University Clinical Hospital №1, Sechenov University
Moscow, Russia
Location status: Recruiting
NCT Number: NCT07330297
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.
Interested in participating?
Request Info18 year and older
All sexes
Observational
Moscow, Russia
Location status: Recruiting
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.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Non-inclusion criteria for all groups:
Exclusion criteria
A 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).
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).
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.
Contact information is provided by the study sponsor or research team.
Aida Gadzhiakhmedova
CONTACT
Philipp Kopylov
CONTACT
I.M. Sechenov First Moscow State Medical University
Other
The Capabilities of Exhaled Breath Mass Spectrometry in Identifying Metabolic Syndrome and Metabolically Healthy Obesity
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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