- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07589322
Comparative Observation of Metabolic and Pharmacologic Adipose Remodeling With Enhanced Incretin AgonisTs (COMPARE-AT)
Comparative Adipose Tissue and Cardiometabolic System Remodeling by Tirzepatide and Semaglutide: an AI-integrated Multimodal Metabolomics and Translational Mechanistic Study
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
This study is a single-center, randomized, open-label, active-comparator trial designed to characterize the differential effects of tirzepatide and semaglutide on adipose tissue biology and cardiometabolic remodeling over 12 months in adults with obesity and metabolic syndrome. The trial integrates pharmacologic weight-loss therapy with multimodal phenotyping to quantify changes across body composition, hepatic steatosis, metabolic biomarkers, functional strength, and AI-derived electrophysiologic signatures.
The scientific premise is that incretin-based therapies may produce qualitatively distinct patterns of fat loss, ectopic fat mobilization, and cardiometabolic improvement. Tirzepatide, a dual GIP/GLP-1 receptor agonist, may induce greater reductions in visceral adiposity and hepatic fat compared with GLP-1 receptor agonism alone. This trial is designed to directly compare these mechanistic profiles using harmonized imaging, biochemical, and digital phenotyping platforms.
Participants are randomized 1:1 to tirzepatide or semaglutide using a computer-generated permuted block scheme stratified by sex and baseline BMI category. Both interventions follow standard titration schedules and are paired with structured lifestyle counseling to ensure comparable background care. Study visits occur at baseline, 3, 6, and 12 months, with deep phenotyping at baseline, 6, and 12 months.
The phenotyping framework emphasizes regional adiposity, lean mass preservation, hepatic steatosis, and cardiometabolic risk signatures. Whole-body DXA provides quantification of total and regional fat and lean mass, enabling derivation of fat-to-lean mass loss ratios and redistribution indices. Abdominal MRI with proton density fat fraction (PDFF) quantifies liver fat content and abdominal fat compartments. Functional and behavioral assessments-including grip strength and the Chinese version of the Weight-Related Eating Questionnaire-characterize changes in physical function and eating behavior patterns over time.
Fasting biochemical panels measure glycemic indices, lipid metabolism, inflammation, renal and hepatic function, and cardiometabolic biomarkers. Standard 12-lead ECGs are processed through a validated AI pipeline to generate electrophysiologic risk features (e.g., predicted ASCVD risk, ECG-derived heart age), which serve as exploratory digital biomarkers.
A centralized biobanking program supports mechanistic analyses. Serum, plasma, and PBMCs collected at each deep-phenotyping visit are stored under standardized SOPs for targeted and discovery-based metabolomic, proteomic, epigenetic and transcriptomic analyses. These biospecimens will enable downstream investigation of molecular pathways underlying differential treatment responses.
Together, this integrated platform allows for a comprehensive comparison of tirzepatide and semaglutide across structural, metabolic, functional, and molecular domains, providing mechanistic insight into how incretin-based therapies remodel adipose tissue and cardiometabolic physiology.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Feng-Chih Kuo, M.D., Ph.D.
- Phone Number: 12687 886-2-87923311
- Email: shoummie@hotmail.com
Study Locations
-
-
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Taipei, Taiwan, 114202
- Recruiting
- Tri-Service General Hospital
-
Contact:
- Feng-Chih Kuo, M.D., Ph.D.
- Phone Number: 12687 886-2-87923311
- Email: shoummie@hotmail.com
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Age 20-65 years.
- BMI ≥27 kg/m² with metabolic syndrome (ATP III or IDF criteria).
- Stable background medications (antihypertensives, statins, etc.) for ≥3 months.
- Able and willing to provide informed consent and comply with study procedures.
Exclusion Criteria:
- History of diabetes; history of pancreatitis; personal/family history of medullary thyroid carcinoma or MEN2.
- eGFR <30 mL/min/1.73 m², decompensated liver disease, NYHA class III-IV heart failure.
- Recent (<3 months) acute coronary syndrome, stroke, or coronary revascularization.
- Current use of GLP 1RA, tirzepatide, or other incretin based therapies within 3 months.
- Contraindications to MRI or DXA (e.g., metal implants incompatible with MRI, pregnancy).
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Active Comparator: Tirzepatide arm
starting at 2.5 mg weekly and escalated every month (5.0 mg, 7.5 mg to 10 mg) as tolerated
|
Starting at Tirzepatide 2.5 mg weekly and escalated as tolerated to 10 mg along with standardized lifestyle counseling by a dietitian (caloric deficit, physical activity guidance) and written materials.
|
|
Active Comparator: Semaglutide arm
starting at 0.25 mg weekly and escalated every month (0.5 mg, 1.0 mg, 1.7 mg to 2.4 mg) as tolerated
|
Starting at Semaglutide 0.25 mg weekly and escalated as tolerated to 2.4 mg along with standardized lifestyle counseling by a dietitian (caloric deficit, physical activity guidance) and written materials.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
Percent change in total body weight from baseline to 6 months.
Time Frame: Baseline to 6 months
|
Baseline to 6 months
|
|
Total fat to lean mass loss ratio (DXA derived) from baseline to 6 months.
Time Frame: Baseline to 6 months
|
Baseline to 6 months
|
|
Change in metabolic syndrome severity Z score from baseline to 6 months.
Time Frame: Baseline to 6 months.
|
Baseline to 6 months.
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in waist circumference (cm)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in waist-to-hip ratio (unitless ratio)
Time Frame: Baseline to 6 months and 12 months.
|
Baseline to 6 months and 12 months.
|
|
|
Change in regional fat mass measured by DXA (grams)
Time Frame: Baseline to 6 months and 12 months.
|
Baseline to 6 months and 12 months.
|
|
|
Change in regional lean mass measured by DXA (grams)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in 7-site skinfold thickness (mm)
Time Frame: Baseline to 6 months and 12 months.
|
Baseline to 6 months and 12 months.
|
|
|
Change in liver fat content measured by MRI-PDFF (percentage, %PDFF)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in abdominal visceral fat volume (mL)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in abdominal subcutaneous fat volume (mL)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in systolic and diastolic blood pressure (mmHg)
Time Frame: Baseline to 6 months and 12 months
|
Baseline to 6 months and 12 months
|
|
|
Change in fasting lipid profile (mg/dL)
Time Frame: Baseline to 6 months and 12 months
|
Lipid profile includes total cholesterol, LDL-C, HDL-C and Triglycerides
|
Baseline to 6 months and 12 months
|
|
Change in fasting glucose (mg/dL)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in hsCRP (mg/L)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in insulin sensitivity (HOMA-IR, unitless)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in β-cell function (HOMA-β, percentage, %)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in AI-ECG predicted ASCVD risk score (percentage, %)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in ECG-derived heart age (years)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in AI-ECG diabetes risk index (HbA1c, percentage, %)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in estimated 10-year ASCVD risk (percentage, %)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in bone mineral density (g/cm²)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in serum P1NP (ng/mL)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in serum CTX-1 (ng/mL)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in fasting plasma metabolomics profile (relative abundance units)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in fasting plasma proteomics profile (relative abundance units)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in microRNA expression signatures (normalized expression units)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in RNA-seq transcriptomic signatures (normalized counts, e.g., TPM)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in epigenetic methylation signatures (Methylation, percentage, %)
Time Frame: Baseline to 6 and 12 months
|
Baseline to 6 and 12 months
|
|
|
Change in depressive symptoms (scale score)
Time Frame: Baseline to 6 and 12 months
|
Instrument: e.g., PHQ-9
|
Baseline to 6 and 12 months
|
|
Change in sleep quality (scale score)
Time Frame: Baseline to 6 and 12 months
|
Instrument: e.g., PSQI
|
Baseline to 6 and 12 months
|
|
Change in quality of life (scale score)
Time Frame: Baseline to 6 and 12 months
|
Instrument: e.g., EQ-5D or SF-36
|
Baseline to 6 and 12 months
|
|
Change in eating behavior (WREQ-C total and subscale scores)
Time Frame: Baseline to 3, 6, and 12 months
|
Baseline to 3, 6, and 12 months
|
Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Study Director: Feng-Chih Kuo, M.D., Ph.D., Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Nutrition Disorders
- Metabolic Diseases
- Overnutrition
- Body Weight
- Glucose Metabolism Disorders
- Insulin Resistance
- Hyperinsulinism
- Overweight
- Pathological Conditions, Signs and Symptoms
- Nutritional and Metabolic Diseases
- Signs and Symptoms
- Obesity
- Metabolic Syndrome
- Amino Acids, Peptides, and Proteins
- Proteins
- Glucagon-Like Peptide-1 Receptor
- Glucagon-Like Peptide Receptors
- Receptors, G-Protein-Coupled
- Receptors, Cell Surface
- Membrane Proteins
- Receptors, Gastrointestinal Hormone
- Receptors, Peptide
- Tirzepatide
- semaglutide
Other Study ID Numbers
- C202505161
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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