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2. Dietary antioxidant intake reduces carotid intima-media thickness in coronary heart disease patients: From the CORDIOPREV study

Author

Rivas-Garcia, Lorenzo, Quintana-Navarro, Gracia M., Torres-Peña, Jose D., Arenas-de Larriva, Antonio P., Alcala-Díaz, Juan F., Yubero-Serrano, Elena M., Perez Caballero, Ana I., Ortiz-Morales, Ana M., Rangel-Zuñiga, Oriol Alberto, López-Moreno, Alejandro, Ordovas, Jose M., Perez-Martinez, Pablo, Lopez-Miranda, Jose, and Delgado-Lista, Javier

Published
2024
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3. Changes in quantity plant-based protein intake on type 2 diabetes remission in coronary heart disease patients: from the CORDIOPREV study

Author

Gutierrez-Mariscal, Francisco M., Alcalá-Diaz, Juan F., Quintana-Navarro, Gracia M., de la Cruz-Ares, Silvia, Torres-Peña, José D., Cardelo, Magdalena P., Arenas-Larriva, Antonio P., Malagón, María M., Romero-Cabrera, Juan L., Ordovás, José M., Pérez-Martínez, Pablo, Delgado-Lista, Javier, Yubero-Serrano, Elena M., and Lopez-Miranda, José

Published
2023
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6. Association between telomere length and intima-media thickness of both common carotid arteries in patients with coronary heart disease: From the CORDIOPREV randomized controlled trial

Author

Ojeda-Rodriguez, Ana, Alcala-Diaz, Juan F., Rangel-Zuñiga, Oriol Alberto, Arenas-de Larriva, Antonio Pablo, Gutierrez-Mariscal, Francisco M., Gómez-Luna, Purificación, Torres-Peña, Jose D., Garcia-Rios, Antonio, Romero-Cabrera, Juan L., Malagon, Maria M., Perez-Martinez, Pablo, Ordovas, Jose M., Delgado-Lista, Javier, Yubero-Serrano, Elena M., and Lopez-Miranda, Jose

Published
2023
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8. Perspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches

Author

Maruvada, Padma, Lampe, Johanna W, Wishart, David S, Barupal, Dinesh, Chester, Deirdra N, Dodd, Dylan, Djoumbou-Feunang, Yannick, Dorrestein, Pieter C, Dragsted, Lars O, Draper, John, Duffy, Linda C, Dwyer, Johanna T, Emenaker, Nancy J, Fiehn, Oliver, Gerszten, Robert E, B Hu, Frank, Karp, Robert W, Klurfeld, David M, Laughlin, Maren R, Little, A Roger, Lynch, Christopher J, Moore, Steven C, Nicastro, Holly L, O'Brien, Diane M, Ordovás, José M, Osganian, Stavroula K, Playdon, Mary, Prentice, Ross, Raftery, Daniel, Reisdorph, Nichole, Roche, Helen M, Ross, Sharon A, Sang, Shengmin, Scalbert, Augustin, Srinivas, Pothur R, and Zeisel, Steven H

Subjects
Prevention, Nutrition, Metabolic and endocrine, Oral and gastrointestinal, Cancer, Biomarkers, Diet, Food, Genomics, Humans, Metabolomics, Metagenomics, Nutritional Physiological Phenomena, Nutritional Sciences, Nutritional Status, Reproducibility of Results, dietary biomarkers, dietary intervention studies, diet, nutrition, metabolomics, Nutrition and Dietetics
Abstract

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research.

Published
2020

9. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium

Author

Merino, Jordi, Dashti, Hassan S, Li, Sherly X, Sarnowski, Chloé, Justice, Anne E, Graff, Misa, Papoutsakis, Constantina, Smith, Caren E, Dedoussis, George V, Lemaitre, Rozenn N, Wojczynski, Mary K, Männistö, Satu, Ngwa, Julius S, Kho, Minjung, Ahluwalia, Tarunveer S, Pervjakova, Natalia, Houston, Denise K, Bouchard, Claude, Huang, Tao, Orho-Melander, Marju, Frazier-Wood, Alexis C, Mook-Kanamori, Dennis O, Pérusse, Louis, Pennell, Craig E, de Vries, Paul S, Voortman, Trudy, Li, Olivia, Kanoni, Stavroula, Rose, Lynda M, Lehtimäki, Terho, Zhao, Jing Hua, Feitosa, Mary F, Luan, Jian’an, McKeown, Nicola M, Smith, Jennifer A, Hansen, Torben, Eklund, Niina, Nalls, Mike A, Rankinen, Tuomo, Huang, Jinyan, Hernandez, Dena G, Schulz, Christina-Alexandra, Manichaikul, Ani, Li-Gao, Ruifang, Vohl, Marie-Claude, Wang, Carol A, van Rooij, Frank JA, Shin, Jean, Kalafati, Ioanna P, Day, Felix, Ridker, Paul M, Kähönen, Mika, Siscovick, David S, Langenberg, Claudia, Zhao, Wei, Astrup, Arne, Knekt, Paul, Garcia, Melissa, Rao, DC, Qi, Qibin, Ferrucci, Luigi, Ericson, Ulrika, Blangero, John, Hofman, Albert, Pausova, Zdenka, Mikkilä, Vera, Wareham, Nick J, Kardia, Sharon LR, Pedersen, Oluf, Jula, Antti, Curran, Joanne E, Zillikens, M Carola, Viikari, Jorma S, Forouhi, Nita G, Ordovás, José M, Lieske, John C, Rissanen, Harri, Uitterlinden, André G, Raitakari, Olli T, Kiefte-de Jong, Jessica C, Dupuis, Josée, Rotter, Jerome I, North, Kari E, Scott, Robert A, Province, Michael A, Perola, Markus, Cupples, L Adrienne, Turner, Stephen T, Sørensen, Thorkild IA, Salomaa, Veikko, Liu, Yongmei, Sung, Yun J, Qi, Lu, Bandinelli, Stefania, Rich, Stephen S, de Mutsert, Renée, Tremblay, Angelo, Oddy, Wendy H, Franco, Oscar H, and Paus, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Obesity, Human Genome, Genetics, Prevention, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Metabolic and endocrine, Aged, Aging, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Cohort Studies, Energy Intake, Female, Fibroblast Growth Factors, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Genotype, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Nutrients, Polymorphism, Single Nucleotide, Receptors, Retinoic Acid, White People, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P

Published
2019

10. A Genome-Wide Association Study Identifies Blood Disorder–Related Variants Influencing Hemoglobin A1c With Implications for Glycemic Status in U.S. Hispanics/Latinos

Author

Moon, Jee-Young, Louie, Tin L, Jain, Deepti, Sofer, Tamar, Schurmann, Claudia, Below, Jennifer E, Lai, Chao-Qiang, Aviles-Santa, M Larissa, Talavera, Gregory A, Smith, Caren E, Petty, Lauren E, Bottinger, Erwin P, Chen, Yii-Der Ida, Taylor, Kent D, Daviglus, Martha L, Cai, Jianwen, Wang, Tao, Tucker, Katherine L, Ordovás, José M, Hanis, Craig L, Loos, Ruth JF, Schneiderman, Neil, Rotter, Jerome I, Kaplan, Robert C, and Qi, Qibin

Subjects
Biomedical and Clinical Sciences, Health Sciences, Diabetes, Minority Health, Genetics, Clinical Research, Hematology, Sickle Cell Disease, Human Genome, Rare Diseases, Adult, Alleles, Blood Glucose, Diabetes Mellitus, Fasting, Female, Genetic Variation, Genome-Wide Association Study, Glucose Tolerance Test, Glycated Hemoglobin, Hematologic Diseases, Hispanic or Latino, Humans, Hyperglycemia, Male, Middle Aged, Phenotype, Prediabetic State, Prevalence, United States, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveWe aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries.Research design and methodsWe conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies.ResultsOur GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28).ConclusionsThis study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.

Published
2019

13. One-year longitudinal association between changes in dietary choline or betaine intake and cardiometabolic variables in the PREvención con DIeta MEDiterránea-Plus (PREDIMED-Plus) trial

Author

Díez-Ricote, Laura, San-Cristobal, Rodrigo, Concejo, M José, Martínez-González, Miguel Á, Corella, Dolores, Salas-Salvadó, Jordi, Goday, Albert, Martínez, J Alfredo, Alonso-Gómez, Ángel M, Wärnberg, Julia, Vioque, Jesús, Romaguera, Dora, López-Miranda, José, Estruch, Ramon, Tinahones, Francisco J, Lapetra, José, Serra-Majem, Lluís, Bueno-Cavanillas, Aurora, Tur, Josep A, Martín Sánchez, Vicente, Pintó, Xavier, Gaforio, José J, Matía-Martín, Pilar, Vidal, Josep, Mas Fontao, Sebastián, Ros, Emilio, Vázquez-Ruiz, Zenaida, Ortega-Azorín, Carolina, García-Gavilán, Jesús F, Malcampo, Mireia, Martínez-Urbistondo, Diego, Tojal-Sierra, Lucas, García Rodríguez, Antonio, Gómez-Bellvert, Nuria, Chaplin, Alice, García-Ríos, Antonio, Bernal-López, Rosa M, Santos-Lozano, José M, Basterra-Gortari, Javier, Sorlí, José V, Murphy, Michelle, Gasulla, Griselda, Micó, Víctor, Salaverria-Lete, Itziar, Goñi Ochandorena, Estibaliz, Babio, Nancy, Herraiz, Xavier, Ordovás, José M, and Daimiel, Lidia

Published
2022
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19. Long-term secondary prevention of cardiovascular disease with a Mediterranean diet and a low-fat diet (CORDIOPREV): a randomised controlled trial

Author

Alcala-Diaz, Juan F, Almaden Peña, Yolanda, Aranda, Enrique, Arenas de Larriva, Antonio P, Badimon, Lina, Badimon, Juan J, Blanco-Molina, Angeles, Blanco-Rojo, Ruth, Bolivar-Muñoz, Julia, Caballero-Villarraso, Javier, Camargo, Antonio, Chica, Javier, Corina, Andreea, Criado-Garcia, Juan, Cruz-Teno, Cristina, Daponte-Codina, Antonio, de Teresa Galvan, Eduardo, Delgado-Casado, Nieves, Delgado-Lista, Javier, Estruch, Ramon, Fernandez, Juan M, Fernandez-Gandara, Carolina, Fuentes-Jimenez, Francisco, Garcia-Carpintero Fernandez-Pacheco, Sonia, Garcia-Rios, Antonio, Gomez-Delgado, Francisco, Gomez-Garduño, Angela, Gomez-Luna, Purificacion, Gomez-Luna, Maria J, Gonzalez-Guardia, Lorena, Gonzalez-Requero, Ana I., Gutierrez-Mariscal, Francisco M, Haro-Mariscal, Carmen M, Jimenez-Lucena, Rosa, Jimenez-Morales, Ana I., Leon-Acuña, Ana, Lopez-Miranda, Jose, Lopez-Segura, Fernando, Marin-Hinojosa, Carmen, Meneses Alvarez, Maria E, Mesa-Luna, Dolores, Moya-Garrido, Maria N, Muñoz-Carvajal, Ignacio, Navarro-Martos, Vanessa, Ochoa, Juan J, Ordovas, Jose M, Ortiz-Minuesa, Juan A, Ortiz-Morales, Ana M, Pan, Manuel, Peña-Orihuela, Patricia, Perez-Caballero, Ana I, Perez-Corral, Isabel, Perez-Jimenez, Francisco, Perez-Martinez, Pablo, Pi-Sunyer, Francesc X, Quintana-Navarro, Gracia M, Ramirez-Lara, Irene, Rangel-Zuñiga, Oriol A, Rodriguez-Artalejo, Fernando, Rodriguez-Cantalejo, Fernando, Romero, Miguel A, Roncero-Ramos, Irene, Ruano-Ruiz, Juan A., Ruiz de Castroviejo, Joaquin, Sanchez-Villegas, Pablo, Suarez de Lezo, Jose, Suarez de Lezo, Javier, Torres-Peña, Jose D, Vals-Delgado, Cristina, Valverde, Roberto, Visioli, Francisco, Yubero-Serrano, Elena M, Fuentes, Francisco, and Gonzalez-Requero, Ana I

Published
2022
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20. Chronodisruption and diet associated with increased cardiometabolic risk in coronary heart disease patients: the CORDIOPREV study

Author

Romero-Cabrera, Juan Luis, Garaulet, Marta, Jimenez-Torres, Jose, Alcala-Diaz, Juan F., Quintana Navarro, Gracia M., Martin-Piedra, Laura, Torres-Peña, Jose David, Rodriguez-Cantalejo, Fernando, Rangel-Zuñiga, Oriol Alberto, Yubero-Serrano, Elena Maria, Luque, Raul M., Ordovas, Jose M., Lopez-Miranda, Jose, Pérez-Martínez, Pablo, and García-Rios, Antonio

Published
2022
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22. Long-term consumption of a mediterranean diet or a low-fat diet on kidney function in coronary heart disease patients: The CORDIOPREV randomized controlled trial

Author

Podadera-Herreros, Alicia, Alcala-Diaz, Juan F., Gutierrez-Mariscal, Francisco M., Jimenez-Torres, Jose, Cruz-Ares, Silvia de la, Arenas-de Larriva, Antonio P., Cardelo, Magdalena P., Torres-Peña, Jose D., Luque, Raul M., Ordovas, Jose M., Delgado-Lista, Javier, Lopez-Miranda, Jose, and Yubero-Serrano, Elena M.

Published
2022
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25. Beta cell functionality and hepatic insulin resistance are major contributors to type 2 diabetes remission and starting pharmacological therapy: from CORDIOPREV randomized controlled trial

Author

Roncero-Ramos, Irene, Gutierrez-Mariscal, Francisco M., Gomez-Delgado, Francisco, Villasanta-Gonzalez, Alejandro, Torres-Peña, Jose D., Cruz-Ares, Silvia De La, Rangel-Zuñiga, Oriol A., Luque, Raul M., Ordovas, Jose M., Delgado-Lista, Javier, Perez-Martinez, Pablo, Camargo, Antonio, Alcalá-Diaz, Juan F., and Lopez-Miranda, Jose

Published
2021
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26. Association of BCAT2 and BCKDH polymorphisms with clinical, anthropometric and biochemical parameters in young adults

Author

Vargas-Morales, Juan M., Guizar-Heredia, Rocio, Méndez-García, Ana L., Palacios-Gonzalez, Berenice, Schcolnik-Cabrera, Alejandro, Granados, Omar, López-Barradas, Adriana M., Vázquez-Manjarrez, Natalia, Medina-Vera, Isabel, Aguilar-López, Miriam, Tovar-Palacio, Claudia, Ordaz-Nava, Guillermo, Rocha-Viggiano, Ana K., Medina-Cerda, Eduardo, Torres, Nimbe, Ordovas, José M., Tovar, Armando R., Guevara-Cruz, Martha, and Noriega, Lilia G.

Published
2021
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28. Genome‐Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

Author

Smith, Caren E, Follis, Jack L, Dashti, Hassan S, Tanaka, Toshiko, Graff, Mariaelisa, Fretts, Amanda M, Kilpeläinen, Tuomas O, Wojczynski, Mary K, Richardson, Kris, Nalls, Mike A, Schulz, Christina‐Alexandra, Liu, Yongmei, Frazier‐Wood, Alexis C, van Eekelen, Esther, Wang, Carol, de Vries, Paul S, Mikkilä, Vera, Rohde, Rebecca, Psaty, Bruce M, Hansen, Torben, Feitosa, Mary F, Lai, Chao‐Qiang, Houston, Denise K, Ferruci, Luigi, Ericson, Ulrika, Wang, Zhe, de Mutsert, Renée, Oddy, Wendy H, de Jonge, Ester AL, Seppälä, Ilkka, Justice, Anne E, Lemaitre, Rozenn N, Sørensen, Thorkild IA, Province, Michael A, Parnell, Laurence D, Garcia, Melissa E, Bandinelli, Stefania, Orho‐Melander, Marju, Rich, Stephen S, Rosendaal, Frits R, Pennell, Craig E, Jong, Jessica C Kiefte‐de, Kähönen, Mika, Young, Kristin L, Pedersen, Oluf, Aslibekyan, Stella, Rotter, Jerome I, Mook‐Kanamori, Dennis O, Zillikens, M Carola, Raitakari, Olli T, North, Kari E, Overvad, Kim, Arnett, Donna K, Hofman, Albert, Lehtimäki, Terho, Tjønneland, Anne, Uitterlinden, André G, Rivadeneira, Fernando, Franco, Oscar H, German, J Bruce, Siscovick, David S, Cupples, L Adrienne, and Ordovás, José M

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Genetics, Human Genome, 2.1 Biological and endogenous factors, Cancer, Metabolic and endocrine, Actins, Adult, Aged, Body Mass Index, Cohort Studies, Cross-Sectional Studies, Dairy Products, Female, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Myosin-Light-Chain Phosphatase, Polymorphism, Single Nucleotide, White People, body mass index, CHARGE consortium, dairy intake, genome-wide interaction study, meta-analysis, Food Sciences, Public Health and Health Services, Food Science, Nutrition & Dietetics, Food sciences, Nutrition and dietetics
Abstract

ScopeBody weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.Methods and resultsA genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction

Published
2018

30. Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF)

Author

Martinez-Perez, Celia, Daimiel, Lidia, Climent-Mainar, Cristina, Martínez-González, Miguel Ángel, Salas-Salvadó, Jordi, Corella, Dolores, Schröder, Helmut, Martinez, Jose Alfredo, Alonso-Gómez, Ángel M., Wärnberg, Julia, Vioque, Jesús, Romaguera, Dora, López-Miranda, José, Estruch, Ramón, Tinahones, Francisco J., Lapetra, José, Serra-Majem, Lluis, Bueno-Cavanillas, Aurora, Tur, Josep A., Sánchez, Vicente Martín, Pintó, Xavier, Delgado-Rodríguez, Miguel, Matía-Martín, Pilar, Vidal, Josep, Vázquez, Clotilde, Ros, Emilio, Basterra, Javier, Babio, Nancy, Guillem-Saiz, Patricia, Zomeño, María Dolores, Abete, Itziar, Vaquero-Luna, Jessica, Barón-López, Francisco Javier, Gonzalez-Palacios, Sandra, Konieczna, Jadwiga, Garcia-Rios, Antonio, Bernal-López, María Rosa, Santos-Lozano, José Manuel, Bes-Rastrollo, Maira, Khoury, Nadine, Saiz, Carmen, Pérez-Vega, Karla Alejandra, Zulet, María Angeles, Tojal-Sierra, Lucas, Ruiz, Zenaida Vázquez, Martinez, Maria Angeles, Malcampo, Mireia, Ordovás, José M., and San-Cristobal, Rodrigo

Published
2022
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34. MiRNAs profile as biomarkers of nutritional therapy for the prevention of type 2 diabetes mellitus: From the CORDIOPREV study

Author

Jimenez-Lucena, Rosa, Alcala-Diaz, Juan Francisco, Roncero-Ramos, Irene, Lopez-Moreno, Javier, Camargo, Antonio, Gomez-Delgado, Francisco, Quintana-Navarro, Gracia M., Vals-Delgado, Cristina, Rodriguez-Cantalejo, Fernando, Luque, Raul M., Delgado-Lista, Javier, Ordovas, Jose M., Perez-Martinez, Pablo, Rangel-Zuñiga, Oriol Alberto, and Lopez-Miranda, Jose

Published
2021
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41. Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood

Author

Zheng, Yan, Huang, Tao, Wang, Tiange, Mei, Zhendong, Sun, Zhonghan, Zhang, Tao, Ellervik, Christina, Chai, Jin-Fang, Sim, Xueling, van Dam, Rob M., Tai, E-Shyong, Koh, Woon-Puay, Dorajoo, Rajkumar, Saw, Seang-Mei, Sabanayagam, Charumathi, Wong, Tien Yin, Gupta, Preeti, Rossing, Peter, Ahluwalia, Tarunveer S., Vinding, Rebecca K., Bisgaard, Hans, Bønnelykke, Klaus, Wang, Yujie, Graff, Mariaelisa, Voortman, Trudy, van Rooij, Frank J. A., Hofman, Albert, van Heemst, Diana, Noordam, Raymond, Estampador, Angela C., Varga, Tibor V., Enzenbach, Cornelia, Scholz, Markus, Thiery, Joachim, Burkhardt, Ralph, Orho-Melander, Marju, Schulz, Christina-Alexandra, Ericson, Ulrika, Sonestedt, Emily, Kubo, Michiaki, Akiyama, Masato, Zhou, Ang, Kilpeläinen, Tuomas O., Hansen, Torben, Kleber, Marcus E., Delgado, Graciela, McCarthy, Mark, Lemaitre, Rozenn N., Felix, Janine F., Jaddoe, Vincent W. V., Wu, Ying, Mohlke, Karen L., Lehtimäki, Terho, Wang, Carol A., Pennell, Craig E., Schunkert, Heribert, Kessler, Thorsten, Zeng, Lingyao, Willenborg, Christina, Peters, Annette, Lieb, Wolfgang, Grote, Veit, Rzehak, Peter, Koletzko, Berthold, Erdmann, Jeanette, Munz, Matthias, Wu, Tangchun, He, Meian, Yu, Caizheng, Lecoeur, Cécile, Froguel, Philippe, Corella, Dolores, Moreno, Luis A., Lai, Chao-Qiang, Pitkänen, Niina, Boreham, Colin A., Ridker, Paul M., Rosendaal, Frits R., de Mutsert, Renée, Power, Chris, Paternoster, Lavinia, Sørensen, Thorkild I. A., Tjønneland, Anne, Overvad, Kim, Djousse, Luc, Rivadeneira, Fernando, Lee, Nanette R., Raitakari, Olli T., Kähönen, Mika, Viikari, Jorma, Langhendries, Jean-Paul, Escribano, Joaquin, Verduci, Elvira, Dedoussis, George, König, Inke, Balkau, Beverley, Coltell, Oscar, Dallongeville, Jean, Meirhaeghe, Aline, Amouyel, Philippe, Gottrand, Frédéric, Pahkala, Katja, Niinikoski, Harri, Hyppönen, Elina, März, Winfried, Mackey, David A., Gruszfeld, Dariusz, Tucker, Katherine L., Fumeron, Frédéric, Estruch, Ramon, Ordovas, Jose M., Arnett, Donna K., Mook-Kanamori, Dennis O., Mozaffarian, Dariush, Psaty, Bruce M., North, Kari E., Chasman, Daniel I., and Qi, Lu

Published
2020

42. Nutrigenomics, the Microbiome, and Gene-Environment Interactions

Author

Ferguson, Jane F, Allayee, Hooman, Gerszten, Robert E, Ideraabdullah, Folami, Kris-Etherton, Penny M, Ordovás, José M, Rimm, Eric B, Wang, Thomas J, and Bennett, Brian J

Subjects
Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Prevention, Nutrition, Human Genome, Genetics, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, American Heart Association, Animals, Biomedical Research, Cardiovascular Diseases, Diet, Diffusion of Innovation, Epigenesis, Genetic, Forecasting, Gastrointestinal Microbiome, Gastrointestinal Tract, Gene-Environment Interaction, Genetic Predisposition to Disease, Genetic Variation, Host-Pathogen Interactions, Humans, Metagenomics, Nutrigenomics, Nutrition Assessment, Nutritional Status, Phenotype, Preventive Health Services, Risk Assessment, Risk Factors, United States, AHA Scientific Statements, diet, metagenomics, microbiota, nutrigenetics, nutrigenomics, nutritional status, American Heart Association Council on Functional Genomics and Translational Biology, Council on Epidemiology and Prevention, and Stroke Council, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

Published
2016

45. Lipidomic profiling identifies signatures of metabolic risk

Author

Yin, Xiaoyan, Willinger, Christine M., Keefe, Joshua, Liu, Jun, Fernández-Ortiz, Antonio, Ibáñez, Borja, Peñalvo, José, Adourian, Aram, Chen, George, Corella, Dolores, Pamplona, Reinald, Portero-Otin, Manuel, Jove, Mariona, Courchesne, Paul, van Duijn, Cornelia M., Fuster, Valentín, Ordovás, José M., Demirkan, Ayşe, Larson, Martin G., and Levy, Daniel

Published
2020
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47. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals

Author

Asnicar, Francesco, Berry, Sarah E., Valdes, Ana M., Nguyen, Long H., Piccinno, Gianmarco, Drew, David A., Leeming, Emily, Gibson, Rachel, Le Roy, Caroline, Khatib, Haya Al, Francis, Lucy, Mazidi, Mohsen, Mompeo, Olatz, Valles-Colomer, Mireia, Tett, Adrian, Beghini, Francesco, Dubois, Léonard, Bazzani, Davide, Thomas, Andrew Maltez, Mirzayi, Chloe, Khleborodova, Asya, Oh, Sehyun, Hine, Rachel, Bonnett, Christopher, Capdevila, Joan, Danzanvilliers, Serge, Giordano, Francesca, Geistlinger, Ludwig, Waldron, Levi, Davies, Richard, Hadjigeorgiou, George, Wolf, Jonathan, Ordovás, José M., Gardner, Christopher, Franks, Paul W., Chan, Andrew T., Huttenhower, Curtis, Spector, Tim D., and Segata, Nicola

Published
2021
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49. Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta‐analysis of nine studies in the CHARGE consortium

Author

Smith, Caren E, Follis, Jack L, Nettleton, Jennifer A, Foy, Millennia, Wu, Jason HY, Ma, Yiyi, Tanaka, Toshiko, Manichakul, Ani W, Wu, Hongyu, Chu, Audrey Y, Steffen, Lyn M, Fornage, Myriam, Mozaffarian, Dariush, Kabagambe, Edmond K, Ferruci, Luigi, Chen, Yii-Der Ida, Rich, Stephen S, Djoussé, Luc, Ridker, Paul M, Tang, Weihong, McKnight, Barbara, Tsai, Michael Y, Bandinelli, Stefania, Rotter, Jerome I, Hu, Frank B, Chasman, Daniel I, Psaty, Bruce M, Arnett, Donna K, King, Irena B, Sun, Qi, Wang, Lu, Lumley, Thomas, Chiuve, Stephanie E, Siscovick, David S, Ordovás, José M, and Lemaitre, Rozenn N

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Dietary Supplements, Prevention, Heart Disease, Nutrition, Genetics, Complementary and Integrative Health, Cardiovascular, Acetyltransferases, Acyltransferases, Adaptor Proteins, Signal Transducing, Carboxy-Lyases, Delta-5 Fatty Acid Desaturase, Diet, Docosahexaenoic Acids, Eicosapentaenoic Acid, Erythrocyte Membrane, Fatty Acid Desaturases, Fatty Acid Elongases, Fatty Acids, Fatty Acids, Omega-3, Female, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, FADS1, Gene-diet interactions, Meta-analysis, Omega-3 fatty acids, Food Sciences, Public Health and Health Services, Food Science, Nutrition & Dietetics, Food sciences, Nutrition and dietetics
Abstract

ScopeTissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid.Methods and resultsWe conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid.ConclusionOur findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.

Published
2015

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