Wang Yuxuan, Wang Xuewen, Yang Luqin, Wang Ke, Zhang Fengqin, Yue Huihui, Wang Junqi, Peng Minhua, Fan Pengnan, Qiu Xiangcheng, Zhang Han, Lin Wei, Lin Yuhang, Chen Sitong, Geng Qian, Sima Chaotan, Liu Deming, Lu Ping, Zhang Huilan
The Center for Biomedical Research, Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, 430074, China.
Mol Cell Biochem. 2025 Mar 18. doi: 10.1007/s11010-025-05249-4.
Interstitial lung diseases (ILDs) are a group of pulmonary disorders characterized by fibrosis, inflammation, and lung tissue deterioration. Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5-ILD), a subtype, is associated with high mortality due to rapid progression and severe lung damage. Volatile organic compounds (VOCs) in exhaled breath, reflecting metabolic changes, have been identified as potential non-invasive biomarkers for various diseases, including respiratory conditions. However, their role in MDA5-ILD has not been extensively studied. This retrospective cohort study included 45 exhaled breath samples from 19 ILD patients, with 31 samples from 9 patients with MDA5-ILD and 10 samples from 7 patients with non-MDA5-ILD. VOCs were collected using thermal desorption tubes and analyzed via gas chromatography-mass spectrometry (GC-MS). Clinical data, including the APACHE II score, were integrated with VOC profiles. Two logistic regression models were developed: Model 1 based on 11 clinical indicators, and Model 2 integrating 11 clinical indicators with 5 VOC features. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, sensitivity, specificity, and accuracy metrics. Five VOCs-N-(2-Aziridinyl)ethanamine, Cyclohexanone, Nonanal, Dodecamethylcyclohexasiloxane, and 4-Methyltetradecane-were identified as significant biomarkers distinguishing MDA5-ILD from non-MDA5-ILD. Model 2, which integrated VOC data, outperformed Model 1, achieving an area under the curve (AUC) of 0.93 compared to 0.70. Model 2 also demonstrated enhanced accuracy (84.6% vs. 76.9%), specificity (66.7% vs. 33.3%), precision (90.0% vs. 81.8%), and F1-score (90.0% vs. 85.7%). Additionally, 1,3-Pentadiene and 3-Methylundecane were identified as potential markers of disease severity, with 1,3-Pentadiene negatively correlating and 3-Methylundecane positively correlating with both APACHE II scores and creatinine levels. VOCs in exhaled breath significantly enhance the diagnostic sensitivity and accuracy for detecting MDA5-ILD. In addition, VOCs show promise as disease severity markers, potentially aiding in the assessment of disease severity and progression. While the integration of VOCs holds great potential for improving diagnostic performance, further validation through larger, multicenter studies is necessary.
间质性肺疾病（ILDs）是一组以纤维化、炎症和肺组织恶化为特征的肺部疾病。抗黑色素瘤分化相关基因5阳性皮肌炎相关间质性肺疾病（MDA5-ILD）是其中一种亚型，因其进展迅速和严重的肺损伤而与高死亡率相关。呼出气体中的挥发性有机化合物（VOCs）反映了代谢变化，已被确定为包括呼吸系统疾病在内的各种疾病的潜在非侵入性生物标志物。然而，它们在MDA5-ILD中的作用尚未得到广泛研究。这项回顾性队列研究纳入了19例ILD患者的45份呼出气体样本，其中9例MDA5-ILD患者有31份样本，7例非MDA5-ILD患者有10份样本。使用热解吸管收集VOCs，并通过气相色谱-质谱联用（GC-MS）进行分析。将包括急性生理学与慢性健康状况评分系统II（APACHE II）评分在内的临床数据与VOC谱相结合。建立了两个逻辑回归模型：模型1基于11个临床指标，模型2将11个临床指标与5个VOC特征相结合。使用受试者工作特征（ROC）曲线分析、敏感性、特异性和准确性指标评估模型性能。五种VOCs——N-（2-氮丙啶基）乙胺、环己酮、壬醛、十二甲基环己硅氧烷和4-甲基十四烷——被确定为区分MDA5-ILD和非MDA5-ILD的重要生物标志物。整合了VOC数据的模型2优于模型1，曲线下面积（AUC）为0.93，而模型1为0.70。模型2还表现出更高的准确性（84.6%对76.9%）、特异性（66.7%对33.3%）、精确性（90.0%对81.8%）和F1分数（90.0%对85.7%）。此外，1,3-戊二烯和3-甲基十一烷被确定为疾病严重程度的潜在标志物，1,3-戊二烯与APACHE II评分和肌酐水平呈负相关，3-甲基十一烷与二者呈正相关。呼出气体中的VOCs显著提高了检测MDA5-ILD的诊断敏感性和准确性。此外，VOCs有望作为疾病严重程度标志物，可能有助于评估疾病严重程度和进展。虽然整合VOCs在提高诊断性能方面具有巨大潜力，但仍需要通过更大规模的多中心研究进行进一步验证。
