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.

LRP1 Repression by SNAIL Results in ECM Remodeling in Genetic Risk for Vascular Diseases

BACKGROUND

Genome-wide association studies implicate common genetic variations in the LRP1 (low-density lipoprotein receptor-related protein 1 gene) locus at risk for multiple vascular diseases and traits. However, the underlying biological mechanisms are unknown.

METHODS

Fine mapping analyses included Bayesian colocalization to identify the most likely causal variant. Human induced pluripotent stem cells were genome-edited using CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated protein 9) to delete or modify candidate enhancer regions and generate LRP1 knockout cell lines. Cells were differentiated into smooth muscle cells through a mesodermal lineage. Transcription regulation was assessed using luciferase reporter assay, transcription factor knockdown, and chromatin immunoprecipitation. Phenotype changes in cells were conducted using cellular assays, bulk RNA sequencing, and mass spectrometry.

RESULTS

Multitrait colocalization analyses pointed at rs11172113 as the most likely causal variant in LRP1 for fibromuscular dysplasia, migraine, pulse pressure, and spontaneous coronary artery dissection. We found the rs11172113-T allele to associate with higher LRP1 expression. Genomic deletion in induced pluripotent stem cell-derived smooth muscle cells supported rs11172113 to locate in an enhancer region regulating LRP1 expression. We found transcription factors MECP2 (methyl CpG binding protein 2) and SNAIL (Zinc Finger Protein SNAI1) to repress LRP1 expression through an allele-specific mechanism, involving SNAIL interaction with disease risk allele. LRP1 knockout decreased induced pluripotent stem cell-derived smooth muscle cell proliferation and migration. Differentially expressed genes were enriched for collagen-containing extracellular matrix and connective tissue development. LRP1 knockout and deletion of rs11172113 enhancer showed potentiated canonical TGF-β (transforming growth factor beta) signaling through enhanced phosphorylation of SMAD2/3 (Mothers against decapentaplegic homolog 2/3). Analyses of the protein content of decellularized extracts indicated partial extracellular matrix remodeling involving enhanced secretion of CYR61 (cystein rich angiogenic protein 61), a known LRP1 ligand involved in vascular integrity and TIMP3 (Metalloproteinase inhibitor 3), implicated in extracellular matrix maintenance and also known to interact with LRP1.

CONCLUSIONS

Our findings support allele-specific LRP1 expression repression by the endothelial-to-mesenchymal transition regulator SNAIL. We propose decreased LRP1 expression in smooth muscle cells to remodel the extracellular matrix enhanced by TGF-β as a potential mechanism of this pleiotropic locus for vascular diseases.

Genome-wide association study of susceptibility to Pseudomonas aeruginosa infection in cystic fibrosis

BACKGROUND

Pseudomonas aeruginosa is a common pathogen that contributes to progressive lung disease in cystic fibrosis (CF). Genetic factors other than CF-causing CFTR (CF transmembrane conductance regulator) variations contribute ∼85% of the variation in chronic P. aeruginosa infection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility to P. aeruginosa infection.

MATERIALS AND METHODS

We conducted a genome-wide association study of chronic P. aeruginosa infection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronic P. aeruginosa infection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bidirectional Mendelian randomisation analysis.

RESULTS

Two novel genome-wide significant loci with lead single nucleotide polymorphisms (SNPs) rs62369766 (chr5p12; p=1.98×10-8) and rs927553 (chr13q12.12; p=1.91×10-8) were associated with chronic P. aeruginosa infection age. The rs62369766 locus was validated using an independent French cohort (n=501). Furthermore, the PRS constructed from CF lung function-associated SNPs was significantly associated with chronic P. aeruginosa infection age (p=0.002). Finally, our analysis presented evidence for a causal effect of lung function on chronic P. aeruginosa infection age (β=0.782 years, p=4.24×10-4). In the reverse direction, we observed a moderate effect (β=0.002, p=0.012).

CONCLUSIONS

We identified two novel loci that are associated with chronic P. aeruginosa infection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship between P. aeruginosa infection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections, which account for significant remaining morbidity in CF.

Association of inflammatory cytokines with lung function, chronic lung diseases, and COVID-19

We investigated the effects of 35 inflammatory cytokines on respiratory outcomes, including COVID-19, asthma (atopic and non-atopic), chronic obstructive pulmonary disease (COPD), and pulmonary function indices, using Mendelian randomization and colocalization analyses. The emerging associations were further explored using observational analyses in the UK Biobank. We found an inverse association between genetically predicted macrophage colony stimulating factor (MCSF), soluble intercellular adhesion molecule-1 (sICAM), and soluble vascular cell adhesion molecule-1 with risk of COVID-19 outcomes. sICAM was positively associated with atopic asthma risk, whereas tumor necrosis factor-alfa showed an inverse association. A positive association was shown between interleukin-18 and COPD risk (replicated in observational analysis), whereas an inverse association was shown for interleukin-1 receptor antagonist (IL-1ra). IL-1ra and monocyte chemotactic protein-3 were positively associated with lung function indices, whereas inverse associations were shown for MCSF and interleukin-18 (replicated in observational analysis). Our results point to these cytokines as potential pharmacological targets for respiratory traits.

No genetic causal relationship between lung function and osteoporosis - evidence from a mendelian randomization study

For a long time, the decline in lung function has been regarded as a potential factor associated with the risk of osteoporosis (OP). Although several observational studies have investigated the relationship between lung function and OP, their conclusions have been inconsistent. Given that Mendelian randomization (MR) studies can help reduce the interference of confounding factors on outcomes, we adopted this approach to explore the causal relationship between lung function and OP at the genetic level. To investigate the potential causality between lung function (FVC, FEV1, FEV1/FVC, PEF) and OP, we conducted a MR analysis employing three approaches: inverse variance weighted (IVW), MR-Egger, and weighted median. We used Cochran's Q test to detect potential heterogeneity, MR-Egger regression to evaluate directional pleiotropy, and the MR-PRESSO method to evaluate horizontal pleiotropy. In addition, we used MR-PRESSO and MR radial methods to exclude SNPs exhibiting pleiotropic outliers. Upon identification of potential outliers, we removed them and subsequently ran MR analysis again to assess the reliability of our findings. The MR analysis suggested that there was no causal effect of lung function (FVC, PEF, FEV1/FVC, FEV1) on OP, which is consistent with the. results after excluding potential outliers using MR-PRESSO and MR radial. methods. Sensitivity analysis confirmed the reliability and consistency of these. results. The study concluded that there is no causal link between lung function and OP. The association found in observational studies might be attributable to shared risk factors.

Mid-pass whole-genome sequencing in a Malagasy cohort uncovers body composition associations

The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location and find high rates of hypertension, particularly in the Southern Highlands sampling site, as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214 minimally related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and potentially impacts our understanding of human health and disease.

A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study

The Long Life Family Study (LLFS) enrolled 4953 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 ).

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.

Association between lung function and risk of microvascular diseases in patients with diabetes: A prospective cohort and Mendelian randomization study

BACKGROUND AND AIMS

To investigate causal relationships of lung function with risks microvascular diseases among participants with diabetes, type 2 diabetes mellitus (T2DM) and type 1 diabetes mellitus (T1DM), respectively, in prospective and Mendelian randomization (MR) study.

METHODS AND RESULTS

14,617 participants with diabetes and without microvascular diseases at baseline from the UK Biobank were included in the prospective analysis. Of these, 13,421 had T2DM and 1196 had T1DM. The linear MR analyses were conducted in the UK Biobank with 6838 cases of microvascular diseases and 10,755 controls. Lung function measurements included forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). The study outcome was microvascular diseases, a composite outcome including chronic kidney diseases, retinopathy and peripheral neuropathy. During a median follow-up of 12.1 years, 2668 new-onset microvascular diseases were recorded. FVC (%predicted) was inversely associated with the risk of new-onset microvascular diseases in participants with diabetes (Per SD increment, adjusted HR = 0.86; 95%CI:0.83-0.89), T2DM (Per SD increment, adjusted HR = 0.86; 95%CI:0.82-0.90) and T1DM (Per SD increment, adjusted HR = 0.87; 95%CI: 0.79-0.97), respectively. Similar results were found for FEV1 (%predicted). In MR analyses, genetically predicted FVC (adjusted RR = 0.55, 95%CI:0.39-0.77) and FEV1 (adjusted RR = 0.48, 95%CI:0.28-0.83) were both inversely associated with microvascular diseases in participants with T1DM. No significant association was found in those with T2DM. Similar findings were found for each component of microvascular diseases.

CONCLUSION

There was a causal inverse association between lung function and risks of microvascular diseases in participants with T1DM, but not in those with T2DM.

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

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. Mouse body composition was assessed using dual-energy X-ray absorptiometry. Mouse lung function was measured using flexiVent.

RESULTS

Contrary to prior publications, the KO was not neonatal lethal. KO mice had lower body weight and shorter tibial length than wild-type (WT) mice. Their body composition revealed lower soft weight, fat weight, and bone mineral content. 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.

Tobacco and COPD: presenting the World Health Organization (WHO) Tobacco Knowledge Summary

The WHO recently published a Tobacco Knowledge Summary (TKS) synthesizing current evidence on tobacco and COPD, aiming to raise awareness among a broad audience of health care professionals. Furthermore, it can be used as an advocacy tool in the fight for tobacco control and prevention of tobacco-related disease. This article builds on the evidence presented in the TKS, with a greater level of detail intended for a lung-specialist audience. Pulmonologists have a vital role to play in advocating for the health of their patients and the wider population by sharing five key messages: (1) Smoking is the leading cause of COPD in high-income countries, contributing to approximately 70% of cases. Quitting tobacco is an essential step toward better lung health. (2) People with COPD face a significantly higher risk of developing lung cancer. Smoking cessation is a powerful measure to reduce cancer risk. (3) Cardiovascular disease, lung cancer and type-2 diabetes are common comorbidities in people with COPD. Quitting smoking not only improves COPD management, but also reduces the risk of developing these coexisting conditions. (4) Tobacco smoke also significantly impacts children's lung growth and development, increasing the risk of respiratory infections, asthma and up to ten other conditions, and COPD later in life. Governments should implement effective tobacco control measures to protect vulnerable populations. (5) The tobacco industry's aggressive strategies in the marketing of nicotine delivery systems and all tobacco products specifically target children, adolescents, and young adults. Protecting our youth from these harmful tactics is a top priority.

Causal effects of air pollutants on lung function and chronic respiratory diseases: a Mendelian randomization study

Objectives

Our study aims to clarify the causality between air pollutants and lung function, chronic respiratory diseases, and the potential mediating effects of inflammatory proteins.

Method

We employed Mendelian Randomization (MR) analysis with comprehensive instrumental variables screening criteria to investigate the effects of air pollutants on lung function and chronic lung diseases. Our study incorporated genetic instruments for air pollutants, ensuring F-statistics above 20.86. A total of 18 MR analyses were conducted using the inverse-variance weighted approach, along with heterogeneity and pleiotropy tests to validate the results. Mediated MR analysis was utilized to evaluate the inflammatory proteins mediating the effects of air pollutants.

Result

MR analysis demonstrated significant causal interactions of particulate matter 2.5 (PM2.5), PM10, and Nitrogen dioxide (NO2) with lung function decline. Specifically, PM10 negatively affected forced expiratory volume in one second (FEV1) (OR: 0.934, 95% CI: 0.904-0.965, p = 4.27 × 10-5), forced vital capacity (FVC) (OR: 0.941, 95% CI: 0.910-0.972, p = 2.86 × 10-4), and FEV1/FVC (OR: 0.965, 95% CI: 0.934-0.998, p = 0.036). PM2.5 and NO2 were identified as potential risk factors for impairing FEV1 (OR: 0.936, 95% CI: 0.879-0.998, p = 0.042) and FEV1/FVC (OR: 0.943, 95% CI: 0.896-0.992, p = 0.024), respectively. For chronic respiratory diseases, PM2.5 and NO2 were associated with increased COPD incidence (OR: 1.273, 95% CI: 1.053-1.541, p = 0.013 for PM2.5; OR: 1.357, 95% CI: 1.165-1.581, p = 8.74 × 10-5 for NO2). Sensitivity analyses confirmed the robustness of these findings, with no significant heterogeneity or horizontal pleiotropy detected.

Conclusion

Our study ascertained the causal correlations of air pollutants with lung function and COPD, emphasizing the importance of reducing air pollution. Interleukin-17A mediates the reduction of FEV1 and FVC by PM10, revealing potential therapeutic targets.

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 a 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.

Genetics and Genomics of Pulmonary Fibrosis: Charting the Molecular Landscape and Shaping Precision Medicine

Recent genetic and genomic advancements have elucidated the complex etiology of idiopathic pulmonary fibrosis (IPF) and other progressive fibrotic interstitial lung diseases (ILDs), emphasizing the contribution of heritable factors. This state-of-the-art review synthesizes evidence on significant genetic contributors to pulmonary fibrosis (PF), including rare genetic variants and common SNPs. The MUC5B promoter variant is unusual, a common SNP that markedly elevates the risk of early and established PF. We address the utility of genetic variation in enhancing understanding of disease pathogenesis and clinical phenotypes, improving disease definitions, and informing prognosis and treatment response. Critical research gaps are highlighted, particularly the underrepresentation of non-European ancestries in PF genetic studies and the exploration of PF phenotypes beyond usual interstitial pneumonia/IPF. We discuss the role of telomere length, often critically short in PF, and its link to progression and mortality, underscoring the genetic complexity involving telomere biology genes (TERT, TERC) and others like SFTPC and MUC5B. In addition, we address the potential of gene-by-environment interactions to modulate disease manifestation, advocating for precision medicine in PF. Insights from gene expression profiling studies and multiomic analyses highlight the promise for understanding disease pathogenesis and offer new approaches to clinical care, therapeutic drug development, and biomarker discovery. Finally, we discuss the ethical, legal, and social implications of genomic research and therapies in PF, stressing the need for sound practices and informed clinical genetic discussions. Looking forward, we advocate for comprehensive genetic testing panels and polygenic risk scores to improve the management of PF and related ILDs across diverse populations.

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.

The influence of CLEC5A on early macrophage-mediated inflammation in COPD progression

Chronic obstructive pulmonary disease (COPD) is a complex syndrome with poorly understood mechanisms driving its early progression (GOLD stages 1-2). Elucidating the genetic factors that influence early-stage COPD, particularly those related to airway inflammation and remodeling, is crucial. This study analyzed lung tissue sequencing data from patients with early-stage COPD (GSE47460) and smoke-exposed mice. We employed Weighted Gene Co-Expression Network Analysis (WGCNA) and machine learning to identify potentially pathogenic genes. Further analyses included single-cell sequencing from both mice and COPD patients to pinpoint gene expression in specific cell types. Cell-cell communication and pseudotemporal analyses were conducted, with findings validated in smoke-exposed mice. Additionally, Mendelian randomization (MR) was used to confirm the association between candidate genes and lung function/COPD. Finally, functional validation was performed in vitro using cell cultures. Machine learning analysis of 30 differentially expressed genes identified 8 key genes, with CLEC5A emerging as a potential pathogenic factor in early-stage COPD. Bioinformatics analyses suggested a role for CLEC5A in macrophage-mediated inflammation during COPD. Two-sample Mendelian randomization linked CLEC5A single nucleotide polymorphisms (SNPs) with Forced Expiratory Volume in One Second (FEV1), FEV1/Forced Vital Capacity (FVC) and early/later on COPD. In vitro, the knockdown of CLEC5A led to a reduction in inflammatory markers within macrophages. Our study identifies CLEC5A as a critical gene in early-stage COPD, contributing to its pathogenesis through pro-inflammatory mechanisms. This discovery offers valuable insights for developing early diagnosis and treatment strategies for COPD and highlights CLEC5A as a promising target for further investigation.

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.

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.

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.

Inverse association between lung function and nonalcoholic fatty liver disease: An observational and mendelian randomization study

BACKGROUND AND AIM

The association between lung function with non-alcoholic fatty liver disease (NAFLD) in the general population remains unknown. We aimed to examine the association between lung function and NAFLD among the general population in an observational and Mendelian randomization (MR) study.

METHODS AND RESULTS

340, 253 participants without prior liver diseases were included from the UK Biobank. Of these, 30,397 participants had liver proton density fat fraction (PDFF) measurements by magnetic resonance image (MRI). Lung function parameters included forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC). The primary outcome was the presence of NAFLD, defined as a PDFF greater than 5.5%. The secondary outcome included incident severe NAFLD and severe liver diseases (including liver cirrhosis, liver failure, hepatocellular carcinoma and liver-related death), defined by the International Classification of Disease codes with different data sources. During a media follow-up duration of 9.3 years, 7335 (24.1%) the presence of NAFLD cases were documented. There was an inverse association of FEV1 (% predicted) (Per SD increment, adjusted OR = 0.91, 95%CI: 0.88-0.94) and FVC (% predicted) (Per SD increment, adjusted OR = 0.90, 95%CI: 0.87-0.92) with the presence of NAFLD. Similar results were found for incident severe NAFLD, severe liver disease, liver cirrhosis, liver failure and liver-related death. MR analyses showed that the genetically predicted FEV1 (adjusted OR = 0.63, 95%CI: 0.46-0.87) and FVC (adjusted OR = 0.69, 95%CI: 0.51-0.95) were both inversely associated with the presence of NAFLD.

CONCLUSIONS

There was an inverse causal relationship between lung function and NAFLD in the general population.

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.

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.

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.