Helena Marcos-Pasero

Excess weight (EW) in children has become a severe public health problem. The present study aimed to describe the main lifestyle characteristics and their possible association with nutritional status in a group of schoolchildren enrolled in the GENYAL study, where 221 children in the first or second grade of primary education (6–9 years old) were included. Anthropometric (BMI and bioimpedance), dietary intake (twice-repeated 24 h food record), and physical activity (twice-repeated 24 h physical activity questionnaire) data were collected. Logistic and linear regressions, with p-values adjusted for multiple tests by Bonferroni’s method and with sex and age as covariates, were applied. The prevalence of EW was 19%, 25.4%, and 32.2%, according to Orbegozo Foundation, IOFT, and WHO criteria, respectively. The results showed a significant association between schoolchildren’s nutritional status and energy balance, defined as the ratio of estimated energy intake to estimated energy expenditure (%), (β = −1.49 (−1.9–1.07), p < 0.01) and KIDMED Mediterranean Diet Quality Index score (β = −0.19 (95% IC −0.38–0), p = 0.04), and between the availability of TV or other technological devices in their room and the child’s BMI (β = 1.15 (95% IC 0.20–2.10), p = 0.017) and their fat mass (β = 3.28 (95% IC 0.69–5.87), p = 0.013). The number of dairy servings/day had a protective effect against EW (OR = 0.48 (0.29–0.75), p adjusted = 0.05)). Studying lifestyle factors associated with obesity is essential for developing tools and strategies for obesity prevention in children.

Over 1.6 billion people (aged 15 years and above) worldwide are currently either overweight or obese, and this number is predicted to increase to 2.3 billion by 2050 (WHO). Excessive or impaired energy storage in the liver incurs a high risk of liver dysfunction and development of obesity, lipodystrophy, or cachexia, and impairs organismal homeostasis. Chenopodium quinoa seeds constitute a good source of immunonutritional compounds, enabling the selective functional differentiation and function of intrahepatic monocyte-derived macrophages. The latter play a key role in controlling adiposity associated with innate lymphoid cells (ILCs), which determine the induction of diet-induced obesity (DIO). Herein, two immune-conditioned mouse models—Rag2^−/− and Rag2^−/−IL2^−/−—were used to examine the influences preventing DIO with a protein-rich fraction (PRF) and oil obtained from C. quinoa seeds. Variations in myeloid cells and precursors of ILCs were evaluated by FACS analyses as well as the hepatosomatic index to estimate liver inflammation. Only the administration of C. quinoa PRF prevented alterations in the liver/body weight ratio, both in animals carrying ILCs (i.e., Rag2^−/−) and not (Rag2^−/−IL2^−/−). These effects were associated with significantly decreased variations in the hepatic triglyceride content. FACS revealed that PRF from C. quinoa favors the hepatic infiltration of myeloid and enables the selective functional differentiation and function of intrahepatic monocyte-derived macrophages, preserving tissue integrity and function.

Alzheimer’s disease (AD) is a prototypical inflammation-associated loss of cognitive function, with approximately 90% of the AD burden associated with invading myeloid cells controlling the function of the resident microglia. This indicates that the immune microenvironment has a pivotal role in the pathogenesis of the disease. Multiple peripheral stimuli, conditioned by complex and varied interactions between signals that stem at the intestinal level and neuroimmune processes, are involved in the progression and severity of AD. Conceivably, the targeting of critical innate immune signals and cells is achievable, influencing immune and metabolic health within the gut–brain axis. Considerable progress has been made, modulating many different metabolic and immune alterations that can drive AD development. However, non-pharmacological strategies targeting immunometabolic processes affecting neuroinflammation in AD treatment remain general and, at this point, are applied to all patients regardless of disease features. Despite these possibilities, improved knowledge of the relative contribution of the different innate immune cells and molecules comprising the chronically inflamed brain network to AD pathogenesis, and elucidation of the network hierarchy, are needed for planning potent preventive and/or therapeutic interventions. Moreover, an integrative perspective addressing transdisciplinary fields can significantly contribute to molecular pathological epidemiology, improving the health and quality of life of AD patients. This review is intended to gather modifiable immunometabolic processes based on their importance in the prevention and management of AD.

Objective: This article describes the methodology and summarizes some preliminary results of the GENYAL study aiming to design and validate a predictive model, considering both environmental and genetic factors, that identifies children who would benefit most from actions aimed at reducing the risk of obesity and its complications.Design: The study is a cluster randomized clinical trial with 5-year follow-up. The initial evaluation was carried out in 2017. The schools were randomly split into intervention (nutritional education) and control schools. Anthropometric measurements, social and health as well as dietary and physical activity data of schoolchildren and their families are annually collected. A total of 26 single nucleotide polymorphisms (SNPs) were assessed. Machine Learning models are being designed to predict obesity phenotypes after the 5-year follow-up.Settings: Six schools in Madrid.Participants: A total of 221 schoolchildren (6–8 years old).Results: Collected results show that the prevalence of excess weight was 19.0, 25.4, and 32.2% (according to World Health Organization, International Obesity Task Force and Orbegozo Foundation criteria, respectively). Associations between the nutritional state of children with mother BMI [β = 0.21 (0.13–0.3),p(adjusted) p(adjusted) = 0.06], dairy servings per day [OR = 0.48 (0.29–0.75),p(adjusted) = 0.05] and 8 SNPs [rs1260326, rs780094, rs10913469, rs328, rs7647305, rs3101336, rs2568958, rs925946;p(not adjusted) <0.05] were found.Conclusions: These baseline data support the evidence that environmental and genetic factors play a role in the development of childhood obesity. After 5-year follow-up, the GENYAL study pretends to validate the predictive model as a new strategy to fight against obesity.Clinical Trial Registration: This study has been registered inClinicalTrials.govwith the identifier NCT03419520,https://clinicaltrials.gov/ct2/show/NCT03419520.

The scarcity of the results obtained for the treatment of obesity leads us to consider new strategies, contemplating all the factors involved in the development of the disease. One of the key molecules for controlling body weight and energy homeostasis is the brain-derived neurotrophic factor (BDNF). This work summarizes the mechanisms in which BDNF gene regulates this multifactorial disease. In addition, we discuss the role of other BDNF polymorphisms as genetic determinants of obesity. In this context, a total of 14 SNPs near or inside BDNF/BDNF-AS related to BMI were identified in various GWASs. Finally, we assess gene-diet interaction as a novel tool to prevent obesity and formulate solid and personalized nutritional management. Our research group has performed the first study on the association of BDNF-AS rs925946 polymorphism and calcium intake as potential modulators of the nutritional status. Although these results should be confirmed in future studies, they open the path for new prevention opportunities.

The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potential risk factors: genetics, dietary and physical activity habits, socio-economic environment, lifestyle, etc. In addition, all these factors are expected to exert their influence through a specific and especially convoluted way during childhood, given the fast growth along this period. Machine Learning methods are the appropriate tools to model this complexity, given their ability to cope with high-dimensional, non-linear data. Here, we have analyzed by Machine Learning a sample of 221 children (6–9 years) from Madrid, Spain. Both Random Forest and Gradient Boosting Machine models have been derived to predict the body mass index from a wide set of 190 multidomain variables (including age, sex, genetic polymorphisms, lifestyle, socio-economic, diet, exercise, and gestation ones). A consensus relative importance of the predictors has been estimated through variable importance measures, implemented robustly through an iterative process that included permutation and multiple imputation. We expect this analysis will help to shed light on the most important variables associated to childhood obesity, in order to choose better treatments for its prevention.

Fibromyalgia (FM), chronic fatigue syndrome (CFS) and multiple chemical sensitivity (MCS) are some of the central sensitization syndromes (CSSs). The complexity of their diagnosis, the high interindividual heterogeneity and the existence of multi-syndromic patients requires a multifaceted treatment. The scientific literature is contradictory regarding the role of food in CSS, and evidence on the role of nutrition in MCS is particularly scarce. This review consists in gathering information about the current status of dietary recommendations (i.e., special dietary interventions, the role of additives, presence of micronutrient deficiencies, nutritional supplements and elimination of other nutrients and substances) and discussing the scientific evidence in depth to shed light on appropriate nutritional treatment managements for CSS patients. Current indications show that dietary modifications may vastly improve the patients’ quality of life at a low cost. We suggest personalized treatment, taking into consideration the severity of the disease symptoms, quality of life, coexistence with other diseases, pharmacological treatment, changing clinical characteristics, nutritional status, energy requirements and food tolerances, among others, as the best ways to tailor specific dietary interventions. These approaches will partially overcome the lack of scientific and clinical research on MSC. Patients should also be advised on the serious consequences of following dietary guidelines without a dietitian’s and clinician’s supervision.

Sport performance is influenced by several factors, including genetic susceptibility. In the past years, specific single nucleotide polymorphisms have been associated to sport performance; however, these effects should be considered in multivariable prediction systems since they are related to a polygenic inheritance. The aim of this study was to design a genetic endurance prediction score (GES) of endurance performance and analyze its association with anthropometric, nutritional and sport efficiency variables in a cross-sectional study within fifteen male cyclists. A statistically significant positive relationship between GES and the VO₂ maximum (P = 0.033), VO₂ VT1 (P = 0.049) and VO₂ VT2 (P < 0.001) was observed. Moreover, additional remarkable associations between genotype and the anthropometric, nutritional and sport performance variables, were achieved. In addition, an interesting link between the habit of consuming caffeinated beverages and the GES was observed. The outcomes of the present study indicate a potential use of this genetic prediction algorithm in the sports’ field, which may facilitate the finding of genetically talented athletes, improve their training and food habits, as well as help in the improvement of physical conditions of amateurs.

(1) Background: Childhood rapid weight gain during development has been postulated as a predictor of obesity. The objective of this study was to investigate the effect of single nucleotide polymorphisms (SNPs) on the annual weight gain and height growth, as well as identifying possible lifestyle factors involved. (2) Methods: As part of the GENYAL study, 221 children (6–8 years old) of Madrid (Spain) were enrolled. A total of 11 SNPs associated with high childhood body mass indexes (BMIs) were assessed. Anthropometric measurements, dietary and physical activity data, were collected in 2017 and 2018. Bonferroni-corrected linear models were used to fit the data. (3) Results: A significant association between the Q223R LEPR and the weight growth was found, showing a different behavior between GA and GG genotypes (p = 0.001). Regarding lifestyle factors, an interaction between Q223R genotypes and total active weekly hours/week to predict the weight growth (kg/year) was observed (p = 0.023). In all the genotypes, a beneficial effect against rapid weight growth was observed, but the effect size of the interaction was much more significant in homozygous (GG) minor homozygous (β = −0.61 (−0.95, −0.26) versus heterozygous (AG) and wild-type homozygous (AA) genotypes (β = −0.07 (−0.24, 0.09) and β = −0.12 (−0.32, 0.08), respectively). (4) Conclusions: These results may contribute to more personalized recommendations to prevent childhood obesity.