Chronic obstructive pulmonary disease (COPD) and asthma are the most common chronic respiratory diseases. In middle-aged and elderly patients, it is difficult to distinguish between COPD and asthma based on clinical symptoms and pulmonary function examinations in clinical practice. Thus, an accurate and reliable inspection method is required. In this study, we aimed to identify breath biomarkers and evaluate the accuracy of breathomics-based methods for discriminating between COPD and asthma. In this multi-center cross-sectional study, exhaled breath samples were collected from 89 patients with COPD and 73 with asthma and detected on a high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform from 20 October 2022, to 20 May 2023, in four hospitals. Data analysis was performed from 15 June 2023 to 16 August 2023. The sensitivity, specificity, and accuracy were calculated to assess the overall performance of the volatile organic component (VOC)-based COPD and asthma discrimination models. Potential VOC markers related to COPD and asthma were also analyzed. The age of all participants ranged from to 18–86 years, and 54 (33.3%) were men. The age [median (minimum, maximum)] of COPD and asthma participants were 66.0 (46.0, 86.0), and 44.0 (17.0, 80.0). The male and female ratio of COPD and asthma participants were 14/75 and 40/33, respectively. Based on breathomics feature selection, ten VOCs were identified as COPD and asthma discrimination biomarkers via breath testing. The joint panel of these ten VOCs achieved an area under the curve of 0.843, sensitivity of 75.9%, specificity of 87.5%, and accuracy of 80.0% in COPD and asthma discrimination. Furthermore, the VOCs detected in the breath samples were closely related to the clinical characteristics of COPD and asthma. The VOC-based COPD and asthma discrimination model showed good accuracy, providing a new strategy for clinical diagnosis. Breathomics-based methods may play an important role in the diagnosis of COPD and asthma.

Autophagy mediates PM2.5-related lung injury (LI) and is tightly linked to inflammation and apoptosis processes. IL-37 has been demonstrated to regulate autophagy. This research aimed to examine the involvement of IL-37 in the progression of PM2.5-related LI and assess whether autophagy serves as a mediator for its effects.To create a model of PM2.5-related LI, this research employed a nose-only PM2.5 exposure system and utilized both human IL-37 transgenic mice and wild-type mice. The hIL-37tg mice demonstrated remarkable reductions in pulmonary inflammation and pathological LI compared to the WT mice. Additionally, they exhibited activation of the AKT/mTOR signaling pathway, which served to regulate the levels of autophagy and apoptosis.Furthermore, in vitro experiments revealed a dose-dependent upregulation of autophagy and apoptotic proteins following exposure to PM2.5 DMSO extraction. Simultaneously, p-AKT and p-mTOR expression was found to decrease. However, pretreatment with IL-37 demonstrated a remarkable reduction in the levels of autophagy and apoptotic proteins, along with an elevation of p-AKT and p-mTOR. Interestingly, pretreatment with rapamycin, an autophagy inducer, weakened the therapeutic impact of IL-37. Conversely, the therapeutic impact of IL-37 was enhanced when treated with 3-MA, a potent autophagy inhibitor. Moreover, the inhibitory effect of IL-37 on autophagy was successfully reversed by administering AKT inhibitor MK2206. The findings suggest that IL-37 can inhibit both the inflammatory response and autophagy, leading to the alleviation of PM2.5-related LI. At the molecular level, IL-37 may exert its anti autophagy and anti apoptosis effects by activating the AKT/mTOR signaling pathway.