FRUVEDomics: Behavioral Intervention in Young Adults to Identify Metabolomics and Microbiome Risk

NCT ID: NCT03115866

Last Updated: 2024-09-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

53 participants

Study Classification

INTERVENTIONAL

Study Start Date

2015-01-15

Study Completion Date

2019-01-15

Brief Summary

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Rates of obesity and the metabolic syndrome are increasing in the young adult population (years 18-28). Modifying diet, especially increasing fruit and vegetable intake, can help assist in health maintenance and disease prevention. The purpose of this project is to evaluate the impact of the FRUVEDomics behavior intervention on dietary behaviors and metabolic parameters on young adults "at-risk" of disease. FRUVEDomics is an 8-week free-living dietary intervention, based on the USDA Dietary Guidelines for Americans and driven by the Social Cognitive Theory, conducted in young adults (18-28 years old) at West Virginia University. Individuals were recruited if they had pre-existing poor nutritional habits. A metabolic syndrome risk screening score was given to participants at baseline to measure "risk" status for chronic disease. Subjects were randomized into one of three nutritional intervention groups: 1) "FRUVED" (50% fruit \& vegetable), 2) "FRUVED+LRC" (50% fruit \& vegetable plus low refined carbohydrate), and 3) "FRUVED+LF" (50% fruit \& vegetable plus low fat). Anthropometrics, surveys, venous blood samples and body composition were collected before and after the intervention. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

Detailed Description

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Background: Rates of obesity and the metabolic syndrome are increasing in the young adult population (years 18-28), further creating a need for interventions that will improve later quality of life. Modifying diet, especially increasing fruit and vegetable intake, can help assist in health maintenance and disease prevention. In the past decade, there has been considerable research on behavior interventions focusing on dietary change for the promotion of health. However, successful theory-based dietary behavioral interventions for young adults who follow poor lifestyle habits, are limited. The purpose of this paper is to evaluate the impact of the FRUVEDomics pilot study on dietary behaviors and metabolic parameters on young adults "at-risk" of disease.

Methods: An 8-week free-living dietary intervention, based on the USDA Dietary Guidelines for Americans and driven by the Social Cognitive Theory, was conducted in young adults (18-28 years old) at West Virginia University. Individuals were recruited if they had pre-existing poor nutritional habits. A metabolic syndrome risk screening score was given to participants at baseline to measure "risk" status for chronic disease. Subjects (n=36) were randomized into one of three nutritional intervention groups; 1) "FRUVED" (50% fruit \& vegetable), 2) "FRUVED+LRC" (50% fruit \& vegetable plus low refined carbohydrate), and 3) "FRUVED+LF" (50% fruit \& vegetable plus low fat). Anthropometrics, surveys, venous blood samples and body composition were collected before and after the intervention. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were successfully delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

Specific Aim: Identify novel metabolomic and microbiome phenotypes in response to fruit and vegetable diet intervention in young adults with and without metabolic syndrome (MetS).

Hypothesis 1: Diet consisting of 50% fruit \& vegetable consumption (FRUVED diet) will improve metabolic health as evidenced by lower plasma concentrations of adipokines, inflammatory mediators, and ceramides.

Hypothesis 2. Diet induced changes in the metabolome and micobiome will reveal novel phenotypes that have the potential to be used as new diagnostic biomarkers to distinguish between MetS and healthy adolescents.

Conditions

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Metabolic Syndrome

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

FACTORIAL

2 interventions evaluated against the other and a control.
Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

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FRUVED

Individuals that are at risk for metS and those with metS went through an 8-week dietary intervention called FRUVEDomics to increase fruit and vegetable consumption measuring metabolome and microbiome markers with health-related behaviors. In this arm, individuals were assigned to a diet with 50% fruit and vegetables.

Group Type EXPERIMENTAL

FRUVEDomics

Intervention Type BEHAVIORAL

FRUVEDomics is a behavioral nutrition intervention in young adults 'at risk for metS' and young adults 'with metS' to identify modifiable metabolomics and microbiome risk. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

FRUVED + LRC

Individuals at risk for metS and those with metS went through an 8-week dietary intervention called FRUVEDomics to increase fruit and vegetable consumption measuring metabolome and microbiome markers with health-related behaviors. In this arm, individuals were assigned to a diet of 50% fruit and vegetables plus low refined carbohydrates.

Group Type EXPERIMENTAL

FRUVEDomics

Intervention Type BEHAVIORAL

FRUVEDomics is a behavioral nutrition intervention in young adults 'at risk for metS' and young adults 'with metS' to identify modifiable metabolomics and microbiome risk. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

FRUVED + LF

Individuals at risk for metS and those with metS went through an 8-week dietary intervention called FRUVEDomics to increase fruit and vegetable consumption measuring metabolome and microbiome markers with health-related behaviors. In this arm, individuals were assigned to a diet of 50% fruit and vegetables plus low fat.

Group Type EXPERIMENTAL

FRUVEDomics

Intervention Type BEHAVIORAL

FRUVEDomics is a behavioral nutrition intervention in young adults 'at risk for metS' and young adults 'with metS' to identify modifiable metabolomics and microbiome risk. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

Interventions

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FRUVEDomics

FRUVEDomics is a behavioral nutrition intervention in young adults 'at risk for metS' and young adults 'with metS' to identify modifiable metabolomics and microbiome risk. Group nutrition education including basic nutrition for the prescribed intervention, culinary tool kit distribution, sample budget and grocery shopping tips were delivered to each participant group prior to the start of the intervention. Participants underwent individual weekly consultations with a Registered Dietitian Nutritionist using food logs, food pictures and receipt management, to assess adherence and cost of the intervention.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* 18 to 28 years of age
* either showing evidence of metabolic syndrome or at risk for metabolic syndrome

Exclusion Criteria

* no evidence of metabolic syndrome or of being at-risk for metabolic syndrome
Minimum Eligible Age

18 Years

Maximum Eligible Age

28 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Tennessee

OTHER

Sponsor Role collaborator

University of New Hampshire

OTHER

Sponsor Role collaborator

West Virginia University

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Melissa D. Olfert, DrPH, RDN

Role: PRINCIPAL_INVESTIGATOR

West Virginia University

References

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Tabas I. Cholesterol in health and disease. J Clin Invest. 2002 Sep;110(5):583-90. doi: 10.1172/JCI16381. No abstract available.

Reference Type BACKGROUND
PMID: 12208856 (View on PubMed)

Barsh GS, Schwartz MW. Genetic approaches to studying energy balance: perception and integration. Nat Rev Genet. 2002 Aug;3(8):589-600. doi: 10.1038/nrg862. No abstract available.

Reference Type BACKGROUND
PMID: 12154382 (View on PubMed)

Seeman E. Pathogenesis of bone fragility in women and men. Lancet. 2002 May 25;359(9320):1841-50. doi: 10.1016/S0140-6736(02)08706-8.

Reference Type BACKGROUND
PMID: 12044392 (View on PubMed)

Catalan U, Rodriguez MA, Ras MR, Macia A, Mallol R, Vinaixa M, Fernandez-Castillejo S, Valls RM, Pedret A, Griffin JL, Salek R, Correig X, Motilva MJ, Sola R. Biomarkers of food intake and metabolite differences between plasma and red blood cell matrices; a human metabolomic profile approach. Mol Biosyst. 2013 Jun;9(6):1411-22. doi: 10.1039/c3mb25554a. Epub 2013 Mar 14.

Reference Type BACKGROUND
PMID: 23493899 (View on PubMed)

German JB, Roberts MA, Fay L, Watkins SM. Metabolomics and individual metabolic assessment: the next great challenge for nutrition. J Nutr. 2002 Sep;132(9):2486-7. doi: 10.1093/jn/132.9.2486. No abstract available.

Reference Type BACKGROUND
PMID: 12221197 (View on PubMed)

Morrow DA. Fat cow syndrome. J Dairy Sci. 1976 Sep;59(9):1625-9. doi: 10.3168/jds.S0022-0302(76)84415-3.

Reference Type BACKGROUND
PMID: 965540 (View on PubMed)

McCann JP, Reimers TJ. Insulin response to glucose in estrous and diestrous obese and lean heifers. J Anim Sci. 1985 Sep;61(3):619-23. doi: 10.2527/jas1985.613619x.

Reference Type BACKGROUND
PMID: 3905736 (View on PubMed)

Despres JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature. 2006 Dec 14;444(7121):881-7. doi: 10.1038/nature05488.

Reference Type BACKGROUND
PMID: 17167477 (View on PubMed)

Holland WL, Summers SA. Sphingolipids, insulin resistance, and metabolic disease: new insights from in vivo manipulation of sphingolipid metabolism. Endocr Rev. 2008 Jun;29(4):381-402. doi: 10.1210/er.2007-0025. Epub 2008 May 1.

Reference Type BACKGROUND
PMID: 18451260 (View on PubMed)

Long SD, Pekala PH. Lipid mediators of insulin resistance: ceramide signalling down-regulates GLUT4 gene transcription in 3T3-L1 adipocytes. Biochem J. 1996 Oct 1;319 ( Pt 1)(Pt 1):179-84. doi: 10.1042/bj3190179.

Reference Type BACKGROUND
PMID: 8870666 (View on PubMed)

Kanety H, Hemi R, Papa MZ, Karasik A. Sphingomyelinase and ceramide suppress insulin-induced tyrosine phosphorylation of the insulin receptor substrate-1. J Biol Chem. 1996 Apr 26;271(17):9895-7. doi: 10.1074/jbc.271.17.9895.

Reference Type BACKGROUND
PMID: 8626623 (View on PubMed)

Shah C, Yang G, Lee I, Bielawski J, Hannun YA, Samad F. Protection from high fat diet-induced increase in ceramide in mice lacking plasminogen activator inhibitor 1. J Biol Chem. 2008 May 16;283(20):13538-48. doi: 10.1074/jbc.M709950200. Epub 2008 Mar 22.

Reference Type BACKGROUND
PMID: 18359942 (View on PubMed)

Zhang HH, Halbleib M, Ahmad F, Manganiello VC, Greenberg AS. Tumor necrosis factor-alpha stimulates lipolysis in differentiated human adipocytes through activation of extracellular signal-related kinase and elevation of intracellular cAMP. Diabetes. 2002 Oct;51(10):2929-35. doi: 10.2337/diabetes.51.10.2929.

Reference Type BACKGROUND
PMID: 12351429 (View on PubMed)

Laurencikiene J, van Harmelen V, Arvidsson Nordstrom E, Dicker A, Blomqvist L, Naslund E, Langin D, Arner P, Ryden M. NF-kappaB is important for TNF-alpha-induced lipolysis in human adipocytes. J Lipid Res. 2007 May;48(5):1069-77. doi: 10.1194/jlr.M600471-JLR200. Epub 2007 Feb 1.

Reference Type BACKGROUND
PMID: 17272828 (View on PubMed)

Bocci G, Fioravanti A, Orlandi P, Di Desidero T, Natale G, Fanelli G, Viacava P, Naccarato AG, Francia G, Danesi R. Metronomic ceramide analogs inhibit angiogenesis in pancreatic cancer through up-regulation of caveolin-1 and thrombospondin-1 and down-regulation of cyclin D1. Neoplasia. 2012 Sep;14(9):833-45. doi: 10.1593/neo.12772.

Reference Type BACKGROUND
PMID: 23019415 (View on PubMed)

Sung HK, Doh KO, Son JE, Park JG, Bae Y, Choi S, Nelson SM, Cowling R, Nagy K, Michael IP, Koh GY, Adamson SL, Pawson T, Nagy A. Adipose vascular endothelial growth factor regulates metabolic homeostasis through angiogenesis. Cell Metab. 2013 Jan 8;17(1):61-72. doi: 10.1016/j.cmet.2012.12.010.

Reference Type BACKGROUND
PMID: 23312284 (View on PubMed)

Olfert IM, Howlett RA, Tang K, Dalton ND, Gu Y, Peterson KL, Wagner PD, Breen EC. Muscle-specific VEGF deficiency greatly reduces exercise endurance in mice. J Physiol. 2009 Apr 15;587(Pt 8):1755-67. doi: 10.1113/jphysiol.2008.164384. Epub 2009 Feb 23.

Reference Type BACKGROUND
PMID: 19237429 (View on PubMed)

Olfert IM, Howlett RA, Wagner PD, Breen EC. Myocyte vascular endothelial growth factor is required for exercise-induced skeletal muscle angiogenesis. Am J Physiol Regul Integr Comp Physiol. 2010 Oct;299(4):R1059-67. doi: 10.1152/ajpregu.00347.2010. Epub 2010 Aug 4.

Reference Type BACKGROUND
PMID: 20686173 (View on PubMed)

Haus JM, Kashyap SR, Kasumov T, Zhang R, Kelly KR, Defronzo RA, Kirwan JP. Plasma ceramides are elevated in obese subjects with type 2 diabetes and correlate with the severity of insulin resistance. Diabetes. 2009 Feb;58(2):337-43. doi: 10.2337/db08-1228. Epub 2008 Nov 13.

Reference Type BACKGROUND
PMID: 19008343 (View on PubMed)

Blachnio-Zabielska AU, Pulka M, Baranowski M, Nikolajuk A, Zabielski P, Gorska M, Gorski J. Ceramide metabolism is affected by obesity and diabetes in human adipose tissue. J Cell Physiol. 2012 Feb;227(2):550-7. doi: 10.1002/jcp.22745.

Reference Type BACKGROUND
PMID: 21437908 (View on PubMed)

Gatt S, Dagan A. Cancer and sphingolipid storage disease therapy using novel synthetic analogs of sphingolipids. Chem Phys Lipids. 2012 May;165(4):462-74. doi: 10.1016/j.chemphyslip.2012.02.006. Epub 2012 Feb 23.

Reference Type BACKGROUND
PMID: 22387097 (View on PubMed)

Brindley DN, Lin FT, Tigyi GJ. Role of the autotaxin-lysophosphatidate axis in cancer resistance to chemotherapy and radiotherapy. Biochim Biophys Acta. 2013 Jan;1831(1):74-85. doi: 10.1016/j.bbalip.2012.08.015. Epub 2012 Aug 29.

Reference Type BACKGROUND
PMID: 22954454 (View on PubMed)

Morrell JS, Byrd-Bredbenner C, Quick V, Olfert M, Dent A, Carey GB. Metabolic syndrome: comparison of prevalence in young adults at 3 land-grant universities. J Am Coll Health. 2014;62(1):1-9. doi: 10.1080/07448481.2013.841703.

Reference Type BACKGROUND
PMID: 24313691 (View on PubMed)

National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002 Dec 17;106(25):3143-421. No abstract available.

Reference Type BACKGROUND
PMID: 12485966 (View on PubMed)

Turconi G, Guarcello M, Berzolari FG, Carolei A, Bazzano R, Roggi C. An evaluation of a colour food photography atlas as a tool for quantifying food portion size in epidemiological dietary surveys. Eur J Clin Nutr. 2005 Aug;59(8):923-31. doi: 10.1038/sj.ejcn.1602162.

Reference Type BACKGROUND
PMID: 15928683 (View on PubMed)

Swanson M. Digital photography as a tool to measure school cafeteria consumption. J Sch Health. 2008 Aug;78(8):432-7. doi: 10.1111/j.1746-1561.2008.00326.x.

Reference Type BACKGROUND
PMID: 18651930 (View on PubMed)

Cockburn AF, Dehlin JM, Ngan T, Crout R, Boskovic G, Denvir J, Primerano D, Plassman BL, Wu B, Cuff CF. High throughput DNA sequencing to detect differences in the subgingival plaque microbiome in elderly subjects with and without dementia. Investig Genet. 2012 Sep 21;3(1):19. doi: 10.1186/2041-2223-3-19.

Reference Type BACKGROUND
PMID: 22998923 (View on PubMed)

Related Links

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Other Identifiers

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2014-67001-21851

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

1409433435

Identifier Type: -

Identifier Source: org_study_id

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