The Capabilities of Exhaled Breath Mass Spectrometry in Identifying Metabolic Syndrome and Metabolically Healthy Obesity
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 300
- 试验地点
- 1
- 主要终点
- Specificity of the combined PTR-MS and machine learning model.
研究概览
简要总结
This study aims to develop a non-invasive diagnostic method for metabolic syndrome (MetS) and metabolically healthy obesity (MHO) through analysis of exhaled air. Using proton-transfer-reaction mass spectrometry combined with machine learning algorithms, we will characterize volatile organic compound profiles in 300 participants across three groups: MetS patients, MHO patients, and healthy controls. The primary goal is to create and validate a classification model capable of accurately differentiating these metabolic states based on breath analysis.
详细描述
This study focuses on characterizing the volatilome - the complete set of volatile organic compounds in exhaled air - as a novel biomarker source for metabolic health assessment.
The study represents the first comprehensive attempt to compare volatilome signatures between metabolically healthy and unhealthy obesity phenotypes. Successful validation of this approach could establish breath analysis as a new diagnostic paradigm in metabolic medicine, enabling rapid, non-invasive screening and personalized treatment strategies for patients with obesity-related conditions.
Methodological innovations include real-time breath analysis capabilities and development of specialized machine learning algorithms for pattern recognition in complex mass spectrometry data. The findings are expected to contribute significantly to understanding metabolic pathway alterations in different obesity phenotypes.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •For Group 1 (Metabolic syndrome): Age >18 years, signed informed consent, diagnosis of Metabolic Syndrome (IDF 2006 criteria: waist circumference >94 cm (men)/ >80 cm (women) + ≥2 of: BP ≥130/85 mmHg or antihypertensive therapy; TG ≥1.7 mmol/L; HDL-C <1.03 mmol/L (men) / <1.29 mmol/L (women); Fasting glucose ≥5.6 mmol/L).
- •For Group 2 (Metabolically healthy obesity): Age >18 years, signed informed consent, waist circumference ≥94 cm (men) / ≥80 cm (women), absence of other Metabolic Syndrome criteria (hypertension, dyslipidemia, impaired fasting glucose).
- •For Group 3 (Control): Age >18 years, signed informed consent, normal BMI, absence of signs of Metabolic Syndrome.
- •Non-inclusion criteria for all groups:
- •Inability to provide informed consent;
- •History of myocardial infarction or stroke;
- •Chronic kidney disease stage 3B, 4, 5 (eGFR <30 ml/min/1.73m2);
- •Acute or subacute cardiovascular disease;
- •Familial hypercholesterolemia;
- •Bronchopulmonary diseases;
- •Acute or chronic infectious diseases;
- •Type 1 or Type 2 diabetes mellitus;
- •Systemic connective tissue diseases;
- •Current or past history of oncological diseases;
- •Severe liver dysfunction, decompensated liver cirrhosis (Child-Pugh class C);
- •Pregnancy or lactation;
- •Severe mental illness (severe dementia, schizophrenia);
- •Comorbid conditions with life expectancy less than 1 year.
排除标准
- •Patient refusal to continue participation in the study;
- •Identification of any non-inclusion criteria after enrollment.
研究组 & 干预措施
Metabolic Syndrome Group
100 patients diagnosed with Metabolic Syndrome according to International Diabetes Federation (IDF) 2006 criteria.
干预措施: Breath Sampling and Analysis by PTR-MS (Diagnostic Test)
Metabolically Healthy Obesity Group
100 patients with waist circumference ≥94 cm (men)/≥80 cm (women), but without other components of Metabolic Syndrome (hypertension, dyslipidemia, impaired fasting glucose).
干预措施: Breath Sampling and Analysis by PTR-MS (Diagnostic Test)
Control Group
100 individuals with normal BMI and no signs of Metabolic Syndrome.
干预措施: Breath Sampling and Analysis by PTR-MS (Diagnostic Test)
结局指标
主要结局
Specificity of the combined PTR-MS and machine learning model.
时间窗: Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).
Specificity (true negative rate) of the diagnostic model, based on the analysis of exhaled breath VOCs by PTR-MS and subsequent machine learning classification, for distinguishing between participants with Metabolic Syndrome, Metabolically Healthy Obesity, and healthy controls. The value will be reported with a 95% confidence interval.
Sensitivity of the combined PTR-MS and machine learning model.
时间窗: Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).
Sensitivity (true positive rate) of the diagnostic model, based on the analysis of exhaled breath Volatile Organic Compounds (VOCs) by Proton Transfer Reaction Mass Spectrometry (PTR-MS) and subsequent machine learning classification, for distinguishing between participants with Metabolic Syndrome, Metabolically Healthy Obesity, and healthy controls. The value will be reported with a 95% confidence interval.
Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of the combined PTR-MS and machine learning model.
时间窗: Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).
The Area Under the Receiver Operating Characteristic Curve (AUC-ROC) as a composite measure of the diagnostic performance of the model based on PTR-MS breath analysis and machine learning. The AUC will be calculated for pairwise comparisons between the three study groups (Metabolic Syndrome vs. Metabolically Healthy Obesity; Metabolic Syndrome vs. Control; Metabolically Healthy Obesity vs. Control) and reported with a 95% confidence interval.
次要结局
- Identification of specific Volatile Organic Compound (VOC) patterns.(Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).)