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

Exploring the molecular mechanisms of asthma across multiple datasets

BACKGROUND

Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.

MATERIALS AND METHODS

In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.

RESULTS

Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.

CONCLUSION

This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential.

Causal Role of Immune Cells in Chronic Obstructive Pulmonary Disease: A Two-Sample Mendelian Randomization Study

Accumulating evidence has highlighted the importance of immune cells in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, the understanding of the causal association between immunity and COPD remains incomplete due to the existence of confounding variables. In this study, we employed a two-sample Mendelian randomization (MR) analysis, utilizing the genome-wide association study database, to investigate the causal association between 731 immune-cell signatures and the susceptibility to COPD from a host genetics perspective. To validate the consistency of our findings, we utilized MR analysis results of lung function data to assess directional concordance. Furthermore, we employed MR-Egger intercept tests, Cochrane's Q test, MR-PRESSO global test, and "leave-one-out" sensitivity analyses to evaluate the presence of horizontal pleiotropy, heterogeneity, and stability, respectively. Inverse variance weighting results showed that seven immune phenotypes were associated with the risk of COPD. Analyses of heterogeneity and pleiotropy analysis confirmed the reliability of MR results. These results highlight the interactions between the immune system and the lungs. Further investigations into their mechanisms are necessary and will contribute to inform targeted prevention strategies for COPD.

Genetics of chronic respiratory disease

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma and interstitial lung diseases are frequently occurring disorders with a polygenic basis that account for a large global burden of morbidity and mortality. Recent large-scale genetic epidemiology studies have identified associations between genetic variation and individual respiratory diseases and linked specific genetic variants to quantitative traits related to lung function. These associations have improved our understanding of the genetic basis and mechanisms underlying common lung diseases. Moreover, examining the overlap between genetic associations of different respiratory conditions, along with evidence for gene-environment interactions, has yielded additional biological insights into affected molecular pathways. This genetic information could inform the assessment of respiratory disease risk and contribute to stratified treatment approaches.

House dust metagenome and pulmonary function in a US farming population

BACKGROUND

Chronic exposure to microorganisms inside homes can impact respiratory health. Few studies have used advanced sequencing methods to examine adult respiratory outcomes, especially continuous measures. We aimed to identify metagenomic profiles in house dust related to the quantitative traits of pulmonary function and airway inflammation in adults. Microbial communities, 1264 species (389 genera), in vacuumed bedroom dust from 779 homes in a US cohort were characterized by whole metagenome shotgun sequencing. We examined two overall microbial diversity measures: richness (the number of individual microbial species) and Shannon index (reflecting both richness and relative abundance). To identify specific differentially abundant genera, we applied the Lasso estimator with high-dimensional inference methods, a novel framework for analyzing microbiome data in relation to continuous traits after accounting for all taxa examined together.

RESULTS

Pulmonary function measures (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio) were not associated with overall dust microbial diversity. However, many individual microbial genera were differentially abundant (p-value < 0.05 controlling for all other microbial taxa examined) in relation to FEV1, FVC, or FEV1/FVC. Similarly, fractional exhaled nitric oxide (FeNO), a marker of airway inflammation, was unrelated to overall microbial diversity but associated with differential abundance for many individual genera. Several genera, including Limosilactobacillus, were associated with a pulmonary function measure and FeNO, while others, including Moraxella to FEV1/FVC and Stenotrophomonas to FeNO, were associated with a single trait.

CONCLUSIONS

Using state-of-the-art metagenomic sequencing, we identified specific microorganisms in indoor dust related to pulmonary function and airway inflammation. Some were previously associated with respiratory conditions; others were novel, suggesting specific environmental microbial components contribute to various respiratory outcomes. The methods used are applicable to studying microbiome in relation to other continuous outcomes. Video Abstract.

COPD, PRISm and lung function reduction affect the brain cortical structure: a Mendelian randomization study

Chronic obstructive pulmonary disease (COPD) has been associated with alterations in the brain cortical structure. Nonetheless, the causality between COPD and brain cortical structure has not been determined. In the present study, we used Mendelian randomization (MR) analysis to explore the causal effects of genetic predicated COPD on brain cortical structure, namely cortical surface area (SA) and cortical thickness (TH). Genetic association summary data for COPD were obtained from the FinnGen consortium (N = 358,369; Ncase = 20,066). PRISm summary genetic data were retrieved from a case-control GWAS conducted in the UK Biobank (N = 296,282). Lung function indices, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC, were extracted from a meta-analysis of the UK Biobank and SpiroMeta consortium (N = 400,102). Brain cortical structure data were obtained from the ENIGMA consortium (N = 51,665). Inverse-variance weighted (IVW) method was used as the primary analysis, and a series of sensitivity tests were exploited to evaluate the heterogeneity and pleiotropy of our results. The results identified potential causal effects of COPD on several brain cortical specifications, including pars orbitalis, cuneus and inferior parietal gyrus. Furthermore, genetic predicated lung function index (FEV1, FVC and FEV1/FVC), as well as PRISm, also has causal effects on brain cortical structure. According to our results, a total of 15 functional specifications were influenced by lung function index and PRISm. These findings contribute to understanding the causal effects of COPD and lung function to brain cortical structure.

Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

Overlap between COPD genetic association results and transcriptional quantitative trait loci

Rationale

Genome-wide association studies (GWAS) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). When integrated with GWAS results, expression quantitative trait locus (eQTL) studies can provide insight into biological mechanisms involved in disease by identifying single nucleotide polymorphisms (SNPs) that contribute to whole gene expression. However, there are multiple genetically driven regulatory and isoform-specific effects which cannot be detected in traditional eQTL analyses. Here, we identify SNPs that are associated with alternative splicing (sQTL) in addition to eQTLs to identify novel functions for COPD associated genetic variants.

Methods

We performed RNA sequencing on whole blood from 3743 subjects in the COPDGene Study. RNA sequencing data from lung tissue of 1241 subjects from the Lung Tissue Research Consortium (LTRC), and whole genome sequencing data on all subjects. Associations between all SNPs within 1000 kb of a gene (cis-) and splice and gene expression quantifications were tested using tensorQTL. In COPDGene a total of 11,869,333 SNPs were tested for association with 58,318 splice clusters, and 8,792,206 SNPs were tested for association with 70,094 splice clusters in LTRC. We assessed colocalization with COPD-associated SNPs from a published GWAS[1].

Results

After adjustment for multiple statistical testing, we identified 28,110 splice-sites corresponding to 3,889 unique genes that were significantly associated with genotype in COPDGene whole blood, and 58,258 splice-sites corresponding to 10,307 unique genes associated with genotype in LTRC lung tissue. We found 7,576 sQTL splice-sites corresponding to 2,110 sQTL genes were shared between whole blood and lung, while 20,534 sQTL splice-sites in 3,518 genes were unique to blood and 50,682 splice-sites in 9,677 genes were unique to lung. To determine what proportion of COPD-associated SNPs were associated with transcriptional splicing, we performed colocalization analysis between COPD GWAS and sQTL data, and found that 38 genomic windows, corresponding to 38 COPD GWAS loci had evidence of colocalization between QTLs and COPD. The top five colocalizations between COPD and lung sQTLs include NPNT , FBXO38 , HHIP , NTN4 and BTC .

Conclusions

A total of 38 COPD GWAS loci contain evidence of sQTLs, suggesting that analysis of sQTLs in whole blood and lung tissue can provide novel insights into disease mechanisms.

Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction

Although high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, Representation Learning for Genetic Discovery on Low-Dimensional Embeddings (REGLE), for discovering associations between genetic variants and HDCD. REGLE leverages variational autoencoders to compute nonlinear disentangled embeddings of HDCD, which become the inputs to genome-wide association studies (GWAS). REGLE can uncover features not captured by existing expert-defined features and enables the creation of accurate disease-specific polygenic risk scores (PRSs) in datasets with very few labeled data. We apply REGLE to perform GWAS on respiratory and circulatory HDCD-spirograms measuring lung function and photoplethysmograms measuring blood volume changes. REGLE replicates known loci while identifying others not previously detected. REGLE are predictive of overall survival, and PRSs constructed from REGLE loci improve disease prediction across multiple biobanks. Overall, REGLE contain clinically relevant information beyond that captured by existing expert-defined features, leading to improved genetic discovery and disease prediction.

SCARF2 is a target for chronic obstructive pulmonary disease: Evidence from multi-omics research and cohort validation

Age-related chronic inflammatory lung diseases impose a threat on public health, including idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD). However, their etiology and potential targets have not been clarified. We performed genome-wide meta-analysis for IPF with the largest sample size (2883 cases and 741,929 controls) and leveraged the summary statistics of COPD (17,547 cases and 617,598 controls). Transcriptome-wide and proteome-wide Mendelian randomization (MR) designs, together with genetic colocalization, were implemented to find robust targets. The mediation effect was assessed using leukocyte telomere length (LTL). The single-cell transcriptome analysis was performed to link targets with cell types. Individual-level data from UK Biobank (UKB) were used to validate our findings. Sixteen genetically predicted plasma proteins were causally associated with the risk of IPF and 6 proteins were causally associated with COPD. Therein, genetically-elevated plasma level of SCARF2 protein should reduce the risk of both IPF (odds ratio, OR = 0.9974 [0.9970, 0.9978]) and COPD (OR = 0.7431 [0.6253, 0.8831]) and such effects were not mediated by LTL. Genetic colocalization further corroborated these MR results of SCARF2. The transcriptome-wide MR confirmed that higher expression level of SCARF2 was associated with a reduced risk of both. However, the single-cell RNA analysis indicated that SCARF2 expression level was only relatively lower in epithelial cells of COPD lung tissue compared to normal lung tissue. UKB data implicated an inverse association of serum SCARF2 protein with COPD (hazard ratio, HR = 1.215 [1.106, 1.335]). The SCARF2 gene should be a novel target for COP.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Treatable traits in pre-COPD: Time to extend the treatable traits paradigm beyond established disease

To date, the treatable traits (TTs) approach has been applied in the context of managing diagnosed diseases. TTs are clinical characteristics and risk factors that can be identified clinically and/or biologically, and that merit treatment if present. There has been an exponential increase in the uptake of this approach by both researchers and clinicians. Realizing the potential of the TTs approach to pre-clinical disease, this expert review proposes that it is timely to consider acting on TTs present before a clinical diagnosis is made, which might help to prevent development of the full disease. Such an approach is ideal for diseases where there is a long pre-clinical phase, such as in chronic obstructive pulmonary disease (COPD). The term 'pre-COPD' has been recently proposed to identify patients with respiratory symptoms and/or structural or functional abnormalities without airflow limitation. They may eventually develop airflow limitation with time but patients with pre-COPD are likely to have traits that are already treatable. This review first outlines the contribution of recently generated knowledge into lifetime lung function trajectories and the conceptual framework of 'GETomics' to the field of pre-COPD. GETomics is a dynamic and cumulative model of interactions between genes and the environment throughout the lifetime that integrates information from multi-omics to understand aetiology and mechanisms of diseases. This review then discusses the current evidence on potential TTs in pre-COPD patients and makes recommendations for practice and future research. At a broader level, this review proposes that introducing the TTs in pre-COPD may help reenergize the preventive approaches to health and diseases.

Crosstalk between epitranscriptomic and epigenomic modifications and its implication in human diseases

Crosstalk between N6-methyladenosine (m6A) and epigenomes is crucial for gene regulation, but its regulatory directionality and disease significance remain unclear. Here, we utilize quantitative trait loci (QTLs) as genetic instruments to delineate directional maps of crosstalk between m6A and two epigenomic traits, DNA methylation (DNAme) and H3K27ac. We identify 47 m6A-to-H3K27ac and 4,733 m6A-to-DNAme and, in the reverse direction, 106 H3K27ac-to-m6A and 61,775 DNAme-to-m6A regulatory loci, with differential genomic location preference observed for different regulatory directions. Integrating these maps with complex diseases, we prioritize 20 genome-wide association study (GWAS) loci for neuroticism, depression, and narcolepsy in brain; 1,767 variants for asthma and expiratory flow traits in lung; and 249 for coronary artery disease, blood pressure, and pulse rate in muscle. This study establishes disease regulatory paths, such as rs3768410-DNAme-m6A-asthma and rs56104944-m6A-DNAme-hypertension, uncovering locus-specific crosstalk between m6A and epigenomic layers and offering insights into regulatory circuits underlying human diseases.

Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

Clarifying Chronic Obstructive Pulmonary Disease Genetic Associations Observed in Biobanks via Mediation Analysis of Smoking

Varying case definitions of COPD have heterogenous genetic risk profiles, potentially reflective of disease subtypes or classification bias (e.g., smokers more likely to be diagnosed with COPD). To better understand differences in genetic loci associated with ICD-defined versus spirometry-defined COPD we contrasted their GWAS results with those for heavy smoking among 337,138 UK Biobank participants. Overlapping risk loci were found in/near the genes ZEB2, FAM136B, CHRNA3, and CHRNA4, with the CHRNA3 locus shared across all three traits. Mediation analysis to estimate the effects of lead genotyped variants mediated by smoking found significant indirect effects for the FAM136B, CHRNA3, and CHRNA4 loci for both COPD definitions. Adjustment for mediator-outcome confounders modestly attenuated indirect effects, though in the CHRNA4 locus for spirometry-defined COPD the proportion mediated increased an additional 8.47%. Our results suggest that differences between ICD-defined and spirometry-defined COPD associated genetic loci are not a result of smoking biasing classification.

Association between n-3 PUFA and lung function: results from the NHANES 2007-2012 and Mendelian randomisation study

This study aimed to investigate the association between n-3 PUFA and lung function. First, a cross-sectional study was conducted based on the National Health and Nutrition Examination Survey (NHANES) 2007-2012 data. n-3 PUFA intake was obtained from 24-h dietary recalls. A multivariable linear regression model was used to assess the observational associations of n-3 PUFA intake with lung function. Subsequently, a two-sample Mendelian randomisation (MR) was performed to estimate the potential causal effect of n-3 PUFA on lung function. Genetic instrumental variables were extracted from published genome-wide association studies. Summary statistics about n-3 PUFA was from UK Biobank. Inverse variance weighted was the primary analysis approach. The observational study did not demonstrate a significant association between n-3 PUFA intake and most lung function measures; however, a notable exception was observed with significant findings in the highest quartile for forced vital capacity (FVC) and % predicted FVC. The MR results also showed no causal effect of circulating n-3 PUFA concentration on lung function (forced expiratory volume in one second (FEV1), β = 0·01301, se = 0·01932, P = 0·5006; FVC, β = -0·001894, se = 0·01704, P = 0·9115; FEV1:FVC, β = 0·03118, se = 0·01743, P = 0·07359). These findings indicate the need for further investigation into the impact of higher n-3 PUFA consumption on lung health.

Genetic variations in anti-diabetic drug targets and COPD risk: evidence from mendelian randomization

BACKGROUND

Previous research has emphasized the potential benefits of anti-diabetic medications in inhibiting the exacerbation of Chronic Obstructive Pulmonary Disease (COPD), yet the role of anti-diabetic drugs on COPD risk remains uncertain.

METHODS

This study employed a Mendelian randomization (MR) approach to evaluate the causal association of genetic variations related to six classes of anti-diabetic drug targets with COPD. The primary outcome for COPD was obtained from the Global Biobank Meta-analysis Initiative (GBMI) consortium, encompassing a meta-analysis of 12 cohorts with 81,568 cases and 1,310,798 controls. Summary-level data for HbA1c was derived from the UK Biobank, involving 344,182 individuals. Positive control analysis was conducted for Type 2 Diabetes Mellitus (T2DM) to validate the choice of instrumental variables. The study applied Summary-data-based MR (SMR) and two-sample MR for effect estimation and further adopted colocalization analysis to verify evidence of genetic variations.

RESULTS

SMR analysis revealed that elevated KCNJ11 gene expression levels in blood correlated with reduced COPD risk (OR = 0.87, 95% CI = 0.79-0.95; p = 0.002), whereas an increase in DPP4 expression corresponded with an increased COPD incidence (OR = 1.18, 95% CI = 1.03-1.35; p = 0.022). Additionally, the primary method within MR analysis demonstrated a positive correlation between PPARG-mediated HbA1c and both FEV1 (OR = 1.07, 95% CI = 1.02-1.13; P = 0.013) and FEV1/FVC (OR = 1.08, 95% CI = 1.01-1.14; P = 0.007), and a negative association between SLC5A2-mediated HbA1c and FEV1/FVC (OR = 0.86, 95% CI = 0.74-1.00; P = 0.045). No colocalization evidence with outcome phenotypes was detected (all PP.H4 < 0.7).

CONCLUSION

This study provides suggestive evidence for anti-diabetic medications' role in improving COPD and lung function. Further updated MR analyses are warranted in the future, following the acquisition of more extensive and comprehensive data, to validate our results.

Genetic association of inflammatory marker GlycA with lung function and respiratory diseases

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = -0.14), FVC (rg = -0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.

Exploiting meta-analysis of genome-wide interaction with serum 25-hydroxyvitamin D to identify novel genetic loci associated with pulmonary function

BACKGROUND

Higher 25-hydroxyvitamin D (25(OH)D) concentrations in serum has a positive association with pulmonary function. Investigating genome-wide interactions with 25(OH)D may reveal new biological insights into pulmonary function.

OBJECTIVES

We aimed to identify novel genetic variants associated with pulmonary function by accounting for 25(OH)D interactions.

METHODS

We included 211,264 participants from the observational United Kingdom Biobank study with pulmonary function tests (PFTs), genome-wide genotypes, and 25(OH)D concentrations from 4 ancestral backgrounds-European, African, East Asian, and South Asian. Among PFTs, we focused on forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) because both were previously associated with 25(OH)D. We performed genome-wide association study (GWAS) analyses that accounted for variant×25(OH)D interaction using the joint 2 degree-of-freedom (2df) method, stratified by participants' smoking history and ancestry, and meta-analyzed results. We evaluated interaction effects to determine how variant-PFT associations were modified by 25(OH)D concentrations and conducted pathway enrichment analysis to examine the biological relevance of our findings.

RESULTS

Our GWAS meta-analyses, accounting for interaction with 25(OH)D, revealed 30 genetic variants significantly associated with FEV1 or FVC (P2df <5.00×10-8) that were not previously reported for PFT-related traits. These novel variant signals were enriched in lung function-relevant pathways, including the p38 MAPK pathway. Among variants with genome-wide-significant 2df results, smoking-stratified meta-analyses identified 5 variants with 25(OH)D interactions that influenced FEV1 in both smoking groups (never smokers P1df interaction<2.65×10-4; ever smokers P1df interaction<1.71×10-5); rs3130553, rs2894186, rs79277477, and rs3130929 associations were only evident in never smokers, and the rs4678408 association was only found in ever smokers.

CONCLUSION

Genetic variant associations with lung function can be modified by 25(OH)D, and smoking history can further modify variant×25(OH)D interactions. These results expand the known genetic architecture of pulmonary function and add evidence that gene-environment interactions, including with 25(OH)D and smoking, influence lung function.

Breathing new life into the study of COPD with genes identified from genome-wide association studies

COPD is a major cause of morbidity and mortality globally. While the significance of environmental exposures in disease pathogenesis is well established, the functional contribution of genetic factors has only in recent years drawn attention. Notably, many genes associated with COPD risk are also linked with lung function. Because reduced lung function precedes COPD onset, this association is consistent with the possibility that derangements leading to COPD could arise during lung development. In this review, we summarise the role of leading genes (HHIP, FAM13A, DSP, AGER and TGFB2) identified by genome-wide association studies in lung development and COPD. Because many COPD genome-wide association study genes are enriched in lung epithelial cells, we focus on the role of these genes in the lung epithelium in development, homeostasis and injury.

Assessing the causal role of physical activity and leisure sedentary behaviours with chronic obstructive pulmonary disease: a Mendelian randomisation study

BACKGROUND

Observational studies show that patients with chronic obstructive pulmonary disease (COPD) tend to be sedentary during leisure time. Physical activity (PA) may reduce the risk of COPD, but the causal relationship is unclear. We used a Mendelian randomisation (MR) method to elucidate the association of leisure sedentary behaviours (LSB) and PA with lung function and COPD.

METHODS

Data on LSB (n=422 218), PA (n=608 595), COPD (n=299 929) and lung function (n=79 055) were obtained from the large-scale genome-wide association study. Causal inference used inverse variance-weighted, MR-Egger and weighted median. Sensitivity analysis was performed to assess heterogeneity and pleiotropy, and radial MR was used to distinguish outliers. The primary outcome was analysed by multifactorial MR adjusted for daily smoking.

RESULTS

The inverse variance weighted analysis indicated that increased moderate-to-vigorous PA (MVPA) is associated with higher levels of forced vital capacity (FVC) (beta=0.27, 95% CI 0.12 to 0.42; p=3.51×10-4). For each increment of 2.8 hours in television watching, the odds of COPD were 2.25 times greater (OR=2.25; 95% CI 1.84 to 2.75; p=2.38×10-15). For early-onset COPD, the odds were 2.11 times greater (OR=2.11; 95% CI 1.56 to 2.85; p=1.06×10-6), and for late-onset COPD, the odds were 2.16 times greater (OR=2.16; 95% CI 1.64 to 2.84; p=3.12×10-8). Similarly, the odds of hospitalisation for COPD were 2.02 times greater with increased television watching (OR=2.02; 95% CI 1.59 to 2.55; p=4.68×10-9). Television watching was associated with lower FVC (beta=-0.19, 95% CI -0.28 to -0.10; p=1.54×10-5) and forced expiratory volume in the 1 s (FEV1) (beta=-0.16, 95% CI -0.25 to -0.08; p=1.21×10-4) levels. The results remained significant after adjustment for smoking.

CONCLUSIONS

Our study suggests a potential association with LSB, particularly television watching, is associated with higher odds of COPD and lower indices of lung function as measured continuously, including FEV1 and FVC. Conversely, an increase in MVPA is associated with higher indices of lung function, particularly reflected in increased FVC levels.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Adam19 Deficiency Impacts Pulmonary Function: Human GWAS Follow-up in Mouse

Purpose

Over 550 loci have been associated with human pulmonary function in genome-wide association studies (GWAS); however, the causal role of most remains uncertain. Single nucleotide polymorphisms in a disintegrin and metalloprotease domain 19 (ADAM19) are consistently related to pulmonary function in GWAS. Thus, we used a mouse model to investigate the causal link between Adam19 and pulmonary function.

Methods

We created an Adam19 knockout (KO) mouse model and validated the gene targeting using RNA-Seq and RT-qPCR. Contrary to prior publications, the KO was not neonatal lethal. Thus, we phenotyped the Adam19 KO.

Results

KO mice had lower body weight and shorter tibial length than wild type (WT). Dual-energy X-ray Absorptiometry indicated lower soft weight, fat weight, and bone mineral content in KO mice. In lung function analyses using flexiVent, compared to WT, Adam19 KO had decreased baseline respiratory system elastance, minute work of breathing, tissue damping, tissue elastance, and forced expiratory flow at 50% forced vital capacity but higher FEV0.1 and FVC. Adam19 KO had attenuated tissue damping and tissue elastance in response to methacholine following LPS exposure. Adam19 KO also exhibited attenuated neutrophil extravasation into the airway after LPS administration compared to WT. RNA-Seq analysis of KO and WT lungs identified several differentially expressed genes (Cd300lg, Kpna2, and Pttg1) implicated in lung biology and pathogenesis. Gene set enrichment analysis identified negative enrichment for TNF pathways.

Conclusion

Our murine findings support a causal role of ADAM19, implicated in human GWAS, in regulating pulmonary function.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

Role of CaMKII in diabetes induced vascular injury and its interaction with anti-diabetes therapy

Diabetes mellitus is a metabolic disorder denoted by chronic hyperglycemia that drives maladaptive structural changes and functional damage to the vasculature. Attenuation of this pathological remodeling of blood vessels remains an unmet target owing to paucity of information on the metabolic signatures of this process. Ca2+/calmodulin-dependent kinase II (CaMKII) is expressed in the vasculature and is implicated in the control of blood vessels homeostasis. Recently, CaMKII has attracted a special attention in view of its chronic upregulated activity in diabetic tissues, yet its role in the diabetic vasculature remains under investigation.This review highlights the physiological and pathological actions of CaMKII in the diabetic vasculature, with focus on the control of the dialogue between endothelial (EC) and vascular smooth muscle cells (VSMC). Activation of CaMKII enhances EC and VSMC proliferation and migration, and increases the production of extracellular matrix which leads to maladaptive remodeling of vessels. This is manifested by activation of genes/proteins implicated in the control of the cell cycle, cytoskeleton organization, proliferation, migration, and inflammation. Endothelial dysfunction is paralleled by impaired nitric oxide signaling, which is also influenced by CaMKII signaling (activation/oxidation). The efficiency of CaMKII inhibitors is currently being tested in animal models, with a focus on the genetic pathways involved in the regulation of CaMKII expression (microRNAs and single nucleotide polymorphisms). Interestingly, studies highlight an interaction between the anti-diabetic drugs and CaMKII expression/activity which requires further investigation. Together, the studies reviewed herein may guide pharmacological approaches to improve health-related outcomes in patients with diabetes.

MGDHGS: Gene-bridged metabolite-disease relationships prediction via GraphSAGE and self-attention mechanism

Metabolites represent the underlying information of biological systems. Revealing the links between metabolites and diseases can facilitate the development of targeted drugs. Traditional biological experiments can be used to validate the relationships of metabolite-disease, but these methods are time-consuming and labor-intensive. In contrast, the prevailing computational methods have improved efficiency but primarily rely on the metabolite-disease interactions, overlooking the impact of other biological components. To remedy the problem, we present a novel computational framework (MGDHGS) based on metabolite-gene-disease heterogeneous network to forecast potential associations. Specifically, we initially integrate data from multiple sources to construct metabolite-gene-disease heterogeneous network that includes known associations and computationally-derived similarities. Then, the GraphSAGE is harnessed to learn the low dimensional neighborhood representation in the heterogeneous network and self-attention mechanism is applied to effectively capture the connectivity patterns, which contributions to combine with nodes intrinsic and extrinsic features. Finally, the ultimate relationships probability scores are predicted by linear regression based on the these characteristics. The five-fold cross-validation showcases impressive AUC (0.9734) and PR (0.9718) for MGDHGS compared with five state-of-the-art methods, and the case studies validate that the metabolite-disease associations predicted by MGDHGS can be substantiated through pertinent biological experiments. The findings of this study show great potential contribution in the development of targeted drugs as well as offering solid support for our understanding of the complex interactions between metabolites, genes and diseases.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study

BACKGROUND

Respiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors.

METHODS

We conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed.

FINDINGS

MR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (β = 0.10, 95% CI 0.06, 0.14), FVC (β = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (β = - 0.005, 95% CI - 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (β = 0.10, 95% CI 0.04, 0.16), FVC (β = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (β = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease.

CONCLUSION

High levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study

The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8×10-7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform (https://nf-co.re/omicsgenetraitassociation).

Air pollution, lung function and mortality: survival and mediation analyses in UK Biobank

Background

Air pollution is associated with lower lung function, and both are associated with premature mortality and cardiovascular disease (CVD). Evidence remains scarce on the potential mediating effect of impaired lung function on the association between air pollution and mortality or CVD.

Methods

We used data from UK Biobank (n∼200 000 individuals) with 8-year follow-up to mortality and incident CVD. Exposures to particulate matter <10 µm (PM10), particulate matter <2.5 µm (PM2.5) and nitrogen dioxide (NO2) were assessed by land-use regression modelling. Lung function (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and the FEV1/FVC ratio) was measured between 2006 and 2010 and transformed to Global Lung Function Initiative (GLI) z-scores. Adjusted Cox proportional hazards and causal proportional hazards mediation analysis models were fitted, stratified by smoking status.

Results

Lower FEV1 and FVC were associated with all-cause and CVD mortality, and incident CVD, with larger estimates in ever- than never-smokers (all-cause mortality hazard ratio per FEV1 GLI z-score decrease 1.29 (95% CI 1.24-1.34) for ever-smokers and 1.16 (95% CI 1.12-1.21) for never-smokers). Long-term exposure to PM2.5 or NO2 was associated with incident CVD, with similar effect sizes for ever- and never-smokers. Mediated proportions of the air pollution-all-cause mortality estimates driven by FEV1 were 18% (95% CI 2-33%) for PM2.5 and 27% (95% CI 3-51%) for NO2. Corresponding mediated proportions for incident CVD were 9% (95% CI 4-13%) for PM2.5 and 16% (95% CI 6-25%) for NO2.

Conclusions

Lung function may mediate a modest proportion of associations between air pollution and mortality and CVD outcomes. Results likely reflect the extent of either shared mechanisms or direct effects relating to lower lung function caused by air pollution.

Proteomic Networks and Related Genetic Variants Associated with Smoking and Chronic Obstructive Pulmonary Disease

Background

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

Methods

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a dimension reduction technique leveraging network topology, to produce summary scores of each proteomic network, referred to as NetSHy scores. We next performed genome-wide association study (GWAS) to identify variants associated with the NetSHy scores, or network quantitative trait loci (nQTLs). Finally, we evaluated the replicability of the networks in an independent cohort, SPIROMICS.

Results

We identified networks of 13 to 104 proteins for each phenotype and exposure in NHW and AA, and the derived NetSHy scores significantly associated with the variable of interests. Networks included known (sRAGE, ALPP, MIP1) and novel molecules (CA10, CPB1, HIS3, PXDN) and interactions involved in COPD pathogenesis. We observed 7 nQTL loci associated with NetSHy scores, 4 of which remained after conditional analysis. Networks for smoking status and emphysema, but not airflow obstruction, demonstrated a high degree of replicability across race groups and cohorts.

Conclusions

In this work, we apply state-of-the-art molecular network generation and summarization approaches to proteomic data from COPDGene participants to uncover protein networks associated with COPD phenotypes. We further identify genetic associations with networks. This work discovers protein networks containing known and novel proteins and protein interactions associated with clinically relevant COPD phenotypes across race groups and cohorts.

Tea intake and lung diseases: a Mendelian randomization study

Background

Existing studies on the relationship between tea intake and lung diseases have yielded inconsistent results, leading to an ongoing dispute on this issue. The impact of tea consumption on the respiratory system remained elucidating.

Materials and methods

We conducted a two-sample Mendelian randomization (MR) study to evaluate the associations between five distinct tea intake phenotypes and 15 different respiratory outcomes using open Genome-wide association study (GWAS) data. The inverse variance weighted (IVW) was used for preliminary screening and a variety of complementary methods were used as sensitivity analysis to validate the robustness of MR estimates. Pathway enrichment analysis was used to explore possible mechanisms.

Results

IVW found evidence for a causal effect of standard tea intake on an increased risk of lung squamous cell cancer (LSCC) (OR = 1.004; 95% CI = 1.001-1.007; P = 0.00299). No heterogeneity or pleiotropy was detected. After adjustment for potential mediators, including smoking, educational attainment, and time spent watching television, the association was still robust in multivariable MR. KEGG and GO enrichment predicted proliferation and activation of B lymphocytes may play a role in this causal relation. No causalities were observed when evaluating the effect of other kinds of tea intake on various pulmonary diseases.

Conclusion

Our MR estimates provide causal evidence of the independent effect of standard tea intake (black tea intake) on LSCC, which may be mediated by B lymphocytes. The results implied that the population preferring black tea intake should be wary of a higher risk of LSCC.

Lung function and the risk of frailty in the European population: a mendelian randomization study

BACKGROUND

Epidemiological evidence has suggested a relationship between lung function and frailty, but the precise nature of the causality remains unclear. In this study, we applied a two-sample Mendelian randomization (MR) analysis to determine the causal effects of lung function on frailty.

METHODS

Single nucleotide polymorphisms (SNPs) independently related (P ≤ 5E-08) to lung function, as identified by genome-wide association study (GWAS), were applied as instrumental variables (IV). The association with frailty index (FI) was investigated using summary-level data from the latest GWAS on FI (n = 175,226). Different statistical methods were employed to evaluate the causal estimates between lung function and FI. The pleiotropy, heterogeneity, and leave-one-out analysis were applied to confirm the stability of the MR estimates.

RESULTS

Using the random-effect inverse-variance weighted approach, genetically proxied forced expiratory volume in the first second (FEV1), ratio of FEV1 on forced vital capacity (FVC) [FEV1/FVC], and peak expiratory flow (PEF) were significantly and inversely associated with FI (FEV1, β = -0.08, P = 2.03E-05; FEV1/FVC, β = -0.06, P = 9.51E-06; PEF, β = -0.07, P = 4.09E-04) with good statistical power (99.7-100%). However, no significant association was observed between FVC and FI (β = -0.01, P = 0.681). Leave-one-out analysis showed that there was no single SNP driving the bias of the estimates. There was potential heterogeneity, but no obvious pleiotropy was founded in this MR study.

CONCLUSIONS

Our findings indicate that impaired pulmonary function is closely related to the risk of frailty. Enhancing lung function in the elderly population may contribute to the prevention of frailty to a certain extent.

Metabolic syndrome, genetic susceptibility, and risk of chronic obstructive pulmonary disease: The UK Biobank Study

AIM

To investigate the effect of metabolic syndrome (MetS), genetic predisposition, and their interactions, on the risk of developing chronic obstructive pulmonary disease (COPD).

METHODS

Cohort analyses included 287 868 participants from the UK Biobank Study. A genetic risk score for COPD was created using 277 single nucleotide polymorphisms. Cox proportional hazard models were used to evaluate the hazard ratios (HRs) with 95% confidence intervals (CIs) for COPD in relation to exposure factors.

RESULTS

During 2 658 936 person-years of follow-up, 5877 incident cases of COPD were documented. Compared with participants without MetS, those with MetS had a higher risk of COPD (HR 1.24, 95% CI 1.17-1.32). Compared to participants with low genetic predisposition, those with high genetic predisposition had a 17% increased risk of COPD. In the joint analysis, compared with participants without MetS and low genetic predisposition, the HR for COPD for those with MetS and high genetic predisposition was 1.50 (95% CI 1.36-1.65; P < 0.001). However, no significant interaction between MetS and genetic risk was found.

CONCLUSIONS

Metabolic syndrome was found to be associated with an increased risk of COPD, regardless of genetic risk. It is crucial to conduct further randomized control trials to determine whether managing MetS and its individual components can potentially reduce the likelihood of developing COPD.

Associations of combined phenotypic ageing and genetic risk with incidence of chronic respiratory diseases in the UK Biobank: a prospective cohort study

BACKGROUND

Accelerated biological ageing has been associated with an increased risk of several chronic respiratory diseases. However, the associations between phenotypic age, a new biological age indicator based on clinical chemistry biomarkers, and common chronic respiratory diseases have not been evaluated.

METHODS

We analysed data from 308 592 participants at baseline in the UK Biobank. The phenotypic age was calculated from chronological age and nine clinical chemistry biomarkers, including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width and white blood cell count. Furthermore, phenotypic age acceleration (PhenoAgeAccel) was calculated by regressing phenotypic age on chronological age. The associations of PhenoAgeAccel with incident common chronic respiratory diseases and cross-sectional lung function were investigated. Moreover, we constructed polygenic risk scores and evaluated whether PhenoAgeAccel modified the effect of genetic susceptibility on chronic respiratory diseases and lung function.

RESULTS

The results showed significant associations of PhenoAgeAccel with increased risk of idiopathic pulmonary fibrosis (IPF) (hazard ratio (HR) 1.52, 95% CI 1.45-1.59), COPD (HR 1.54, 95% CI 1.51-1.57) and asthma (HR 1.18, 95% CI 1.15-1.20) per 5-year increase and decreased lung function. There was an additive interaction between PhenoAgeAccel and the genetic risk for IPF and COPD. Participants with high genetic risk and who were biologically older had the highest risk of incident IPF (HR 5.24, 95% CI 3.91-7.02), COPD (HR 2.99, 95% CI 2.66-3.36) and asthma (HR 2.07, 95% CI 1.86-2.31). Mediation analysis indicated that PhenoAgeAccel could mediate 10∼20% of the associations between smoking and chronic respiratory diseases, while ∼10% of the associations between particulate matter with aerodynamic diameter <2.5 µm and the disorders were mediated by PhenoAgeAccel.

CONCLUSION

PhenoAgeAccel was significantly associated with incident risk of common chronic respiratory diseases and decreased lung function and could serve as a novel clinical biomarker.

Precision Approaches to Chronic Obstructive Pulmonary Disease Management

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. COPD heterogeneity has hampered progress in developing pharmacotherapies that affect disease progression. This issue can be addressed by precision medicine approaches, which focus on understanding an individual's disease risk, and tailoring management based on pathobiology, environmental exposures, and psychosocial issues. There is an urgent need to identify COPD patients at high risk for poor outcomes and to understand at a mechanistic level why certain individuals are at high risk. Genetics, omics, and network analytic techniques have started to dissect COPD heterogeneity and identify patients with specific pathobiology. Drug repurposing approaches based on biomarkers of specific inflammatory processes (i.e., type 2 inflammation) are promising. As larger data sets, additional omics, and new analytical approaches become available, there will be enormous opportunities to identify high-risk individuals and treat COPD patients based on their specific pathophysiological derangements. These approaches show great promise for risk stratification, early intervention, drug repurposing, and developing novel therapeutic approaches for COPD.

Three linked variants have opposing regulatory effects on isovaleryl-CoA dehydrogenase gene expression

While genome-wide association studies (GWAS) and positive selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD gene locus-which encodes the isovaleryl-CoA dehydrogenase enzyme-implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and a deletion tiling MPRA strategy across regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

Proteomic associations with forced expiratory volume: a Mendelian randomisation study

BACKGROUND

A decline in forced expiratory volume (FEV1) is a hallmark of respiratory diseases that are an important cause of morbidity among the elderly. While some data exist on biomarkers that are related to FEV1, we sought to do a systematic analysis of causal relations of biomarkers with FEV1.

METHODS

Data from the population-based AGES-Reykjavik study were used. Serum proteomic measurements were done using 4782 DNA aptamers (SOMAmers). Data from 1479 participants with spirometric data were used to assess the association of SOMAmer measurements with FEV1 using linear regression. Bi-directional two-sample Mendelian randomisation (MR) analyses were done to assess causal relations of observationally associated SOMAmers with FEV1, using genotype and SOMAmer data from 5368 AGES-Reykjavik participants and genetic associations with FEV1 from a publicly available GWAS (n = 400,102).

RESULTS

In observational analyses, 530 SOMAmers were associated with FEV1 after multiple testing adjustment (FDR < 0.05). The most significant were Retinoic Acid Receptor Responder 2 (RARRES2), R-Spondin 4 (RSPO4) and Alkaline Phosphatase, Placental Like 2 (ALPPL2). Of the 257 SOMAmers with genetic instruments available, eight were associated with FEV1 in MR analyses. Three were directionally consistent with the observational estimate, Thrombospondin 2 (THBS2), Endoplasmic Reticulum Oxidoreductase 1 Beta (ERO1B) and Apolipoprotein M (APOM). THBS2 was further supported by a colocalization analysis. Analyses in the reverse direction, testing whether changes in SOMAmer levels were caused by changes in FEV1, were performed but no significant associations were found after multiple testing adjustments.

CONCLUSIONS

In summary, this large scale proteogenomic analyses of FEV1 reveals circulating protein markers of FEV1, as well as several proteins with potential causality to lung function.

Genome-wide association study of preserved ratio impaired spirometry (PRISm)

BACKGROUND

Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≥0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities.

METHODS

We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed.

RESULTS

22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits.

CONCLUSION

This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.

Longitudinal association of polycyclic aromatic hydrocarbons and genetic risk with lung function

To quantify the association of polycyclic aromatic hydrocarbons (PAHs) and the polygenic risk score (PRS) with lung function decline, we developed a repeated-measures study with 4681 observations from baseline and 6-year follow-up of the Wuhan-Zhuhai cohort. Lung function and urinary monohydroxylated PAH metabolites (OH-PAHs) were measured for each observation. The PRS was derived from 246 lung function-associated genetic variants weighted by the effect size of the decreasing ratio of forced expiratory volume in 1 s by forced vital capacity (FEV1/FVC). Linear mixed models were used to estimate the longitudinal exposure-response relationships between OH-PAHs and lung function, and to evaluate the interactions between OH-PAHs and PRS on the longitudinal change of lung function. We found that each 1-unit increase in log-transformed values of 9-hydroxyfluorene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 9-hydroxyphenanthrene, 2-hydroxyphenanthrene, 1-hydroxyphenanthrene, 1-hydroxypyrene, low molecular weight OH-PAHs (ΣLMW-OH-PAHs), and total OH-PAHs (ΣOH-PAHs) was associated with an annual change in FEV1/FVC of -0.140, -0.112, -0.260, -0.300, -0.159, -0.220, -0.145, -0.156, and -0.177 %/year, respectively. Interactions on the annual decline of FEV1/FVC were detected between ΣLMW-OH-PAHs and PRS (-0.010 %/year, 95% confidence interval -0.018 to -0.001, Pint = 0.0228), and between ΣOH-PAHs and PRS (-0.010 %/year, -0.018 to -0.001, Pint = 0.0203). These results indicated that specific and total urinary OH-PAHs were associated with the longitudinal FEV1/FVC decline, and ΣLMW-OH-PAHs as well as ΣOH-PAHs interacted with PRS on the annual decline of FEV1/FVC.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

Genetic and observational associations of lung function with gastrointestinal tract diseases: pleiotropic and mendelian randomization analysis

BACKGROUND

The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated.

METHODS

We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis.

RESULTS

We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, PPLACO=1.38 × 10- 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis.

CONCLUSIONS

Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

Prediction and stratification of longitudinal risk for chronic obstructive pulmonary disease across smoking behaviors

Smoking is the leading risk factor for chronic obstructive pulmonary disease (COPD) worldwide, yet many people who never smoke develop COPD. We perform a longitudinal analysis of COPD in the UK Biobank to derive and validate the Socioeconomic and Environmental Risk Score which captures additive and cumulative environmental, behavioral, and socioeconomic exposure risks beyond tobacco smoking. The Socioeconomic and Environmental Risk Score is more predictive of COPD than smoking status and pack-years. Individuals in the highest decile of the risk score have a greater risk for incident COPD compared to the remaining population. Never smokers in the highest decile of exposure risk are more likely to develop COPD than previous and current smokers in the lowest decile. In general, the prediction accuracy of the Social and Environmental Risk Score is lower in non-European populations. While smoking status is often considered in screening COPD, our finding highlights the importance of other non-smoking environmental and socioeconomic variables.

Sex-Specific Genetic Determinants of Asthma-COPD Phenotype and COPD in Middle-Aged and Older Canadian Adults: An Analysis of CLSA Data

The etiology of sex differences in the risk of asthma-COPD phenotype and COPD is still not completely understood. Genetic and environmental risk factors are commonly believed to play an important role. This study aims to identify sex-specific genetic markers associated with asthma-COPD phenotype and COPD using the Canadian Longitudinal Study on Aging (CLSA) Baseline Comprehensive and Genomic data. There were a total of 1,415 COPD cases. Out of them, 504 asthma-COPD phenotype cases were identified. 20,524 participants without a diagnosis of asthma and COPD served as controls. We performed genome-wide SNP-by-sex interaction analysis. SNPs with an interaction p-value < 10^-5 were included in a sex-stratified multivariable logistic regression for asthma-COPD phenotype and COPD outcomes. 18 and 28 SNPs had a significant interaction term p-value < 10^-5 with sex in the regression analyses of asthma-COPD phenotype and COPD outcomes, respectively. Sex-stratified multivariable analysis of asthma-COPD phenotype showed that 7 SNPs in/near SMYD3, FHIT, ZNF608, RIMBP2, ZNF133, BPIFB1, and S100B loci were significant in males. Sex-stratified multivariable analysis of COPD showed that 8 SNPs in/near MAGI1, COX18, OSTC, ELOVL5, C7orf72 FGF14, and NKAIN4 were significant in males, and 4 SNPs in/near genes CAMTA1, SATB2, PDE10A, and LINC00908 were significant in females. An SNP in the ZPBP gene was associated with COPD in both males and females. Identification of sex-specific loci associated with asthma-COPD phenotype and COPD may offer valuable evidence toward a better understanding of the sex-specific differences in the pathophysiology of the diseases.

Polygenic risk scores identify heterogeneity in asthma and chronic obstructive pulmonary disease

BACKGROUND

Asthma and chronic obstructive pulmonary disease (COPD) have distinct and overlapping genetic and clinical features.

OBJECTIVE

We sought to test the hypothesis that polygenic risk scores (PRSs) for asthma (PRSAsthma) and spirometry (FEV1 and FEV1/forced vital capacity; PRSspiro) would demonstrate differential associations with asthma, COPD, and asthma-COPD overlap (ACO).

METHODS

We developed and tested 2 asthma PRSs and applied the higher performing PRSAsthma and a previously published PRSspiro to research (Genetic Epidemiology of COPD study and Childhood Asthma Management Program, with spirometry) and electronic health record-based (Mass General Brigham Biobank and Genetic Epidemiology Research on Adult Health and Aging [GERA]) studies. We assessed the association of PRSs with COPD and asthma using modified random-effects and binary-effects meta-analyses, and ACO and asthma exacerbations in specific cohorts. Models were adjusted for confounders and genetic ancestry.

RESULTS

In meta-analyses of 102,477 participants, the PRSAsthma (odds ratio [OR] per SD, 1.16 [95% CI, 1.14-1.19]) and PRSspiro (OR per SD, 1.19 [95% CI, 1.17-1.22]) both predicted asthma, whereas the PRSspiro predicted COPD (OR per SD, 1.25 [95% CI, 1.21-1.30]). However, results differed by cohort. The PRSspiro was not associated with COPD in GERA and Mass General Brigham Biobank. In the Genetic Epidemiology of COPD study, the PRSAsthma (OR per SD: Whites, 1.3; African Americans, 1.2) and PRSspiro (OR per SD: Whites, 2.2; African Americans, 1.6) were both associated with ACO. In GERA, the PRSAsthma was associated with asthma exacerbations (OR, 1.18) in Whites; the PRSspiro was associated with asthma exacerbations in White, LatinX, and East Asian participants.

CONCLUSIONS

PRSs for asthma and spirometry are both associated with ACO and asthma exacerbations. Genetic prediction performance differs in research versus electronic health record-based cohorts.

Impact of intrinsic and extrinsic risk factors on early-onset lung disease in cystic fibrosis

BACKGROUND

Although respiratory pathology is known to develop in young children with cystic fibrosis (CF), the determinants of early-onset lung disease have not been elucidated.

OBJECTIVE

We aimed to determine the impact of potential intrinsic and extrinsic risk factors during the first 3 years of life, testing the hypothesis that both contribute significantly to early-onset CF lung disease.

DESIGN

We studied 104 infants born during 2012-2017, diagnosed through newborn screening by age 3 months, and evaluated comprehensively to 36 months of age. Lung disease manifestations were quantified with a new scoring system known as CFELD for Cystic Fibrosis Early-onset Lung Disease. The variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene were determined and categorized. Whole genome sequencing was performed on each subject and the data transformed to polygenic risk scores (PRS) that aggregate variants associated with lung function. Extrinsic factors included socioeconomic status (SES) indicators and environmental experiences such as exposures to smoking, pets, and daycare.

RESULTS

We found by univariate analysis that CFTR genotype and genetic modifiers aggregated by the PRS method were significantly associated with early-onset CF lung disease. Ordinal logistic regression analysis demonstrated that high and stable SES (maternal education ≥community college, stable 2-parent home, and not receiving Medicaid) and better growth (weight-for-age and height-for-age z-scores) reduced risks, while exposure to smoking and daycare ≥20 h/week increased the risk of CFELD severity.

CONCLUSIONS

Extrinsic, modifiable determinants are influential early and potentially as important as the intrinsic risk factors in the onset of CF lung disease.

TNS1 and NRXN1 Genes Interacting With Early-Life Smoking Exposure in Asthma-Plus-Eczema Susceptibility

PURPOSE

Numerous genes have been associated with allergic diseases (asthma, allergic rhinitis, and eczema), but they explain only part of their heritability. This is partly because most previous studies ignored complex mechanisms such as gene-environment (G-E) interactions and complex phenotypes such as co-morbidity. However, it was recently evidenced that the co-morbidity of asthma-plus-eczema appears as a sub-entity depending on specific genetic factors. Besides, evidence also suggest that gene-by-early life environmental tobacco smoke (ETS) exposure interactions play a role in asthma, but were never investigated for asthma-plus-eczema. To identify genetic variants interacting with ETS exposure that influence asthma-plus-eczema susceptibility.

METHODS

To conduct a genome-wide interaction study (GWIS) of asthma-plus-eczema according to ETS exposure, we applied a 2-stage strategy with a first selection of single nucleotide polymorphisms (SNPs) from genome-wide association meta-analysis to be tested at a second stage by interaction meta-analysis. All meta-analyses were conducted across 4 studies including a total of 5,516 European-ancestry individuals, of whom 1,164 had both asthma and eczema.

RESULTS

Two SNPs showed significant interactions with ETS exposure. They were located in 2 genes, NRXN1 (2p16) and TNS1 (2q35), never reported associated and/or interacting with ETS exposure for asthma, eczema or more generally for allergic diseases. TNS1 is a promising candidate gene because of its link to lung and skin diseases with possible interactive effect with tobacco smoke exposure.

CONCLUSIONS

This first GWIS of asthma-plus-eczema with ETS exposure underlines the importance of studying sub-phenotypes such as co-morbidities as well as G-E interactions to detect new susceptibility genes.

Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans

BACKGROUND

Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.

METHODS

New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined.

RESULTS

The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome.

CONCLUSION

Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

Association between severe bronchiolitis in infancy and age 6-year lung function

BACKGROUND AND OBJECTIVES

Understanding early life risk factors for decreased lung function could guide prevention efforts and improve lung health throughout the lifespan. Our objective was to investigate the association between history of severe (hospitalized) bronchiolitis in infancy and age 6-year lung function.

METHODS

We analyzed data from two prospective cohort studies: infants hospitalized with bronchiolitis and a parallel cohort of healthy infants. Children were followed longitudinally, and spirometry was performed at age 6 years. To examine the relationship between history of severe bronchiolitis and primary outcomes - FEV1% predicted (pp) and FEV1/FVCpp - we used multivariable linear regression models adjusted for insurance status, perterm birth, secondhand smoke exposure, breastfeeding status, traffic-related air pollution and polygenic risk score. Secondary outcomes included FVCpp and bronchodilator responsiveness (BDR).

RESULTS

Age 6-year spirometry was available for 425 children with history of severe bronchiolitis in infancy and 48 controls. Unadjusted analysis revealed that while most children had normal range lung function, children with a history of severe bronchiolitis had lower FEV1pp and FEV1/FVCpp. In adjusted analyses, the same findings were observed: FEV1pp was 8% lower (p = 0.004) and FEV1/FVCpp was 4% lower (p = 0.007) in children with history of severe bronchiolitis versus controls. FVC and BDR did not differ between groups.

CONCLUSIONS

Children with severe bronchiolitis in infancy have decreased FEV1 and FEV1/FVC at age 6 years, compared to controls. These children may be at increased risk for chronic respiratory illness later in life.

The COPD GWAS gene ADGRG6 instructs function and injury response in human iPSC-derived type II alveolar epithelial cells

Emphysema and chronic obstructive pulmonary disease (COPD) most commonly result from the effects of environmental exposures in genetically susceptible individuals. Genome-wide association studies have implicated ADGRG6 in COPD and reduced lung function, and a limited number of studies have examined the role of ADGRG6 in cells representative of the airway. However, the ADGRG6 locus is also associated with DLCO/VA, an indicator of gas exchange efficiency and alveolar function. Here, we sought to evaluate the mechanistic contributions of ADGRG6 to homeostatic function and disease in type 2 alveolar epithelial cells. We applied an inducible CRISPR interference (CRISPRi) human induced pluripotent stem cell (iPSC) platform to explore ADGRG6 function in iPSC-derived AT2s (iAT2s). We demonstrate that ADGRG6 exerts pleiotropic effects on iAT2s including regulation of focal adhesions, cytoskeleton, tight junctions, and proliferation. Moreover, we find that ADGRG6 knockdown in cigarette smoke-exposed iAT2s alters cellular responses to injury, downregulating apical complexes in favor of proliferation. Our work functionally characterizes the COPD GWAS gene ADGRG6 in human alveolar epithelium.