Genetic Polymorphisms, Mediterranean Diet and Microbiota-Associated Urolithin Metabotypes can Predict Obesity in Childhood-Adolescence

Chronic consumption of orange juice modifies urinary excretion of flavanone gut-derived metabolites through gut microbiota modulation

The metabolism and absorption of citrus flavanones are intrinsically linked to the gut microbiota, creating a bidirectional relationship where these compounds influence the microbiome, and in turn, the microbiota affects their metabolism. This study evaluates the effect of acute and chronic consumption of orange juice (OJ) on the urinary excretion of gut-derived flavanone metabolites and the gut microbiota. Health volunteers ingested 500 mL of OJ for 60 days in a single-arm human intervention study. Blood and feces were collected at baseline and after 60 days, with an additional 24-hour urine collection after a single dose on day 1 and day 63. LC-MS/MS analyzed urinary flavanone metabolites, while 16S rRNA sequencing characterized gut microbiota. Total urinary hesperetin conjugates excretion significantly decreased over 60 days, while gut-derived total phenolic acids, particularly three hydroxybenzoic acids, increased. Moreover, the heterogeneity of the total amount of flavanone conjugates, initially categorizing individuals into high-, medium- and low- urinary excretor profiles, shifted towards medium-excretor, except for five individuals who remained as low-excretors. This alteration was accompanied by a decrease in intestinal β-glucosidase activity and a shift in the relative abundance of specific genera, such as decreases in Blautia, Eubacterium hallii, Anaerostipes, and Fusicatenibacter, among which, Blautia was associated with higher urinary flavanone conjugates excretion. Conversely, an increase in Prevotella was observed. In summary, chronic OJ consumption induced transient changes in gut microbiota and altered the metabolism of citrus flavanones, leading to distinct urinary excretion profiles of flavanone metabolites.

Assessment of ADRB1 polymorphism in patients with acute coronary syndrome treated with ticagrelor and aspirin

Background: This study investigated the influence of ADRB1 gene rs1801253 polymorphism on the treatment response of ticagrelor and aspirin in patients with acute coronary syndrome (ACS). Methods: Genetic typing was detected by Sanger sequencing. Platelet inhibition was assessed using thromboelastography. Kaplan-Meier and Cox regression were applied for prognosis analysis. Results: Out of 200 participants, 94 cases with rs1801253-CC genotype and 106 cases with CG+GG genotype were found. There was no significant difference between the rs1801253-CC and CG+GG groups in the number of ST-segment elevation myocardial infarction, non-ST-segment elevation myocardial infarction and unstable angina patients. There was no statistical difference in the basic data of patients in the two groups in terms of age, sex, medical history and medicine use in the dominant model. The rs1801253-CC genotype was a risk prognostic factor for ACS patients based on the Cox regression analysis results. Conclusion: Detecting ADRB1 polymorphism is crucial for ACS patients undergoing treatment with ticagrelor and aspirin.

Mechanisms and risk factors of metabolic syndrome in children and adolescents

Metabolic syndrome (MetS) is a complex disorder characterized by abdominal obesity, elevated blood pressure, hyperlipidemia, and elevated fasting blood glucose levels. The diagnostic criteria for MetS in adults are well-established, but there is currently no consensus on the definition in children and adolescents. The etiology of MetS is believed to involve a complex interplay between genetic predisposition and environmental factors. While genetic predisposition explains only a small part of MetS pathogenesis, modifiable environmental risk factors play a significant role. Factors such as maternal weight during pregnancy, children's lifestyle, sedentariness, high-fat diet, fructose and branched-chain amino acid consumption, vitamin D deficiency, and sleep disturbances contribute to the development of MetS. Early identification and treatment of MetS in children and adolescents is crucial to prevent the development of chronic diseases later in life. In this review we discuss the latest research on factors contributing to the pathogenesis of MetS in children, focusing on non-modifiable and modifiable risk factors, including genetics, dysbiosis and chronic low-grade inflammation.

(Poly)phenol-related gut metabotypes and human health: an update

Dietary (poly)phenols have received great interest due to their potential role in the prevention and management of non-communicable diseases. In recent years, a high inter-individual variability in the biological response to (poly)phenols has been demonstrated, which could be related to the high variability in (poly)phenol gut microbial metabolism existing within individuals. An interplay between (poly)phenols and the gut microbiota exists, with (poly)phenols being metabolised by the gut microbiota and their metabolites modulating gut microbiota diversity and composition. A number of (poly)phenol metabolising phenotypes or metabotypes have been proposed, however, potential metabotypes for most (poly)phenols have not been investigated, and the relationship between metabotypes and human health remains ambiguous. This review presents updated knowledge on the reciprocal interaction between (poly)phenols and the gut microbiome, associated gut metabotypes, and subsequent impact on human health.

Evaluation of the role of FTO (rs9939609) and MC4R (rs17782313) gene polymorphisms in type 1 diabetes and their relation to obesity

OBJECTIVES

This study aims to explore the effects of fat mass obesity-associated (FTO) (rs9939609) and melanocortin 4 receptor (MC4R) (rs17782313) gene polymorphisms in children with type 1 diabetes (T1D) and their relation to obesity.

METHODS

Fat mass obesity-associated (FTO) (rs9939609) and melanocortin 4 receptor (MC4R) (rs17782313) gene polymorphisms were evaluated in 164 patients and 100 controls, and genotypes, alleles, and haplotype frequencies were compared between cases and controls.

RESULTS

A significant association with T1D development was found with the TC, CC, and TC+CC genotypes and the C allele of MC4R rs17782313. In addition, TA, AA, and TA+AA genotypes and the A allele of FTO rs9939609 may also be risky for T1D development. While the TC and TC+CC genotypes of MC4R rs17782313 may be protective against obesity development, the AA genotype and A allele of FTO rs9939609 may also be protective against obesity development. Regarding obese subjects, comparing diabetics vs. non-diabetic studied subjects, FTO rs9939609, TA, AA, and TA+AA genotypes and the A allele had significantly higher frequencies in T1D with a higher risk of developing T1D. However, conducting multivariable analysis using significant covariates in univariable analysis revealed that only earlier age of T1D onset, lower C-peptide, and the MC4R dominant model were considered independent predictors of obesity within T1D.

CONCLUSIONS

The role of both genes' polymorphisms on the pathogenesis and the outcome of T1D and obesity can help in understanding the pathogenesis of both diseases and their associations with each other's and may be used as novel therapeutic targets for both diseases.

Exploring substrate-microbe interactions: a metabiotic approach toward developing targeted synbiotic compositions

Gut microbiota is an important modulator of human health and contributes to high inter-individual variation in response to food and pharmaceutical ingredients. The clinical outcomes of interventions with prebiotics, probiotics, and synbiotics have been mixed and often unpredictable, arguing for novel approaches for developing microbiome-targeted therapeutics. Here, we review how the gut microbiota determines the fate of and individual responses to dietary and xenobiotic compounds via its immense metabolic potential. We highlight that microbial metabolites play a crucial role as targetable mediators in the microbiota-host health relationship. With this in mind, we expand the concept of synbiotics beyond prebiotics' role in facilitating growth and engraftment of probiotics, by focusing on microbial metabolism as a vital mode of action thereof. Consequently, we discuss synbiotic compositions that enable the guided metabolism of dietary or co-formulated ingredients by specific microbes leading to target molecules with beneficial functions. A workflow to develop novel synbiotics is presented, including the selection of promising target metabolites (e.g. equol, urolithin A, spermidine, indole-3 derivatives), identification of suitable substrates and producer strains applying bioinformatic tools, gut models, and eventually human trials.In conclusion, we propose that discovering and enabling specific substrate-microbe interactions is a valuable strategy to rationally design synbiotics that could establish a new category of hybrid nutra-/pharmaceuticals.

Pharmacological Effects of Urolithin A and Its Role in Muscle Health and Performance: Current Knowledge and Prospects

Urolithin A (UA) is a naturally occurring compound derived from the metabolism of gut microbiota, which has attracted considerable research attention due to its pharmacological effects and potential implications in muscle health and performance. Recent studies have demonstrated that Urolithin A exhibits diverse biological activities, encompassing anti-inflammatory, antioxidant, anti-tumor, and anti-aging properties. In terms of muscle health, accumulating evidence suggests that Urolithin A may promote muscle protein synthesis and muscle growth through various pathways, offering promise in mitigating muscle atrophy. Moreover, Urolithin A exhibits the potential to enhance muscle health and performance by improving mitochondrial function and regulating autophagy. Nonetheless, further comprehensive investigations are still warranted to elucidate the underlying mechanisms of Urolithin A and to assess its feasibility and safety in human subjects, thereby advancing its potential applications in the realms of muscle health and performance.

Urolithins: a Comprehensive Update on their Metabolism, Bioactivity, and Associated Gut Microbiota

Urolithins, metabolites produced by the gut microbiota from the polyphenols ellagitannins and ellagic acid, are discovered by the research group in humans almost 20 years ago. Pioneering research suggests urolithins as pleiotropic bioactive contributors to explain the health benefits after consuming ellagitannin-rich sources (pomegranates, walnuts, strawberries, etc.). Here, this study comprehensively updates the knowledge on urolithins, emphasizing the review of the literature published during the last 5 years. To date, 13 urolithins and their corresponding conjugated metabolites (glucuronides, sulfates, etc.) have been described and, depending on the urolithin, detected in different human fluids and tissues (urine, blood, feces, breastmilk, prostate, colon, and breast tissues). There has been a substantial advance in the research on microorganisms involved in urolithin production, along with the compositional and functional characterization of the gut microbiota associated with urolithins metabolism that gives rise to the so-called urolithin metabotypes (UM-A, UM-B, and UM-0), relevant in human health. The design of in vitro studies using physiologically relevant assay conditions (molecular forms and concentrations) is still a pending subject, making some reported urolithin activities questionable. In contrast, remarkable progress has been made in the research on the safety, bioactivity, and associated mechanisms of urolithin A, including the first human interventions.

Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease

The combination of multiple omics approaches has emerged as an innovative holistic scope to provide a more comprehensive view of the molecular and physiological events underlying human diseases (including obesity, dyslipidemias, fatty liver, insulin resistance, and inflammation), as well as for elucidating unique and specific metabolic phenotypes. These omics technologies include genomics (polymorphisms and other structural genetic variants), epigenomics (DNA methylation, histone modifications, long non-coding RNA, telomere length), metagenomics (gut microbiota composition, enterotypes), transcriptomics (RNA expression patterns), proteomics (protein quantities), and metabolomics (metabolite profiles), as well as interactions with dietary/nutritional factors. Although more evidence is still necessary, it is expected that the incorporation of integrative omics could be useful not only for risk prediction and early diagnosis but also for guiding tailored dietary treatments and prognosis schemes. Some challenges include ethical and regulatory issues, the lack of robust and reproducible results due to methodological aspects, the high cost of omics methodologies, and high-dimensional data analyses and interpretation. In this review, we provide examples of system biology studies using multi-omics methodologies to unravel novel insights into the mechanisms and pathways connecting the genotype to clinically relevant traits and therapy outcomes for precision nutrition applications in health and disease.

Urolithins: potential biomarkers of gut dysbiosis and disease stage in Parkinson's patients

Gut microbiota alteration (gut dysbiosis) occurs during the onset and progression of Parkinson's disease. Gut dysbiosis biomarkers could be relevant to prodromal disease. Urolithins, anti-inflammatory metabolites produced from some dietary polyphenols by specific gut microbial ecologies (urolithin metabotypes), have been proposed as biomarkers of gut microbiota composition and functionality. However, this has not been explored in Parkinson's disease patients. The current study aimed to assess associations between urolithin metabotypes, gut dysbiosis and disease severity in Parkinson's disease patients. Participants (52 patients and 117 healthy controls) provided stool samples for microbiota sequencing and urine samples for urolithin profiling before and after consuming 30 g of walnuts for three days. Data on demographics, medication, disease duration and Hoehn and Yahr disease stage were collected. We observed a significant gradual increase of urolithin non-producers (metabotype-0) as the disease severity increased. The gut microbiome of metabotype-0 patients and patients with the greatest severity was characterized by a more altered bacterial composition, i.e., increased pro-inflammatory Enterobacteriaceae and reduced protective bacteria against autoimmune and inflammatory processes, including butyrate and urolithin-producing bacteria (Lachnospiraceae members and Gordonibacter). Besides, their microbiome was characterized by predictive functions of lipopolysaccharide biosynthesis and metabolism of glutathione, cysteine and methionine that could indirectly reflect the gut pro-inflammatory status. Urolithin detection in urine is a feasible, non-invasive and fast approach that can reflect gut microbiome dysbiosis and intestinal inflammation in Parkinson's disease patients. Our current study could provide novel strategies for improving diagnostics, and for preventing and treating disease progression in microbiota-based interventions.

Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques

OBJECTIVES

We adopted the machine-learning algorithms and deep-learning sequential model to determine and optimize most important factors for overweight and obesity in Chinese preschool-aged children.

METHODS

This is a cross-sectional survey conducted in 2020 at Beijing and Tangshan. Using a stratified cluster random sampling strategy, children aged 3-6 years were enrolled. Data were analyzed using the PyCharm and Python.

RESULTS

A total of 9478 children were eligible for inclusion, including 1250 children with overweight or obesity. All children were randomly divided into the training group and testing group at a 6:4 ratio. After comparison, support vector machine (SVM) outperformed the other algorithms (accuracy: 0.9457), followed by gradient boosting machine (GBM) (accuracy: 0.9454). As reflected by other 4 performance indexes, GBM had the highest F1 score (0.7748), followed by SVM with F1 score at 0.7731. After importance ranking, the top 5 factors seemed sufficient to obtain descent performance under GBM algorithm, including age, eating speed, number of relatives with obesity, sweet drinking, and paternal education. The performance of the top 5 factors was reinforced by the deep-learning sequential model.

CONCLUSIONS

We have identified 5 important factors that can be fed to GBM algorithm to better differentiate children with overweight or obesity from the general children, with decent prediction performance.

Leptin Signaling in Obesity and Colorectal Cancer

Obesity and colorectal cancer (CRC) are among the leading diseases causing deaths in the world, showing a complex multifactorial pathology. Obesity is considered a risk factor in CRC development through inflammation, metabolic, and signaling processes. Leptin is one of the most important adipokines related to obesity and an important proinflammatory marker, mainly expressed in adipose tissue, with many genetic variation profiles, many related influencing factors, and various functions that have been ascribed but not yet fully understood and elucidated, the most important ones being related to energy metabolism, as well as endocrine and immune systems. Aberrant signaling and genetic variations of leptin are correlated with obesity and CRC, with the genetic causality showing both inherited and acquired events, in addition to lifestyle and environmental risk factors; these might also be related to specific pathogenic pathways at different time points. Moreover, mutation gain is a crucial factor enabling the genetic process of CRC. Currently, the inconsistent and insufficient data related to leptin's relationship with obesity and CRC indicate the necessity of further related studies. This review summarizes the current knowledge on leptin genetics and its potential relationship with the main pathogenic pathways of obesity and CRC, in an attempt to understand the molecular mechanisms of these associations, in the context of inconsistent and contradictory data. The understanding of these mechanisms linking obesity and CRC could help to develop novel therapeutic targets and prevention strategies, resulting in a better prognosis and management of these diseases.

LPL, FNDC5 and PPARγ gene polymorphisms related to body composition parameters and lipid metabolic profile in adolescents from Southern Italy

Background

Plasma lipid profile and anthropometric variables are known to be under strong genetic control and the identification of genetic variants associated with bioclinical parameters is of considerable public health importance. In this study, a young cohort of healthy individuals was genotyped for genes related to health and pathological conditions, to analyze the association of single nucleotide polymorphisms (SNPs) with different bioclinical parameters, adherence to the Mediterranean Diet (MD) and physical activity, studying the role of lifestyle and body composition parameters on biochemical metabolic profile.

Methods

Association analysis of single variants in the genes of lipoprotein lipase (LPL), fibronectin type III domain containing protein 5 (FNDC5), and peroxisome proliferator-activated receptor-gamma (PPARγ) and haplotype analyses were performed.

Results

Multiple (n = 14) common variants in the three genes demonstrated a significant effect on plasma lipoprotein-lipid levels and/or on biochemical parameters in our sample. Specifically, SNPs were related to lipid metabolism (rs3866471, rs4922115, rs11570892, rs248, rs316, rs1059507, rs1801282) or glycemic profile (rs3208305) or anthropometric parameters (rs3480, rs726344, rs1570569) for a total of 26 significant associations (P < 0.01 and/or P < 0.05) and two haplotypes, for the first time, were strongly associated with lipid and body composition parameters. Interestingly, we identified twenty-four new variants not previously described in the literature and a novel significant association between rs80143795 and body composition.

Conclusions

In this study we confirm the association between these SNPs on lipid metabolism and body parameters also in a young cohort, indicating the important role of these genetic factors as determinants of health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03314-w.

Innate-Immunity Genes in Obesity

The main functions of adipose tissue are thought to be storage and mobilization of the body’s energy reserves, active and passive thermoregulation, participation in the spatial organization of internal organs, protection of the body from lipotoxicity, and ectopic lipid deposition. After the discovery of adipokines, the endocrine function was added to the above list, and after the identification of crosstalk between adipocytes and immune cells, an immune function was suggested. Nonetheless, it turned out that the mechanisms underlying mutual regulatory relations of adipocytes, preadipocytes, immune cells, and their microenvironment are complex and redundant at many levels. One possible way to elucidate the picture of adipose-tissue regulation is to determine genetic variants correlating with obesity. In this review, we examine various aspects of adipose-tissue involvement in innate immune responses as well as variants of immune-response genes associated with obesity.

Main drivers of (poly)phenol effects on human health: metabolite production and/or gut microbiota-associated metabotypes?

Despite the high human interindividual variability in response to (poly)phenol consumption, the cause-and-effect relationship between some dietary (poly)phenols (flavanols and olive oil phenolics) and health effects (endothelial function and prevention of LDL oxidation, respectively) has been well established. Most of the variables affecting this interindividual variability have been identified (food matrix, gut microbiota, single-nucleotide-polymorphisms, etc.). However, the final drivers for the health effects of (poly)phenol consumption have not been fully identified. At least partially, these drivers could be (i) the (poly)phenols ingested that exert their effect in the gastrointestinal tract, (ii) the bioavailable metabolites that exert their effects systemically and/or (iii) the gut microbial ecology associated with (poly)phenol metabolism (i.e., gut microbiota-associated metabotypes). However, statistical associations between health effects and the occurrence of circulating and/or excreted metabolites, as well as cross-sectional studies that correlate gut microbial ecologies and health, do not prove a causal role unequivocally. We provide a critical overview and perspective on the possible main drivers of the effects of (poly)phenols on human health and suggest possible actions to identify the putative actors responsible for the effects.

Polymorphisms on rs9939609 FTO and rs17782313 MC4R genes in children and adolescent obesity: A systematic review

The aim of this review was to assess whether the presence of rs9939609 and rs17782313 polymorphisms increase the risk for obesity among children and adolescents. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and it was registered in PROSPERO. The search was performed in the PubMed/Medline, The Cochrane Library, and Web of Science databases. The risk of bias of the studies was accessed using the Newcastle-Ottawa scale and JBI Critical Appraisal Checklist for Analytical. The search of the databases retrieved 859 references. Twelve studies were eligible to be included in this systematic review. Five studies founded a positive association between overweight and obesity in children and adolescents with the presence of the rs17783213 and four studies with rs9939609. Three studies did not find an association between overweight and obesity in children and adolescents with the presence of rs17782313 or rs9939609. One found a protective effect for obesity in individuals with risk A allele referring to rs9939609, one found a synergistic effect in relation to the presence of polymorphisms rs17782313 and rs9939609 for obese phenotype, and one observed that the presence together of the rs9939609, rs17782313, and rs12970134 MC4R were significant for the presence of obesity in children and adolescents. The results suggest that depending on the population evaluated and ethnicity, the polymorphisms rs17782313 and rs9939609 could be associated with overweight and obesity in children and adolescents.

Pharmacological Therapy Determines the Gut Microbiota Modulation by a Pomegranate Extract Nutraceutical in Metabolic Syndrome: A Randomized Clinical Trial

SCOPE

Poly-pharmacological therapy shapes the gut microbiota (GM) in metabolic syndrome (MetS) patients. The effects of polyphenols in poly-medicated MetS patients are unknown.

METHODS AND RESULTS

A randomized, placebo-controlled, double-blinded, and crossover trial in poly-medicated MetS patients (n=50) explored whether the effects of a pomegranate extract nutraceutical (PE, 320 mg phenolics/day for 1 month) are affected by the drug therapy. Considering the lipid-lowering (LL-), anti-hypertensive (HP-) and(or) anti-diabetic (AD-) treatments: GM (16S rRNA sequencing), short-chain fatty acids, 40 inflammatory-metabolic and endotoxemia-related biomarkers, associations between biomarkers and GM with 53 cardiometabolic dysfunctions-related single-nucleotide polymorphisms (SNPs), and urolithin metabotypes (UMs) influence are evaluated. Representative SNPs-GM associations after PE include Lactococcus and ClostridiumXIVa with rs5443-GNB3 (G-protein-β-polypeptide-3) and ClostridiumXIVa with rs7903146-TCF7L2 (transcription-factor-7-like-2) and rs1137101-LEPR (leptin-receptor). PE decreases sICAM-1 in LL-patients and the lipopolysaccharide-binding protein in all the patients. PE does not affect the other patients' markers as a group or stratifying by UMs. After PE, Lactococcus increases in AD-, LL-, and HP-patients, Bifidobacterium increases in LL- and AD-, while Clostridium XIVa decreases in non-LL- and non-HP-patients.

CONCLUSION

The prebiotic effect of PE depends on the medication, mainly on HP-treatments. Targeting GM can complement MetS therapy, but the patients' drug therapy should be considered individually.

Gut microbiome and Mediterranean diet in the context of obesity. Current knowledge, perspectives and potential therapeutic targets

Mediterranean Diet has been recognized as one of the healthiest and sustainable dietary patterns worldwide, based on the food habits of people living in the Mediterranean region. It is focused on a plant-based cuisine combining local agricultural products and moderate intake of fish. As eating habits seem to exert a major impact on the composition of gut microbiota, numerous studies show that an adherence to the Mediterranean diet positively influences the microbiome ecosystem network. This has a profound effect on multiple host metabolic pathways and plays a major role in immune and metabolic homeostasis. Among metabolic disorders, obesity represents a major health issue where Mediterranean Dietary regime could possibly slowdown its spread. The aim of this review is to emphasize the interaction between diet and gut microbiota and the potential beneficial effects of Mediterranean diet on metabolic disorders like obesity, which is responsible for the development of many noncommunicable diseases.

Genetic polymorphisms associated with obesity in the Arab world: a systematic review

BACKGROUND

Obesity, one of the most common chronic health conditions worldwide, is a multifactorial disease caused by complex genetic and environmental interactions. Several association studies have revealed a considerable number of candidate loci for obesity; however, the genotype-phenotype correlations remain unclear. To date, no comprehensive systematic review has been conducted to investigate the genetic risk factors for obesity among Arabs.

OBJECTIVES

This study aimed to systematically review the genetic polymorphisms that are significantly associated with obesity in Arabs.

METHODS

We searched four literature databases (PubMed, Science Direct, Scopus, and Google Scholar) from inception until May 2020 to obtain all reported genetic data related to obesity in Arab populations. Quality assessment and data extraction were performed individually by three investigators.

RESULTS

In total, 59 studies comprising a total of 15,488 cases and 9,760 controls were included in the systematic review. A total of 76 variants located within or near 49 genes were reported to be significantly associated with obesity. Among the 76 variants, two were described as unique to Arabs, as they have not been previously reported in other populations, and 19 were reported to be distinctively associated with obesity in Arabs but not in non-Arab populations.

CONCLUSIONS

There appears to be a unique genetic and clinical susceptibility profile of obesity in Arab patients.

Novel role of cholesteryl ester transfer protein (CETP): attenuation of adiposity by enhancing lipolysis and brown adipose tissue activity

OBJECTIVE

The systemic function of CETP has been well characterized. CETP plasma activity reduces HDL cholesterol and thus increases the risk of atherosclerosis. Here, we investigated whether CETP expression modulate adiposity.

METHODS

Body adiposity and energy metabolism related assays and gene/protein expression were compared in CETP transgenic and non-transgenic mice and in hamsters treated with CETP neutralizing antibody.

RESULTS

We found that transgenic mice expressing human CETP present less white adipose tissue mass and lower leptinemia than nontransgenic (NTg) littermates. No differences were found in physical activity, food intake, fat fecal excretion, lipogenesis or exogenous lipid accumulation in adipose depots. Nonetheless, adipose lipolysis rates and whole-body energy expenditure were elevated in CETP mice. In accordance, lipolysis-related gene expression and protein content were increased in visceral and brown adipose tissue (BAT). In addition, we verified increased BAT temperature and oxygen consumption. These results were confirmed in two other animal models: 1) hamsters treated with CETP neutralizing antibody and 2) an independent line of transgenic mice expressing simian CETP.

CONCLUSIONS

These findings reveal a novel anti-adipogenic role for CETP.

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.