Research Project: Personalized Nutrition and Healthy Aging

Location: Jean Mayer Human Nutrition Research Center On Aging

2022 Annual Report

Objectives
Objective 1: Conduct and analyze dietary intervention studies to validate gene-diet interactions and identify the underlying mechanisms using omic technologies. Sub-Objective 1A: To characterize the response of cardiometabolic, epigenetics and other age-related biomarkers and the microbiome to diets differing in saturated fat and prebiotics content (animal-based diet versus plant-based diet) in individuals carrying CC and TT genotypes at the common APOA2 -265T>C (rs5082) SNP using a short-term crossover, randomized feeding study, and to elucidate the physiological mechanism(s) by which diet impinges on metabolic pathways through APOA2 genotypes. Sub-Objective 1B: To characterize the TCF7L2-by-diet interaction with respect to those type 2 diabetes (T2D) and cardiovascular disease (CVD) risk factors identified in observational studies for validation in the context of a short-term randomized controlled feeding study (low-fat diet versus Mediterranean diet), and to elucidate the molecular mechanisms responsible for these GxD interactions using epigenetics and metabolomics. Sub-Objective 1C: To develop polygenic risk scores (PRS) predicting the changes in and relationships between cardiovascular disease (CVD) risk factors and disease incidence in response to long-term (>=1 y) dietary interventions [Mediterranean diet (MedDiet) or Low-fat control diet]. Objective 2: Identify genomic, epigenomic, metabolomic, and microbiome-related biomarkers that sustain healthy aging, and define specific personalized dietary, physical activity, and other lifestyle factors associated with optimal health of older adults. Subobjective 2A: To identify genetic and dietary factors that modify CPT1A methylation and cardio-metabolic traits. Subobjective 2B: To identify interactions between the genome, epigenome and diet and lifestyle on lipid profiles that signify CMD risk.

Approach
Promoting healthy aging by tailoring nutritional guidance based on a person's genetic makeup is an emerging science that has great promise. The Nutrition and Genomics lab is a pioneer in this area and focuses its research on the role of precision nutrition and cardiometabolic diseases – the leading cause of death in the United States. Our approach harnesses the availability of tremendous computing power and huge datasets from existing cohorts to study the crosstalk between habitual diets and the genome to identify gene-by-diet interactions that sustain individual optimal health for older adults. This objective will be accomplished using Big Data analytics of omics data (i.e., genome-wide datasets on gene and protein expression, genetic variation, methylation, and metabolite levels). We also conduct short-term feeding studies in people preselected based on particular genotypes to validate gene-by-diet interactions revealed by previous observational studies and, using multi-omic data integration (i.e., genomics, epigenomics, microbiomics, and metabolomics) methods, identifying the mechanisms underlying such interactions. This research will generate new knowledge on how non-modifiable and modifiable factors interact to prevent cardiovascular diseases and type 2 diabetes. Further, it will contribute much-needed evidence and tools to define and implement personalized nutrition as a common practice for the benefit of all stakeholders.

Progress Report
Under Objective 1, we investigated more deeply the association between genetic loci and cardiometabolic traits. Whereas, many genetic loci have shown associations with individual cardiometabolic disease (CMD)-related traits, no investigations have simultaneously tested associations identifying loci across multiple traits. Therefore, we conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high-density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N~456,823). Multiple loci were significant (N=145-333) for each trait. Still, only four loci (VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P<5×10-8). Understanding the pathways between these loci and CMD risk may eventually identify factors that can be used to identify new gene-by-diet interactions to be used in precision nutrition. We also explored novel factors of interest for inclusion in precision nutrition studies. In this regard, chronobiology is an emerging factor associated with CMD and could be the target of dietary intervention. Therefore, we investigated in the CORDIOPREV study (n=857) whether individuals with evening chronotypes are prone to suffer chronodisruption and display worse lifestyle habits and higher cardiovascular disease (CVD) risk than morning types. We also investigated whether potential associations were moderated by long-term consumption of two healthy diets (Mediterranean and low-fat diets). Our analyses show that evening types had higher TGs, C-reactive protein, and homocysteine and lower HDL-C than morning types (P<0.05). Moreover, they were more sedentary, displayed less and delayed physical activity, and ate and slept later. In conclusion, evening types with CVD had higher cardiometabolic risk and less robust circadian-related rhythms than morning types, which remained even during the nutritional intervention. Other emerging factors relevant to precision nutrition are smell and taste. Therefore, we conducted an integrated analysis of the influence of sweet taste preference on the preference for sugary foods and its modulation by T2D. Moreover, we explored new genetic factors associated with sweet taste preference. We studied 425 elderly white European subjects with metabolic syndrome and analyzed taste preference, taste perception, sugary-food likings, and biochemical and genetic markers. We found that T2D subjects have a higher preference for sweet taste and thus sugary foods than non-T2D subjects. We did not detect statistically significant differences in preferences for the other tastes (bitter, salty, sour, or umami). In an exploratory GWAS, we identified some single nucleotide polymorphisms (SNPs) associated with sweet taste preference, especially in the PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) gene, whose minor allele was associated with a lower sweet taste preference. In conclusion, this population strongly related sweet taste preference to sugary food liking. Our exploratory GWAS identified an interesting new candidate gene associated with sweet taste preference. For Objective 2, we investigated whether network analysis revealed clusters of coregulated metabolites associated with T2D among Puerto Rican adults. We measured fasting plasma metabolites (n>600) among participants aged 40-75 years in the Boston Puerto Rican Health Study (BPRHS) and San Juan Overweight Adult Longitudinal Study (SOALS), with and without T2D. Our results show that six metabolite clusters, including glucose transport, sphingolipids, acyl-cholines, sugar metabolism, branched-chain and aromatic amino acids, and fatty acid biosynthesis, were significantly associated with T2D in the BPRHS and replicated in SOALS. In summary, we identified several known and novel metabolite clusters among Puerto Rican adults associated with the prevalence of T2D. We have been developing, validating, and improving several dietary and disease risk biomarkers to support both objectives. These activities are essential to improve the reliability of the data used to inform Artificial Intelligence and Machine Learning approaches in precision nutrition. In this regard, continuous glucose monitors (CGM) are commonly used devices in precision nutrition that measure glycemic variation throughout the day. However, despite their popularity, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application. Using the PREDICT (Personalised REsponses to DIetary Composition Trial) 1 Study, we evaluated the concordance of two simultaneously worn CGM devices in measuring postprandial glycemic responses. Participants wore 2 CGM devices simultaneously, either from the same brand or different brands, for =14 d while consuming standardized and ad libitum foods. We examined the coefficient of variation (CV) and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Our results demonstrated that the CV of glucoseiAUC0-2 h was 3.7% for intrabrand device and 12.5% for interbrand device comparisons. Overall, our data showed strong concordance of CGM devices in monitoring glycemic responses and support their potential use in precision nutrition.

Accomplishments

Review Publications
Diez-Ricote, L., Ruiz-Valderrey, P., Mico, V., Blanco-Rojo, R., Tome-Carneiro, J., Davalos, A., Ordovas, J.M., Daimiel, L. 2021. Trimethylamine n-Oxide (TMAO) modulates the expression of cardiovascular disease-related microRNAs and their targets. International Journal of Molecular Sciences. 22(20):11145. https://doi.org/10.3390/ijms222011145.
Rangel-Zuniga, O.A., Vals-Delgado, C., Alcala-Diaz, J.F., Quintana-Navarro, G., Krylova, Y., Leon-Acuna, A., Luque, R.M., Gomez-Delgado, F., Delgado-Lista, J., Ordovas, J.M., Perez-Martinez, P., Camargo, A., Lopez-Miranda, J. 2020. A set of miRNAs predicts T2DM remission in patients with coronary heart disease: from the CORDIOPREV study. Molecular Therapy - Nucleic Acids. 23:255-263. https://doi.org/10.1016/j.omtn.2020.11.001.
Roncero-Ramos, I., Gutierrez-Mariscal, F.M., Gomez-Delgado, F., Villasanta-Gonzalez, A., Torres-Pena, J.D., De La Cruz-Ares, S., Rangel-Zuniga, O.A., Luque, R.M., Ordovas, J.M., Delgado-Lista, J., Perez-Martinez, P., Camargo, A., Alcala-Diaz, J.F., Lopez-Miranda, J. 2021. Beta cell functionality and hepatic insulin resistance are major contributors to type 2 diabetes remission and starting pharmacological therapy: from CORDIOPREV randomized controlled trial. Translational Research. https://doi.org/10.1016/j.trsl.2021.07.001.
Westerman, K., Fernandez-Sanles, A., Patil, P., Sebastiani, P., Jacques, P.F., Starr, J.M., Deary, I.J., Liu, Q., Liu, S., Elosua, R., DeMeo, D.F., Ordovas, J.M. 2020. Epigenomic assessment of cardiovascular disease risk and interactions with traditional risk metrics. Journal of the American Heart Association. 9(8):e015299. https://doi.org/10.1161/JAHA.119.015299.
Daimiel, L., Mico, V., Valls, R.M., Pedret, A., Motilva, M., Rubio, L., Fito, M., Farras, M., Covas, M., Sola, R., Ordovas, J.M. 2020. Impact of phenol-enriched virgin olive oils on the postprandial levels of circulating microRNAs related to cardiovascular disease. Molecular Nutrition and Food Research. 64(15):e2000049. https://doi.org/10.1002/mnfr.202000049.
Baquerizo-Sedano, L., Chaquila, J.A., Aguilar, L., Ordovas, J.M., Gonzalez-Muniesa, P., Garaulet, M. 2021. Anti-COVID-19 measures threaten our healthy body weight: Changes in sleep and external synchronizers of circadian clocks during confinement. Clinical Nutrition. https://doi.org/10.1016/j.clnu.2021.06.019.
Jimenez-Torres, J., Alcala-Diaz, J.F., Torres-Pena, J.D., Gutierrez-Mariscal, F.M., Leon-Acuna, A., Gomez-Luna, P., Fernandez-Gandara, C., Quintana-Navarro, G., Fernandez-Garcia, J.C., Perez-Martinez, P., Ordovas, J.M., Delgado-Lista, J., Yubero-Serrano, E.M., Lopez-Miranda, J. 2021. Mediterranean diet reduces atherosclerosis progression in coronary heart disease: An analysis of the CORDIOPREV randomized controlled trial. Stroke. 52(11):3440-3449. https://doi.org/10.1161/STROKEAHA.120.033214.
Camargo, A., Vais-Delgado, C., Alcala-Diaz, J.F., Vallasanta-Gonzalez, A., Gomez-Delgado, F., Haro, C., Leon-Acuna, A., Cardelo, M.P., Torres-Pena, J.D., Guler, I., Malagon, M.M., Ordovas, J.M., Perez-Martinez, P., Delgado-Lista, J., Lopez-Miranda, J. 2020. A diet-dependent microbiota profile associated with incident type 2 diabetes: From the CORDIOPREV study. Molecular Nutrition and Food Research. 64(23):2000730. https://doi.org/10.1002/mnfr.202000730.
Martinez-Perez, C., San-Cristobal, R., Guallar-Castillon, P., Martinez-Gonzalez, M.A., Salas-Salvado, J., Corella, D., Castaner, O., Martinez, J., Alonso-Gomez, A., Warnberg, J., Vioque, J., Romaguera, D., Lopez-Miranda, J., Estruch, R., Tinahones, F., Lapetra, J., Serra-Majem, L., Bueno-Cavanillas, A., Tur, J.A., Sanchez, V.M., Pinto, X., Gaforio, J., Matia-Martin, P., Vidal, J., Vasquez, C., Ros, E., Bes-Rostrollo, M., Babio, N., Sorli, J.V., Lassale, C., Perez-Sanz, B., Vaquero-Luna, J., Ajejas Bazan, M., Barcelo-Iglesias, M.N., Konieczna, J., Garcia-Rios, A., Bernal-Lopez, M., Santos-Lozano, J., Toledo, E., Becerra-Tomas, N., Portoles, O., Zomeno, M., Abete, I., Moreno-Rodriguez, A., Lecea-Juarez, O., Nishi, S., Munoz-Martinez, J., Ordovas, J.M., Daimiel, L. 2021. Use of different food classification systems to assess the association between ultra-processed food consumption and cardiometabolic health in an elderly population with metabolic syndrome (PREDIMED-Plus Cohort). Nutrients. 13(7):2471. https://doi.org/10.3390/nu13072471.
Haslam, D.E., Liang, L., Wang, D.D., Kelly, R.S., Wittenbecher, C., Perez, C.M., Martinez, M., Lee, C., Clish, C., Wong, D., Parnell, L.D., Lai, C., Ordovas, J.M., Manson, J.E., Hu, F.B., Stampfer, M.J., Tucker, K.L., Joshipura, K., Bhupathiraju, S.N. 2021. Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent. BMJ Open Diabetes Research & Care. https://doi.org/10.1136/bmjdrc-2021-002298.
Penalvo, J.L., Mertens, E., Munoz-Cabrejas, A., Leon-Latre, M., Jarauta, E., Laclaustra, M., Ordovas, J.M., Casasnovas, J.A., Uzhova, I., Moreno-Franco, B. 2021. Work shift, lifestyle factors, and subclinical atherosclerosis in Spanish male workers: A mediation analysis. Nutrients. https://doi.org/10.3390/nu13041077.
Astrup, A., Magkos, F., Bier, D.M., Brenna, J.Thomas, de Oliveira Otto, M.C., Hill, J.O., King, J.C., Mente, A., Ordovas, J.M., Volek, J.S., Yusuf, S., Krauss, R.M. 2020. Saturated fats and health: A reassessment and proposal for food-based recommendations: JACC State-of-the-Art review. Journal of the American College of Cardiology. 76(7):844-857. https://doi.org/10.1016/j.jacc.2020.05.077.
Astrup, A., Teicholz, N., Magkos, F., Bier, D., Brenna, J., King, J.C., Mente, A., Ordovas, J.M., Volek, J.S., Yussuf, S., Krauss, R.M. 2021. Dietary saturated fats and health: Are the U.S. guidelines evidence-based? Nutrients. 13(10):3305. https://doi.org/10.3390/nu13103305.
Bush, C.L., Blumberg, J.B., El-Sohemy, A., Minich, D.M., Ordovas, J.M., Reed, D.G., Yunez Behm, V.A. 2019. Toward the definition of personalized nutrition: A proposal by the American Nutrition Association. Journal of the American College of Nutrition. https://doi.org/10.1080/07315724.2019.1685332.
Westerman, K.E., Ordovas, J.M. 2020. DNA methylation and incident cardiovascular disease. Current Opinion in Clinical Nutrition and Metabolic Care. 23(4):236-240. https://doi.org/10.1097/MCO.0000000000000659.
Dashti, H.S., Ordovas, J.M. 2021. Genetics of sleep and insights into its relationship with obesity. Annual Review of Nutrition. https://doi.org/10.1146/annurev-nutr-082018-124258.
Lee, Y., Christensen, J.J., Parnell, L.D., Smith, C.E., Shao, J.Y., McKeown, N.M., Ordovas, J.M., Lai, C. 2022. Using machine learning to predict obesity based on genome-wide, epigenome-wide gene-gene and gene-diet interactions. Frontiers in Genetics. 12:783845. https://doi.org/10.3389/fgene.2021.783845.
Tsereteli, N., Vallat, R., Fernandez-Tajes, J., Delahanty, L.M., Ordovas, J.M., Drew, D.A., Valdes, A.M., Segata, N., Chan, A., Wolf, J., Berry, S.E., Walker, M.P., Spector, T.D., Franks, P.W. 2021. Impact of insufficient sleep on dysregulated blood glucose control under standardised meal conditions. Diabetologia. 65:356-365. https://doi.org/10.1007/s00125-021-05608-y.
Sorli, J.V., Barragan, R., Coltell, O., Portoles, O., Pascual, E.C., Ortega-Azorin, C., Gonzalez, J.I., Estruch, R., Saiz, C., Perez-Fidalgo, A., Ordovas, J.M., Corella, D. 2020. Chronological age interacts with the circadian melatonin receptor 1B gene variation, determining fasting glucose concentrations in Mediterranean populations. Additional analyses on type-2 diabetes risk. Nutrients. 12(11):3323. https://doi.org/10.3390/nu12113323.
Yubero-Serrano, E., Fernandez-Gandara, C., Garcia-Rios, A., Rangel-Zuniga, O.A., Gutierrez-Mariscal, F.M., Torres-Pena, J.D., Marin, C., Lopez-Moreno, J., Castano, J., Delgado-Lista, J., Ordovas, J.M., Perez-Martinez, P., Lopez-Miranda, J. 2020. Mediterranean diet and endothelial function in patients with coronary heart disease: an analysis of the CORDIOPREV randomized controlled trial. PLoS Medicine. 17(9):e1003282. https://doi.org/10.1371/journal.pmed.1003282.
Berry, S.E., Valdes, A.M., Drew, D.A., Asnicar, F., Mazidi, M., Wolf, J., Capdevila, J., Hadjigeorgiou, G., Davies, R., Al Khatib, H., Bonnett, C., Ganesh, S., Bakker, E., Hart, D., Mangino, M., Merino, J., Linenberg, I., Wyatt, P., Ordovas, J.M., Gardner, C.D., Dalahanty, L.M., Chan, A.T., Segata, N., Franks, P.W., Spector, T.D. 2020. Human postprandial responses to food and potential for precision nutrition. Nature Medicine. 26(6):964-973. https://doi.org/10.1038/s41591-020-0934-0.
Mazidi, M., Valdes, A.M., Ordovas, J.M., Hall, W.L., Pujol, J.C., Wolf, J., Hadjigeorgiou, G., Segata, N., Sattar, N., Koivula, R., Spector, T.D., Franks, P.W., Berry, S.E. 2021. Meal-induced inflammation: postprandial insights from the Personalised REsponses to DIetary Composition Trial (PREDICT) study in 1000 participants. American Journal of Clinical Nutrition. 114(3):1028-1038. https://doi.org/10.1093/ajcn/nqab132.
Ma, Y., Fu, Y., Tian, Y., Gou, W., Miao, Z., Yang, M., Ordovas, J.M., Zheng, J. 2021. Individual postprandial glycemic responses to diet in n-of-1 trials: Westlake N-of-1 trials for macronutrient intake (WE-MACNUTR). Journal of Nutrition. 151(10):3158-3167. https://doi.org/10.1093/jn/nxab227.
Romero-Cabrera, J., Garaulet, M., Jimenez-Torres, J., Alcala-Diaz, J.F., Quintana-Navarro, G.M., Martin-Piedra, L., Torres-Pena, J.D., Rodriguez-Cantalejo, F., Rangel-Zuniga, O.A., Yubero-Serrano, E.M., Luque, R.M., Ordovas, J.M., Lopez-Miranda, J., Perez-Martinez, P., Garcia-Rios, A. 2021. Chronodisruption and diet associated with increased cardiometabolic risk in coronary heart disease patients: the CORDIOPREV study. Translational Research. https://doi.org/10.1016/j.trsl.2021.11.001.
Vals-Delgado, C., Alcala-Diaz, J.F., Molina-Abril, H., Roncero-Ramos, I., Caspers, M.P., Schuren, F.H., Van Den Broek, T.J., Luque, R.M., Perez-Martinez, P., Katsiki, N., Delgado-Lista, J., Ordovas, J., Van Ommen, B., Camargo, A., Lopez-Miranda, J. 2021. An altered microbiota pattern precedes Type 2 diabetes mellitus development: From the CORDIOPREV study. Journal of Advanced Research. https://doi.org/10.1016/j.jare.2021.05.001.
Fernandez-Carrion, R., Sorli, J.V., Coltell, O., Pascual, E.C., Ortega-Azorin, C., Barragan, R., Gimenez-Alba, I., Alvarez-Sala, A., Fito, M., Ordovas, J., Corella, D. 2021. Sweet taste preference: Relationships with other tastes, liking for sugary foods and exploratory genome-wide association analysis in subjects with metabolic syndrome. Biomedicines. https://doi.org/10.3390/biomedicines10010079.
Podadera-Herreros, A., Alcala-Diaz, J.F., Gutierrez-Mariscal, F.M., Jimenez-Torres, J., Cruz-Ares, S., Arenas-De Larriva, A.P., Cardelo, M.P., Torres-Pena, J.D., Luque, R.M., Ordovas, J.M., Delgado-Lista, J., Lopez-Miranda, J., Yubereo-Serrano, E.M. 2022. 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. Clinical Nutrition. 41(2):552-559. https://doi.org/10.1016/j.clnu.2021.12.041.
Daimiel, L., Mico, V., Diez-Ricote, L., Ruiz-Valderrey, P., Istas, G., Rodriguez-Mateos, A., Ordovas, J. 2020. Alcoholic and non-alcoholic beer modulate plasma and macrophage microRNAs differently in a pilot intervention in humans with cardiovascular risk. Nutrients. 13(1):69. https://doi.org/10.3390/nu13010069.
Martinez-Perez, C., Daimiel, L., Climent-Mainar, C., Martinez-Gonzalez, M.A., Salas-Salvado, J., Corella, D., Schroder, H., Martinez, J., Alonso-Gomez, A.M., Warnberg, J., Vioque, J., Romaguera, D., Lopez-Miranda, J., Estruch, R., Tinahones, F.J., Lapetra, J., Serra-Majem, L., Bueno-Cavanillas, A., Tur, J.A., Sanchez, V.M., Pinto, X., Delgado-Rodriguez, M.A., Matia-Martin, P., Vidal, J., Vazquez, C., Ros, E., Basterra, J., Babio, N., Guillem-Saiz, P., Zomeno, M., Abete, I., Vaquero-Luna, J., Baron-Lopez, F.J., Gonzalez-Palacios, S., Konieczna, J., Garcia-Rios, A., Bernal-Lopez, M., Santos-Lozano, J., Bes-Rastrollo, M., Khoury, N., Saiz, C., Perez-Vega, K.A., Zulet, M., Tojal-Sierra, L., Vazquez Ruiz, Z., Martinez, M.A., Malcampo, M., Ordovas, J.M., San-Cristobal, R. 2022. Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF). International Journal of Behavioral Nutrition and Physical Activity. 19(1):6. https://doi.org/10.1186/s12966-021-01240-6.
Merino, J., Linenberg, I., Bermingham, K.M., Ganesh, S., Bakker, E., Delahanty, L.M., Chan, A.T., Pujol, J.C., Wolf, J., Al Khatib, H., Franks, P.W., Spector, T.D., Ordovas, J.M., Berry, S.E., Valdes, A.M. 2022. Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition. American Journal of Clinical Nutrition. https://doi.org/10.1093/ajcn/nqac026.
Daimiel, L., Martinez-Gonzalez, M.A., Corella, D., Salas-Salvado, J., Schroder, H., Vioque, J., Romaguera, D., Martinez, J.A., Warnberg, J., Lopez-Miranda, J., Estruch, R., Cano-Ibanez, N., Alonso-Gomez, A.M., Tur, J.A., Tinahones, F.J., Serra-Majem, L., Mico-Perez, R.M., Lapetra, J., Galdon, A., Pinto, X., Vidal, J., Mico, V., Colmenarejo, G., Gaforio, J.J., Matia-Martin, P., Ros, E., Buil-Cosiales, P., Vazquez-Ruiz, Z., Sorli, J.V., Graniel, I.P., Cuenca-Royo, A., Gisbert-Selles, C., Galmes-Panades, A.M., Zulet, M., Garcia-Rios, A., Diaz-Lopez, A., De La Torre, R., Galilea-Zabalza, I., Ordovas, J.M. 2020. Physical fitness and physical activity association with cognitive function and quality of life: baseline cross-sectional analysis of the PREDIMED-Plus trial. Scientific Reports. 10(1):3472. https://doi.org/10.1038/s41598-020-59458-6.
Mieko de Meneses Fujii, T., Maintinguer Norde, M., Fisberg, R., Lobo Marchioni, D., Ordovas, J.M., Macedo Rogero, M. 2020. FADS1 and ELOVL2 polymorphisms reveal associations for differences in lipid metabolism in a cross-sectional population-based survey of Brazilian men and women. Nutrition Research. 78:42-49. http://doi.org/10.1016/j.nutres.2020.04.003.
Ordovas, J.M., Berciano, S. 2020. Personalized nutrition and healthy aging. Nutrition Reviews. 78(S3):58-65. https://doi.org/10.1093/nutrit/nuaa102.
Aronica, L., Ordovas, J.M., Volkov, A., Lamb, J.J., Stone, P., Minich, D.M., Leary, M., Class, M., Metti, D., Larson, I.A., Contractor, N., Eck, B., Bland, J. 2022. Genetic biomarkers of metabolic detoxification for personalized lifestyle medicine. Nutrients. https://doi.org/10.3390/nu14040768.
Jimenez-Lucena, R., Alcala-Diaz, J.F., Roncero-Ramos, I., Lopez-Moreno, J., Camargo, A., Gomez-Delgado, F., Quintana-Navarro, G., Vals-Delgado, C., Rodriguez-Cantalejo, F., Luque, R.M., Delgado-Lista, J., Ordovas, J.M., Perez-Martinez, P., Rangel-Zuniga, O.A., Lopez-Miranda, J. 2020. MiRNAs profile as biomarkers of nutritional therapy for the prevention of type 2 diabetes mellitus: from the CORDIOPREV study. Clinical Nutrition. https://doi.org/10.1016/j.clnu.2020.06.035.
Westerman, K., Liu, Q., Liu, S., Parnell, L.D., Sebastiani, P., Jacques, P.F., Demeo, D.L., Ordovas, J. 2020. A gene-diet interaction-based score predicts response to dietary fat in the Women's Health Initiative. American Journal of Clinical Nutrition. 111(4):893-902. https://doi.org/10.1093/ajcn/nqaa037.
Ortiz-Morales, A.M., Alcala-Diaz, J.F., Rangel-Zuniga, O.A., Corina, A., Quintana-Navarro, G., Cardelo, M.P., Yubero-Serrano, E.M., Malagon, M.M., Delgado-Lista, J., Ordovas, J.M., Lopez-Miranda, J., Perez-Martinez, P. 2020. Biological senescence risk score. A practical tool to predict biological senescence status. European Journal of Clinical Investigation. 50(11):e13305. https://doi.org/10.1111/eci.13305.
Westerman, K., Kelly, J.M., Ordovas, J.M., Booth, S.L., DeMeo, D.F. 2020. Epigenome-wide association study reveals a molecular signature of response to phylloquinone (vitaminK1) supplementation. Epigenetics. 15(8):859-870. https://doi.org/10.1080/15592294.2020.1734714.
Moreno, V., Areces, F., Ruiz-Vincente, D., Ordovas, J.M., Del Coso, J. 2020. Influence of the ACTN3 R577X genotype on the injury epidemiology of marathon runners. PLoS ONE. 15(1):e0227548. https://doi.org/10.1371/journal.pone.0227548.
Cardelo, M.P., Alcala-Diaz, J.F., Gutierrez-Mariscal, F.M., Lopez-Moreno, J., Villasanta-Gonzalez, A., Arenas-De Larriva, A., De La Cruz-Ares, S., Delgado-Lista, J., Rodriguez-Cantalejo, F., Luque, R.M., Ordovas, J., Perez-Martinez, P., Camargo, A., Lopez-Miranda, J. 2022. Diabetes remission is modulated by branched chain amino acids according to the diet consumed: From the CORDIOPREV Study. Molecular Nutrition and Food Research. https://doi.org/10.1002/mnfr.202100652.