- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03421301
Dietary Intervention Modifies Gut Microbiota in Type 2 Diabetes.
A Dietary Intervention With Functional Foods Reduce Metabolic Endotoxemia and Attenuates Biochemical Abnormalities in Subjects With Type 2 Diabetes by Modifying the Gut Microbiota.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
This study was a single-center, randomized, controlled, double-blind, parallel versus placebo that consisted of six visits. The first visit was a screening evaluation to determine whether subjects meet the inclusion criteria. The selected subjects were invited to a second visit that consisted of a medical history, 2-h oral glucose tolerance test (OGTT), collection of stool samples for DNA isolation and collection of 5 ml blood sample. The participants received the first stage dietary strategy for 15 days. In the third visit and second stage of dietary treatment, subjects were randomized to received the dietary portfolio (DP) or placebo (P) treatment accompanied of the reduced energy diet for 1 mo. In the fourth and fifth visits, with a 1 mo interval, dietary assessment and compliance to the DP or P was evaluated. During each follow-up visit, a 24-h dietary recall was collected, a physical activity questionnaire was filled out and anthropometric and clinical parameters were assessed. In the sixth visit, a 2-h oral glucose tolerance test (OGTT) was performed, and a stool sample for DNA isolation and 5 ml blood were collected.
Dietary Intervention In the first stage, the participants consumed a reduced-energy diet tailored to provide a 500-kcal/d deficit as recommended by NIH (8) the with respect to their habitual diet for 15 days. The diet plan consisted in 45-55% carbohydrates, 15-20% protein, 25-35% fat, <7% saturated fat, 200 mg/d cholesterol, 20-35g fiber, 2000-3000 mg/d sodium based on total energy. In the second stage the participants continued to consume the reduced energy diet with the addition of a combination of functional foods (dietary portfolio; DP). The DP provided 200 kcal that were subtracted from the diet. The DP consisted of a mixture of 14g of dehydrated nopal, 4g of chia seed, 30g of soy protein, 4g of inulin,) and 1g of flavoring. The placebo (P) consisted of 28 g of calcium caseinate, 15g of maltodextrin and 1g of flavoring. The kcal, appearance and flavor were similar in DP and P. The DP and P was given in a package in dehydrated form ready to be dissolved in water. The DP was divided into two packages, the first package contained 17.3 g of DP or P given in the breakfast and dissolved in 250 ml and the second package was given at the dinner time (15:00-16:00 h) and contained 34.7g of P and DP dissolved in 300 mL of water.
Dietary compliance Dietary compliance was assessed with a 24-h dietary recall and 3-d food record (food log), during each visit that were analyzed by Food Processor Nutrition Analysis Software. The compliance of the consumption of the DP or P was evaluated with the number of empty packages returned at the following visit. Physical activity was assessed using the International physical activity questionnaire (IPAQ).
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- clinical diagnosis of type 2 diabetes
- Male or female.
- Adults between 30 and 60 years old.
- BMI of 25 to 39.9 kg / m².
- Pharmacological treatment with metformin, a combination of metformin and glibenclamide.
- Evolution of the type 2 diabetes of 4 ± 3 years.
- Patients who knew how to read and write.
- Signature of informed consent.
Exclusion Criteria:
- Diseases that produce secondary obesity.
- Cardiovascular event.
- Weight loss> 3 kg in the last 3 months after the evaluation of the criteria.
- Catabolic diseases such as cancer and acquired immunodeficiency syndrome.
- Gravidity status.
- Positive smoking.
- Treatment with antihypertensive drugs
- Treatment with other hypoglycemic agents that were not metformin
- Treatment with statins, fibrates or other drugs to control dyslipidemia, 6 months before the start of the protocol.
- Any drug or medication that activates intestinal motility
- Use of laxatives or antispasmodics 4 weeks before the study
- Treatment with antibiotics 6 months before the study
- Use of steroids, chemotherapy, immunosuppressant or radiotherapy.
- Uncontrolled type 2 diabetes, ( HbA1c concentration ≥ 9.9%)
- Fasting glucose ≥ 220 mg / dL
- Fasting cholesterol ≥ 240 mg / dL
- Fasting triglycerides ≥ 350 mg / dL
- Serum creatinine in women> 1.2 mg / dL in men> 1.3 mg / d
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Double
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: 1. Dietary portfolio (DP)
the dietary portfolio was given daily in the breakfast and dinner for 2.5 months
|
The dietary intervention was a combination of functional foods (dehydrated nopal, chia seed, soy protein and inulin) that was provided in dehydrated form in packages of 17.3 g dissolved in 250 ml water for breakfast and 34.7 g in 300 ml water for dinner.
|
Placebo Comparator: 2. placebo (P)
the placebo (P) was based was given daily in the breakfast and dinner for 2.5 months
|
The dietary intervention was a combination of functional foods (dehydrated nopal, chia seed, soy protein and inulin) that was provided in dehydrated form in packages of 17.3 g dissolved in 250 ml water for breakfast and 34.7 g in 300 ml water for dinner.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
intestinal microbiota
Time Frame: Change from baseline gut microbiota at three months after the dietary intervention
|
Measurement of intestinal microbiota by sequencing using the Illumina platform
|
Change from baseline gut microbiota at three months after the dietary intervention
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Glucose metabolism profile
Time Frame: Change from baseline serum glucose at three months after dietary intervention
|
serum glucose (mg/dl)
|
Change from baseline serum glucose at three months after dietary intervention
|
Glucose metabolism profile
Time Frame: Change from baseline serum insulin at three months after dietary intervention
|
serum insulin (µUI/ml)
|
Change from baseline serum insulin at three months after dietary intervention
|
Glucose metabolism profile
Time Frame: Change from baseline plasma HbA1c at three months after dietary intervention
|
plasma glycated hemoglobin (HbA1c) (%)
|
Change from baseline plasma HbA1c at three months after dietary intervention
|
Lipid metabolism profile
Time Frame: Change from baseline serum triglycerides at three months after dietary intervention
|
serum triglycerides (mg/dl)
|
Change from baseline serum triglycerides at three months after dietary intervention
|
Lipid metabolism profile
Time Frame: Change from baseline serum total cholesterol at three months after dietary intervention
|
serum total cholesterol (mg/dl)
|
Change from baseline serum total cholesterol at three months after dietary intervention
|
Lipid metabolism profile
Time Frame: Change from baseline serum LDL cholesterol at three months after dietary intervention
|
serum LDL cholesterol (mg/dl)
|
Change from baseline serum LDL cholesterol at three months after dietary intervention
|
Lipid metabolism profile
Time Frame: Change from baseline serum HDL cholesterol at three months after dietary intervention
|
serum HDL cholesterol (mg/dl)
|
Change from baseline serum HDL cholesterol at three months after dietary intervention
|
Lipid metabolism profile
Time Frame: Change from baseline plasma free fatty acids at three months after dietary intervention
|
plasma free fatty acids (FFA) (mmol/L)
|
Change from baseline plasma free fatty acids at three months after dietary intervention
|
metabolomic profile
Time Frame: Change from baseline plasma betaine at three months after dietary intervention
|
plasma betaine (µmol/L)
|
Change from baseline plasma betaine at three months after dietary intervention
|
metabolomic profile
Time Frame: Change from baseline plasma choline at three months after dietary intervention
|
plasma choline (µmol/L)
|
Change from baseline plasma choline at three months after dietary intervention
|
metabolomic profile
Time Frame: Change from baseline plasma TMAO at three months after dietary intervention
|
plasma trimethylamine oxide (TMAO) (µmol/L)
|
Change from baseline plasma TMAO at three months after dietary intervention
|
metabolomic profile
Time Frame: Change from baseline plasma BCAA at three months after dietary intervention
|
plasma branched chain amino acids (BCAA) (µmol/L)
|
Change from baseline plasma BCAA at three months after dietary intervention
|
inflammatory profile
Time Frame: Change from baseline plasma LPS at three months after dietary intervention
|
plasma lipopolysaccharide (LPS) (ng/ml)
|
Change from baseline plasma LPS at three months after dietary intervention
|
inflammatory profile
Time Frame: Change from baseline serum CRP at three months after dietary intervention
|
serum C reactive protein (CRP) (mg/dl)
|
Change from baseline serum CRP at three months after dietary intervention
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Nimbe Torres, PhD, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
Publications and helpful links
General Publications
- Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004 May;27(5):1047-53. doi: 10.2337/diacare.27.5.1047.
- Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, Peters AL, Tsapas A, Wender R, Matthews DR; American Diabetes Association (ADA); European Association for the Study of Diabetes (EASD). Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2012 Jun;35(6):1364-79. doi: 10.2337/dc12-0413. Epub 2012 Apr 19. No abstract available. Erratum In: Diabetes Care. 2013 Feb;36(2):490.
- Lopez-Romero P, Pichardo-Ontiveros E, Avila-Nava A, Vazquez-Manjarrez N, Tovar AR, Pedraza-Chaverri J, Torres N. The effect of nopal (Opuntia ficus indica) on postprandial blood glucose, incretins, and antioxidant activity in Mexican patients with type 2 diabetes after consumption of two different composition breakfasts. J Acad Nutr Diet. 2014 Nov;114(11):1811-8. doi: 10.1016/j.jand.2014.06.352. Epub 2014 Aug 12.
- Sanchez-Tapia M, Aguilar-Lopez M, Perez-Cruz C, Pichardo-Ontiveros E, Wang M, Donovan SM, Tovar AR, Torres N. Nopal (Opuntia ficus indica) protects from metabolic endotoxemia by modifying gut microbiota in obese rats fed high fat/sucrose diet. Sci Rep. 2017 Jul 5;7(1):4716. doi: 10.1038/s41598-017-05096-4.
- Mahendran Y, Cederberg H, Vangipurapu J, Kangas AJ, Soininen P, Kuusisto J, Uusitupa M, Ala-Korpela M, Laakso M. Glycerol and fatty acids in serum predict the development of hyperglycemia and type 2 diabetes in Finnish men. Diabetes Care. 2013 Nov;36(11):3732-8. doi: 10.2337/dc13-0800. Epub 2013 Sep 11.
- Evans JL, Goldfine ID, Maddux BA, Grodsky GM. Are oxidative stress-activated signaling pathways mediators of insulin resistance and beta-cell dysfunction? Diabetes. 2003 Jan;52(1):1-8. doi: 10.2337/diabetes.52.1.1.
- Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, Britt EB, Fu X, Wu Y, Li L, Smith JD, DiDonato JA, Chen J, Li H, Wu GD, Lewis JD, Warrier M, Brown JM, Krauss RM, Tang WH, Bushman FD, Lusis AJ, Hazen SL. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013 May;19(5):576-85. doi: 10.1038/nm.3145. Epub 2013 Apr 7.
- Griffin JL, Wang X, Stanley E. Does our gut microbiome predict cardiovascular risk? A review of the evidence from metabolomics. Circ Cardiovasc Genet. 2015 Feb;8(1):187-91. doi: 10.1161/CIRCGENETICS.114.000219.
- Pedersen HK, Gudmundsdottir V, Nielsen HB, Hyotylainen T, Nielsen T, Jensen BA, Forslund K, Hildebrand F, Prifti E, Falony G, Le Chatelier E, Levenez F, Dore J, Mattila I, Plichta DR, Poho P, Hellgren LI, Arumugam M, Sunagawa S, Vieira-Silva S, Jorgensen T, Holm JB, Trost K; MetaHIT Consortium; Kristiansen K, Brix S, Raes J, Wang J, Hansen T, Bork P, Brunak S, Oresic M, Ehrlich SD, Pedersen O. Human gut microbes impact host serum metabolome and insulin sensitivity. Nature. 2016 Jul 21;535(7612):376-81. doi: 10.1038/nature18646. Epub 2016 Jul 13.
- Serralde-Zuniga AE, Guevara-Cruz M, Tovar AR, Herrera-Hernandez MF, Noriega LG, Granados O, Torres N. Omental adipose tissue gene expression, gene variants, branched-chain amino acids, and their relationship with metabolic syndrome and insulin resistance in humans. Genes Nutr. 2014 Nov;9(6):431. doi: 10.1007/s12263-014-0431-5. Epub 2014 Sep 27.
- Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res. 1998 Sep;6 Suppl 2:51S-209S. No abstract available. Erratum In: Obes Res 1998 Nov;6(6):464.
- Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011 Jun 24;12(6):R60. doi: 10.1186/gb-2011-12-6-r60.
- Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E, Sunagawa S, Prifti E, Vieira-Silva S, Gudmundsdottir V, Pedersen HK, Arumugam M, Kristiansen K, Voigt AY, Vestergaard H, Hercog R, Costea PI, Kultima JR, Li J, Jorgensen T, Levenez F, Dore J; MetaHIT consortium; Nielsen HB, Brunak S, Raes J, Hansen T, Wang J, Ehrlich SD, Bork P, Pedersen O. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature. 2015 Dec 10;528(7581):262-266. doi: 10.1038/nature15766. Epub 2015 Dec 2. Erratum In: Nature. 2017 May 3;545(7652):116.
- van der Hulst RR, van Kreel BK, von Meyenfeldt MF, Brummer RJ, Arends JW, Deutz NE, Soeters PB. Glutamine and the preservation of gut integrity. Lancet. 1993 May 29;341(8857):1363-5. doi: 10.1016/0140-6736(93)90939-e.
- Achamrah N, Dechelotte P, Coeffier M. Glutamine and the regulation of intestinal permeability: from bench to bedside. Curr Opin Clin Nutr Metab Care. 2017 Jan;20(1):86-91. doi: 10.1097/MCO.0000000000000339.
- Gomes AC, Bueno AA, de Souza RG, Mota JF. Gut microbiota, probiotics and diabetes. Nutr J. 2014 Jun 17;13:60. doi: 10.1186/1475-2891-13-60.
- Wexler HM. Bacteroides: the good, the bad, and the nitty-gritty. Clin Microbiol Rev. 2007 Oct;20(4):593-621. doi: 10.1128/CMR.00008-07.
- Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract. 2011 Dec;94(3):311-21. doi: 10.1016/j.diabres.2011.10.029. Epub 2011 Nov 12.
- Timper K, Grisouard J, Sauter NS, Herzog-Radimerski T, Dembinski K, Peterli R, Frey DM, Zulewski H, Keller U, Muller B, Christ-Crain M. Glucose-dependent insulinotropic polypeptide induces cytokine expression, lipolysis, and insulin resistance in human adipocytes. Am J Physiol Endocrinol Metab. 2013 Jan 1;304(1):E1-13. doi: 10.1152/ajpendo.00100.2012. Epub 2012 Oct 23.
- Boden G, Shulman GI. Free fatty acids in obesity and type 2 diabetes: defining their role in the development of insulin resistance and beta-cell dysfunction. Eur J Clin Invest. 2002 Jun;32 Suppl 3:14-23. doi: 10.1046/j.1365-2362.32.s3.3.x.
- Wilson PW, Meigs JB, Sullivan L, Fox CS, Nathan DM, D'Agostino RB Sr. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med. 2007 May 28;167(10):1068-74. doi: 10.1001/archinte.167.10.1068.
- Gomes JMG, Costa JA, Alfenas RCG. Metabolic endotoxemia and diabetes mellitus: A systematic review. Metabolism. 2017 Mar;68:133-144. doi: 10.1016/j.metabol.2016.12.009. Epub 2016 Dec 18.
- Leite AZ, Rodrigues NC, Gonzaga MI, Paiolo JCC, de Souza CA, Stefanutto NAV, Omori WP, Pinheiro DG, Brisotti JL, Matheucci Junior E, Mariano VS, de Oliveira GLV. Detection of Increased Plasma Interleukin-6 Levels and Prevalence of Prevotella copri and Bacteroides vulgatus in the Feces of Type 2 Diabetes Patients. Front Immunol. 2017 Sep 15;8:1107. doi: 10.3389/fimmu.2017.01107. eCollection 2017.
- Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, Liang S, Zhang W, Guan Y, Shen D, Peng Y, Zhang D, Jie Z, Wu W, Qin Y, Xue W, Li J, Han L, Lu D, Wu P, Dai Y, Sun X, Li Z, Tang A, Zhong S, Li X, Chen W, Xu R, Wang M, Feng Q, Gong M, Yu J, Zhang Y, Zhang M, Hansen T, Sanchez G, Raes J, Falony G, Okuda S, Almeida M, LeChatelier E, Renault P, Pons N, Batto JM, Zhang Z, Chen H, Yang R, Zheng W, Li S, Yang H, Wang J, Ehrlich SD, Nielsen R, Pedersen O, Kristiansen K, Wang J. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. 2012 Oct 4;490(7418):55-60. doi: 10.1038/nature11450. Epub 2012 Sep 26.
- Jardine M. Nutrition Considerations for Microbiota Health in Diabetes. Diabetes Spectr. 2016 Nov;29(4):238-244. doi: 10.2337/ds16-0003. No abstract available.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
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
Other Study ID Numbers
- 1165
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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