Breath Mass Spectrometry in Metabolic Syndrome and Metabolically Healthy Obesity

NCT07330297 | Recruiting

• 1 other identifier: MHO-MetS-Breath-001
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Metabolic Syndrome; Obesity & Overweight; Metabolically Healthy Obesity

Keywords

Breath Analysis; Volatile Organic Compounds; Proton-Transfer-Reaction Mass Spectrometry; Artificial Intelligence; Machine Learning; Metabolic syndrome; Obesity; Metabolically healthy obesity

Outcome Measures

Primary Outcomes (3)

• 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 Outcomes (1)

• 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).

Study Arms (3)

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

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

Control Group

100 individuals with normal BMI and no signs of Metabolic Syndrome.

Diagnostic Test: Breath Sampling and Analysis by PTR-MS

Interventions

Breath Sampling and Analysis by PTR-MS DIAGNOSTIC_TEST

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; Metabolic Syndrome Group; Metabolically Healthy Obesity Group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• 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).

You may qualify if:

• 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;
• 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;

You may not qualify if:

• Patient refusal to continue participation in the study;

Sponsors & Collaborators

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

Study Sites (1)

University Clinical Hospital №1, Sechenov University

Moscow, Russia

RECRUITING

MeSH Terms

Conditions

Metabolic Syndrome; Obesity; Overweight; Obesity, Metabolically Benign

Condition Hierarchy (Ancestors)

Insulin Resistance; Hyperinsulinism; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Overnutrition; Nutrition Disorders; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Philipp Kopylov

CONTACT

+7 (903) 687-72-64; kopylov_f_yu@staff.sechenov.ru

Aida Gadzhiakhmedova

CONTACT

+7 (989) 899-53-01; ai.kidman@mail.ru

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 29, 2025
• First Posted: January 9, 2026
• Study Start: September 19, 2024
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): December 30, 2026
• Last Updated: January 9, 2026

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

RU (1)