Breath Mass Spectrometry in Metabolic Syndrome and Metabolically Healthy Obesity

The Capabilities of Exhaled Breath Mass Spectrometry in Identifying Metabolic Syndrome and Metabolically Healthy Obesity

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.

Study Overview

• Status: Recruiting
• Conditions: Metabolic Syndrome; Obesity & Overweight; Metabolically Healthy Obesity
• Intervention / Treatment: Diagnostic test: Breath Sampling and Analysis by PTR-MS

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 300

Contacts and Locations

• Study Contact: Name: Philipp Kopylov; Phone Number: +7 (903) 687-72-64; Email: kopylov_f_yu@staff.sechenov.ru
• Study Contact Backup: Name: Aida Gadzhiakhmedova; Phone Number: +7 (989) 899-53-01; Email: ai.kidman@mail.ru

Study Locations

• Russia
  • Moscow, Russia
    • Recruiting
    • University Clinical Hospital №1, Sechenov University
    • Contact: Philipp Kopylov; Phone Number: +7 (903) 687-72-64; Email: kopylov_f_yu@staff.sechenov.ru

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study 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).

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• Patient refusal to continue participation in the study;
• Identification of any non-inclusion criteria after enrollment.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Metabolic Syndrome Group; 100 patients diagnosed with Metabolic Syndrome according to International Diabetes Federation (IDF) 2006 criteria.	Diagnostic test: Breath Sampling and Analysis by PTR-MS; 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).
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).	Diagnostic test: Breath Sampling and Analysis by PTR-MS; 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).
Control Group; 100 individuals with normal BMI and no signs of Metabolic Syndrome.	Diagnostic test: Breath Sampling and Analysis by PTR-MS; 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).

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).
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.	Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).
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.	Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).

Collaborators and Investigators

• Sponsor: I.M. Sechenov First Moscow State Medical University

Study record dates

Study Major Dates

• Study Start (Actual): September 19, 2024
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: December 29, 2025
• First Submitted That Met QC Criteria: December 29, 2025
• First Posted (Actual): January 9, 2026

Study Record Updates

• Last Update Posted (Actual): January 9, 2026
• Last Update Submitted That Met QC Criteria: December 29, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Obesity; Metabolic syndrome; Artificial Intelligence; Volatile Organic Compounds; Machine Learning; Breath Analysis; Proton-Transfer-Reaction Mass Spectrometry; Metabolically healthy obesity
• Additional Relevant MeSH Terms: Nutrition Disorders; Metabolic Diseases; Overnutrition; Body Weight; Glucose Metabolism Disorders; Insulin Resistance; Hyperinsulinism; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Signs and Symptoms; Obesity, Metabolically Benign; Overweight; Obesity; Metabolic Syndrome
• Other Study ID Numbers: MHO-MetS-Breath-001

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: IPD will not be available for public sharing. The local Ethics Committee and national data protection laws do not permit public deposition of individual patient data. The informed consent does not include such provisions.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No