The Q223R polymorphism of the leptin receptor gene as a predictor of weight gain in childhood obesity and the identification of possible factors involved

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 obesit

Polymorphism of CLOCK gene rs3749474 as a modulator of the circadian evening carbohydrate intake impact on nutritional status in an adult sample

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 genotyp

New compound sets identified from high throughput phenotypic screening against three kinetoplastid parasites:an open resource

Using whole-cell phenotypic assays, the GlaxoSmithKline high-throughput screening (HTS) diversity set of 1.8 million compounds was screened against the three kinetoplastids most relevant to human disease, i.e. Leishmania donovani, Trypanosoma cruzi and Trypanosoma brucei. Secondary confirmatory and orthogonal intracellular anti-parasiticidal assays were conducted, and the potential for non-specific cytotoxicity determined. Hit compounds were chemically clustered and triaged for desirable physicochemical properties. The hypothetical biological target space covered by these diversity sets was investigated through bioinformatics methodologies. Consequently, three anti-kinetoplastid chemical boxes of ~200 compounds each were assembled. Functional analyses of these compounds suggest a wide array of potential modes of action against kinetoplastid kinases, proteases and cytochromes as well as potential host–pathogen targets. This is the first published parallel high throughput screening of a pharma compound collection against kinetoplastids. The compound sets are provided as an open resource for future lead discovery programs, and to address important research questions.The support and funding of Tres Cantos Open Lab Foundation is gratefully acknowledgedPeer reviewe

Polymorphic appetite effects on waist circumference depend on rs3749474 CLOCK gene variant

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

Hundreds of dual-stage antimalarial molecules discovered by a functional gametocyte screen.

Plasmodium falciparum stage V gametocytes are responsible for parasite transmission, and drugs targeting this stage are needed to support malaria elimination. We here screen the Tres Cantos Antimalarial Set (TCAMS) using the previously developed P. falciparum female gametocyte activation assay (Pf FGAA), which assesses stage V female gametocyte viability and functionality using Pfs25 expression. We identify over 400 compounds with activities <2 μM, chemically classified into 57 clusters and 33 singletons. Up to 68% of the hits are chemotypes described for the first time as late-stage gametocyte-targeting molecules. In addition, the biological profile of 90 compounds representing the chemical diversity is assessed. We confirm in vitro transmission-blocking activity of four of the six selected molecules belonging to three distinct scaffold clusters. Overall, this TCAMS gametocyte screen provides 276 promising antimalarial molecules with dual asexual/sexual activity, representing starting points for target identification and candidate selection

Inhibiting the stringent response blocks Mycobacterium tuberculosis entry into quiescence and reduces persistence

The stringent response enables Mycobacterium tuberculosis (Mtb) to shut down its replication and metabolism under various stresses. Here we show that Mtb lacking the stringent response enzyme RelMtb was unable to slow its replication rate during nutrient starvation. Metabolomics analysis revealed that the nutrient-starved relMtb-deficient strain had increased metabolism similar to that of exponentially growing wild-type bacteria in nutrient-rich broth, consistent with an inability to enter quiescence. Deficiency of relMtb increased the susceptibility of mutant bacteria to killing by isoniazid during nutrient starvation and in the lungs of chronically infected mice. We screened a pharmaceutical library of over 2 million compounds for inhibitors of RelMtb and showed that the lead compound X9 was able to directly kill nutrient-starved M. tuberculosis and enhanced the killing activity of isoniazid. Inhibition of RelMtb is a promising approach to target M. tuberculosis persisters, with the potential to shorten the duration of TB treatment.This work was supported by R01AI083125, R21AI122922, and R21AI114507A to P.C.

Phenolic diterpenes from Rosemary supercritical extract inhibit non-small cell lung cancer lipid metabolism and synergise with therapeutic drugs in the clinic

Lung cancer is one of the most deadly and common cancers in the world. The molecular features of patient’s tumours dictate the different therapeutic decisions, which combines targeted therapy, chemotherapy, and immunotherapy. Altered cellular metabolism is one of the hallmarks of cancer. Tumour cells reprogram their metabolism to adapt to their novel requirements of growth, proliferation, and survival. Together with the Warburg effect, the role of lipid metabolism alterations in cancer development and prognosis has been highlighted. Several lipid related genes have been shown to promote transformation and progression of cancer cells and have been proposed as biomarkers for prognosis. Nevertheless, the exact mechanisms of the regulation of lipid metabolism and the biological consequences in non-small cell lung cancer (NSCLC) have not been elucidated yet. There is an urgent necessity to develop multidisciplinary and complementary strategies to improve NSCLC patients´ well-being and treatment response. Nutrients can directly affect fundamental cellular processes and some diet-derived ingredients, bioactive natural compounds and natural extracts have been shown to inhibit the tumour growth in preclinical and clinical trials. Previously, we described a supercritical extract of rosemary (SFRE) (12 - 16% composition of phenolic diterpenes carnosic acid and carnosol) as a potential antitumoral agent in colon and breast cancer due to its effects on the inhibition of lipid metabolism and DNA synthesis, and in the reduction of resistance to 5-FluoroUracil (5-FU). Herein, we demonstrate SFRE inhibits NSCLC cell bioenergetics identifying several lipid metabolism implicated targets. Moreover, SFRE synergises with standard therapeutic drugs used in the clinic, such as cisplatin, pemetrexed and pembrolizumab to inhibit of cell viability of NSCLC cells. Importantly, the clinical relevance of SFRE as a complement in the treatment of NSCLC patients is suggested based on the results of a pilot clinical trial where SFRE formulated with bioactive lipids (PCT/ES2017/070263) diminishes metabolic and inflammatory targets in peripheral-blood mononuclear cells (PBMC), such as MAPK (p=0.04), NLRP3 (p=0.044), and SREBF1 (p=0.047), which may augment the immune antitumour function. Based on these results, SFRE merits further investigation as a co-adjuvant in the treatment of NSCLC.This research was funded by Regional Government of Community of Madrid (IND2017/BIO-7857; P2018/BAA-4343-ALIBIRD2020-CM), Ministerio de Ciencia e Innovación, Spain (PID2019-110183RB-C21); Ramon Areces Foundation (CIVP19A5937); EU Structural Funds and COST Action (CA17118); Synergistic Projects Community of Madrid (NUTRISION-CM/Y2020/BIO-6350) and REACT EU Program (Comunidad de Madrid and The European Regional Development Fund. ERDF. European Union- FACINGLCOVID-CM project). Adrián Bouzas has a predoctoral grant from the industrial predoctoral program of Community of Madrid (IND2017/BIO-7857).Peer reviewe

Fatty acids homeostasis during fasting predicts protection from chemotherapy toxicity.

Fasting exerts beneficial effects in mice and humans, including protection from chemotherapy toxicity. To explore the involved mechanisms, we collect blood from humans and mice before and after 36 or 24 hours of fasting, respectively, and measure lipid composition of erythrocyte membranes, circulating micro RNAs (miRNAs), and RNA expression at peripheral blood mononuclear cells (PBMCs). Fasting coordinately affects the proportion of polyunsaturated versus saturated and monounsaturated fatty acids at the erythrocyte membrane; and reduces the expression of insulin signaling-related genes in PBMCs. When fasted for 24 hours before and 24 hours after administration of oxaliplatin or doxorubicin, mice show a strong protection from toxicity in several tissues. Erythrocyte membrane lipids and PBMC gene expression define two separate groups of individuals that accurately predict a differential protection from chemotherapy toxicity, with important clinical implications. Our results reveal a mechanism of fasting associated with lipid homeostasis, and provide biomarkers of fasting to predict fasting-mediated protection from chemotherapy toxicity.General: We thank Prof. Jose Maria. Ordovas for his kind suggestions; nutritionists Helena Marcos-Pasero, Elena Aguilar-Aguilar and Isabel Espinosa-Salinas for their help with volunteers management; Rosa Serrano for her help with animal experiments; Susana Molina for her advice with PBMC isolation; Luisa Mariscal, Domingo Fernandez, Lola Martinez, Diego Megias, Patricia Gonzalez, Fernando Pelaez, Anabel Sanz, Carolina Pola, Celia de la Calle, Ana Ortega, Ana Sagrera, Jose Miguel Frade, Elena Lopez-Guadamillas, Maribel Munoz, Susana Llanos, Andres Fernandez, Aranzazu Sierra, Andres Lopez, Noemi Haro and Ildefonso Rodriguez for their excellent technical and scientific support. Work at the laboratory of P.J.F.M. is funded by the Ramon Areces Foundation, (CIVP18A3891), Asociacion Espanola contra el Cancer-AECC (SIRTBIO-LABAE18008FERN), a Ramon y Cajal Award from the Spanish Ministry of Science, Innovation and Universities (MICINN) (RYC-2017-22335), RETOS projects Program of MICINN (SAF2017-85766-R) and the Portuguese Foundation for Science and Technology (FCT-MCTES, SFRH/BD/124022/2016). Work at the laboratory of ARM was funded by the MICINN (PID2019-110183RB-C21), Regional Government of Community of Madrid (P2018/BAA-4343-ALIBIRD2020-CM) and the Ramon Areces Foundation. Work at the laboratory of A.D.R. Funded by the Comunidad de Madrid-Talento Grant 2018-T1/BMD-11966 and the MICINN PID-2019-106893RA-100. Work at the laboratory of L.D. is funded by projects from the Health Research Fund (ISCIII FIS PI14/01374 and FISPI17/00508) and from a Manuel de Oya research fellowship from the Beer and Health Foundation. Work at the laboratory of A.E. is funded by a Ramon y Cajal Award from MICINN (RYC-2013-13546) and RETOS projects Program of the MICINN, co-funded by the European Regional Development Fund (ERDF) (SAF2015-67538-R). Work in the laboratory of M.S. was funded by the IRB and by grants from the Spanish Ministry of Economy co-funded by the European Regional Development Fund (ERDF) (SAF2013-48256-R), the European Research Council (ERC-2014-AdG/669622), and the "laCaixa" Foundation.S

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the current and near-future health systems, given the association of these conditions with different comorbidities (cardiovascular diseases, type II diabetes, and metabolic syndrome) and even death. In order to design appropriate strategies for its prevention, as well as understand its origins, the development of predictive models for childhood/adolescent overweight/obesity and related outcomes is of extreme value. Obesity has a complex etiology, and in the case of childhood and adolescence obesity, this etiology includes also specific factors like (pre)-gestational ones; weaning; and the huge anthropometric, metabolic, and hormonal changes that during this period the body suffers. In this way, Machine Learning models are becoming extremely useful tools in this area, given their excellent predictive power; ability to model complex, nonlinear relationships between variables; and capacity to deal with high-dimensional data typical in this area. This is especially important given the recent appearance of large repositories of Electronic Health Records (EHR) that allow the development of models using datasets with many instances and predictor variables, from which Deep Learning variants can generate extremely accurate predictions. In the current work, the area of Machine Learning models to predict childhood and adolescent obesity and related outcomes is comprehensively and critically reviewed, including the latest ones using Deep Learning with EHR. These models are compared with the traditional statistical ones that used mainly logistic regression. The main features and applications appearing from these models are described, and the future opportunities are discussed

Diseño de drogas fotoactivas dirigidas a ácidos nucléicos : viológenos derivados de 6-(2-Piridil) fenantridina

Se ha caracterizado la interacción y fotoquímica con ácidos nucleicos de cinco candidatos de un nuevo grupo de drogas quirales, los viologenos derivados de n,n-dialquil 6-(2-piridil)fenantridina. Se han utilizado múltiples técnicas biofísicas, espectroscópicas, fotoquímicas y de modelado molecular. La interacción con dna es fuerte y por intercalacion en todos los casos. Los candidatos sin grupos amino en la fenantridina son luminiscentes y fotooxidan las bases del dna. Presentan rapida disociación, intercalación parcial y unión conducida termodinámicamente por efecto de polielectrolito. Las drogas con grupos amino no son luminiscentes; su disociación es lenta, la intercalación clásica y la kb dos ordenes de magnitud mayor. La unión esta conducida por efecto de polielectrolito y otras contribuciones (van der waals, efecto hidrofóbico, etc). En todos los casos la unión es enantioespecifica, pudiéndose separar en algunos casos los dos atropisomeros. En todos los casos las drogas presentan actividad fotonucleasica, probablemente iniciada por fotooxidación de las bases del dn