- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02728635
Epigenetic Regulation of Human Adipose Tissue Distribution (Eiffel 2)
July 21, 2023 updated by: AdventHealth Translational Research Institute
The purpose of this study is to collect data to help researchers better understand the different ways that women or men store fat (apple shape versus pear shape).
Study Overview
Status
Active, not recruiting
Conditions
Study Type
Interventional
Enrollment (Actual)
27
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Florida
-
Orlando, Florida, United States, 32804
- Translational Research Institute for Metabolism and Diabetes
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years to 45 years (Adult)
Accepts Healthy Volunteers
Yes
Description
Inclusion Criteria:
- Age 18-45 years inclusive;
- BMI 23-35 kg/m2 inclusive;
- HbA1C <6.0%;
- Weight stable (± 3 kg) during the 3 months prior to enrollment;
- Women must be > 9 months post-partum;
- Able to provide written, informed consent.
Exclusion Criteria:
- Postmenopausal women
- Women with an oophorectomy
- Fasting plasma glucose > 126 mg/dL, or diagnosis with Type 2 Diabetes (T2DM)
- Untreated or symptomatic thyroid disease.
- Aminotransferase or aspartate aminotransferase > 3x upper limit of laboratory reference range, or known diagnosis of liver disease.
- Creatinine > 2x upper limit of laboratory reference range, or known diagnosis of kidney disease.
- Uncontrolled hypertension (BP > 140 systolic or > 90 diastolic)
- New onset (<3 months on a stable regime) use of oral contraceptives or hormone replacement therapy.
- History of drug or alcohol abuse (> 3 drinks per day) within the last 5 years, or psychiatric disease prohibiting adherence to study protocol. Current drug use may be determine by plasma or urine drug screens.
- History of cancer within the last 5 years (skin cancers, with the exception of melanoma, may be acceptable).
- History of organ transplant.
- Myocardial Infarction within the last 6 months.
- Current treatment with blood thinners or antiplatelet medications that cannot be safely stopped for biopsy and testing procedures.
- History of HIV, active Hepatitis B or C or tuberculosis
- Presence of clinically significant abnormalities on EKG.
- Current smokers (smoking within the past 3 months).
- Use of any medications known to influence glucose, fat and/or energy metabolism within the last 3 months (eg. growth hormone therapy, glucocorticoids [steroids], etc.)
- Other chronic or acute illness that might affect study results / interpretation in the opinion of the clinical
- Other items related to procedural risk (outlined below) such as bleeding disorder, claustrophobia, etc.
- Elevated high sensitivity c-reactive protein or known active infection.
- There are some implants which are MR compatible (safe) but would cause artifacts which could obscure our ability to measure an organ, e.g. full braces may negate the ability to measure brain size.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Basic Science
- Allocation: Non-Randomized
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Active Comparator: Group A- Women- Healthy 'pears'
This group will consist of healthy women with a BMI between 23 and 35 kg/m2 as a waist-to-hip ratio of 0.78 or less.
|
A DEXA scan for body composition will also be completed.
After a MRI safety screening a whole body MRI for the volumetric measurement of visceral fat, subcutaneous fat, liver, kidneys, heart, brain, skeletal muscle and intramuscular adipose tissue (IMAT) and hepatic lipid by MRS will be performed.
Whole body imaging will include low resolution positioning images, followed by several sets of 3D images which will be digitally connected to create a 3D image the entire length of the body.
The liver spectroscopy will be performed using PRESS (point resolved spectroscopy) and STEAM (Stimulated Echo Acquisition Mode) sequence during the same imaging session, using the whole body images for positioning.
Two biopsies will be performed to collect fat tissue from the abdomen and thigh region.
Insertion of two intravenous (IV) catheters for performing a Frequently Sampled Intravenous Glucose Tolerance Test (FSIGTT) to measure the acute insulin response to glucose (AIRg) and insulin sensitivity (Si) will be performed.
Resting metabolic rate (RMR) will be used to measure metabolic flexibility.
Point of care blood glucose measurements will be taken frequently to ensure safety.
|
Active Comparator: Group B- Women- Healthy 'apples'
The group will consist of healthy women with a BMI between 23 and 35 kg/m2 as a waist-to-hip ratio of 0.85 or more.
|
A DEXA scan for body composition will also be completed.
After a MRI safety screening a whole body MRI for the volumetric measurement of visceral fat, subcutaneous fat, liver, kidneys, heart, brain, skeletal muscle and intramuscular adipose tissue (IMAT) and hepatic lipid by MRS will be performed.
Whole body imaging will include low resolution positioning images, followed by several sets of 3D images which will be digitally connected to create a 3D image the entire length of the body.
The liver spectroscopy will be performed using PRESS (point resolved spectroscopy) and STEAM (Stimulated Echo Acquisition Mode) sequence during the same imaging session, using the whole body images for positioning.
Two biopsies will be performed to collect fat tissue from the abdomen and thigh region.
Insertion of two intravenous (IV) catheters for performing a Frequently Sampled Intravenous Glucose Tolerance Test (FSIGTT) to measure the acute insulin response to glucose (AIRg) and insulin sensitivity (Si) will be performed.
Resting metabolic rate (RMR) will be used to measure metabolic flexibility.
Point of care blood glucose measurements will be taken frequently to ensure safety.
|
Active Comparator: Group C- Men- Healthy 'apples'
The group will consist of men with a BMI between 23 and 35 kg/m2.
|
A DEXA scan for body composition will also be completed.
After a MRI safety screening a whole body MRI for the volumetric measurement of visceral fat, subcutaneous fat, liver, kidneys, heart, brain, skeletal muscle and intramuscular adipose tissue (IMAT) and hepatic lipid by MRS will be performed.
Whole body imaging will include low resolution positioning images, followed by several sets of 3D images which will be digitally connected to create a 3D image the entire length of the body.
The liver spectroscopy will be performed using PRESS (point resolved spectroscopy) and STEAM (Stimulated Echo Acquisition Mode) sequence during the same imaging session, using the whole body images for positioning.
Two biopsies will be performed to collect fat tissue from the abdomen and thigh region.
Insertion of two intravenous (IV) catheters for performing a Frequently Sampled Intravenous Glucose Tolerance Test (FSIGTT) to measure the acute insulin response to glucose (AIRg) and insulin sensitivity (Si) will be performed.
Resting metabolic rate (RMR) will be used to measure metabolic flexibility.
Point of care blood glucose measurements will be taken frequently to ensure safety.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Epigenetic marks in abdominal vs gluteal subcutaneous adipose tissue and adipocytes
Time Frame: 6 weeks
|
The preadipocytes obtained from biopsies of Abdominal Fat and Gluteofemoral Fat from patients in the 'pears' woman, 'apple' women and men will be cultured by our standard methods in proliferative medium followed by our standard protocol for differentiation into mature adipocytes.
We propose to evaluate samples from 3 individuals from each Group to identify a large number of differentially regulated regions genome wide.
All the data obtained in vitro in culture cells will be compared with the data obtained from RNA and chromatin isolated from the whole tissue Abdominal fat and Gluteofemoral fat biopsies
|
6 weeks
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Collaborators
Investigators
- Principal Investigator: Steven R Smith, MD, Study Principal Investigator
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Weber RV, Buckley MC, Fried SK, Kral JG. Subcutaneous lipectomy causes a metabolic syndrome in hamsters. Am J Physiol Regul Integr Comp Physiol. 2000 Sep;279(3):R936-43. doi: 10.1152/ajpregu.2000.279.3.R936.
- Tran TT, Yamamoto Y, Gesta S, Kahn CR. Beneficial effects of subcutaneous fat transplantation on metabolism. Cell Metab. 2008 May;7(5):410-20. doi: 10.1016/j.cmet.2008.04.004.
- Elbers JM, Asscheman H, Seidell JC, Megens JA, Gooren LJ. Long-term testosterone administration increases visceral fat in female to male transsexuals. J Clin Endocrinol Metab. 1997 Jul;82(7):2044-7. doi: 10.1210/jcem.82.7.4078.
- Elbers JM, Asscheman H, Seidell JC, Gooren LJ. Effects of sex steroid hormones on regional fat depots as assessed by magnetic resonance imaging in transsexuals. Am J Physiol. 1999 Feb;276(2):E317-25. doi: 10.1152/ajpendo.1999.276.2.E317.
- Shi H, Seeley RJ, Clegg DJ. Sexual differences in the control of energy homeostasis. Front Neuroendocrinol. 2009 Aug;30(3):396-404. doi: 10.1016/j.yfrne.2009.03.004. Epub 2009 Mar 31.
- Perrot-Sinal TS. Do these genes make me look fat? Endocrinology. 2009 Mar;150(3):1075-7. doi: 10.1210/en.2008-1586. No abstract available.
- Lavebratt C, Almgren M, Ekstrom TJ. Epigenetic regulation in obesity. Int J Obes (Lond). 2012 Jun;36(6):757-65. doi: 10.1038/ijo.2011.178. Epub 2011 Sep 13.
- Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM, Millen BE, Nonas CA, Pi-Sunyer FX, Stevens J, Stevens VJ, Wadden TA, Wolfe BM, Yanovski SZ; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):2985-3023. doi: 10.1016/j.jacc.2013.11.004. Epub 2013 Nov 12. No abstract available. Erratum In: J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):3029-3030.
- Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, Lang CC, Rumboldt Z, Onen CL, Lisheng L, Tanomsup S, Wangai P Jr, Razak F, Sharma AM, Anand SS; INTERHEART Study Investigators. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005 Nov 5;366(9497):1640-9. doi: 10.1016/S0140-6736(05)67663-5.
- de Koning L, Merchant AT, Pogue J, Anand SS. Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies. Eur Heart J. 2007 Apr;28(7):850-6. doi: 10.1093/eurheartj/ehm026. Epub 2007 Apr 2.
- Divoux A, Karastergiou K, Xie H, Guo W, Perera RJ, Fried SK, Smith SR. Identification of a novel lncRNA in gluteal adipose tissue and evidence for its positive effect on preadipocyte differentiation. Obesity (Silver Spring). 2014 Aug;22(8):1781-5. doi: 10.1002/oby.20793. Epub 2014 May 23.
- Karastergiou K, Fried SK, Xie H, Lee MJ, Divoux A, Rosencrantz MA, Chang RJ, Smith SR. Distinct developmental signatures of human abdominal and gluteal subcutaneous adipose tissue depots. J Clin Endocrinol Metab. 2013 Jan;98(1):362-71. doi: 10.1210/jc.2012-2953. Epub 2012 Nov 12.
- Manolopoulos KN, Karpe F, Frayn KN. Gluteofemoral body fat as a determinant of metabolic health. Int J Obes (Lond). 2010 Jun;34(6):949-59. doi: 10.1038/ijo.2009.286. Epub 2010 Jan 12.
- Boston RC, Stefanovski D, Moate PJ, Sumner AE, Watanabe RM, Bergman RN. MINMOD Millennium: a computer program to calculate glucose effectiveness and insulin sensitivity from the frequently sampled intravenous glucose tolerance test. Diabetes Technol Ther. 2003;5(6):1003-15. doi: 10.1089/152091503322641060.
- Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993 Apr 10;341(8850):938-41. doi: 10.1016/0140-6736(93)91224-a.
- Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia. 1993 Jan;36(1):62-7. doi: 10.1007/BF00399095.
- Divoux A, Eroshkin A, Erdos E, Sandor K, Osborne TF, Smith SR. DNA Methylation as a Marker of Body Shape in Premenopausal Women. Front Genet. 2021 Jul 29;12:709342. doi: 10.3389/fgene.2021.709342. eCollection 2021.
- McAllister EJ, Dhurandhar NV, Keith SW, Aronne LJ, Barger J, Baskin M, Benca RM, Biggio J, Boggiano MM, Eisenmann JC, Elobeid M, Fontaine KR, Gluckman P, Hanlon EC, Katzmarzyk P, Pietrobelli A, Redden DT, Ruden DM, Wang C, Waterland RA, Wright SM, Allison DB. Ten putative contributors to the obesity epidemic. Crit Rev Food Sci Nutr. 2009 Nov;49(10):868-913. doi: 10.1080/10408390903372599.
- Roberson L, Shaharyar S, Aneni E, Freitas W, Blaha M, Agatston A, Blumenthal R, Santos RD, Feiz H, Nasir K, Sposito A. The prevalence of the metabolically healthy obese phenotype in an aging population and its association with subclinical cardiovascular disease: The Brazilian study on healthy aging. Diabetol Metab Syndr. 2014 Nov 7;6(1):121. doi: 10.1186/1758-5996-6-121. eCollection 2014.
- Roberson LL, Aneni EC, Maziak W, Agatston A, Feldman T, Rouseff M, Tran T, Blaha MJ, Santos RD, Sposito A, Al-Mallah MH, Blankstein R, Budoff MJ, Nasir K. Beyond BMI: The "Metabolically healthy obese" phenotype & its association with clinical/subclinical cardiovascular disease and all-cause mortality -- a systematic review. BMC Public Health. 2014 Jan 8;14:14. doi: 10.1186/1471-2458-14-14.
- Qiao Q, Nyamdorj R. Is the association of type II diabetes with waist circumference or waist-to-hip ratio stronger than that with body mass index? Eur J Clin Nutr. 2010 Jan;64(1):30-4. doi: 10.1038/ejcn.2009.93. Epub 2009 Sep 2.
- VAGUE J. The degree of masculine differentiation of obesities: a factor determining predisposition to diabetes, atherosclerosis, gout, and uric calculous disease. Am J Clin Nutr. 1956 Jan-Feb;4(1):20-34. doi: 10.1093/ajcn/4.1.20. No abstract available.
- Vague J. Sexual differentiation. A determinant factor of the forms of obesity. 1947. Obes Res. 1996 Mar;4(2):201-3. doi: 10.1002/j.1550-8528.1996.tb00535.x. No abstract available.
- Santosa S, Jensen MD. Why are we shaped differently, and why does it matter? Am J Physiol Endocrinol Metab. 2008 Sep;295(3):E531-5. doi: 10.1152/ajpendo.90357.2008. Epub 2008 May 20. Erratum In: Am J Physiol Endocrinol Metab. 2009 Feb;296(2):E403.
- Fu J, Hofker M, Wijmenga C. Apple or pear: size and shape matter. Cell Metab. 2015 Apr 7;21(4):507-8. doi: 10.1016/j.cmet.2015.03.016.
- Muhlhausler B, Smith SR. Early-life origins of metabolic dysfunction: role of the adipocyte. Trends Endocrinol Metab. 2009 Mar;20(2):51-7. doi: 10.1016/j.tem.2008.10.006. Epub 2008 Dec 16.
- Armitage JA, Khan IY, Taylor PD, Nathanielsz PW, Poston L. Developmental programming of the metabolic syndrome by maternal nutritional imbalance: how strong is the evidence from experimental models in mammals? J Physiol. 2004 Dec 1;561(Pt 2):355-77. doi: 10.1113/jphysiol.2004.072009. Epub 2004 Sep 30.
- McMillen IC, Robinson JS. Developmental origins of the metabolic syndrome: prediction, plasticity, and programming. Physiol Rev. 2005 Apr;85(2):571-633. doi: 10.1152/physrev.00053.2003.
- Martin RJ, Hausman GJ, Hausman DB. Regulation of adipose cell development in utero. Proc Soc Exp Biol Med. 1998 Dec;219(3):200-10. doi: 10.3181/00379727-219-44333.
- Barker M, Robinson S, Osmond C, Barker DJ. Birth weight and body fat distribution in adolescent girls. Arch Dis Child. 1997 Nov;77(5):381-3. doi: 10.1136/adc.77.5.381.
- Tchoukalova YD, Nathanielsz PW, Conover CA, Smith SR, Ravussin E. Regional variation in adipogenesis and IGF regulatory proteins in the fetal baboon. Biochem Biophys Res Commun. 2009 Mar 13;380(3):679-83. doi: 10.1016/j.bbrc.2009.01.149. Epub 2009 Jan 29.
- Tchoukalova YD, Votruba SB, Tchkonia T, Giorgadze N, Kirkland JL, Jensen MD. Regional differences in cellular mechanisms of adipose tissue gain with overfeeding. Proc Natl Acad Sci U S A. 2010 Oct 19;107(42):18226-31. doi: 10.1073/pnas.1005259107. Epub 2010 Oct 4.
- Tchkonia T, Giorgadze N, Pirtskhalava T, Tchoukalova Y, Karagiannides I, Forse RA, DePonte M, Stevenson M, Guo W, Han J, Waloga G, Lash TL, Jensen MD, Kirkland JL. Fat depot origin affects adipogenesis in primary cultured and cloned human preadipocytes. Am J Physiol Regul Integr Comp Physiol. 2002 May;282(5):R1286-96. doi: 10.1152/ajpregu.00653.2001.
- Terashima M, Barbour S, Ren J, Yu W, Han Y, Muegge K. Effect of high fat diet on paternal sperm histone distribution and male offspring liver gene expression. Epigenetics. 2015;10(9):861-71. doi: 10.1080/15592294.2015.1075691.
- McPherson NO, Owens JA, Fullston T, Lane M. Preconception diet or exercise intervention in obese fathers normalizes sperm microRNA profile and metabolic syndrome in female offspring. Am J Physiol Endocrinol Metab. 2015 May 1;308(9):E805-21. doi: 10.1152/ajpendo.00013.2015. Epub 2015 Feb 17.
- Livesey G, Elia M. Estimation of energy expenditure, net carbohydrate utilization, and net fat oxidation and synthesis by indirect calorimetry: evaluation of errors with special reference to the detailed composition of fuels. Am J Clin Nutr. 1988 Apr;47(4):608-28. doi: 10.1093/ajcn/47.4.608. Erratum In: Am J Clin Nutr 1989 Dec;50(6):1475.
- Shadid S, Koutsari C, Jensen MD. Direct free fatty acid uptake into human adipocytes in vivo: relation to body fat distribution. Diabetes. 2007 May;56(5):1369-75. doi: 10.2337/db06-1680. Epub 2007 Feb 7.
- Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM, Park PJ, Pazin MJ, Perry MD, Raha D, Reddy TE, Rozowsky J, Shoresh N, Sidow A, Slattery M, Stamatoyannopoulos JA, Tolstorukov MY, White KP, Xi S, Farnham PJ, Lieb JD, Wold BJ, Snyder M. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 2012 Sep;22(9):1813-31. doi: 10.1101/gr.136184.111.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
July 1, 2016
Primary Completion (Estimated)
December 1, 2023
Study Completion (Estimated)
December 1, 2023
Study Registration Dates
First Submitted
March 24, 2016
First Submitted That Met QC Criteria
March 30, 2016
First Posted (Estimated)
April 5, 2016
Study Record Updates
Last Update Posted (Estimated)
July 24, 2023
Last Update Submitted That Met QC Criteria
July 21, 2023
Last Verified
July 1, 2023
More Information
Terms related to this study
Other Study ID Numbers
- TRIMDFH 869496
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
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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