Chronic obstructive pulmonary disease (COPD) is a disease with high incidence rate and mortality rates worldwide. It is the third leading cause of death in the world. Nevertheless, little progress has been made in treating and preventing the disease. Under these circumstances, the concept of “early COPD” was proposed. Although this concept is not new, most health-care workers do not fully understand early COPD and tend to confuse it with mild COPD. In this review, we mainly discuss the definition of early COPD and the developmental trajectory of lung function. Although patients with early COPD have no symptoms, their lung function is already lower than that of normal people. A relatively complete definition is needed to identify this group of people. Reduced lung function is the diagnostic criterion for COPD, but lung development is a long-term dynamic process. In addition to smoking and air pollution, we should pay more attention to prenatal and childhood risk factors, for example, parents smoking, birth weight, preterm birth, mode of delivery, childhood respiratory infections and childhood asthma. Health-care workers need to be fully aware of early COPD, to reduce the morbidity of COPD and take effective measures to prevent these risk factors.

Background: Coronary artery disease (CAD) is a cardiovascular disease with significant personal health and socioeconomic consequences. The biological functions of decanoic acid and the pathogenesis of CAD overlap considerably; however, studies exploring their relationship are limited. Methods: Data from 34,186 Americans from the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2018 were analyzed. The relationship between dietary decanoic acid (DDA) and CAD prevalence was explored using weighted multivariate logistic regression models, generalized summation models, and fitted smoothing curves. Stratified analyses and interaction tests were conducted to explore the potential modifiers between them. Results: DDA was negatively associated with CAD prevalence, with each 1 g/d increase in the DDA being associated with a 21% reduction in CAD prevalence (odds ratio (OR) 0.79, 95% confidence interval (CI) 0.61–1.02). This relationship persisted after log10 and trinomial transformations, respectively. The OR after log10 transformation was 0.81 (95% CI 0.69–0.96), and the OR for tertile 3 compared with tertile 1 was 0.83 (95% CI 0.69–1.00). The subgroup analyses found this relationship to be significant among males and non-Hispanic white individuals, and there was a significant interaction (interaction p-values of 0.011 and 0.012, respectively). Conclusions: DDA was negatively associated with the prevalence of CAD, and both sex and race may modify this relationship.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein–protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.