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

Mendelian randomisation studies for causal inference in chronic obstructive pulmonary disease: A narrative review

BACKGROUND AND OBJECTIVE

Most non-randomised controlled trials are unable to establish clear causal relationships in chronic obstructive pulmonary disease (COPD) due to the presence of confounding factors. This review summarises the evidence that the Mendelian randomisation method can be a powerful tool for performing causal inferences in COPD.

METHODS

A non-systematic search of English-language scientific literature was performed on PubMed using the following keywords: 'Mendelian randomisation', 'COPD', 'lung function', and 'GWAS'. No date restrictions were applied. The types of articles selected included randomised controlled trials, cohort studies, observational studies, and reviews.

RESULTS

Mendelian randomisation is becoming an increasingly popular method for identifying the risk factors of COPD. Recent Mendelian randomisation studies have revealed some risk factors for COPD, such as club cell secretory protein-16, impaired kidney function, air pollutants, asthma, and depression. In addition, Mendelian randomisation results suggest that genetically predicted factors such as PM2.5, inflammatory cytokines, growth differentiation factor 15, docosahexaenoic acid, and testosterone may have causal relationships with lung function.

CONCLUSION

Mendelian randomisation is a robust method for performing causal inferences in COPD research as it reduces the impact of confounding factors.

Identification of genetic variants of the IL18R1 gene in association with COPD susceptibility

BACKGROUND

Although existing studies have identified some genetic loci associated with chronic obstructive pulmonary disease (COPD) susceptibility, many variants remain to be discovered. The aim of this study was to further explore the potential relationship between IL18R1 single nucleotide polymorphisms (SNPs) and COPD risk.

METHODS

Nine hundred and ninety-six subjects were recruited (498 COPD cases and 498 healthy controls). Five candidate SNPs of IL18R1 were selected and genotyped using MassARRAY iPLEX platform. Logistic regression analysis was performed to assess the association of these SNPs with COPD risk. Multifactor dimensionality reduction (MDR) software was applied to calculate the interaction of SNP-SNP on COPD risk.

RESULTS

IL18R1 rs9807989 (OR = 0.42, p < .001), rs3771166 (OR = 0.40, p < .001) and rs6543124 (OR = 0.44, p < .001) were associated with the reduced COPD risk, while rs2287037 (OR = 2.71, p < .001) and rs2058622 (OR = 2.06, p < .001) might be the risk-increasing factor for COPD occurrence in both the overall analysis and subgroup analysis (age, gender, drinking, and smoking). The best multi-locus model was the combination of rs2058622 and rs3771166.

CONCLUSION

Our study provided a reference and basis for investigating the association of IL18R1 polymorphisms with COPD risk.

Uncovering covariance patterns across energy balance traits enables the discovery of new obesity-related genes

OBJECTIVE

Effective solutions to obesity remain elusive, partly owing to its root in a positive energy balance (EB), which stems from the interplay of numerous traits spanning body size and composition, diet, physical activity, and metabolic profile. Nevertheless, EB-contributing traits are typically studied in isolation. We integrate numerous EB-related traits measured in the UK Biobank to uncover the underlying patterns of EB and associated genes in study participants.

METHODS

We used sparse factor analysis to integrate traits and performed genome-wide association analyses on the integrated phenotypes to elucidate EB-related genes and metabolic pathways. We performed pleiotropy analyses on candidate single-nucleotide polymorphisms to uncover the genetic basis of EB.

RESULTS

We identified multiple genes and genomic regions associated with EB, including many that have previously not been directly associated with obesity measures (e.g., MIR5591, FNDC3B, ANAPC10, SULT1A1, AXIN1, SKIDA1, ERLIN1, DOCK7), which we validated using an independent subset of the UK Biobank dataset along with data from the Atherosclerosis Risk in Communities cohort. We found that the covariances in EB traits are primarily driven by genome-wide pleiotropic associations.

CONCLUSIONS

We offer new insight into EB patterns and the genetic basis of EB.

Maternal asthma and newborn DNA methylation

BACKGROUND

Prenatal exposure to maternal asthma may influence DNA methylation patterns in offspring, potentially affecting their susceptibility to later diseases including asthma.

OBJECTIVE

To investigate the relationship between parental asthma and newborn blood DNA methylation.

METHODS

Epigenome-wide association analyses were conducted in 13 cohorts on 7433 newborns with blood methylation data from the Illumina450K or EPIC array. We used fixed effects meta-analyses to identify differentially methylated CpGs (DMCs) and comb-p to identify differentially methylated regions (DMRs) associated with maternal asthma during pregnancy and maternal asthma ever. Paternal asthma was analyzed for comparison. Models were adjusted for covariates and cell-type composition. We examined whether implicated sites related to gene expression analyses in publicly available data for childhood blood and adult lung.

RESULTS

We identified 27 CpGs associated with maternal asthma during pregnancy at False Discovery Rate < 0.05 but none for maternal asthma ever. Two distinct CpGs were associated with paternal asthma. We observed 5 DMRs associated with maternal asthma during pregnancy 3 associated with maternal asthma ever and 13 DMRs associated with paternal asthma. Gene expression analysis using data in blood from 832 children and lung from 424 adults showed associations between identified DMCs using maternal asthma and expression of several genes, including HLA genes and HOXA5, previously implicated in asthma or lung function.

CONCLUSION

Parental asthma, especially maternal asthma during pregnancy, may be associated with alterations in newborn DNA methylation. These findings might shed light on underlying mechanisms for asthma susceptibility.

An integrated machine learning model of transcriptomic genes in multi-center chronic obstructive pulmonary disease reveals the causal role of TIMP4 in airway epithelial cell

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome, resulting in inconsistent findings across studies. Identifying a core set of genes consistently involved in COPD pathogenesis, independent of patient variability, is essential.

METHODS

We integrated lung tissue sequencing data from patients with COPD across two centers. We used weighted gene co-expression network analysis and machine learning to identify 13 potential pathogenic genes common to both centers. Additionally, a gene-based model was constructed to distinguish COPD at the molecular level and validated in independent cohorts. Gene expression in specific cell types was analyzed, and Mendelian randomization was used to confirm associations between candidate genes and lung function/COPD. Preliminary in vitro functional validation was performed on prioritized core candidate genes.

RESULTS

Tissue inhibitor of metalloproteinase 4 (TIMP4) was identified as a key pathogenic gene and validated in COPD cohorts. Further analysis using single-cell sequencing from mice and patients with COPD revealed that TIMP4 is involved in ciliated cells. In primary human airway epithelial cells cultured at the air-liquid interface, TIMP4 overexpression reduced ciliated cell numbers.

CONCLUSIONS

We developed a 13-gene model for distinguishing COPD at the molecular level and identified TIMP4 as a potential hub pathogenic gene. This finding provides insights into shared disease mechanisms and positions TIMP4 as a promising therapeutic target for further investigation.

Differential DNA methylation 7 months after SARS-CoV-2 infection

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), and SARS-CoV-2 has been linked to changes in DNA methylation (DNAm) patterns. Studies focused on post-SARS-CoV-2 infection and DNAm have been mainly carried out among severe COVID-19 cases or without distinguishing the severity of cases. However, investigations into mild and asymptomatic cases after SARS-CoV-2 infection are limited. In this study, we analyzed DNAm patterns of mild and asymptomatic cases seven months after SARS-CoV-2 infection in a household setting by conducting epigenome-wide association studies (EWAS).

RESULTS

We identified DNAm changes at 42 CpG sites associated with anti-SARS-CoV-2 antibody levels. We additionally report EWAS between COVID-19 cases and controls, with the case status being confirmed by either an antibody test or a PCR test. The EWAS with an antibody test case definition identified 172 CpG sites to be differentially methylated, while the EWAS with a PCR test case definition identified 502 CpG sites. Two common sites, namely cg17126990 (annotated to AFAP1L2) and cg25483596 (annotated to PC), were identified to be hypermethylated across the three EWAS. Both CpG sites have been reported to be involved in molecular pathways after SARS-CoV-2 infection. While AFAP1L2 has been found to be upregulated after SARS-CoV-2 infection, the pyruvate carboxylase (PC) activity seems to be affected by SARS-CoV-2 infection resulting in changes to the host cell metabolism. Additionally, an EWAS to assess persistent health restrictions among PCR-confirmed cases showed 40 CpG sites to be differentially methylated.

CONCLUSIONS

We detected associations between DNAm in individuals who had asymptomatic and mild SARS-CoV-2 infections as compared to their household controls. These findings contribute to our understanding of the molecular consequences of SARS-CoV-2 infection observed months after infection.

Epigenomic and proteomic analyses provide insights into early-life immune regulation and asthma development in infants

Infants with severe bronchiolitis (i.e., bronchiolitis requiring hospitalization) face increased risks of respiratory diseases in childhood. We conduct epigenome-wide association studies in a multi-ethnic cohort of these infants. We identify 61 differentially methylated regions in infant blood (<1 year of age) associated with recurrent wheezing by age 3 (170 cases, 318 non-cases) and/or asthma by age 6 (112 cases, 394 non-cases). These differentially methylated regions are enriched in the enhancers of peripheral blood neutrophils. Several differentially methylated regions exhibit interaction with rhinovirus infection and/or specific blood cell types. In the same blood samples, circulating levels of 104 proteins correlate with the differentially methylated regions, and many proteins show phenotypic association with asthma. Through Mendelian randomization, we find causal evidence supporting a protective role of higher plasma ST2 (also known as IL1RL1) protein against asthma. DNA methylation is also associated with ST2 protein level in infant blood. Taken together, our findings suggest the contribution of DNA methylation to asthma development through regulating early-life systemic immune responses.

Characterisation of a COPD-associated nephronectin (NPNT) functional splicing genetic variant in human lung tissue via long-read sequencing

BACKGROUND

Identification of COPD disease-causing genes is an important tool for understanding why COPD develops, who is at highest COPD risk and how new COPD treatments can be developed. Previous COPD genetic studies have identified a highly significant genetic association near NPNT (nephronectin), a gene involved in tissue repair, but the biological mechanisms underlying this association are unknown.

METHODS

Splicing quantitative trait locus (sQTL) analysis was performed to identify common genetic variants that alter RNA splicing in lung tissues. These lung sQTL signals were compared to COPD genetic association results near the NPNT gene using colocalisation analysis to determine whether genetic risk for COPD in this region may act through altered splicing. Long-read sequencing characterised COPD-associated splicing events at isoform-level resolution and in silico protein structural analysis identified likely functional effects of this alternative splicing.

RESULTS

An established COPD genetic risk variant, rs34712979-A, creates a cryptic splice acceptor site that causes four separate splicing changes in NPNT. The only one of these splicing changes that was associated with COPD phenotypes involved a cassette exon (exon 3). Long-read RNA sequencing demonstrated that the COPD risk allele causes a shift in isoform usage away from the dominant NPNT isoform B precursor, which excludes exon 3, to the isoform A precursor, which splices-in exon 3. AlphaFold protein structural analysis reveals that inclusion of this exon disrupts an epidermal growth factor-like functional domain in NPNT.

CONCLUSION

Genetic variants in the NPNT gene increase COPD risk by changing RNA splicing of NPNT in the lung.

Enhancer RNA transcription pinpoints functional genetic variants linked to asthma

Bidirectional enhancer RNA (eRNA) transcription is a widespread response to environmental signals and glucocorticoids. We investigated whether single nucleotide polymorphisms (SNPs) within dynamically regulated eRNA-transcribing regions contribute to genetic variation in asthma. Through applying multivariate regression modeling with permutation-based significance thresholding to a large clinical cohort, we identified novel associations between asthma and 35 SNPs located in eRNA-transcribing regions implicated in regulating cellular processes relevant to asthma, including rs258760 (mean allele frequency = 0.34, asthma odds ratio = 0.95; P = 5.04E-03). We show that rs258760 disrupts an active aryl hydrocarbon receptor (AHR) response element linked to transcriptional regulation of the glucocorticoid receptor gene by AHR ligands, which are commonly found in combusted air pollution. The role of rs258760 as a protective variant for asthma was independently validated using UK Biobank data. Our findings establish eRNA signatures as a tool for discovery of functional genetic variants and define a novel association between air pollution, glucocorticoid signaling and asthma.

Elucidating the Relationship Between Body Fat Index and Pulmonary Health: Insights from Cross-Sectional Analysis and Mendelian Randomization

Objective

To evaluate the relationship between body fat index and pulmonary health.

Methods

In the multiethnic population-based cross-sectional study, a multivariable linear regression model was adapted to assess the association of fat mass/percentage with forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC). The Mendelian Randomization (MR) method was used to assess the causal associations of fat mass/percentage in specific body parts with FEV1 and COPD risk. Sensitivity analysis of MR was performed to assess the robustness of estimates.

Results

In the cross-sectional analysis, a non-linear relationship was observed between fat mass and FEV1 without adjustment. After multivariate adjustment, the negative associations of fat mass/percentage with FEV1/FVC were found. In the MR study, genetically determined fat presented a negative causal effect on FEV1 (e.g., estimate = -0.170, P < 0.001 for left leg fat mass). The causal associations of genetically determined body fat with clinical diagnosis COPD were also determined (e.g., OR = 1.936, P < 0.001 per 1.9 kilograms increase in left leg fat mass).

Conclusion

We present strong evidence on the causal relationship between body fat mass/percentage and both the deterioration of lung function and the increased risk of COPD. Additional efforts are required to mitigate the negative effects of body fat.

A genome-wide cross-trait analysis characterizes the shared genetic architecture between lung and gastrointestinal diseases

Lung and gastrointestinal diseases often occur together, leading to more adverse health outcomes than when a disease of one of these systems occurs alone. However, the potential genetic mechanisms underlying lung-gastrointestinal comorbidities remain unclear. Here, we leverage lung and gastrointestinal trait data from individuals of European, East Asian and African ancestries, to perform a large-scale genetic cross trait analysis, followed by functional annotation and Mendelian randomization analysis to explore the genetic mechanisms involved in the development of lung-gastrointestinal comorbidities. Notably, we find significant genetic correlations between 27 trait pairs among the European population. The highest correlation is between chronic bronchitis and peptic ulcer disease. At the variant level, we identify 42 candidate pleiotropic genetic variants (3 of them previously uncharacterized) in 14 trait pairs by integrating cross-trait meta-analysis, fine-mapping and colocalization analyses. We also find 66 candidate pleiotropic genes, most of which were enriched in immune or inflammatory response-related activities. Causal inference approaches result in 4 potential lung-gastrointestinal associations. Introducing the gut microbiota as a variable establishes a relationship between the genus Parasutterella, gastro-oesophageal reflux disease and asthma. In summary, our findings highlight the genetic relationship between lung and gastrointestinal diseases, providing insights into the genetic mechanisms underlying the development of lung gastrointestinal comorbidities.

Identifying cross-tissue molecular targets of lung function by multi-omics integration analysis from DNA methylation and gene expression of diverse human tissues

BACKGROUND

Previous studies have reported several genetic loci associated with lung function. However, the mediating mechanism between these genetic loci and lung function phenotype is rarely explored. In this research, we used a cross-tissue multi-omics post-GWAS analysis to explain the associations between DNA methylation, gene expression, and lung function.

METHODS

We conducted integration analyses of lung function traits using genome-wide association study (GWAS) summary data alongside expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) derived from whole blood, utilizing multi-omics SMR and Bayesian colocalization analysis. Considering the genetic differences of tissues, we replicated the shared causal signals of eQTLs and lung function in 48 diverse tissues and the shared causal signals of mQTLs and lung function in 8 diverse tissues. Multi-trait colocalization analyses were utilized to identify the causal signals between gene expression in blood, blood cell traits, and lung function, as well as between cross-tissue gene expression in diverse tissues and lung function.

RESULTS

Eight genes from blood tissue were prioritized as FEV1 causal genes using multi-omics SMR analysis and COLOC colocalization analysis: EML3, UBXN2A, ROM1, ZBTB38, RASGRP3, FAIM, PABPC4, and SNIP1. Equally, five genes (CD46, EML3, UBXN2A, ZBTB38, and LMCD1) were prioritized as FVC causal genes and one gene (LMCD1) was prioritized as FEV1/FVC causal genes. The causal signals between 8 genes (EML3, ROM1, UBXN2A, ZBTB38, RASGRP3, FAIM, PABPC4, and CD46) and lung function were successfully replicated in diverse tissues. More importantly, MOLCO colocalization analysis showed that 3 genes (CD46, LMCD1, and ZBTB38) expression in blood, blood cell traits, and lung function traits shared the same causal signals. Finally, through cross-tissue colocalization analysis of multiple traits, we found that the heart-lung axis EML3 expressions and lung function mediate the same causal signal.

CONCLUSION

This study identified potential cross-tissue molecular targets associated with lung function traits from DNA methylation and gene expression of diverse tissues and explored the probable regulation mechanism of these molecular targets. This provides multi-omics and cross-tissue evidence for the molecular regulation mechanism of lung function and may provide new insight into the influence of crosstalk between organs and tissues on lung function.

Genome wide interaction study of genetic variants associated with lung function decline

Some genetic variants are associated with lung function decline and chronic obstructive pulmonary disease (COPD), but functional studies are necessary to confirm causality. We investigated the genetic susceptibility-associated lung function decline with or without COPD, using data from a community-based cohort (N = 8554). A genome-wide interaction study was conducted to identify the association between genetic variants and pulmonary function, and the way variants relate to lung impairment in accordance with smoking status and amount was examined. We further used a linear mixed model to examine the association and interaction to time effect. We found annual mean FEV1 declines of 41.7 mL for men and 33.4 mL for women, and the annual rate of decline in FEV1 was the fastest for current smokers. We also found a previously identified locus near FAM13A, the most significant SNPs from the results of two likelihood ratio tests for FEV1/FVC (P = 1.56 × 10-10). These selected SNPs were located in the upstream region of FAM13A on chromosome 4 and had similar minor allele frequencies (MAFs). Furthermore, we found that certain SNPs tended to have lower FEV1/FVC values, and lung function decreased much faster with time interactions. The SNP most associated with lung function decline was the rs75679995 SNP on chromosome 7, and those SNPs located within the TAD of the DNAH11 region and the eQTL of rs9991425 revealed a higher expression of MFAP3L and AADAT genes (P = 2.28 × 10-7 and 2.01 × 10-6, respectively). This is the first study to investigate gene-time interactions in lung function decline as a risk factor for COPD in the Korean population. In addition to replicating previously known signals for FAM13A, we identified two genomic regions (DNAH11, AADAT) that are potentially involved in gene-environment interactions, warranting further investigation to confirm their roles.

Nonlinear association of TSH with pulmonary ventilation: insights from bidirectional Mendelian randomization and cross-sectional study

BACKGROUND

Thyroid hormones play a crucial role in numerous physiological processes, including pulmonary function. However, the relationship between thyroid function and different patterns of pulmonary ventilation remains unclear.

METHODS

This study employed a bidirectional two-sample Mendelian randomization (MR) approach combined with a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) to explore the relationship between thyroid function and pulmonary ventilation indicators. We used genomic data from the ThyroidOmics Consortium and the UK Biobank to derive instrumental variables for thyroid and pulmonary functions. Adults from the NHANES 2007-2012 were included to validate the MR findings through weighted generalized linear model (GLM) regression and restricted cubic spline (RCS) analysis.

RESULTS

Genetically predicted thyroid-stimulating hormone (TSH) was associated with pulmonary ventilatory function (forced expiratory volume in 1 s (FEV1): β = 0.0223, 95% confidence interval (CI) 0.0040-0.0406, p-value = 0.0170), particularly with a restrictive ventilatory pattern (forced vital capacity (FVC): β = 0.0237, 95% CI 0.0047-0.0427, p-value = 0.0143). This association was more robust in the low TSH subgroup. Additionally, the NHANES data revealed a nonlinear relationship between both FEV1% predicted and FVC% predicted and TSH, characterized by a positive relationship at lower TSH ranges and a negative relationship at higher TSH ranges.

CONCLUSIONS

Our findings highlight a significant association between TSH levels and a restrictive ventilatory pattern, underscoring the importance of thyroid health in the clinical evaluation of certain pulmonary diseases. These insights may guide more personalized interventions in respiratory medicine.

Effect of vitamin A on adult lung function: a triangulation of evidence approach

BACKGROUND

Vitamin A, an essential micronutrient obtained through the diet, plays a crucial role in lung development and contributes to lung regeneration. We aimed to investigate its effect on adult lung function using triangulation of evidence from both observational and genetic data.

METHODS

Using data on 150 000 individuals from UK Biobank and correcting for measurement error (generalised structural equation modelling), we first investigated the association of dietary vitamin A intake (total vitamin A, carotene and retinol) with lung function (forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1)/FVC)). We then assessed the causality of these associations using Mendelian randomisation (MR), and we investigated the effects on adult lung function of 39 genes related to vitamin A, and their interaction with vitamin A intake.

FINDINGS

Our observational analysis suggests a positive association between carotene intake and FVC only (13.3 mL per 100 µg/day; p=2.9×10-9), with stronger associations in smokers, but no association of retinol intake with FVC or FEV1/FVC. The MR similarly shows a beneficial effect of serum beta-carotene on FVC only, with no effect of serum retinol on FVC nor FEV1/FVC. Nine of the vitamin A-related genes were associated with adult lung function, six of which have not been previously identified in genome-wide studies and three (NCOA2, RDH10, RXRB) in any type of genetic study of lung function. Five genes showed possible gene-vitamin A intake interactions.

INTERPRETATION

Our triangulation study provides convincing evidence for a causal effect of vitamin A, carotene in particular, on adult lung function, suggesting a beneficial effect of a carotene-rich diet on adult lung health.

Identification of Candidate Lung Function-Related Plasma Proteins to Pinpoint Drug Targets for Common Pulmonary Diseases: A Comprehensive Multi-Omics Integration Analysis

The genome-wide association studies (GWAS) of lung disease and lung function indices suffer from challenges to be transformed into clinical interventions, due to a lack of knowledge on the molecular mechanism underlying the GWAS associations. A proteome-wide association study (PWAS) was first performed to identify candidate proteins by integrating two independent largest protein quantitative trait loci datasets of plasma proteins and four large-scale GWAS summary statistics of lung function indices (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC and peak expiratory flow (PEF)), followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, with a discovery dataset, we conducted Mendelian randomization (MR) and Bayesian colocalization analyses to select potentially causal proteins, followed by a replicated MR analysis with an independent dataset. Mediation analysis was also performed to explore the possible mediating role of these indices on the association between proteins and two common lung diseases (chronic obstructive pulmonary disease, COPD and Asthma). We finally prioritized the potential drug targets. A total of 210 protein-lung function index associations were identified by PWAS, and were significantly enriched in the pulmonary fibrosis and lung tissue repair. Subsequent MR and colocalization analysis identified 59 causal protein-index pairs, among which 42 pairs were replicated. Further mediation analysis identified 3 potential pathways from proteins to COPD or asthma mediated by FEV1/FVC. The mediated proportion ranges from 68.4% to 82.7%. Notably, 24 proteins were reported as druggable targets in Drug Gene Interaction Database, among which 8 were reported to interact with drugs, including FKBP4, GM2A, COL6A3, MAPK3, SERPING1, XPNPEP1, DNER, and FER. Our study identified the crucial plasma proteins causally associated with lung functions and highlighted potential mediating mechanism underlying the effect of proteins on common lung diseases. These findings may have an important insight into pathogenesis and possible future therapies of lung disorders.

Identifying chronic obstructive pulmonary disease subtypes using multi-trait genetics

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) has a broad spectrum of clinical characteristics. The aetiology of these differences is not well understood. The objective of this study is to assess whether respiratory genetic variants cluster by phenotype and associate with COPD heterogeneity.

METHODS

We clustered genome-wide association studies of COPD, lung function, and asthma and phenotypes from the UK Biobank using non-negative matrix factorization. We constructed cluster-specific genetic risk scores and tested these scores for association with phenotypes in non-Hispanic white subjects in the COPDGene study.

FINDINGS

We identified three clusters from 482 variants and 44 traits from genetic associations in 379,337 UK Biobank participants. Variants from asthma, COPD, and lung function were found in all three clusters. Clusters displayed varying effects on white blood cell counts, height, and body mass index (BMI)-related phenotypes in the UK Biobank. In the COPDGene cohort, cluster-specific genetic risk scores were associated with differences in steroid use, BMI, lymphocyte counts, and chronic bronchitis, as well as variations in gene and protein expression.

INTERPRETATION

Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

FUNDING

MHC was supported by R01HL149861, R01HL135142, R01HL137927, R01HL147148, and R01HL089856. HA and HJ were supported by ANR-20-CE36-0009-02 and ANR-16-CONV-0005. The COPDGene study (NCT00608764) is supported by grants from the NHLBI (U01HL089897 and U01HL089856), by NIH contract 75N92023D00011, and by the COPD Foundation through contributions made to an Industry Advisory Committee that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer and Sunovion.

Association between chronic obstructive pulmonary disease and osteoporosis: Mendelian randomization combined with bibliometric analysis

BACKGROUND

Previous observational studies have reported an association between chronic obstructive pulmonary disease (COPD) and osteoporosis (OP). The aim of this study is to investigate the causal relationship between COPD and OP by two-sample Mendelian randomization (MR) analysis. The current status of cross-sectional research between COPD and OP in the past decade was explored through bibliometrics.

METHODS

Single nucleotide polymorphisms (SNPs) that have been found to be strongly associated with COPD were used as instrumental variables (IVs) in MR Analysis. The primary outcome of the study was BMD measurement at five specific anatomical sites, namely the whole body, femoral neck, lumbar spine, forearm, and heel. These BMD measurements were derived primarily from a genome-wide association study (GWAS) and summary statistics from the International Genetic Factors Consortium for Osteoporosis (GEFOS). The main analysis method was inverse variance weighting (IVW). Multiple sensitivity analyses were performed to assess the robustness and reliability of the current MR Results. Further confirmatory MR Analysis between COPD and OP was applied. In bibliometrics. Publications were extracted from the Web of Science core collection publications related to osteoporosis and sarcopenia published between January 2014 and October 2024; Bibliometrics and visualization were performed by Microsoft Office Excel, Citespace, and R (Bibliometrix).

RESULTS

The MR Findings suggest that there is no causal relationship between COPD and BMD at five specific anatomical sites. The results of the primary IVW MR Analysis were generally supported by our sensitivity MR Analysis. We performed MR Analysis for the validation of COPD and OP (IVW OR: 1.019; 95%CI: 0.898-1.564; p = 0.768) also did not support a causal relationship between COPD and BMD. A total of 471 articles written by 1119 organizations from 42 countries/regions by 3331 authors and published in 238 journals were identified in the bibliometric analysis. China is the leading country in terms of the number of publications. China Medical University contributed the most publications. The International Journal of Chronic Obstructive Pulmonary Disease has the highest publication in this field.

CONCLUSIONS

In conclusion, This MR Study found no causal relationship between COPD and OP, suggesting that the observed associations may be due to common genetic effects or environmental confounders. The global research trends in this field in the past decade were summarized through bibliometric analysis, and care became the focus of future research on the relationship between copd and OP.

Asthma and respiratory comorbidities

Asthma is a common respiratory condition with various phenotypes, nonspecific symptoms, and variable clinical course. The occurrence of other respiratory conditions with asthma, or respiratory comorbidities (RCs), is not unusual. A literature search of PubMed was performed for asthma and a variety of respiratory comorbidities for the years 2019 to 2024. The 5 conditions with the largest number of references, other than rhinitis and rhinosinusitis (addressed elsewhere), or that are the most problematic in the authors' clinical experience, are summarized. Others are briefly discussed. The diagnosis and treatment of both asthma and RCs are complicated by the overlap of symptoms and signs. Recognizing RCs is especially problematic in adult-onset, non-type 2 asthma because there are no biomarkers to assist in confirming non-type 2 asthma. Treatment decisions in subjects with suspected asthma and RCs are complicated by the potential similarities between the symptoms or signs of the RC and asthma, the absence of a sine quo non for the diagnosis of asthma, the likelihood that many RCs improve with systemic corticosteroid therapy, and the possibility that manifestations of the RCs are misattributed to asthma or vice versa. Recognition of RCs is critical to the effective management of asthma, particularly severe or difficult-to-treat asthma.

Impact of IL13 genetic polymorphisms on COPD susceptibility in the Chinese Han population

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is characterized by persistent respiratory symptoms and airflow limitation. Interleukin-13 (IL13), associated with T-helper type 2 cells, plays a crucial role in COPD pathophysiology. This study aimed to investigate the relationship of single nucleotide polymorphisms (SNPs) in IL13 to COPD risk.

METHODS

Five candidate SNPs of IL13 were genotyped using MassARRAY iPLEX platform in a cohort of472 COPD patients and 472 healthy controls. Logistic regression analysis was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs). Additionally, Multifactor dimensionality reduction (MDR) software was utilized to assess the combined impact of SNP-SNP interactions on COPD risk.

RESULTS

IL13 rs20541 (OR: 1.24, p: 0.028), rs1295685 (OR: 1.31, p: 0.006), rs848 (OR: 1.27, p: 0.016), and rs847 (OR: 1.30, p: 0.007) were associated with COPD risk. Moreover, IL13 variants were related to the increased COPD risk in females, individuals aged ≥68 year, non-smokers or non-drinkers. The optimal multi-locus model was identified as the combination of rs20541 and rs1295685.

CONCLUSION

Our findings indicated the association between IL13 variants and an elevated risk of developing COPD, especially rs1295685 and rs847. These findings could have implications for understanding the role of IL13 variants in COPD predisposition.

A Haplotype GWAS in Syndromic Familial Colorectal Cancer

A previous genome-wide association study (GWAS) in colorectal cancer (CRC) patients with gastric and/or prostate cancer in their families suggested genetic loci with a shared risk for these three cancers. A second haplotype GWAS was undertaken in the same colorectal cancer patients and different controls with the aim of confirming the result and finding novel loci. The haplotype GWAS analysis involved 685 patients with colorectal cancer cases and 1642 healthy controls from Sweden. A logistic regression model was used with a sliding window haplotype approach. Whole-genome and exome sequencing datawere used to find candidate SNPs to be tested in a nested case-control study. In the analysis of 685 colorectal cancer cases and 1642 controls, all ten candidate loci from the previous study were confirmed. Fifty candidate loci were suggested with a p-value < 5 × 10-6 and odds ratios between 1.35-6.52. Two of the 50 loci, on 13q33.3 and 16q23.3, were the same as in the previous study. Whole-genome or exome data from 122 colorectal cancer patients was used to search for candidate variants in these 50 loci. A nested case-control study was performed to test genetic variants at 11 loci in a cohort of 827 familial colorectal cancer and a sub-cohort of 293 familial CRC cases with colorectal, gastric, and/or prostate cancer within their families and 1530 healthy controls. One SNP, rs115943733 on 10q11.21, reached statistical significance (OR = 3.26, p = 0.009). Seven SNPs in 4 loci had a higher OR in the smaller cohort compared to the larger study CRC cases. The results in this GWAS gave support for suggested loci with an increased shared risk of CRC, gastric, and/or prostate cancer. Further studies are needed to confirm the shared risk to be able to use this information in cancer prevention.

Genome-wide analysis in northern Chinese twins identifies twelve new susceptibility loci for pulmonary function

BACKGROUND

Previous genome-wide association studies (GWAS) have established association between genetic variants and pulmonary function across various ethnics, whereas such associations are scarcely reported in Chinese adults. Therefore, we conducted an GWAS to explore relationships between genetic variants and pulmonary function among middle-aged Chinese dizygotic twins and further validated the top variants using data from the UK Biobank (UKB).

METHODS

In the discovery phase, 139 dizygotic twin pairs were drawn from the Qingdao Twin Registry. Pulmonary function was assessed using three parameters: forced expiratory volume the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio. GWAS was performed using GEMMA, Gene-based analysis was conducted by VEGAS2. And pathway enrichment analysis was performed using PASCAL. In the validation phase, Single-nucleotide polymorphisms (SNPs) with suggestive significance were examined through linear regression analysis of the additive effect model among 1573 Chinese ethnic participants from UKB.

RESULTS

The median age of twin pairs in the study was 49 years. 3 SNPs (rs80345886, rs117883876, and 75139439) related to FEV1 achieved genome-wide significance. Moreover, 222, 150, and 73 SNPs surpassed suggestive evidence level (p < 1 × 10- 5) for FEV1, FVC, and FEV1/FVC, respectively. Among them, 16 SNPs located in TBC1D16 for FEV1, 25 SNPs located in GPR126 for FVC, and 2 SNPs located in CCDC110 for FEV1/FVC, the three genes were also revealed by gene-based analysis. Moreover, 12 novel SNPs related to pulmonary function were validated to reach the nominal significance level (p < 0.05) in the UKB, with some located in the TBC1D16, TAFA5, and MTHFD1L genes.

CONCLUSION

Our GWAS results on Chinese dizygotic twins provide new references for the genetic regulation on pulmonary function. Twelve novel susceptibility loci are considered as possible crucial to pulmonary function.

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.

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.

Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes in the COPDGene and ECLIPSE cohort studies

BACKGROUND

Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

METHODS

We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.

FINDINGS

We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined "high activity" (low PRS, high TRS) and "severe risk" (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. "High activity" but not "severe risk" participants had greater prospective FEV1 decline (COPDGene: -51 mL/year; ECLIPSE: -40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.

INTERPRETATION

Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

FUNDING

National Institutes of Health.

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.

Multi-ancestry genome-wide association study reveals novel genetic signals for lung function decline

Rationale

Accelerated decline in lung function contributes to the development of chronic respiratory disease. Despite evidence for a genetic component, few genetic associations with lung function decline have been identified.

Objectives

To evaluate genome-wide associations and putative downstream functionality of genetic variants with lung function decline in diverse general population cohorts.

Methods

We conducted genome-wide association study (GWAS) analyses of decline in the forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and their ratio (FEV1/FVC) in participants across six cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. Genotypes were imputed to TOPMed (CHARGE cohorts) or Haplotype Reference Consortium (HRC) (UK Biobank) reference panels, and GWAS analyses used generalized estimating equation models with robust standard error. Models were stratified by cohort, ancestry, and sex, and adjusted for important lung function confounders and genotype principal components. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Selected top variants were tested for replication in two independent COPD-enriched cohorts.

Measurements and Main Results

Our discovery analyses included 52,056 self-reported White (N=44,988), Black (N=5,788), Hispanic (N=550), and Chinese American (N=730) participants with a mean of 2.3 spirometry measurements and 8.6 years of follow-up. Functional mapping of GWAS meta-analysis results identified 361 distinct genome-wide significant (p<5E-08) variants in one or more of the FEV1, FVC, and FEV1/FVC decline phenotypes, which overlapped with previously reported genetic signals for several related pulmonary traits. Of these, 8 variants, or 20.5% of the variant set available for replication testing, were nominally associated (p<0.05) with at least one decline phenotype in COPD-enriched cohorts (White [N=4,778] and Black [N=1,118]). Using the GWAS results, gene-level analysis implicated 38 genes, including eight (XIRP2, GRIN2D, SATB1, MARCHF4, SIPA1L2, ANO5, H2BC10, and FAF2) with consistent associations across ancestries or decline phenotypes. Annotation class analysis revealed significant enrichment of several regulatory processes for corticosteroid biosynthesis and metabolism. Drug repurposing analysis identified 43 approved compounds targeting eight of the implicated 38 genes.

Conclusions

Our multi-ancestry GWAS meta-analyses identified numerous genetic loci associated with lung function decline. These findings contribute knowledge to the genetic architecture of lung function decline, provide evidence for a role of endogenous corticosteroids in the etiology of lung function decline, and identify drug targets that merit further study for potential repurposing to slow lung function decline and treat lung disease.

Central role of glycosylation processes in human genetic susceptibility to SARS-CoV-2 infections with Omicron variants

The host genetics of SARS-CoV-2 has previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associated with infection and/or severity. SARS-CoV-2 has shown rapid sequence evolution increasing transmissibility, particularly for Omicron variants, which raises the question whether this affected the host genetic factors. We performed a genome-wide association study of SARS-CoV-2 infection with Omicron variants including more than 150,000 cases from four cohorts. We identified 13 genome-wide significant loci, of which only five were previously described as associated with SARS-CoV-2 infection. The strongest signal was a single nucleotide polymorphism (SNP) intronic of ST6GAL1, a gene affecting immune development and function, and connected to three other associated loci (harboring MUC1, MUC5AC and MUC16) through O-glycan biosynthesis. We also found further evidence for an involvement of blood group systems in SARS-CoV-2 infection, as we observed association 1) for a different lead SNP in the ABO locus indicating a protective effect of blood group B against Omicron infection, 2) for the FUT2 SNP tagging secretor status also reported for SARS-CoV-2 infection with earlier variants, and 3) for the strongest expression quantitative trait locus (eQTL) for FUT3 (Lewis gene). Our study provides robust evidence for individual genetic variation related to glycosylation translating into susceptibility to SARS-CoV-2 infections with Omicron variants.

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.

Identifying key genes in COPD risk via multiple population data integration and gene prioritization

Chronic obstructive pulmonary disease (COPD) is a highly prevalent disease, making it a leading cause of death worldwide. Several genome-wide association studies (GWAS) have been conducted to identify loci associated with COPD. However, different ancestral genetic compositions for the same disease across various populations present challenges in studies involving multi-population data. In this study, we aimed to identify protein-coding genes associated with COPD by prioritizing genes for each population's GWAS data, and then combining these results instead of performing a common meta-GWAS due to significant sample differences in different population cohorts. Lung function measurements are often used as indicators for COPD risk prediction; therefore, we used lung function GWAS data from two populations, Japanese and European, and re-evaluated them using a multi-population gene prioritization approach. This study identified significant single nucleotide variants (SNPs) in both Japanese and European populations. The Japanese GWAS revealed nine significant SNPs and four lead SNPs in three genomic risk loci. In comparison, the European population showed five lead SNPs and 17 independent significant SNPs in 21 genomic risk loci. A comparative analysis of the results found 28 similar genes in the prioritized gene lists of both populations. We also performed a standard meta-analysis for comparison and identified 18 common genes in both populations. Our approach demonstrated that trans-ethnic linkage disequilibrium (LD) could detect some significant novel associations and genes that have yet to be reported or were missed in previous analyses. The study suggests that a gene prioritization approach for multi-population analysis using GWAS data may be a feasible method to identify new associations in data with genetic diversity across different populations. It also highlights the possibility of identifying generalized and population-specific treatment and diagnostic options.

Screening the Best Risk Model and Susceptibility SNPs for Chronic Obstructive Pulmonary Disease (COPD) Based on Machine Learning Algorithms

Background and Purpose

Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors, and genetic factors are important determinants of COPD. This study focuses on screening the best predictive models for assessing COPD-associated SNPs and then using the best models to predict potential risk factors for COPD.

Methods

Healthy subjects (n=290) and COPD patients (n=233) were included in this study, the Agena MassARRAY platform was applied to genotype the subjects for SNPs. The selected sample loci were first screened by logistic regression analysis, based on which the key SNPs were further screened by LASSO regression, RFE algorithm and Random Forest algorithm, and the ROC curves were plotted to assess the discriminative performance of the models to screen the best prediction model. Finally, the best prediction model was used for the prediction of risk factors for COPD.

Results

One-way logistic regression analysis screened 44 candidate SNPs from 146 SNPs, on the basis of which 44 SNPs were screened or feature ranked using LASSO model, RFE-Caret, RFE-Lda, RFE-lr, RFE-nb, RFE-rf, RFE-treebag algorithms and random forest model, respectively, and obtained ROC curve values of 0.809, 0.769, 0.798, 0.743, 0.686, 0.766, 0.743, 0.719, respectively, so we selected the lasso model as the best model, and then constructed a column-line graph model for the 25 SNPs screened in it, and found that rs12479210 might be the potential risk factors for COPD.

Conclusion

The LASSO model is the best predictive model for COPD and rs12479210 may be a potential risk locus for COPD.

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.

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.

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 ).

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.

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.

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.

Proteomic Risk Score of Increased Respiratory Susceptibility: A Multi-Cohort Study

RATIONALE

Accelerated decline in lung function is associated with incident COPD, hospitalizations and death. However, identifying this trajectory with longitudinal spirometry measurements is challenging in clinical practice.

OBJECTIVE

To determine whether a proteomic risk score trained on accelerated decline in lung function can assess risk of future respiratory disease and mortality.

METHODS

In CARDIA, a population-based cohort starting in young adulthood, longitudinal measurements of FEV1 percent predicted (up to six timepoints over 30 years) were used to identify accelerated and normal decline trajectories. Protein aptamers associated with an accelerated decline trajectory were identified with multivariable logistic regression followed by LASSO regression. The proteomic respiratory susceptibility score was derived based on these circulating proteins and applied to the UK Biobank and COPDGene studies to examine associations with future respiratory morbidity and mortality.

MEASUREMENTS AND RESULTS

Higher susceptibility score was independently associated with all-cause mortality (UKBB: HR 1.56, 95%CI 1.50-1.61; COPDGene: HR 1.75, 95%CI 1.63-1.88), respiratory mortality (UKBB: HR 2.39, 95% CI 2.16-2.64; COPDGene: HR 1.83, 95%CI 1.33-2.51), incident COPD (UKBB: HR 1.84, 95%CI 1.71-1.98), incident respiratory exacerbation (COPDGene: OR 1.11, 95%CI 1.03-1.20), and incident exacerbation requiring hospitalization (COPDGene: OR 1.18, 95%CI 1.08-1.28).

CONCLUSIONS

A proteomic signature of increased respiratory susceptibility identifies people at risk of respiratory death, incident COPD, and respiratory exacerbations. This susceptibility score is comprised of proteins with well-known and novel associations with lung health and holds promise for the early detection of lung disease without requiring years of spirometry measurements.

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.

Exploring the genetics of airflow limitation in lung function across the lifespan - a polygenic risk score study

Background

Chronic obstructive pulmonary disease (COPD) is caused by interactions between many factors across the life course, including genetics. A proportion of COPD may be due to reduced lung growth in childhood. We hypothesized that a polygenic risk score (PRS) for COPD is associated with lower lung function already in childhood and up to adulthood.

Methods

A weighted PRS was calculated based on the 82 association signals (p ≤ 5 × 10-8) revealed by the largest GWAS of airflow limitation (defined as COPD) to date. This PRS was tested in association with lung function measures (FEV1, FVC, and FEV1/FVC) in subjects aged 4-50 years from 16 independent cohorts participating in the Chronic Airway Diseases Early Stratification (CADSET) Clinical Research Collaboration. Age-stratified meta-analyses were conducted combining the results from each cohort (n = 45,406). These findings were validated in subjects >50 years old.

Findings

We found significant associations between the PRS for airflow limitation and: (1) lower pre-bronchodilator FEV1/FVC from school age (7-10 years; β: -0.13 z-scores per one PRS z-score increase [-0.15, -0.11], q-value = 7.04 × 10-53) to adulthood (41-50 years; β: -0.16 [-0.19, -0.13], q-value = 1.31 × 10-24); and (2) lower FEV1 (from school age: 7-10 years; β: -0.07 [-0.09, -0.05], q-value = 1.65 × 10-9, to adulthood: 41-50 years; β: -0.17 [-0.20, -0.13], q-value = 4.48 x 10-20). No effect modification by smoking, sex, or a diagnosis of asthma was observed.

Interpretation

We provide evidence that a higher genetic risk for COPD is linked to lower lung function from childhood onwards.

Funding

This study was supported by CADSET, a Clinical Research Collaboration of the European Respiratory Society.

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.