Breath Mass Spectrometry in Metabolic Syndrome and Metabolically Healthy Obesity
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorI.M. Sechenov First Moscow State Medical University
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
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.
Inability to provide informed consent;
Disqualifiers
Patient refusal to continue participation in the study;
Identification of any non-inclusion criteria after enrollment.
Trial population
The study population consists of adults (≥18 years) from three groups: 1) Patients with Metabolic Syndrome (IDF, 2005 criteria), 2) Patients with metabolically healthy obesity (BMI≥30, no metabolic abnormalities), and 3) Healthy controls (BMI\<25, no metabolic disorders).
Trial design
Design model
Cohort
Time perspective
Cross-sectional
Treatments tested in this trial
Breath Sampling and Analysis by PTR-MS
Diagnostic testA single sample of exhaled breath will be collected from each participant during quiet breathing. The sample will be analyzed in real-time using Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (Compact PTR-TOF-MS 1000, Ionicon, Austria) to identify and quantify the spectrum of volatile organic compounds (VOCs).
Treatment groups
300 Participants
are divided into 3 treatment groupsGroup A: Metabolic Syndrome Group1 intervention
Group B: Metabolically Healthy Obesity Group1 intervention
Group C: Control Group1 intervention
Trial outcomes
Primary outcomes
1
Specificity of the combined PTR-MS and machine learning model.
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.
Time frame
Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).2
Sensitivity of the combined PTR-MS and machine learning model.
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.
Time frame
Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).3
Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of the combined PTR-MS and machine learning model.
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.
Time frame
Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).Secondary outcomes
1
Identification of specific Volatile Organic Compound (VOC) patterns.
Qualitative and quantitative assessment of specific Volatile Organic Compounds (VOCs) and VOC profiles significantly associated with Metabolic Syndrome and Metabolically Healthy Obesity compared to the control group. The identification of molecules will be performed using the Human Metabolome Database (HMDB) with an accuracy of ± 100 ppm.
Time frame
Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).Sponsors and contacts
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Source ClinicalTrials.gov