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Adipose Tissue Response to Overfeeding in Insulin Resistance-Prone vs. Insulin Sensitive Humans

The recruitment status of this study is unknown. The completion date has passed and the status has not been verified in more than two years.
Verified March 2014 by Tracey McLaughlin, Stanford University.
Recruitment status was:  Recruiting
Information provided by (Responsible Party):
Tracey McLaughlin, Stanford University Identifier:
First received: March 12, 2013
Last updated: March 9, 2014
Last verified: March 2014

Obesity has become an epidemic worldwide. Data from our laboratory and others demonstrate that most of the excess morbidity from obesity is related to insulin resistance (IR). While total adiposity correlates with insulin resistance, not all obese individuals are IR. When obese IR individuals lose weight in response to caloric restriction, even moderate loss of body fat results in improved insulin sensitivity (IS). With massive weight loss, either dietary or surgical, even the most IR individuals can completely reverse their insulin resistance. But why is one individual IR at a BMI of 26 and another IS at a BMI of 35? There must be differences in the manner in which adipose cells/tissue respond to caloric excess and weight gain. One potentially unifying hypothesis with regard to obesity-associated insulin resistance is that those individuals who fail to respond to caloric excess/obesity with adequate adipocyte differentiation and expanded subcutaneous fat storage capacity develop increased circulating FFAs, ectopic fat deposition, stress on adipocytes, triggering localized and systemic inflammation and ultimately insulin resistance in skeletal muscle.

Clearly, the best way to examine the human response to obesity is to challenge overweight individuals with the need to store excess triglyceride in adipose tissue. Specific aims are:

  1. Test the hypothesis that impaired adipogenesis and fat storage capacity are associated with insulin resistance by comparing 1) cell size distribution; 2) gene markers of adipose cell differentiation; 3) differentiation of isolated preadipocytes in IR-prone vs IS individuals subjected to caloric excess.
  2. Determine if circulating (daylong FFA, two-stage Insulin Suppression Test) and ectopic fat (MRI liver, CT abdomen) are worsened to a greater degree in IR-prone vs IS individuals subjected to caloric excess.
  3. Determine whether differences in inflammation and/or innate or adaptive immune response are associated with insulin resistance by comparing differences in resident dendritic cells, macrophages and their activation profiles, changes in T-cell subpopulations, and other inflammatory mediators in IR-prone vs IS individuals who are subjected to caloric excess via overfeeding.
  4. Exploratory: Evaluate IR-prone vs IS individuals for evidence of hypoxia and insufficient angiogenic response in response to caloric excess.

Condition Intervention
Insulin Resistance
Other: Over feeding

Study Type: Interventional
Study Design: Allocation: Non-Randomized
Intervention Model: Single Group Assignment
Masking: Open Label
Official Title: Adipose Tissue Response to Overfeeding in Insulin Resistance-Prone vs. Insulin Sensitive Humans

Resource links provided by NLM:

Further study details as provided by Tracey McLaughlin, Stanford University:

Primary Outcome Measures:
  • Subcutaneous adipose cell triglyceride storage capacity/differentiation [ Time Frame: 3 years ]
    this will be quantified by measuring: 1) adipose cell size distribution; 2) gene markers of adipose cell differentiation; 3) differentiation of isolated preadipocytes in IR-prone vs IS individuals subjected to caloric excess; in vivo triglyceride synthesis using stable isotope methods

Secondary Outcome Measures:
  • Ectopic fat [ Time Frame: 3 years ]
    Fat deposited in liver (MRI), visceral (intraabdominal) abdominal (CT) versus subcutaneous abdominal and thigh fat (CT)

Other Outcome Measures:
  • Adipose tissue and systemic inflammation: both innate or adaptive immune response [ Time Frame: 3 years ]
    Flow cytometry will be used to quantitate, in both adipose tissue and plasma, populations of dendritic cells, T-cell subpopulations, and macrophages

Estimated Enrollment: 45
Study Start Date: September 2011
Estimated Study Completion Date: December 2016
Estimated Primary Completion Date: December 2016 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
Experimental: Insulin resistant and insulin sensitive
Both groups will be given the same intervention and then outcomes compared between groups
Other: Over feeding
Study participants will be given low saturated fat snacks, an additional 750-1000 calories to gain 6-8 lbs over 4 weeks


Ages Eligible for Study:   35 Years to 65 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes

Inclusion Criteria:

BMI 25-35 kg/m2 Healthy adults Age 35-65 Weight stable Nondiabetic

Exclusion Criteria:

Major organ disease such as heart, kidney, liver Malignancy Inflammatory conditions (eg. lupus, rheumatoid arthritis, Crohn's disease) Eating disorder h/o bariatric surgery or liposuction use of blood thinners such as Coumadin (aspirin is ok)

  Contacts and Locations
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Please refer to this study by its identifier: NCT02084641

Contact: Colleen Craig, MD 650-736-2056
Contact: Dalia Perelman, RD 650-723-6713

United States, California
Stanford University Recruiting
Stanford, California, United States, 94305
Contact: Craig, MD    650-736-2056      
Contact: Lamendola, NP    650-736-2056      
Sponsors and Collaborators
Stanford University
Principal Investigator: Tracey McLaughlin, MD Stanford University
  More Information

Responsible Party: Tracey McLaughlin, Associate Professor, Stanford University Identifier: NCT02084641     History of Changes
Other Study ID Numbers: 20281
Study First Received: March 12, 2013
Last Updated: March 9, 2014

Keywords provided by Tracey McLaughlin, Stanford University:
ectopic fat
triglyceride storage
intrahepatic fat
adipocyte proliferation

Additional relevant MeSH terms:
Insulin Resistance
Glucose Metabolism Disorders
Metabolic Diseases
Insulin, Globin Zinc
Hypoglycemic Agents
Physiological Effects of Drugs processed this record on May 25, 2017