Min Hyung Ryu

Outdoor air pollution exposure is a well-established driver of respiratory disease, while growing evidence highlights an important role for genetic susceptibility. Building on this expanding body of work, our review synthesises findings across studies and provides an integrated overview. Here, we present a structured literature review summarising study characteristics and statistically significant single nucleotide polymorphisms (SNPs) reported in gene–environment interaction studies of air pollution related respiratory outcomes. By consolidating this evidence, the review clarifies current findings and supports more rigorous, evidence-based risk stratification in future observational and intervention studies. We included 48 peer-reviewed studies in humans published between 2014 and 2024 that examined gene–environment interactions involving SNPs, outdoor air pollution exposure and respiratory outcomes. Studies primarily evaluating particulate matter with aerodynamic diameter e.g. rs1695 ( GSTP1 ) and rs2266637 ( GSTT1 )) and inflammatory responses ( e.g. rs1800629 ( TNF ), rs3804099 ( TLR2 ) and rs848 ( IL13 )), consistently modifying pollution-related lung function decline and airway inflammation. By consolidating key genes, study designs and analytic methods, this review provides a curated SNP list to inform future genetic risk stratification. We highlight the need for studies in ancestrally diverse populations, controlled human exposure designs, and multi-omics approaches to strengthen mechanistic understanding of gene–environment interactions in respiratory health.

Traffic-related air pollution (TRAP) exposure is associated with adverse health effects, including chronic inflammation and the exacerbation of respiratory diseases. Although the effects of TRAP exposure begin locally in the lungs, they can spread systemically throughout the body via the blood. To understand blood-lung dynamics upon TRAP exposure, we interrogated blood and airway gene expression and performed a concordant analysis of these datasets. Specifically, we investigated the transcriptomic response of the blood and airway epithelium to inhaled diesel exhaust (DE), an experimental model of TRAP, across thirty-two research participants. In this double-blinded, crossover, controlled human exposure study, participants were exposed to DE and filtered air for two hours on two separate occasions. Paired-end RNA-sequencing was conducted on blood and bronchial brushing samples. Differential gene expression analysis revealed significant gene expression changes in airways, including upregulation of GPX2 and NQO1, genes essential to antioxidant defense. Differentially expressed genes (DEGs) were mapped to hallmark pathways and cell types using the Human Molecular Signatures Database (MSigDB). In the blood and airway epithelium, pathways with altered activity included interferon alpha (IFN-α) response, interferon gamma (IFN-γ) response, inflammatory response, and reactive oxygen species (ROS) pathway. Concordant analysis revealed correlated cellular activity between blood and airways, providing new evidence of a potential blood-lung relationship in response to DE exposure, which was not detectable through independent analysis alone. Combining local and systemic data may enrich our understanding of the downstream biological pathways affected by DE exposure, allowing for new avenues to monitor lung responses through blood analysis.

Background: Blood eosinophil count is an accepted biomarker for type 2 inflammation in COPD. However, the majority of COPD patients are characterized by non-type 2 inflammation. We aimed to test readily obtainable immune cell ratios as biomarkers for clinical phenotypes in the broad COPD population and to determine pathways represented by these ratios using multi-omics data. Methods: Using complete blood counts with differential collected at the Phase 2 (5-year) visit in the COPDGene Study, we calculated three immune cell ratios previously described in COPD and other diseases: the neutrophil–lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the Systemic Immune-Inflammation Index (SII = NLR*platelets). We tested for associations with COPD outcomes, including lung function, chest CT scan phenotypes, and exacerbations. Blood RNA-sequencing and proteomics data were used to identify genes, proteins and pathways associated with the ratios. Results: In univariate analyses, the three biomarkers were associated with COPD severity measures. In zero inflated Poisson regression models, all three were associated with increased odds of having an exacerbation but were not associated with exacerbation counts. Conversely, the three biomarkers were generally associated with prospective exacerbation counts, but not the zero-inflation term. In logistic regression models, the three biomarkers were significantly associated with having two or more exacerbations in the prior year; however, receiver operating characteristic analyses did not lead to clear cutoff values. Complement and PI3K signaling pathways were enriched across more than one ratio in both the RNA-sequencing and proteomics results. Other inflammatory pathways relevant in COPD appeared in different enrichment sets in either omics data type. Conclusions: Higher levels of three easily obtained blood cell ratios were associated with COPD severity and exacerbations outcomes; however, there are not clear thresholds which would be required for clinical application. Blood RNA-sequencing and proteomics identified inflammatory pathways associated with the three biomarkers, including targets for COPD therapies currently in human trials.

Climate change is increasing the frequency and severity of wildfires globally, causing significant woodsmoke (WS) emissions. Vehicles emit sizable amounts of toxic traffic-related air pollution (TRAP), for which diesel exhaust (DE) is a model. Both WS and DE contain particulate matter 2.5 ) which deeply penetrates the lungs, causing respiratory epithelial inflammation that drives health effects. Regulations focus on PM _2.5 concentration, despite emerging research that highlights how composition mediates health effects. As WS and DE are compositionally distinct, we conducted the first head-to-head comparison of effects on the transcriptomes of air-liquid interface cultured primary human bronchial epithelial cells (HBEC). Differentiated donor-matched HBEC transwells were exposed for 2-hours to filtered air (FA; control), or WS (furnace tube burning pine) or DE (Hatz 1B30E generator) both diluted to 300 µg/m ³ of PM _2.5 . WS had higher ultrafine PM, whereas DE exposure contained significantly higher NO ₂ , CO, and O ₃ . RNA sequencing showed that WS exposure resulted in 119 (↑41, ↓78) differentially expressed genes, while DE modulated 399 (↑255, ↓144) compared to FA exposure. WS was associated with small ribosomal subunit and cytochrome complex related genes, while DE exposure was associated with HIF-1 signaling, respiratory chain complex and interferon alpha/beta signaling/ISG15-protein conjugation, suggesting how TRAP exposure may enhance infection risk. We also analyzed exposure effects on protein immune-mediators. We demonstrate that two major air pollution sources modulate different genes and pathways in HBECs, with minimal overlap. This informs the debate regarding the regulatory focus on concentration and assumptions that similar concentrations of air pollution have indistinct effects. Highlights: Lung health effects of diesel exhaust (DE) and wood smoke (WS) are underexplored RNAseq of DE and WS-exposed primary lung epithelial cells revealed larger DE effects DE showed greater repression of host antiviral response-associated genes than WS A regulatory focus on PM concentration may miss composition-specific lung effects

Rationale: Growing evidence suggests that air pollution exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) that is associated with an increased prothrombotic state and adverse cardiovascular outcomes. However, much of this work is based on observational data or human exposure studies involving younger participants. The biological causality and mechanism of air pollution-induced prothrombotic response in patients with COPD remain to be explored. Objective: The main aim of this work was to investigate the impact of short-term diesel exhaust (DE) exposure on circulating prothrombotic markers-fibrinogen and plasminogen activator inhibitor-1 (PAI-1)-and urinary eicosanoids in patients with COPD. Methods: Twenty-nine research participants were recruited in this randomized, double-blinded, crossover, controlled human exposure study to DE. Participants included former smokers with and without mild or moderate COPD (ES and COPD group) and healthy never-smokers without COPD (NS group). Each participant was exposed to DE (300 µg/m³ of PM_2.5) and filtered air (FA) for 2 hours on different occasions, in randomized order, separated by a 4-week washout. Blood and urine samples were collected prior to and 24 hours after each exposure. Plasma fibrinogen and serum PAI-1 concentrations were quantified using ELISAs. Urinary eicosanoid concentrations were quantified using ultra- performance liquid chromatography coupled to tandem mass spectrometry. Linear mixed-effects models were used for statistical comparisons. Results: Participants with COPD showed an increase in plasma fibrinogen (effect estimate: 1.27 [1.06 to 1.53], p=0.01) after DE relative to FA, but no significant DE-associated change in serum PAI-1 (0.95 [0.87 to 1.04], p=0.26). In never-smokers and ex-smokers without COPD, fibrinogen (NS group: 1.10 [0.99 to 1.23], p=0.08; ES group: 0.86 [0.68 to 1.09], p=0.08] and PAI-1 (NS group: 1.12 [ 0.96 to 1.32], p=0.15; ES group: 0.90 [0.79 to 1.03], p=0.13) were not changed after DE exposure. COPD participants showed a DE-attributable increase in urinary thromboxane B₂ (TXB₂) metabolites concentrations as follows: 11-dehydro TXB₂ (1.45 [1.02 to 2.08], p=0.04); 2,3-dinor-TXB₂ (1.45 [1.05 to 2.00], p=0.03). Conclusions: Participants with COPD had increased plasma fibrinogen and urinary TXB₂ metabolites after short-term DE exposure, suggesting they may be more susceptible to pollution-attributable prothrombotic response compared to healthy controls or ex-smokers without COPD. Clinical trial registration available at www.clinicaltrials.gov, ID: NCT02236039.

Rationale: For spirometry interpretation, the European Respiratory Society (ERS) and American Thoracic Society (ATS) recommend using z-scores, and the ATS has recommended using Global Lung Initiative (GLI) “Global” race-neutral reference equations. However, these recommendations have been variably implemented, and the impact has not been widely assessed in clinical or research settings. Objectives: To evaluate the ERS/ATS classification of airflow obstruction severity. Methods: In COPDGene (Genetic Epidemiology of COPD Study) (N = 10,108), airflow obstruction has been defined by an FEV1/FVC ratio <0.70, with spirometric severity graded from class 1 to class 4 based on race-specific percent predicted (pp) FEV1 cutoff points as recommended by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We compared the GOLD approach, using National Health and Nutrition Examination Survey III race-specific equations, versus the application of GLI Global equations using the ERS/ATS definition of airflow obstruction as an FEV1/FVC ratio below the lower limit of normal and z-score–based FEV1 cutoff points of –1.645, –2.5, and –4 (“zGLI Global”). We tested the four-tier severity scheme for association with chronic obstructive pulmonary disease outcomes. Measurements and Main Results: The lowest agreement between ERS/ATS with zGLI Global and the GOLD classification was observed in individuals with milder disease (56.9% and 42.5% in GOLD stages 1 and 2, respectively), and race was a major determinant of redistribution. After adjustment for relevant covariates, zGLI Global distinguished all-cause mortality risk between normal spirometry and the first grade of chronic obstructive pulmonary disease (hazard ratio, 1.23; 95% confidence interval, 1.04–1.44; P = 0.014) and showed a linear increase in exacerbation rates with increasing disease severity in comparison with GOLD. Conclusions: The zGLI Global severity classification outperformed the GOLD criteria in the discrimination of survival, exacerbations, and imaging characteristics.