Looking for Personalized Nutrition for Obesity/Type 2 Diabetes Mellitus Prevention

Analysis of Genetic Aspects of Metabolic Response on Diet With Different Content of Carbohydrate and Fat. Searching for Genetic Markers for Individualized Therapy in Patients With Obesity and Type 2 Diabetes

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.

This is a randomized, crossover study that includes 1 screening visit and four meal challenge test visits, separated by a 1-2-weeks washout period. The screening will include 2000 people, males and females, to evaluate the genotype frequencies in studied population, and to find carriers of the rare genetic single nucleotide polymorphisms (SNPs), who will fulfill all the other inclusion criteria. An oral glucose tolerance test (OGTT) will be completed at screening visit. Moreover, the fasting blood samples will be collected for genetic analysis, and measurements of blood glucose and lipid metabolism profile, high-sensitivity C-reactive protein (hs-CRP), hormones/peptides and other factors involved in energy balance regulation. Subjects will be asked to record their daily food intake for 3 days. Assessments of vital signs and body height and weight, waist and hip circumferences, body fat content and body fat distribution, review of concomitant medication/supplement use and inclusion and exclusion criteria, and evaluation of adverse effects will be performed throughout the study. To meal challenge test only men will be included, since the sex hormones may influence the study endpoints. Subjects will be encouraged to maintain their habitual diet during wash-out periods. During the each meal challenge test subjects will consume one of the study meals in random order. The blood will be collected at fasting state and 30, 60, 120, 180 and 240 minutes after meal intake. The energy expenditure and substrate utilization will be measured by indirect calorimetry method at the fasting and postprandially.

Overweight and Obesity, Diabetes Mellitus, Type 2, Metabolic Syndrome, Genetic Predisposition, Diet Modification

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

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

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.

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.

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)

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.

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.

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.

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.

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

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

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

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

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

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

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

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

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

The postprandial change and differences in plasma metabolites profiles (metabolomic fingerprinting) will be evaluated dependently on the meal type, genetic and metabolic (body weight, body fat content) factors.

Inclusion Criteria: 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 Exclusion Criteria: 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

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.