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GEMM Family Study BINATIONAL CONSORTIUM MEXICO-USA Genetics of Metabolic Diseases in México POPULATION GENETIC RESEARCH PROGRAM FOR METABOLIC DISEASES RELATED TO NUTRITION IN MEXICO Genomic Basis of Postprandial Metabolism Coordinating Institutions for Administrative Affairs Department of Genetics, Texas Biomedical Research Institute, San Antonio, Tx, USA Facultad de Enfermeria, Universidad Autónoma de Nuevo León (UANL), Monterrey, México Fundación Mexicana para la Salud (FUNSALUD), México PARTICIPATING ACADEMIC INSTITUTIONS AND AFFILIATED HOSPITALS MONTERREY, NUEVO LEON Facultad de Enfermeria, Universidad Autónoma de Nuevo Leon (UANL) Facultad de Salud Publica y Nutrición (Faspyn), UANL Hospital Metropolitano Monterrey MERIDA, YUCATAN Escuela de Ciencias de la Salud de la Universidad Marista de Mérida Unidad Hospitalaria de la Universidad Marista de Mérida Facultad de Enfermeria, Universidad Autónoma de Yucatán (UADY) CUERNAVACA, MORELOS Facultad de Medicina de la Universidad Autónoma del Estado de Morelos Unidad de Diagnóstico y Medicina Molecular “Dr. Ruy Pérez Tamayo”/Hospital del Niño Morelense CHIHUAHUA, CHIHUAHUA Facultad de Medicina de la Universidad Autónoma de Chihuahua Hospital Central Universitario MORELIA, MICHOACAN Universidad Latina de América, Licenciatura de Nutrición Clínica de Enfermedades Crónicas y Procedimientos Especiales (CECYPE) GUADALAJARA, JALISCO Instituto Superior Autónomo de Occidente, A.C. Universidad del Valle de Atemajac, Universidad Católica (UNIVA) Hospital Salud de los Enfermos, Guadalajara VERACRUZ, VERACRUZ Instituto de Investigaciones Medico Biológicas Universidad Veracruzana, Veracruz Ver. CIUDAD VICTORIA, TAMAULIPAS Hospital Infantil de Tamaulipas SSA SAN LUIS POTOSI Centro de Investigación y Estudios de Posgrado (CIEP) Facultad de Ciencias Quimicas, Universidad Autónoma de San Luis Potosi Universidad del Centro de Mexico (UCEM), SLP Hospital Central "Ignacio Morones Prieto“ MEXICO, DF Fundación Mexicana para la Salud Facultad de Ciencias de la Salud Universidad Anáhuac México Norte Hospital Juarez SS Mexico DF Genetic Basis of Postprandial Metabolism: Progress Report from the Genetics of Metabolic Diseases in Mexico (The GEMM) Family Study Raúl A Bastarrachea 1 , V Saroja Voruganti 1 , Esther C. Gallegos-Cabrales 2 , Hugo A . Laviada-Molina 2 , Guillermo Meléndez 2 , Edna J. Nava-González 2 , Judith Cornejo Barrera 2 , Irene Leal-Berumen 2 , Laura Gonzalez Lopez 2 , Claudia Escudero Lourdes 2 , Jesús Santa-Olalla Tapia 2 , Jose María Remes Troche 2 , Jose A Cortes Cruz 2 , Victoria Paniagua Lopez 2 , Silvia Ortiz Mata 2 , Juan Carlos Castillo Pineda 2 , Jesus Ángeles Chimal 2 , Jesús G. Benavides Olvera 2 , Salvador B. Valdovinos-Chavez 2 , Ernesto Rodriguez Ayala 2 , Raul Rangel-Rangel 2 , Rosa A. Veloz-Garza 2 , Velia M. Cardenas-Villareal 2 , Fernanda Molina-Segui 2 , Patricia Gomez-Aguilar 2 , Jorge A. Alegría Torres 2 , Alejandro Bassol 2 , Daniel Llanas Rodriguez 2 , Roció A Salinas Osornio 2 , Melesio Valencia 2 , Gustavo Acosta 2 , Víctor M Gomez-Moreno 2 , Elizabeth Perez Cruz 2 , Juan Manuel Villaseñor 2 , Alina Calcaneo 2 , Areli Murillo Ramirez 2 , Juan Carlos Lopez-Alvarenga 1 , Karin Haack 1 , Harald H H Göring 1 , Shelley A Cole 1 , John Blangero 1 , Anthony G Comuzzie 1 , Jack W Kent Jr 1 1 Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX; 2 Population Genetic Research for Metabolic Diseases Related to Nutrition in Mexico Consortium Introduction GEMM stands for Genética de las Enfermedades Metabólicas en México. GEMM is a newly-established, multi-center collaborative study of the genetic epidemiology of the metabolic syndrome, a complex of disorders related to type 2 diabetes, obesity and the risk of cardiovascular disease. 10 adults were recruited from GEMM extended families. Anthropometric measurements and resting energy expenditure (MEDGEM) were performed. An intravenous line was placed in the subject’s arm. 10ml of whole blood (fasting) was withdrawn; 3ml was stored in RNA-stabilizing solution tubes while the remainder was aliquoted for biochemical analysis. The nutritionist then calculated a liquid meal corresponding to 30% of the subject’s daily caloric requirement (TDEE). Additional blood draws were made at 15, 30, 45, 60, 90, 120, 180, 240, and 300 min after meal administration. At 180 min post-prandium a surgeon obtained biopsies of vastus lateralis muscle and overlying adipose tissue under local anesthesia. These samples were quickly divided for gene expression profiling. Subjects returned 14d later. A second biopsy was performed on the opposite leg from the first. The postprandial and fasting biopsies were obtained at different visits. Methods To study gene expression before and after a well-defined meal to characterize normal variation in postprandial metabolism. This expression profiling is expected to find genes contributing to the metabolic flexibility of individuals in the Mexican population, by utilizing the latest advances in genomic science focused on studies based on an integrated systems approach to human biology. Such a focus on the genetic response following the consumption of a defined meal at the level of the specific tissues involved (i.e., fat and muscle), will produce new insights into the genetic architecture of individual variation in metabolism of carbohydrates, fats and proteins, and how this variation in response relates to risk for a variety of chronic diseases including obesity, diabetes and heart disease. Analysis of the coordinated metabolic response of individuals to a defined meal should provide new insights into the basis of individual differences in risk for metabolic diseases related to nutrition (obesity, type 2 diabetes, dyslipidemia, atherosclerosis, hypertension) in response to secular trends toward over-nutrition in most developed societies. Specifically, we will seek to gain answers to these questions: 1. What is the extent of variation in metabolic response in healthy Mexican subjects?; 2. What are the time courses of response for macro- nutrients in this population?; 3. How concordant is gene expression in three tissues (PBMCs, subcutaneous fat, and quadriceps muscle)?; 4. How do changes in macronutrient levels correlate with changes in gene expression? We hope to demonstrate the feasibility of an integrative approach to metabolic flexibility, using transcriptomic information as well as more conventional biomarkers. Initial Aim Innovation Hypothesis Variation of postprandial glucose, RMR and VO2 curves in participants with a Lean BMI (18.5 to 24.9) – Overweight BMI (25-29.9) – Obese BMI (30 or more) Kg/m2 Phenotype Characteristics Mean Value Standard Deviation (N=10: 3 Males - 7 Females) Age (y) 41.9 11.6 Height (m) 1.57 0.10 Weight (Kg) 72.4 21.8 BMI (Kg/m2) 28.8 6.0 Waist (cm) 90.6 14.6 Fat mass (%) 31.5 6.0 Fat mass (Kg) 23.4 9.9 Fat free mass (Kg) 49 13.7 Systolic BP 111.6 12.6 Diastolic BP 68.6 9.7 TDEE (Kcal/day) 1490.2 401.0 Mixed Meal (30% TDEE) 420.4 139.8 30% CHO Kcal 365.5 121.6 30% Fat Kcal 180.9 60.2 30% Prot Kcal 95.0 31.6 Postprandial Phenotypes Mean Value Standard Deviation (N=10: 3 Males - 7 Females) 30% CHO (gr) 91.3 30.4 30% Fat (gr) 20.1 6.6 30% Prot (gr) 23.7 7.9 Fasting Glucose (mg/dl) 87.6 7.1 Postprandial Glucose (3 hr) 99.9 13.8 Postprandial Glucose (5 hr) 81.3 9.2 Fasting RMR 1291.1 395.3 Postprandial RMR (3 hr) 1557.7 477.2 Postprandial RMR (5 hr) 1525.5 584.8 Fasting VO2 186.5 57.4 Postprandial VO2 (3 hr) 224.2 68.5 Postprandial VO2 (5 hr) 219.8 84.2 Biopsy Muscle 1st Visit (mg) 154.3 40.5 Biopsy Muscle 2nd Visit (mg) 226.4 157.2 Biopsy SubQ 1st Visit (mg) 333.5 67.1 Biobsy SubQ 2nd Visit (mg) 382.6 195.1 Fat% Ave. FatAve.(Kg) FFMAve.(Kg) Lean 25.6 12.4 35 Overwt 33.8 25.5 47 Obese 35.4 33.3 61 Date Patient ID Age Height Weight BMI Fat Mass Kg Fat (%) Lean Mass (Kg) 10/25/10 1 49 156 71 29.2 27.8 38.8 43.5 10/25/10 2 27 153 57.3 24.5 17.5 30.5 39.8 10/25/10 3 22 156 40.4 16.6 4.8 11.9 35.6 10/25/10 4 47 160 83.3 32.5 31.6 38 51.7 60 70 80 90 100 110 120 130 140 150 160 0 15 30 45 60 90 120 Glucose-mg/dl Time (minutes) Mixed Meal GEMM Study Patient 1 Patient 2 Patient 3 Patient 4 Results 1. Göring HHH, Curran JE, Johnson MP, Dyer TD, Charslesworth J, et al. (2007) Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 39:1208–1216. 2. Bastarrachea RA, Gallegos-Cabriales EC, Nava-González EJ, Haack K, Voruganti VS, Charlesworth J, Laviada- Molina HA, Veloz-Garza RA, Cardenas- Villarreal VM, Valdovinos-Chavez SB, Gomez-Aguilar P, Meléndez G, López- Alvarenga JC, Göring HHH, Cole SA, Blangero J, Comuzzie AG, Kent Jr, JW (2012) Integrating genomic analysis with the genetic basis of gene expression: preliminary evidence of the identification of causal genes for cardiovascular and metabolic traits related to nutrition in Mexicans. Adv Nutr 3:596S–604S. The GEMM family study aims to investigate gene expression before and after a well-defined meal to characterize normal variation in postprandial metabolism in extended families in Mexico, in order to define novel phenotypes for future genetic analysis. In addition to the benefits to biomedical research and health care, GEMM is structured to enhance the scientific capacity of the Centers in Mexico by providing new equipment, technical training, and research opportunities for Mexican investigators in collaborative projects using GEMM data. Establishment of the diagnostic facilities will involve providing equipment and training to the Centers. We have standardized a complex protocol for recruiting probands, and for postprandial phenotypes/biopsy collections. This approach expects to find genes contributing to the metabolic flexibility of individuals following the consumption of a defined meal through an integrated systems approach to human biology. Discussion Selected References Biopsy Procedures Pictures show 2 different patients with the same standardized surgical technique and size of the tissue biopsies.
