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Genes (Basel). 2018 Nov 2;9(11). pii: E532. doi: 10.3390/genes9110532.

Deep Multi-OMICs and Multi-Tissue Characterization in a Pre- and Postprandial State in Human Volunteers: The GEMM Family Study Research Design.

Author information

1
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. raul@txbiomed.org.
2
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. hlaviada@marista.edu.mx.
3
Facultad de Salud Pública y Nutrición (FASPyN), UANL, Monterrey 64460, Mexico. edna.navag@uanl.mx.
4
Facultad de Medicina y Ciencias Biomédicas, Universidad Autónoma de Chihuahua, Chihuahua 31125, Mexico. ileal@uach.mx.
5
Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí 78240, Mexico. cescuder@uaslp.mx.
6
Centro de Investigación en Ciencias de la Salud (CICSA), Facultad de Ciencias de la Salud, Universidad Anáhuac Norte, Lomas Anahuac 52786, Mexico. fescara@gmail.com.
7
Centro de Investigación en Ciencias de la Salud (CICSA), Facultad de Ciencias de la Salud, Universidad Anáhuac Norte, Lomas Anahuac 52786, Mexico. vanessa-gisellep@wustl.edu.
8
Facultad de Enfermería, Universidad Autónoma de Nuevo León (UANL), Monterrey 64460, Mexico. rosyvelozgarza@hotmail.com.
9
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. khaack@txbiomed.org.
10
Laboratorio de Inmunogenómica y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Ciudad de México C.P. 14610, Mexico. amartinez@inmegen.gob.mx.
11
Laboratorio de Inmunogenómica y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Ciudad de México C.P. 14610, Mexico. fbarajas@inmegen.gob.mx.
12
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. fmolina@marista.edu.mx.
13
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. ln.fatimabuenfil@hotmail.com.
14
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. nut.lucia.gonzalez@hotmail.com.
15
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. rjanssen91@gmail.com.
16
Escuela de Ciencias de la Salud, Universidad Marista de Mérida, Mérida 97300, Mexico. Lopezm.ric@gmail.com.
17
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. cescuder@uaslp.mx.
18
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. janethgaytan@gmail.com.
19
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. ZVaquera@txbiomed.org.
20
Departamento de Enseñanza, Postgrado e Investigación, Hospital Infantil de Tamaulipas, Ciudad Victoria 87150, Mexico. judith.cornejo@tam.gob.mx.
21
Departamento de Nutrición Humana, Universidad Latina de América, Morelia, Michoacán 58170, Mexico. castillomorelia@hotmail.com.
22
Departamento de Nutrición Humana, Universidad Latina de América, Morelia, Michoacán 58170, Mexico. amurillor@unla.edu.mx.
23
Departamento de Nutrición Humana, Universidad Latina de América, Morelia, Michoacán 58170, Mexico. ln.sarapatriciadiaz@victoriamedicalcenter.com.
24
Clínica de Enfermedades Crónicas y Procedimientos Especiales (CECYPE), Morelia 58249, Mexico. benigno.figueroa@cecype.com.
25
Universidad del Valle de Atemajac (UNIVA), Zapopan, Jalisco 45050, Mexico. laura.gonzalez@univa.mx.
26
Universidad del Valle de Atemajac (UNIVA), Zapopan, Jalisco 45050, Mexico. rocio.salinas@univa.mx.
27
Universidad del Valle de Atemajac (UNIVA), Zapopan, Jalisco 45050, Mexico. tantarrea@gmail.com.
28
Facultad de Medicina, Universidad Autónoma Estado de Morelos, Cuernavaca 62209, Mexico. chimal@uaem.mx.
29
Facultad de Medicina, Universidad Autónoma Estado de Morelos, Cuernavaca 62209, Mexico. jsa@uaem.mx.
30
Instituto de Investigaciones Médico-Biológicas, Universidad Veracruzana, Veracruz 91700, Mexico. jose.remes.troche@gmail.com.
31
Facultad de Enfermería, Universidad Autónoma de Nuevo León (UANL), Monterrey 64460, Mexico. svmonterrey@gmail.com.
32
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. lneeha920609@gmail.com.
33
Department of Medicine, Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX 78229, USA. HanX@uthscsa.edu.
34
Laboratorio de Inmunogenómica y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Ciudad de México C.P. 14610, Mexico. lorozco@inmegen.gob.mx.
35
Centro de Investigación en Ciencias de la Salud (CICSA), Facultad de Ciencias de la Salud, Universidad Anáhuac Norte, Lomas Anahuac 52786, Mexico. ernesto.rodriguez@anahuac.mx.
36
Department of Biochemistry, University of Texas Health Science Center, San Antonio, TX 78229, USA. weintraub@uthscsa.edu.
37
Facultad de Enfermería, Universidad Autónoma de Nuevo León (UANL), Monterrey 64460, Mexico. esther.gallegosc@gmail.com.
38
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. scole@txbiomed.org.
39
Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227-0549, USA. jkent@txbiomed.org.

Abstract

Cardiovascular disease (CVD) and type 2 diabetes (T2D) are increasing worldwide. This is mainly due to an unhealthy nutrition, implying that variation in CVD risk may be due to variation in the capacity to manage a nutritional load. We examined the genomic basis of postprandial metabolism. Our main purpose was to introduce the GEMM Family Study (Genetics of Metabolic Diseases in Mexico) as a multi-center study carrying out an ongoing recruitment of healthy urban adults. Each participant received a mixed meal challenge and provided a 5-hours' time course series of blood, buffy coat specimens for DNA isolation, and adipose tissue (ADT)/skeletal muscle (SKM) biopsies at fasting and 3 h after the meal. A comprehensive profiling, including metabolomic signatures in blood and transcriptomic and proteomic profiling in SKM and ADT, was performed to describe tendencies for variation in postprandial response. Our data generation methods showed preliminary trends indicating that by characterizing the dynamic properties of biomarkers with metabolic activity and analyzing multi-OMICS data it could be possible, with this methodology and research design, to identify early trends for molecular biology systems and genes involved in the fasted and fed states.

KEYWORDS:

GEMM family study; mixed meal challenge; multi-OMICS; postprandial metabolism

Conflict of interest statement

The authors declare no conflict of interest. The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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