Colmenarejo, G. (Gonzalo)

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20203

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    Polymorphic appetite effects on waist circumference depend on rs3749474 CLOCK gene variant
    (MDPI AG, 2020) Colmenarejo, G. (Gonzalo); Martinez, J.A. (José Alfredo); Loria-Kohen, V. (Viviana); San-Cristobal, R. (Rodrigo); Ramirez-de-Molina, A. (Ana); Espinosa-Salinas, I. (Isabel); Molina, S. (Susana); Reglero, G. (Guillermo)
    Chronobiological aspects controlled by CLOCK genes may influence obesity incidence. Although there are studies that show an association between the expression of these genes and energy intake, waist circumference or abdominal obesity phenotypes, interactions with appetite have been insufficiently investigated in relation to chrononutrition. The objective was to identify interactions between CLOCK genetic variants involved in appetite status. A total of 442 subjects (329 women, 113 men; aged 18 to 65 years) were recruited. Anthropometric, dietary and lifestyle data were collected by trained nutritionists. Participants were classified according to their appetite feelings with a Likert scale. Multiple linear regression models were used to examine associations of the type genotype x appetite status on adiposity-related variables. p values were corrected by the Bonferroni method. A significant influence was found concerning the effects of appetite on waist circumference with respect to rs3749474 CLOCK polymorphism (p < 0.001). An additive model analysis (adjusted by age, gender, exercise and energy intake) showed that risk allele carriers, increased the waist circumference around 14 cm (β = 14.1, CI = 6.3–22.0) by each increment in the level of appetite. The effects of appetite on waist circumference may be partly modulated by the rs3749474 CLOCK polymorphism.
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    Physical fitness and physical activity association with cognitive function and quality of life: baseline cross-sectional analysis of the PREDIMED-Plus trial
    (Springer Nature, 2020) Buil, P. (Pilar); Colmenarejo, G. (Gonzalo); Martinez, J.A. (José Alfredo); Martinez-Gonzalez, M.A. (Miguel Ángel); Micó-Pérez, R.M. (Rafael Manuel); Galilea-Zabalza, I. (Iñigo); Garcia-Rios, A. (Antonio); Daimiel, L. (Lidia); Tinahones, F.J. (Francisco J.); Vioque, J. (Jesús); Torre, R. (Rafael) de la; Zulet, M.A. (María Ángeles); Tur, J.A. (Josep A.); Romaguera, D. (Dora); Lapetra, J. (José); Paz-Graniel, I. (Indira); Schröder, H. (Helmut); López-Miranda, J. (José); Galdon, A. (Alba); Galmes-Panades, A.M. (Aina M.); Matia, P. (Pilar); Ros, E. (Emilio); Ordovas, J.M. (Jose Manuel); Micó, V. (Victor); Alonso-Gomez, A. (Ángel); Wärnberg, J. (Julia); Estruch, R. (Ramón); Vazquez-Ruiz, Z. (Zenaida); Diaz-Lopez, A. (Andres); Gaforio, J.J. (José Juan); Serra-Majem, L. (Luis); Corella, D. (Dolores); Vidal, J. (Josep); Pinto, X. (Xavier); Salas-Salvado, J. (Jordi); Cano-Ibañez, N. (Naomi); Sorli, J.V. (Jose V.); Cuenca-Royo, A. (Aida); Gisbert-Sellés, C. (Cristina)
    Physical activity (PA) has been hypothesized to be effective to maintaining cognitive function and delay cognitive decline in the elderly, but physical fitness (PF) could be a better predictor of cognitive function. We aimed to study the association between PA and PF with cognitive function and quality of life using cross-sectional data from 6874 participants of the PREDIMED-Plus trial (64.9 ± 4.9 years, 48.5% female). PF and PA were measured with a Chair Stand Test, the REGICOR and Rapid Assessment Physical Activity questionnaires. Cognitive function was measured with Mini-mental State Examination, Control Oral Word Association Test, Trail Making Test and Digit Span tests; whereas health-related quality of life was assessed with the SF36-HRQL test. Cognitive and quality of life scores were compared among PF quartiles and PA levels (low, moderate and high) with ANCOVA and with Chair Stand repetitions and energy expenditure from total PA with multivariable linear regression adjusted for confounding factors. PF associated with higher scores in phonemic and semantic verbal fluency tests and with lower TMT A time. However, PA was not associated with the neurocognitive parameters evaluated. Both PF and PA levels were strongly associated with a better quality of life. We concluded that PF, but not PA, is associated with a better cognitive function. This trial was retrospectively registered at the International Standard Randomized Controlled Trial (ISRCTN89898870, https://www.isrctn.com/ISRCTN89898870?q=ISRCTN89898870&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10&searchType=basic-search) on 07/24/2014.
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    Polymorphism of CLOCK gene rs3749474 as a modulator of the circadian evening carbohydrate intake impact on nutritional status in an adult sample
    (MDPI AG, 2020) Colmenarejo, G. (Gonzalo); Martinez, J.A. (José Alfredo); Borregon-Rivilla, E. (Elena); Loria-Kohen, V. (Viviana); Ramirez-de-Molina, A. (Ana); Camblor-Murube, M. (Marina); Reglero, G. (Guillermo); Aguilar-Aguilar, E. (Elena)
    The aim of this study was to evaluate the distribution of energy intake and macronutrients consumption throughout the day, and how its effect on nutritional status can be modulated by the presence of the rs3749474 polymorphism of the CLOCK gene in the Cantoblanco Platform for Nutritional Genomics (“GENYAL Platform”). This cross-sectional study was carried out on 898 volunteers between 18 and 69 years old (65.5% women). Anthropometric measurements, social issues and health, dietary, biochemical, genetic, and physical activity data were collected. Subsequently, 21 statistical interaction models were designed to predict the body mass index (BMI) considering seven dietary variables analyzed by three genetic models (adjusted by age, sex, and physical activity). The average BMI was 26.9 ± 4.65 kg/m2 , 62.14% presented an excess weight (BMI > 25 kg/m2 ). A significant interaction was observed between the presence of the rs3749474 polymorphism and the evening carbohydrate intake (% of the total daily energy intake [%TEI]) (adjusted p = 0.046), when predicting the BMI. Participants carrying TT/CT genotype showed a positive association between the evening carbohydrate intake (%TEI) and BMI (β = 0.3379, 95% CI = (0.1689,0.5080)) and (β = 0.1529, 95% CI = (−0.0164,0.3227)), respectively, whereas the wild type allele (CC) showed a negative association (β = −0.0321, 95% CI = (−0.1505,0.0862)). No significant interaction with the remaining model variables was identified. New dietary strategies may be implemented to schedule the circadian distribution of macronutrients according to the genotype. Clinical Trial number: NCT04067921.