Exhaled Breath Biomarkers Reflect the Inflammasome and Lipidome Changes in Ischemic Heart Disease: A Study Using Machine Learning Models and Network Analysis.

Q2 Medicine
Journal of Lipid and Atherosclerosis Pub Date : 2025-09-01 Epub Date: 2025-07-08 DOI:10.12997/jla.2025.14.3.350
Basheer Abdullah Marzoog, Peter Chomakhidze, Daria Gognieva, Artemiy Silantyev, Alexander Suvorov, Anastasia Stroeva, Malika Mustafina, Alina Yur'evna Fedorova, Abram Syrkin, Philipp Kopylov
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引用次数: 0

Abstract

Objective: To define relationships between lipidomics, inflammasome, and exhaled volatile organic compounds (VOCs) in ischemic heart disease (IHD) and develop a VOC-based diagnostic machine learning model for non-invasive diagnosis.

Methods: A single-center prospective study involved 80 participants between 27 Oct 2023 and 11 Jun 2024: 31 with stress-computed tomography (CT) myocardial-perfusion-confirmed IHD and 49 perfusion-negative controls. All underwent stress CT perfusion, bicycle-ergometry, and breath collection at rest, peak exercise, and 3-minute recovery into a PTR-TOF-MS-1000. Lipid measurements were made (total, high-density lipoprotein [HDL]-, low-density lipoprotein [LDL]-, very LDL-cholesterol, triglycerides, apolipoprotein B [ApoB], lipoprotein-a) and inflammatory biomarkers (interleukin-6, C-reactive protein). LASSO regression mapped VOC-biomarker associations. An XGBoost classifier integrating VOCs, lipidome, inflammasome, and lipid-lowering therapy status was evaluated with cross-validated Youden index.

Results: Controls showed minimal biomarker-VOC relationships. Patients exhibited significant lipid-VOC correlations, including HDL-C with m/z 49.995 (r=0.31) and an inverse correlation between total cholesterol and m/z 94.053 (r=-0.35). Key discriminative VOCs were 2-ethyl-2,5-dihydro-4,5-dimethylthiazole, HO3PS2, CH8N3P, and m/z 49.995. Exercise revealed dynamic ApoB and LDL interactions exclusive to IHD. Inflammasome had limited direct VOC links; IL-6 inversely correlated with total cholesterol in IHD, while CRP aligned with HDL in controls. The final model achieved: AUC 0.931 (95% confidence interval [CI], 0.869-0.978), sensitivity 0.613 (95% CI, 0.435-0.793), specificity 1.000 (95% CI, 1.000-1.000), NPV 0.803 (95% CI, 0.692-0.903), PPV 1.000 (95% CI, 1.000-1.000).

Conclusion: Exhaled VOC patterns reflect lipid dysregulation in IHD. Combined with lipid and inflammatory data, VOCs enable high-accuracy, non-invasive IHD discrimination, supporting breathomics as a promising diagnostic adjunct.

Trial registration: ClinicalTrials.gov Identifier: NCT06181799.

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呼气生物标志物反映缺血性心脏病炎症体和脂质组的变化:一项使用机器学习模型和网络分析的研究。
目的:明确缺血性心脏病(IHD)患者的脂质组学、炎性体和呼出挥发性有机化合物(VOCs)之间的关系,并建立基于VOCs的无创诊断机器学习模型。方法:在2023年10月27日至2024年6月11日期间,80名参与者参与了一项单中心前瞻性研究:31名应力-计算机断层扫描(CT)心肌灌注确诊IHD, 49名灌注阴性对照。所有患者均接受了应力CT灌注、自行车几何测量、休息时的呼吸收集、高峰运动和3分钟后恢复到PTR-TOF-MS-1000。脂质测量(总、高密度脂蛋白[HDL]-、低密度脂蛋白[LDL]-、极低密度脂蛋白胆固醇、甘油三酯、载脂蛋白B [ApoB]、脂蛋白-a)和炎症生物标志物(白细胞介素-6、c反应蛋白)。LASSO回归映射了voc与生物标志物的关联。结合VOCs、脂质组、炎性体和降脂治疗状态的XGBoost分类器通过交叉验证的约登指数进行评估。结果:对照显示最小的生物标志物- voc关系。患者表现出显著的脂质- voc相关性,包括HDL-C与m/z为49.995 (r=0.31),总胆固醇与m/z为94.053 (r=-0.35)呈负相关。主要鉴别VOCs为2-乙基-2,5-二氢-4,5-二甲基噻唑、HO3PS2、CH8N3P和m/z 49.995。运动揭示了IHD独有的动态ApoB和LDL相互作用。炎性小体与VOC的直接联系有限;在IHD患者中,IL-6与总胆固醇呈负相关,而在对照组中,CRP与HDL呈负相关。最终模型实现:AUC 0.931(95%置信区间[CI], 0.869-0.978),灵敏度0.613 (95% CI, 0.435-0.793),特异性1.000 (95% CI, 1.000-1.000), NPV 0.803 (95% CI, 0.692-0.903), PPV 1.000 (95% CI, 1.000-1.000)。结论:呼出VOC模式反映了IHD患者的脂质失调。结合脂质和炎症数据,VOCs可以实现高精度、无创的IHD识别,支持呼吸组学作为一种有前途的诊断辅助手段。试验注册:ClinicalTrials.gov标识符:NCT06181799。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Lipid and Atherosclerosis
Journal of Lipid and Atherosclerosis Medicine-Internal Medicine
CiteScore
6.90
自引率
0.00%
发文量
26
审稿时长
12 weeks
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