Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Universidad Nacional Autonoma de Mexico | OTHER |
Not provided
Not provided
Not provided
Metabolic flexibility is a process in which the body can switch energy substrates in different physiological states. This flexibility plays an important role in an individual's health because losing it increases the risk of obesity, metabolic syndrome, insulin resistance, and type 2 diabetes. Considering that humans spend most of their awakening hours in a postprandial (PP) state, an organism's metabolic flexibility (MF) to respond to a standardized meal's consumption would provide information on the individual's metabolic health. The PP response to glucose following an oral glucose tolerance test or consumption of a high-carbohydrate meal is well described; however, few studies assess the FM and PP metabolome using mixed meals with different macronutrients. The investigators address how metabolic flexibility and metabolome change after consuming standardized meals with different macronutrient ratios. Data collection includes clinical and diet information, indirect calorimetry, and capillary blood sampling during fasting and after consumption of standardized meals. Samples are collected weekly for one month. The data will determine the metabolic flexibility and metabolome after consuming standardized meals with different macronutrient ratios.
Enrolled subjects are followed every week for one month. At each visit, a questionnaire assesses daily time activity patterns relevant to energy expenditure, general health status, including infectious symptoms, and confirmation of basic social and demographic characteristics. Dietary intake is assessed by a food frequency questionnaire and a multi-step 24-hour dietary recall for quantitative analysis. If symptoms of infection are present, participants are treated with ad-hoc broad antibiotics. Anthropometrics are obtained. Subjects will then be randomized to receive the metabolic challenges in a different order. The procedures will be performed before (fasting; 8-10 hours) and after (postprandial) consumption of the metabolic challenges. Capillary blood samples (40µ) are obtained in the morning after an 8-hour fasting and after test meal consumption. To obtain the capillary blood sample, sterilize the ring finger with alcohol and allow it to dry. Then, puncture the area with a sterile 2 mm long lancet. Once the drop of blood is formed, it is placed directly into the CardioCheck Plus® cassette to determine glucose triglyceride, LDL-cholesterol, HDL-cholesterol, and total cholesterol. A second drop of capillary blood shall be placed on a filter paper (S&S 903) until a circle of filter paper is filled with blood to saturate the paper throughout its thickness. Insulin concentration shall be determined following the protocol for dried blood, which is standardized in the laboratory. Indirect fasting calorimetry is also performed. After the indirect calorimetry, the metabolic and hormonal response to the test meal is performed.
Each challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food.
Nutrient composition of standardized meal and meal example.
Determination of metabolites in dried blood To determine the concentration of metabolites (amino acids and acyl-carnitines), a circle of 3 mm diameter shall be punched out of the filter paper and placed in a 96-well plate. Add 100 µl of the acyl-carnitine and amino acid standards from the NeoBase PerkinElmer kit. Subsequently, follow the manufacturer's instructions for determining metabolites by liquid chromatography coupled to mass spectrometry (LC-MS).
Determination of the respiratory quotient (RQ) To determine the respiratory quotient (RQ= VmaxCO2/ VmaxO2) and lipid and carbohydrate oxidation examinations, the Cardio Coach CO2 Vmax Encore 29 System calorimeter software (Korr, Inc, UT, USA) will be used according to the instructions of the supplier. Examinations are invariably performed in the morning (8:00-9:00 am) in a thermoneutral environment with controlled pressure, humidity, and temperature, with the patient supine but awake. The investigators examine a maximum of two subjects per day. Oxygen consumption and carbon dioxide production were obtained using a canopy and were monitored continuously for 30 minutes. The initial 10 minutes of the measurement are discarded for the calculation to ensure greater data homogeneity. O2 consumption and CO2 production will be recorded continuously for 30 min. VO2 and VCO2 values will be used in the equation proposed by Weir (Energy Expenditure = [3.941(VO2) + 1.11(VCO2)] x 1440 min/day), considered as the standard method [34]. Additionally, one day before the test, subjects are instructed to fast for 8 hours and not engage in physical activity or consume caffeine the day before the exam. All participants will be asked to eat the same dinner the night before each test. Dinner provides 15% of the daily energy intake; 20 g of protein, 7 g of lipids, and 34 g of carbohydrates)
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| High carbohydrate challenge | Experimental | High carbohydrate challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
|
| High lipid challenge | Experimental | High lipid challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
|
| High protein challenge | Experimental | High protein challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| High carbohydrate challenge | Other | Capillary blood samples will be obtained in the morning after an overnight 8-hour fasting; then, an indirect fasting calorimetry will be performed. After the indirect calorimetry, the metabolic and hormonal response to the test meal is performed. The nutritional composition of the standardized meal is shown below. Energy, 479.6 kcal; Carbohydrate, 83.6%; Lipids, 12.4%, and Protein, 4.0% (70 g of hot cake, 100 g of mango, 270 ml of peach nectar, and 40 g of strawberry jam). The food challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
| Measure | Description | Time Frame |
|---|---|---|
| Metabolic Flexibility Assessed by Respiratory Quotient (RQ) and Substrate Oxidation | Metabolic flexibility will be assessed by measuring the respiratory quotient (RQ) and substrate oxidation during fasting and postprandial states. RQ values are expected to range from 0.70 to 0.80 during fasting and vary during the postprandial period depending on the food consumed: 0.87-1.00 for the high-carbohydrate challenge, 0.70-80 for the high-fat challenge, and 0.81-0.90 for the high-protein challenge. Measurements will be conducted using the Cardio Coach CO2 Vmax Encore 29 System Calorimeter. Oxygen consumption (VO2) and carbon dioxide production (VCO2) values will be used to calculate energy expenditure using Weir's equation: Energy Expenditure = [3.941(VO2) + 1.11(VCO2)] × 1440 min/day. | Once a week for three weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Postprandial Glucose Levels | Measure of postprandial glucose concentration (ml/dL) after meal intake. | Once a week for three weeks |
| Postprandial Triglyceride Levels | Measure of postprandial triglyceride concentration (mg/dL) after meal intake. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Elimination criteria:
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Berenice Palacios-Gonzalez, PhD | Contact | 5553501900 | 1451 | bpalacios@inmegen.gob.mx |
| Noemi Meraz-Cruz, PhD | Contact | 5553501900 | 1200 | nmeraz@inmegen.gob.mx |
| Name | Affiliation | Role |
|---|---|---|
| Berenice Palacios-Gonzalez, PhD | National Institute of Genomic Medicine | Principal Investigator |
| Noemi Meraz-Cruz, PhD | Universidad Nacional Autonoma de Mexico | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Berenice Palacios-Gonzalez | Recruiting | Mexico City | 14610 | Mexico |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32223057 | Background | Schonknecht YB, Crommen S, Stoffel-Wagner B, Coenen M, Fimmers R, Holst JJ, Simon MC, Stehle P, Egert S. Acute Effects of Three Different Meal Patterns on Postprandial Metabolism in Older Individuals with a Risk Phenotype for Cardiometabolic Diseases: A Randomized Controlled Crossover Trial. Mol Nutr Food Res. 2020 May;64(9):e1901035. doi: 10.1002/mnfr.201901035. Epub 2020 Apr 15. | |
| 36211489 |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D005215 | Fasting |
| D006943 | Hyperglycemia |
| D052439 | Lipid Metabolism Disorders |
| D044882 | Glucose Metabolism Disorders |
| D007333 | Insulin Resistance |
| ID | Term |
|---|---|
| D005247 | Feeding Behavior |
| D001519 | Behavior |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
Not provided
Not provided
Enrolled subjects are followed every week for one month. At each visit, a questionnaire assesses daily time-activity patterns. Dietary intake is assessed by a food frequency questionnaire and a multi-step 24-hour dietary recall. Subjects will then be randomized to receive the metabolic challenges in a different order. The procedures will be performed before (fasting; 8-10 hours) and after (postprandial) consumption of the metabolic challenges. Capillary blood samples are obtained in the morning after an 8-hour fasting and after test meal consumption. Once the drop of blood is formed, it is placed directly into the CardioCheck Plus® cassette to determine glucose triglyceride, LDL-cholesterol, HDL-cholesterol, and total cholesterol. A second drop of capillary blood shall be placed on a filter paper. Indirect fasting calorimetry is also performed. After the indirect calorimetry, the metabolic and hormonal response to the test meal is performed.
Not provided
Not provided
There will be a single-blind principal investigator (PI). All results will be coded and will remain closed until the study is completed. The PI will remain blind to the results until the codes are opened at the end of the study.
|
| High lipid challenge | Other | Capillary blood samples will be obtained in the morning after an overnight 8-hour fasting; then, an indirect fasting calorimetry will be performed. After the indirect calorimetry, the metabolic and hormonal response to the test meal is performed. The nutritional composition of the standardized meal is shown below. Energy, 1043.4 kcal; Carbohydrate, 4.9%; Lipids, 86.8%, and Protein, 8.3% (60 g of manchego cheese, 25 g of egg, white, dried, 24 g of bacon, 5 ml of oil, 65 g of cream cheese, 70 g of cream, and 16 g of poblano pepper). The food challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
|
| High proteinchallenge | Other | Capillary blood samples will be obtained in the morning after an overnight 8-hour fasting; then, an indirect fasting calorimetry will be performed. After the indirect calorimetry, the metabolic and hormonal response to the test meal is performed. The nutritional composition of the standardized meal is shown below. Energy, 441.3 kcal; Carbohydrate, 1.6%; Lipids, 5.1%, and Protein, 93.3% (2 scoop Isopure Zero Carb, 180 g of chicken breast, 20 g of lettuce and 24 g of ham turkey breast). The food challenge should be consumed within 15 minutes. After 5 minutes of rest, indirect calorimetry will be postprandially, lasting 30 minutes. Capillary blood shall be obtained at the following times: 15-30-45-60-90 and 120 min after ingestion of food. |
|
| Once a week for three weeks |
| Postprandial Acyl Carnitines Levels | Measure of postprandial acyl carnitines concentration (µmol/L) after meal intake. | Once a week for three weeks |
| Postprandial Amino Acid Levels | Measure of postprandial amino acid concentration (µmol/L) after meal intake. | Once a week for three weeks |
| Background |
| Weinisch P, Fiamoncini J, Schranner D, Raffler J, Skurk T, Rist MJ, Romisch-Margl W, Prehn C, Adamski J, Hauner H, Daniel H, Suhre K, Kastenmuller G. Dynamic patterns of postprandial metabolic responses to three dietary challenges. Front Nutr. 2022 Sep 22;9:933526. doi: 10.3389/fnut.2022.933526. eCollection 2022. |
| 10905472 | Background | Kelley DE, Mandarino LJ. Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes. 2000 May;49(5):677-83. doi: 10.2337/diabetes.49.5.677. |
| 34330475 | Background | Delgadillo-Velazquez JA, Nambo-Venegas R, Patino N, Meraz-Cruz N, Razo-Azamar M, Guevara-Cruz M, Fonseca M, Pale Montero LE, Ibarra-Gonzalez I, Vela-Amieva M, Vadillo-Ortega F, Palacios-Gonzalez B. Metabolic flexibility during normal pregnancy allows appropriate adaptation during gestation independently of BMI. Clin Nutr ESPEN. 2021 Aug;44:254-262. doi: 10.1016/j.clnesp.2021.06.007. Epub 2021 Jun 19. |
| 28670546 | Background | Gupta RD, Ramachandran R, Venkatesan P, Anoop S, Joseph M, Thomas N. Indirect Calorimetry: From Bench to Bedside. Indian J Endocrinol Metab. 2017 Jul-Aug;21(4):594-599. doi: 10.4103/ijem.IJEM_484_16. |
| 35276829 | Background | Lepine G, Tremblay-Franco M, Bouder S, Dimina L, Fouillet H, Mariotti F, Polakof S. Investigating the Postprandial Metabolome after Challenge Tests to Assess Metabolic Flexibility and Dysregulations Associated with Cardiometabolic Diseases. Nutrients. 2022 Jan 21;14(3):472. doi: 10.3390/nu14030472. |
| 25480291 | Background | Muoio DM. Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock. Cell. 2014 Dec 4;159(6):1253-62. doi: 10.1016/j.cell.2014.11.034. |
| 26590418 | Background | Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001. |
| 17635891 | Background | Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA. 2007 Jul 18;298(3):309-16. doi: 10.1001/jama.298.3.309. |
| 16405536 | Background | Nishida T, Tsuji S, Tsujii M, Arimitsu S, Haruna Y, Imano E, Suzuki M, Kanda T, Kawano S, Hiramatsu N, Hayashi N, Hori M. Oral glucose tolerance test predicts prognosis of patients with liver cirrhosis. Am J Gastroenterol. 2006 Jan;101(1):70-5. doi: 10.1111/j.1572-0241.2005.00307.x. |
| Background | Vis, D.J., et al., Analyzing metabolomics-based challenge tests. Metabolomics, 2015. 11(1): p. 50-63. |
| 22426117 | Background | Krug S, Kastenmuller G, Stuckler F, Rist MJ, Skurk T, Sailer M, Raffler J, Romisch-Margl W, Adamski J, Prehn C, Frank T, Engel KH, Hofmann T, Luy B, Zimmermann R, Moritz F, Schmitt-Kopplin P, Krumsiek J, Kremer W, Huber F, Oeh U, Theis FJ, Szymczak W, Hauner H, Suhre K, Daniel H. The dynamic range of the human metabolome revealed by challenges. FASEB J. 2012 Jun;26(6):2607-19. doi: 10.1096/fj.11-198093. Epub 2012 Mar 16. |
| 34255076 | Background | LaBarre JL, Singer K, Burant CF. Advantages of Studying the Metabolome in Response to Mixed-Macronutrient Challenges and Suggestions for Future Research Designs. J Nutr. 2021 Oct 1;151(10):2868-2881. doi: 10.1093/jn/nxab223. |
| 33134764 | Background | Yu EA, Yu T, Jones DP, Ramirez-Zea M, Stein AD. Metabolomic Profiling After a Meal Shows Greater Changes and Lower Metabolic Flexibility in Cardiometabolic Diseases. J Endocr Soc. 2020 Aug 25;4(11):bvaa127. doi: 10.1210/jendso/bvaa127. eCollection 2020 Nov 1. |
| Background | Sebedio, j.-l. and S. Polakof, Using metabolomics to identify biomarkers for metabolic diseases: Analytical methods and applications. 2015. p. 145-166. |
| 31049566 | Background | 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. |
| 29225708 | Background | van den Broek TJ, Bakker GCM, Rubingh CM, Bijlsma S, Stroeve JHM, van Ommen B, van Erk MJ, Wopereis S. Ranges of phenotypic flexibility in healthy subjects. Genes Nutr. 2017 Dec 6;12:32. doi: 10.1186/s12263-017-0589-8. eCollection 2017. |
| 29718708 | Background | Fiamoncini J, Rundle M, Gibbons H, Thomas EL, Geillinger-Kastle K, Bunzel D, Trezzi JP, Kiselova-Kaneva Y, Wopereis S, Wahrheit J, Kulling SE, Hiller K, Sonntag D, Ivanova D, van Ommen B, Frost G, Brennan L, Bell J, Daniel H. Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements. FASEB J. 2018 Oct;32(10):5447-5458. doi: 10.1096/fj.201800330R. Epub 2018 May 2. |
| 26198450 | Background | Kardinaal AF, van Erk MJ, Dutman AE, Stroeve JH, van de Steeg E, Bijlsma S, Kooistra T, van Ommen B, Wopereis S. Quantifying phenotypic flexibility as the response to a high-fat challenge test in different states of metabolic health. FASEB J. 2015 Nov;29(11):4600-13. doi: 10.1096/fj.14-269852. Epub 2015 Jul 21. |
| 32597983 | Background | Yu EA, Yu T, Jones DP, Martorell R, Ramirez-Zea M, Stein AD. Macronutrient, Energy, and Bile Acid Metabolism Pathways Altered Following a Physiological Meal Challenge, Relative to Fasting, among Guatemalan Adults. J Nutr. 2020 Aug 1;150(8):2031-2040. doi: 10.1093/jn/nxaa169. |
| 26658764 | Background | Shrestha A, Mullner E, Poutanen K, Mykkanen H, Moazzami AA. Metabolic changes in serum metabolome in response to a meal. Eur J Nutr. 2017 Mar;56(2):671-681. doi: 10.1007/s00394-015-1111-y. Epub 2015 Dec 10. |
| 29040577 | Background | Moriya T, Satomi Y, Kobayashi H. Metabolomics of postprandial plasma alterations: a comprehensive Japanese study. J Biochem. 2018 Feb 1;163(2):113-121. doi: 10.1093/jb/mvx066. |
| 24906381 | Background | Mathew S, Krug S, Skurk T, Halama A, Stank A, Artati A, Prehn C, Malek JA, Kastenmuller G, Romisch-Margl W, Adamski J, Hauner H, Suhre K. Metabolomics of Ramadan fasting: an opportunity for the controlled study of physiological responses to food intake. J Transl Med. 2014 Jun 6;12:161. doi: 10.1186/1479-5876-12-161. |
| 34293154 | Background | Yu EA, Le NA, Stein AD. Measuring Postprandial Metabolic Flexibility to Assess Metabolic Health and Disease. J Nutr. 2021 Nov 2;151(11):3284-3291. doi: 10.1093/jn/nxab263. |
| 30400254 | Background | Bastarrachea RA, Laviada-Molina HA, Nava-Gonzalez EJ, Leal-Berumen I, Escudero-Lourdes C, Escalante-Araiza F, Peschard VG, Veloz-Garza RA, Haack K, Martinez-Hernandez A, Barajas-Olmos FM, Molina-Segui F, Buenfil-Rello FA, Gonzalez-Ramirez L, Janssen-Aguilar R, Lopez-Munoz R, Perez-Cetina F, Gaytan-Saucedo JF, Vaquera Z, Cornejo-Barrera J, Castillo-Pineda JC, Murillo-Ramirez A, Diaz-Tena SP, Figueroa-Nunez B, Gonzalez-Lopez L, Salinas-Osornio RA, Valencia-Rendon ME, Angeles-Chimal J, Santa-Olalla Tapia J, Remes-Troche JM, Valdovinos-Chavez SB, Huerta-Avila EE, Han X, Orozco L, Rodriguez-Ayala E, Weintraub S, Gallegos-Cabrales EC, Cole SA, Kent JW Jr. Deep Multi-OMICs and Multi-Tissue Characterization in a Pre- and Postprandial State in Human Volunteers: The GEMM Family Study Research Design. Genes (Basel). 2018 Nov 2;9(11):532. doi: 10.3390/genes9110532. |
| 28861127 | Background | Wopereis S, Stroeve JHM, Stafleu A, Bakker GCM, Burggraaf J, van Erk MJ, Pellis L, Boessen R, Kardinaal AAF, van Ommen B. Multi-parameter comparison of a standardized mixed meal tolerance test in healthy and type 2 diabetic subjects: the PhenFlex challenge. Genes Nutr. 2017 Aug 29;12:21. doi: 10.1186/s12263-017-0570-6. eCollection 2017. |
| 29697773 | Background | Smith RL, Soeters MR, Wust RCI, Houtkooper RH. Metabolic Flexibility as an Adaptation to Energy Resources and Requirements in Health and Disease. Endocr Rev. 2018 Aug 1;39(4):489-517. doi: 10.1210/er.2017-00211. |
| Background | Patricio, B.P., et al., Normal menstrual cycle. Intech Open, 2019. doi:10.5772/intechopen. 79876 |
| 29211263 | Background | Ibarra-Gonzalez I, Rodriguez-Valentin R, Lazcano-Ponce E, Vela-Amieva M. Metabolic screening and metabolomics analysis in the Intellectual Developmental Disorders Mexico Study. Salud Publica Mex. 2017 Jul-Aug;59(4):423-428. doi: 10.21149/8668. |
| 30283765 | Background | Mtaweh H, Tuira L, Floh AA, Parshuram CS. Indirect Calorimetry: History, Technology, and Application. Front Pediatr. 2018 Sep 19;6:257. doi: 10.3389/fped.2018.00257. eCollection 2018. |
| 28467922 | Background | Goodpaster BH, Sparks LM. Metabolic Flexibility in Health and Disease. Cell Metab. 2017 May 2;25(5):1027-1036. doi: 10.1016/j.cmet.2017.04.015. |
| 26123789 | Background | Morris C, O'Grada CM, Ryan MF, Gibney MJ, Roche HM, Gibney ER, Brennan L. Modulation of the lipidomic profile due to a lipid challenge and fitness level: a postprandial study. Lipids Health Dis. 2015 Jul 1;14:65. doi: 10.1186/s12944-015-0062-x. |
| D006946 |
| Hyperinsulinism |