Metabolic SyndromeNCT07330297
Breath Mass Spectrometry in Metabolic Syndrome and Metabolically Healthy Obesity
An observational study of Metabolic Syndrome and Obesity & Overweight, run by I.M. Sechenov First Moscow State Medical University at 1 site in Russia.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Metabolic Syndrome, Obesity & Overweight, Metabolically Healthy Obesity
- What is being tested?
- Breath Sampling and Analysis by PTR-MS
- How many people
- 300 participants
- Where
- 1 siteRussia
- Study dates
- 19 Sep 2024to 30 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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).
Who may be able to join
- 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;
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- 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.
Who cannot join
- Patient refusal to continue participation in the study;
- Identification of any non-inclusion criteria after enrollment.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Russia1 site, 1 recruiting
- Recruiting
University Clinical Hospital №1, Sechenov University
Moscow
Philipp Kopylov, +7 (903) 687-72-64, kopylov_f_yu@staff.sechenov.ru
About this study
Official title: 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.
Read the 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.
- Being tested
- Breath Sampling and Analysis by PTR-MS
- Keywords
- Breath Analysis, Volatile Organic Compounds, Proton-Transfer-Reaction Mass Spectrometry, Artificial Intelligence, Machine Learning, Metabolic syndrome, Obesity, Metabolically healthy obesity
- Medical subject headings
- Metabolic Syndrome, Obesity, Overweight, Obesity, Metabolically Benign
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Breath Sampling and Analysis by PTR-MSDiagnostic 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).
| Study group | Role | What they receive |
|---|---|---|
| Metabolic Syndrome Group | 100 patients diagnosed with Metabolic Syndrome according to International Diabetes Federation (IDF) 2006 criteria. Receives: 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). Receives: Diagnostic Test: Breath Sampling and Analysis by PTR-MS | |
| Control Group | 100 individuals with normal BMI and no signs of Metabolic Syndrome. Receives: Diagnostic Test: Breath Sampling and Analysis by PTR-MS |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jan 2026
- Study start19 Sep 2024
- Primary completion1 Jun 2026 (estimated)
- Study completion30 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Metabolic SyndromeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- I.M. Sechenov First Moscow State Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07330297
- Sponsor's protocol ID
- MHO-MetS-Breath-001
- Status last verified
- Dec 2025
- First submitted
- 29 Dec 2025
- Last updated
- 9 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: 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.
Study at a glance
From the registry record, last updated by the sponsor on 9 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Capabilities of Exhaled Breath Mass Spectrometry in Identifying Metabolic Syndrome and Metabolically Healthy Obesity
- ClinicalTrials.gov ID
- NCT07330297
- Acronym / sponsor ID
- MHO-MetS-Breath-001
- Keywords
- Breath Analysis, Volatile Organic Compounds, Proton-Transfer-Reaction Mass Spectrometry, Artificial Intelligence, Machine Learning, Metabolic syndrome, Obesity, Metabolically healthy obesity
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- I.M. Sechenov First Moscow State Medical UniversityUniversity, hospital or other
- Study start
- 19 Sep 2024 (actual)
- Primary completion
- 1 Jun 2026 (estimated)
- Study completion
- 30 Dec 2026 (estimated)
- First posted
- 9 Jan 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Metabolic Syndrome Group | – | Diagnostic Test: Breath Sampling and Analysis by PTR-MS100 patients diagnosed with Metabolic Syndrome according to International Diabetes Federation (IDF) 2006 criteria. |
| Metabolically Healthy Obesity Group | – | Diagnostic Test: Breath Sampling and Analysis by PTR-MS100 patients with waist circumference ≥94 cm (men)/≥80 cm (women), but without other components of Metabolic Syndrome (hypertension, dyslipidemia, impaired fasting glucose). |
| Control Group | – | Diagnostic Test: Breath Sampling and Analysis by PTR-MS100 individuals with normal BMI and no signs of Metabolic Syndrome. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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).
Key inclusion criteria (18 listed)
- 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;
Key exclusion criteria (2 listed)
- Patient refusal to continue participation in the study;
- Identification of any non-inclusion criteria after enrollment.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Breath Sampling and Analysis by PTR-MSA 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). | Diagnostic test | Control Group, Metabolic Syndrome Group, Metabolically Healthy Obesity Group |
Primary outcome
Specificity of the combined PTR-MS and machine learning model.
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.
Sensitivity of the combined PTR-MS and machine learning model.
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.
Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of the combined PTR-MS and machine learning model.
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.
1 secondary outcome
Identification of specific Volatile Organic Compound (VOC) patterns.
Time frame: Through study completion, after mass spectrometric data processing and database search are completed (anticipated within 1 year).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Jan 2026.
- Individual participant dataSharing planned: No. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Metabolic Syndrome and Obesity & Overweight, run by I.M. Sechenov First Moscow State Medical University at 1 site in Russia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 18 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 9 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Russia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Philipp Kopylov (+7 (903) 687-72-64, kopylov_f_yu@staff.sechenov.ru), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Specificity of the combined PTR-MS and machine learning model. (time frame: Through study completion, after all participant samples are collected and the final model is validated (anticipated within 1 year).). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 Jan 2026.