation North Carolina GlaxoSmithKline Foundation, 1National Jewish Health, Denver, Colorado; 2School of Public Health; 3Department of Medicine, and 54Department of Immunology, University of Colorado Denver, Denver, Colorado; 4Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee; 5Brigham and Women’s Hospital, Harvard School of Medicine, Boston, Massachusetts; 6Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma;7Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; 8MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom; 9Respiratory Medicine Unit, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom; 10Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom; 11Royal Brompton Hospital and Imperial College, London, United Kingdom; 12Simmons Center for Interstitial Lung Disease, University of Pittsburgh, Pittsburgh, Pennsylvania; 13Department of Medicine, University of California, San Francisco, San Francisco, California; 14Gilead Sciences, Foster City, California; 15Department of Medicine, University of Chicago, Chicago, Illinois; 16Department of Medicine, University of Virginia, Charlottesville, Virginia; 17Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 18National Hospital Organization Kinki-Chuo Chest Medical Center, Osaka, Japan; 19National Hospital Organization Tokyo National Hospital, Tokyo, Japan; 20Helmholtz Zentrum München, Neuherberg, Germany; 21University Hospital Munich, Munich, Germany; 22Department of Pulmonology, Ege University Hospital, Bornova, Izmir, Turkey; 23Royal Prince Alfred Hospital and University of Sydney, Sydney, Australia; 24Alfred Hospital and Monash University, Melbourne, Australia; 25Pulmonary Medicine, GB Morgagni Hospital, Forlì, Italy; 26Department of Diseases of the Thorax, Ospedale GB Morgagni, Forlì, Italy; 27Université Paris Diderot and Hôpital Bichat, Paris, France; 28Royal Papworth Hospital and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; 29Respiratory Department, University Hospital of Bellvitge, University of Barcelona, Barcelona, Spain; 30National University Hospital of Iceland, University of Iceland, Reykjavik, Iceland; 31Department of Medicine, Columbia University Irving Medical Center, New York, New York; 32Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts; 33Department of Respiratory Diseases and Allergy, Aarhus University Hospital, Aarhus, Denmark; 34Instituto Nacional de Enfermedades Respiratorias “Ismael Cosio Villegas,” México City, México; 35Universidad Nacional Autónoma de México, México City, México; 36Cork University Hospital and University College Cork, Cork, Ireland; 37St. Vincent’s University Hospital, Dublin, Ireland; 38School of Medicine, University College Dublin, Dublin, Ireland; 39Department of Respiratory Medicine, First Faculty of Medicine Charles University and Thomayer Hospital, Prague, Czech Republic; 40University of British Columbia, Vancouver, Canada; 41Tokyo Medical and Dental University, Tokyo, Japan; 42Institute for Respiratory Health and; 43Centre for Cell Therapy and Regenerative Medicine, School of Biomedical Sciences, The University of Western Australia, Perth, Australia; 44Department of Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island; 45Advanced Lung Disease and Transplant Program, Inova Fairfax Hospital, Falls Church, Virginia; 46Department of Pulmonary Medicine, Gazi University School of Medicine, Ankara, Turkey; 47Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama; 48Ruhrlandklinik, University Hospital, University of Duisburg-Essen, Essen, Germany; 49Department of Medicine, Tallaght University Hospital, Trinity College Dublin, Dublin, Ireland; 50CardioPulmonary Reserach Center, Alliance Pulmonary Group, Guaynabo, Puerto Rico; 51Department of Internal Medicine, University of Genoa, Genoa, Italy; 52Biomedical Genomics Center, University of Minnesota; Minneapolis, Minnesota; and 53Northwest Genomics Center, University of Washington, Seattle, Washington -- This research was supported by grants from the NHLBI (R01-HL097163, P01-HL092870, and UH3-HL123442) and the Department of Defense (W81XWH-17-1-0597). The COPDGene project was supported by Award Number U01 HL089897 and Award Number U01 HL089856 from the NHLBI. The COPDGene project was also supported by the COPD Foundation through contributions made to an industry advisory board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion.