Metabolic Syndrome (MetS)NCT07248371
Validating Integrative Multi-omics Approaches in Metabolic Syndrome-related Diseases
An observational study of Metabolic Syndrome (MetS) and Obesity & Overweight, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
Trial summary
This study aims to validate integrative multi-omics approaches for understanding complications related to metabolic syndrome. By combining genetic, transcriptomic, metabolomic, and microbiome data from participants with and without metabolic syndrome, the research seeks to determine which biological factors predict… Read more about this study
- Who is it for?
- Ages 20 years and older
- Conditions the study is for
- Metabolic Syndrome (MetS), Obesity & Overweight, Cardiovascular Diseases (CVD)
- How many people
- 6,266 participants
- Where
- 1 siteTaiwan
- Study dates
- 9 Jun 2025to 30 Sep 2035
- How long will I take part?
- 5 Years
- 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 20 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Participants will be recruited from outpatient clinics at Chang Gung Memorial Hospitals in Taiwan. Recruitment will occur through the Departments of Endocrinology, Cardiology, Cardiac Surgery, Nephrology, and Gastroenterology. The study population will include adults receiving routine clinical care at these sites, representing both individuals with metabolic syndrome and those without the condition who serve as healthy controls. This hospital-based community cohort reflects a diverse urban and suburban Taiwanese population, enabling comprehensive multi-omics analysis of metabolic syndrome-related diseases within a real-world clinical setting.
Who may be able to join
- Individuals (male or female) aged 20 years or older
- Willing and able to provide written informed consent to participate in the study
Who cannot join
- Pregnant or breastfeeding women
- Patients with end-stage renal disease receiving hemodialysis or peritoneal dialysis
- Individuals currently undergoing active cancer treatment
- Recipients of any organ transplantation
- Patients diagnosed with dementia
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Chang Gung Memorial Hospitals, Linkou
Taoyuan
Chi-Hsiao Yeh, MD PhD, +886-3-3281200, yehccl@cgmh.org.tw
About this study
Official title: Validating Integrative Multi-omics Approaches in Metabolic Syndrome-related Diseases: A Step Towards Precision Medicine
This study aims to validate integrative multi-omics approaches for understanding complications related to metabolic syndrome. By combining genetic, transcriptomic, metabolomic, and microbiome data from participants with and without metabolic syndrome, the research seeks to determine which biological factors predict disease progression and how these insights can inform precision prevention and treatment strategies for metabolic disorders.
Read the detailed description
This longitudinal, multi-center study is designed to validate integrative multi-omics methodologies for predicting disease progression and complications in metabolic syndrome. Participants will be recruited from all branches of Chang Gung Memorial Hospitals. Individuals who meet the diagnostic criteria for metabolic syndrome will constitute the study group, while age- and sex-matched individuals without metabolic syndrome will serve as controls.
The study will collect peripheral blood, urine, and stool samples for comprehensive multi-omics profiling, including genomics (DNA sequencing), transcriptomics (RNA sequencing), metabolomics (serum and urine metabolite profiling), and microbiomics (stool microbiota analysis). Blood samples (10 mL) will be obtained annually for genetic and metabolomic analyses, while urine (30 mL) and stool (1 mL) samples will be used to assess metabolite and microbial signatures. These biospecimens will be linked with participants' longitudinal clinical data and laboratory test results retrieved from the Chang Gung Research Database (CGRD), providing a unified framework for integrative analysis.
Data integration will utilize advanced bioinformatics pipelines and systems biology tools to identify multi-layered molecular networks associated with disease onset and progression. Analytical methods include dimensionality reduction, clustering, and machine-learning-based feature selection to construct predictive models for metabolic complications such as cardiovascular disease, chronic kidney disease, and fatty liver disease. Identified biomarkers and pathways will be validated internally and cross-compared with pre-existing data from the "Integrated Smart Healthcare Database for Obesity."
All data will be de-identified and securely stored on institutional servers with restricted access. Each participant will be assigned a unique study code to ensure confidentiality. Data linkage between omics datasets and clinical outcomes will be performed through encrypted, privacy-preserving algorithms under the supervision of the institutional data governance committee. The study adheres to the ethical standards set by the Institutional Review Board, ensuring participant protection throughout data collection, analysis, and dissemination.
- Conditions
- Metabolic Syndrome (MetS), Obesity & Overweight, Cardiovascular Diseases (CVD), Chronic Kidney Disease, Nonalcoholic Fatty Liver Disease, Healthy
- Being tested
- No intervention
- Keywords
- Metabolic Syndrome, Multi-Omics, Precision Medicine, Metabolomics, Genomics, Transcriptomics, Microbiome, Machine Learning
- Medical subject headings
- Metabolic Syndrome, Obesity, Overweight, Cardiovascular Diseases, Renal Insufficiency, Chronic, Non-alcoholic Fatty Liver Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
no intervention
| Study group | Role | What they receive |
|---|---|---|
| whole cohort | Participants who meet the diagnostic criteria for metabolic syndrome, as defined by the International Diabetes Federation (IDF) and/or ATP III guidelines and those participants without metabolic syndrome who are matched to the study group by age and sex. These individuals will undergo annual biospecimen collection (blood, urine, and stool) and longitudinal clinical follow-up to identify molecular signatures associated with disease progression and metabolic complications. Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Identification and validation of multi-omics biomarkers associated with metabolic syndrome and its complications
Comprehensive integration of genomic, transcriptomic, metabolomic, and microbiome datasets to identify molecular signatures predictive of metabolic syndrome progression and related complications (e.g., cardiovascular disease, chronic kidney disease, fatty liver).
Measured: 5 years
Secondary outcomes (3)
Longitudinal changes in metabolomic and microbiome profiles
Evaluation of yearly changes in serum metabolite and gut microbiota composition and their correlation with metabolic parameters such as fasting glucose, triglycerides, HDL-C, and blood pressure.
Measured: Annually for 5 years
Association between omics-derived biomarkers and clinical outcomes
Analysis of associations between identified omics signatures and incident cardiometabolic events (e.g., myocardial infarction, heart failure, renal impairment, fatty liver progression).
Measured: Up to 5 years
Development of an integrative risk prediction model
Construction and internal validation of a machine-learning-based model incorporating multi-omics and clinical data to predict metabolic syndrome-related complications.
Measured: 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Nov 2025
- Study start9 Jun 2025
- Primary completion30 Sep 2028 (estimated)
- Study completion30 Sep 2035 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Metabolic Syndrome (MetS)Studies of the same condition, open and under way.
- More trials run by Chang Gung Memorial HospitalThe sponsor's other registered studies.
- 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
- Prospective
- Enrolment
- 6,266 participants (estimated)
- Target duration
- 5 Years
Sponsor and investigators
- Lead sponsor
- Chang Gung Memorial Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07248371
- Sponsor's protocol ID
- 202400297A3
- Status last verified
- Nov 2025
- First submitted
- 18 Nov 2025
- Last updated
- 25 Nov 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Hsu PW, Yeh CH, Lo CJ, Tsai TH, Chan YH, Chou YJ, Yang NI, Cheng ML, Sheu WH, Lai CC, Sytwu HK, Tsai TF. Trans-omics analyses identify the biochemical network of LPCAT1 associated with coronary artery disease. Biomark Res. 2025 Aug 20;13(1):107. doi: 10.1186/s40364-025-00821-y.
PubMed 40830908
Study at a glance
From the registry record, last updated by the sponsor on 25 Nov 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validating Integrative Multi-omics Approaches in Metabolic Syndrome-related Diseases: A Step Towards Precision Medicine
- ClinicalTrials.gov ID
- NCT07248371
- Acronym / sponsor ID
- 202400297A3
- Conditions
- Metabolic Syndrome (MetS), Obesity & Overweight, Cardiovascular Diseases (CVD), Chronic Kidney Disease, Nonalcoholic Fatty Liver Disease, Healthy
- Keywords
- Metabolic Syndrome, Multi-Omics, Precision Medicine, Metabolomics, Genomics, Transcriptomics, Microbiome, Machine Learning
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 6,266 participants (estimated)
- Lead sponsor
- Chang Gung Memorial HospitalUniversity, hospital or other
- Study start
- 9 Jun 2025 (actual)
- Primary completion
- 30 Sep 2028 (estimated)
- Study completion
- 30 Sep 2035 (estimated)
- First posted
- 25 Nov 2025 (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 validate integrative multi-omics approaches for understanding complications related to metabolic syndrome. By combining genetic, transcriptomic, metabolomic, and microbiome data from participants with and without metabolic syndrome, the research seeks to determine which biological factors predict disease progression and how these insights can inform precision prevention and treatment strategies for metabolic disorders.
Detailed description
This longitudinal, multi-center study is designed to validate integrative multi-omics methodologies for predicting disease progression and complications in metabolic syndrome. Participants will be recruited from all branches of Chang Gung Memorial Hospitals. Individuals who meet the diagnostic criteria for metabolic syndrome will constitute the study group, while age- and sex-matched individuals without metabolic syndrome will serve as controls.
The study will collect peripheral blood, urine, and stool samples for comprehensive multi-omics profiling, including genomics (DNA sequencing), transcriptomics (RNA sequencing), metabolomics (serum and urine metabolite profiling), and microbiomics (stool microbiota analysis). Blood samples (10 mL) will be obtained annually for genetic and metabolomic analyses, while urine (30 mL) and stool (1 mL) samples will be used to assess metabolite and microbial signatures. These biospecimens will be linked with participants' longitudinal clinical data and laboratory test results retrieved from the Chang Gung Research Database (CGRD), providing a unified framework for integrative analysis.
Data integration will utilize advanced bioinformatics pipelines and systems biology tools to identify multi-layered molecular networks associated with disease onset and progression. Analytical methods include dimensionality reduction, clustering, and machine-learning-based feature selection to construct predictive models for metabolic complications such as cardiovascular disease, chronic kidney disease, and fatty liver disease. Identified biomarkers and pathways will be validated internally and cross-compared with pre-existing data from the "Integrated Smart Healthcare Database for Obesity."
All data will be de-identified and securely stored on institutional servers with restricted access. Each participant will be assigned a unique study code to ensure confidentiality. Data linkage between omics datasets and clinical outcomes will be performed through encrypted, privacy-preserving algorithms under the supervision of the institutional data governance committee. The study adheres to the ethical standards set by the Institutional Review Board, ensuring participant protection throughout data collection, analysis, and dissemination.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 5 Years
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| whole cohort | – | Other: No interventionParticipants who meet the diagnostic criteria for metabolic syndrome, as defined by the International Diabetes Federation (IDF) and/or ATP III guidelines and those participants without metabolic syndrome who are matched to the study group by age and sex. These individuals will undergo annual biospecimen collection (blood, urine, and stool) and longitudinal clinical follow-up to identify molecular signatures associated with disease progression and metabolic complications. |
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Participants will be recruited from outpatient clinics at Chang Gung Memorial Hospitals in Taiwan. Recruitment will occur through the Departments of Endocrinology, Cardiology, Cardiac Surgery, Nephrology, and Gastroenterology. The study population will include adults receiving routine clinical care at these sites, representing both individuals with metabolic syndrome and those without the condition who serve as healthy controls. This hospital-based community cohort reflects a diverse urban and suburban Taiwanese population, enabling comprehensive multi-omics analysis of metabolic syndrome-related diseases within a real-world clinical setting.
Key inclusion criteria (2 listed)
- Individuals (male or female) aged 20 years or older
- Willing and able to provide written informed consent to participate in the study
Key exclusion criteria (5 listed)
- Pregnant or breastfeeding women
- Patients with end-stage renal disease receiving hemodialysis or peritoneal dialysis
- Individuals currently undergoing active cancer treatment
- Recipients of any organ transplantation
- Patients diagnosed with dementia
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 |
|---|---|---|
| No interventionno intervention | Other | whole cohort |
Primary outcome
Identification and validation of multi-omics biomarkers associated with metabolic syndrome and its complications
Time frame: 5 years
Comprehensive integration of genomic, transcriptomic, metabolomic, and microbiome datasets to identify molecular signatures predictive of metabolic syndrome progression and related complications (e.g., cardiovascular disease, chronic kidney disease, fatty liver).
3 secondary outcomes
Longitudinal changes in metabolomic and microbiome profiles
Time frame: Annually for 5 years
Association between omics-derived biomarkers and clinical outcomes
Time frame: Up to 5 years
Development of an integrative risk prediction model
Time frame: 5 years
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 25 Nov 2025.
- Results publication: PubMed 40830908Hsu PW, Yeh CH, Lo CJ, Tsai TH, Chan YH, Chou YJ, Yang NI, Cheng ML, Sheu WH, Lai CC, Sytwu HK, Tsai TF. Trans-omics analyses identify the biochemical network of LPCAT1 associated with coronary artery disease. Biomark Res. 2025 Aug 20;13(1):107. doi: 10.1186/s40364-025-00821-y.
- Related InfoLink provided by the sponsor.
- Individual participant dataSharing planned: No
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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 (MetS) and Obesity & Overweight, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
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 2 inclusion and 5 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 25 Nov 2025. 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 Taiwan. 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 Chi-Hsiao Yeh, MD PhD (+886-3-3281200 ext. 2118, yehccl@cgmh.org.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Identification and validation of multi-omics biomarkers associated with metabolic syndrome and its complications (time frame: 5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07248371, which also lists 1 linked publication.
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 25 Nov 2025.