NCT03792685

Brief Summary

The objectives of this trial are to assess the effects of interactions between genetic factors and diet with various macronutrient intake on the metabolic disorders, obesity and type 2 diabetes risk, prevention, development and progress.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
150

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Sep 2009

Longer than P75 for not_applicable

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 24, 2009

Completed
9.3 years until next milestone

First Submitted

Initial submission to the registry

December 26, 2018

Completed
8 days until next milestone

First Posted

Study publicly available on registry

January 3, 2019

Completed
1.4 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 1, 2020

Completed
7 months until next milestone

Study Completion

Last participant's last visit for all outcomes

January 1, 2021

Completed
Last Updated

February 21, 2021

Status Verified

February 1, 2021

Enrollment Period

10.7 years

First QC Date

December 26, 2018

Last Update Submit

February 17, 2021

Conditions

Outcome Measures

Primary Outcomes (6)

  • The postprandial change and differences in blood glucose levels associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in blood glucose concentrations (mg/dL) will be evaluated, dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The postprandial change and differences in serum insulin concentrations associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in serum insulin concentrations (IU/mL) will be evaluated, dependently on the meal type, genetic and metabolic (body weight, body fat content)

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial Triglycerides (TGs) concentrations associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in blood TGs (mg/dL) concentrations will be evaluated, dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial Free Fatty Acids (FFAs) concentrations associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in blood FFAs (umol/L) concentrations will be evaluated, dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial energy expenditure levels associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in energy expenditure levels (kcal/min) will be evaluated by indirect calorimetry method, dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

    Fasting (time 0) and 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial substrates (carbohydrate, fat and protein) utilization levels associated with investigated single nucleotide polymorphisms.

    The postprandial change and differences in substrates (carbohydrate, fat and protein) utilization (mg/min) will be evaluated by indirect calorimetry method, dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

    Fasting (time 0) and 60, 120, 180, 240 minutes after meal intake.

Secondary Outcomes (5)

  • The change and differences in postprandial ghrelin concentrations associated with investigated single nucleotide polymorphisms.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial leptin concentrations associated with investigated single nucleotide polymorphisms.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial adiponectin concentrations associated with investigated single nucleotide polymorphisms.

    Fasting (time 0) and 30, 60, 120, 180, 240 minutes after meal intake.

  • The change and differences in postprandial peptide YY (PYY) concentrations associated with investigated single nucleotide polymorphisms.

    Fasting (time 0) and 30, 60, 120, 180 minutes after meal intake.

  • The change and differences in postprandial plasma metabolites profiles associated with investigated single nucleotide polymorphisms.

    Fasting (time 0) and 30, 60, 120, 180 minutes after meal intake.

Study Arms (3)

Normal weight

EXPERIMENTAL

Normal weight men. Interventions: normo-carbohydrate meal intake, high-carbohydrate meal intake, high-fat meal intake, high-protein meal intake.

Other: Normo-carbohydrate meal intakeOther: High-carbohydrate meal intakeOther: High-fat meal intakeOther: High-protein meal intake

Overweight/obesity

EXPERIMENTAL

Men with overweight or obesity. Interventions: normo-carbohydrate meal intake, high-carbohydrate meal intake, high-fat meal intake, high-protein meal intake.

Other: Normo-carbohydrate meal intakeOther: High-carbohydrate meal intakeOther: High-fat meal intakeOther: High-protein meal intake

Diabetes

EXPERIMENTAL

Men with prediabetes or type 2 diabetes mellitus. Interventions: normo-carbohydrate meal intake, high-carbohydrate meal intake, high-fat meal intake, high-protein meal intake.

Other: Normo-carbohydrate meal intakeOther: High-carbohydrate meal intakeOther: High-fat meal intakeOther: High-protein meal intake

Interventions

Subjects are going to receive the normo-carbohydrate meal.

DiabetesNormal weightOverweight/obesity

Subjects are going to receive the high-carbohydrate meal.

DiabetesNormal weightOverweight/obesity

Subjects are going to receive the high-fat meal.

DiabetesNormal weightOverweight/obesity

Subjects are going to receive the high-protein meal.

DiabetesNormal weightOverweight/obesity

Eligibility Criteria

Age18 Years - 65 Years
Sexmale
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • healthy men with normal body weight and with overweight/obesity
  • men with metabolic syndrome, hypertension, type 2 diabetes newly diagnosed, or not treated with any medicines
  • maintaining the usual diet and lifestyle throughout the study

You may not qualify if:

  • infectious or acute diseases in the last 4 weeks before the study visits
  • any medicines/dietary supplements consumption in the last 4 weeks before the study visits
  • high level of daily physical activity
  • the following any special diet or dietary patterns (vegetarian, high-fat etc.)
  • the presence of any other significant disease which may affect the results (hormonal disorders, history of any surgeries on gastrointestinal tract, allergies known or suspected, heart failure, history of cancer, any kidney, pancrea and liver diseases, except non-alcoholic fatty liver)
  • abusive alcohol consumption
  • abusive coffee or energy drinks consumption
  • drug consumption

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Clinical Research Centre, Medical University of Bialystok

Bialystok, Polska, 15-276, Poland

Location

Related Publications (20)

  • Adamska E, Ostrowska L, Goscik J, Waszczeniuk M, Kretowski A, Gorska M. Intake of Meals Containing High Levels of Carbohydrates or High Levels of Unsaturated Fatty Acids Induces Postprandial Dysmetabolism in Young Overweight/Obese Men. Biomed Res Int. 2015;2015:147196. doi: 10.1155/2015/147196. Epub 2015 Nov 2.

  • Ciborowski M, Adamska E, Rusak M, Godzien J, Wilk J, Citko A, Bauer W, Gorska M, Kretowski A. CE-MS-based serum fingerprinting to track evolution of type 2 diabetes mellitus. Electrophoresis. 2015 Sep;36(18):2286-2293. doi: 10.1002/elps.201500021. Epub 2015 Jun 26.

  • Kretowski A, Adamska E, Maliszewska K, Wawrusiewicz-Kurylonek N, Citko A, Goscik J, Bauer W, Wilk J, Golonko A, Waszczeniuk M, Lipinska D, Hryniewicka J, Niemira M, Paczkowska M, Ciborowski M, Gorska M. The rs340874 PROX1 type 2 diabetes mellitus risk variant is associated with visceral fat accumulation and alterations in postprandial glucose and lipid metabolism. Genes Nutr. 2015 Mar;10(2):4. doi: 10.1007/s12263-015-0454-6. Epub 2015 Jan 20.

  • Ostrowska L, Fiedorczuk J, Adamska E. Effect of diet and other factors on serum adiponectin concentrations in patients with type 2 diabetes. Rocz Panstw Zakl Hig. 2013;64(1):61-6.

  • Ostrowska L, Witczak K, Adamska E. Effect of nutrition and atherogenic index on the occurrence and intensity of insulin resistance. Pol Arch Med Wewn. 2013;123(6):289-96. doi: 10.20452/pamw.1774. Epub 2013 Jun 5.

  • Adamska E, Ostrowska L, Adamska E, Maliszewska K, Citko A, Waszczeniuk M, Przystupa W, Majewski R, Wasilewska A, Milewski R, Krytowski A, Gorska M. [Differences in dietary habits and food preferences of adults depending on the age]. Rocz Panstw Zakl Hig. 2012;63(1):73-81. Polish.

  • Adamska E, Waszczeniuk M, Goscik J, Golonko A, Wilk J, Pliszka J, Maliszewska K, Lipinska D, Milewski R, Wasilewska A, Citko A, Nikolajuk A, Ostrowska L, Kretowski A, Gorska M. The usefulness of glycated hemoglobin A1c (HbA1c) for identifying dysglycemic states in individuals without previously diagnosed diabetes. Adv Med Sci. 2012;57(2):296-301. doi: 10.2478/v10039-012-0030-x.

  • Adamska-Patruno E, Ostrowska L, Golonko A, Pietraszewska B, Goscik J, Kretowski A, Gorska M. Evaluation of Energy Expenditure and Oxidation of Energy Substrates in Adult Males after Intake of Meals with Varying Fat and Carbohydrate Content. Nutrients. 2018 May 16;10(5):627. doi: 10.3390/nu10050627.

  • Adamska E, Kretowski A, Goscik J, Citko A, Bauer W, Waszczeniuk M, Maliszewska K, Paczkowska-Abdulsalam M, Niemira M, Szczerbinski L, Ciborowski M, Gorska M. The type 2 diabetes susceptibility TCF7L2 gene variants affect postprandial glucose and fat utilization in non-diabetic subjects. Diabetes Metab. 2018 Sep;44(4):379-382. doi: 10.1016/j.diabet.2017.05.001. Epub 2017 May 31. No abstract available.

  • Adamska-Patruno E, Ostrowska L, Goscik J, Pietraszewska B, Kretowski A, Gorska M. The relationship between the leptin/ghrelin ratio and meals with various macronutrient contents in men with different nutritional status: a randomized crossover study. Nutr J. 2018 Dec 28;17(1):118. doi: 10.1186/s12937-018-0427-x.

  • Adamska-Patruno E, Goscik J, Czajkowski P, Maliszewska K, Ciborowski M, Golonko A, Wawrusiewicz-Kurylonek N, Citko A, Waszczeniuk M, Kretowski A, Gorska M. The MC4R genetic variants are associated with lower visceral fat accumulation and higher postprandial relative increase in carbohydrate utilization in humans. Eur J Nutr. 2019 Oct;58(7):2929-2941. doi: 10.1007/s00394-019-01955-0. Epub 2019 Apr 3.

  • Godzien J, Kalaska B, Adamska-Patruno E, Siroka J, Ciborowski M, Kretowski A, Barbas C. Oxidized glycerophosphatidylcholines in diabetes through non-targeted metabolomics: Their annotation and biological meaning. J Chromatogr B Analyt Technol Biomed Life Sci. 2019 Jul 1;1120:62-70. doi: 10.1016/j.jchromb.2019.04.053. Epub 2019 Apr 29.

  • Szczerbinski L, Goscik J, Bauer W, Wawrusiewicz-Kurylonek N, Paczkowska-Abdulsalam M, Niemira M, Citko A, Adamska-Patruno E, Gorska M, Kretowski A. Efficacy of family history, genetic risk score, and physical activity in assessing the prevalence of type 2 diabetes. Pol Arch Intern Med. 2019 Aug 29;129(7-8):442-450. doi: 10.20452/pamw.14866. Epub 2019 Jun 6.

  • Adamska-Patruno E, Samczuk P, Ciborowski M, Godzien J, Pietrowska K, Bauer W, Gorska M, Barbas C, Kretowski A. Metabolomics Reveal Altered Postprandial Lipid Metabolism After a High-Carbohydrate Meal in Men at High Genetic Risk of Diabetes. J Nutr. 2019 Jun 1;149(6):915-922. doi: 10.1093/jn/nxz024.

  • Adamska-Patruno E, Godzien J, Ciborowski M, Samczuk P, Bauer W, Siewko K, Gorska M, Barbas C, Kretowski A. The Type 2 Diabetes Susceptibility PROX1 Gene Variants Are Associated with Postprandial Plasma Metabolites Profile in Non-Diabetic Men. Nutrients. 2019 Apr 19;11(4):882. doi: 10.3390/nu11040882.

  • Maliszewska K, Adamska-Patruno E, Goscik J, Lipinska D, Citko A, Krahel A, Miniewska K, Fiedorczuk J, Moroz M, Gorska M, Kretowski A. The Role of Muscle Decline in Type 2 Diabetes Development: A 5-Year Prospective Observational Cohort Study. Nutrients. 2019 Apr 12;11(4):834. doi: 10.3390/nu11040834.

  • Adamska-Patruno E, Ostrowska L, Goscik J, Fiedorczuk J, Moroz M, Kretowski A, Gorska M. The Differences in Postprandial Serum Concentrations of Peptides That Regulate Satiety/Hunger and Metabolism after Various Meal Intake, in Men with Normal vs. Excessive BMI. Nutrients. 2019 Feb 26;11(3):493. doi: 10.3390/nu11030493.

  • Czajkowski P, Adamska-Patruno E, Bauer W, Fiedorczuk J, Krasowska U, Moroz M, Gorska M, Kretowski A. The Impact of FTO Genetic Variants on Obesity and Its Metabolic Consequences is Dependent on Daily Macronutrient Intake. Nutrients. 2020 Oct 23;12(11):3255. doi: 10.3390/nu12113255.

  • Paczkowska-Abdulsalam M, Niemira M, Bielska A, Szalkowska A, Raczkowska BA, Junttila S, Gyenesei A, Adamska-Patruno E, Maliszewska K, Citko A, Szczerbinski L, Kretowski A. Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects. Int J Mol Sci. 2020 Feb 20;21(4):1455. doi: 10.3390/ijms21041455.

  • Bauer W, Adamska-Patruno E, Krasowska U, Moroz M, Fiedorczuk J, Czajkowski P, Bielska D, Gorska M, Kretowski A. Dietary Macronutrient Intake May Influence the Effects of TCF7L2 rs7901695 Genetic Variants on Glucose Homeostasis and Obesity-Related Parameters: A Cross-Sectional Population-Based Study. Nutrients. 2021 Jun 4;13(6):1936. doi: 10.3390/nu13061936.

MeSH Terms

Conditions

OverweightObesityDiabetes Mellitus, Type 2Metabolic SyndromeGenetic Predisposition to Disease

Condition Hierarchy (Ancestors)

OvernutritionNutrition DisordersNutritional and Metabolic DiseasesBody WeightSigns and SymptomsPathological Conditions, Signs and SymptomsDiabetes MellitusGlucose Metabolism DisordersMetabolic DiseasesEndocrine System DiseasesInsulin ResistanceHyperinsulinismDisease SusceptibilityDisease AttributesPathologic Processes

Study Officials

  • Edyta Adamska-Patruno, PhD

    Clinical Research Centre, Medical University of Bialystok

    STUDY DIRECTOR
  • Maria Gorska, Prof.

    Dept of Endocrinology, Diabetology and Internal Medicine

    PRINCIPAL INVESTIGATOR
  • Adam Kretowski, Prof.

    Dept of Endocrinology, Diabetology and Internal Medicine; Clinical Research Centre

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
PARTICIPANT
Purpose
BASIC SCIENCE
Intervention Model
CROSSOVER
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 26, 2018

First Posted

January 3, 2019

Study Start

September 24, 2009

Primary Completion

June 1, 2020

Study Completion

January 1, 2021

Last Updated

February 21, 2021

Record last verified: 2021-02

Locations