Effects of exercise on whole-blood transcriptome profile in children with overweight/obesity

BACKGROUND

The current knowledge about the molecular mechanisms underlying the health benefits of exercise is still limited, especially in childhood. We set out to investigate the effects of a 20-week exercise intervention on whole-blood transcriptome profile (RNA-seq) in children with overweight/obesity.

METHODS

Twenty-four children (10.21 ± 1.33 years, 46% girls) with overweight/obesity, were randomized to either a 20-week exercise program (intervention group; n = 10), or to a no-exercise control group (n = 14). Whole-blood transcriptome profile was analyzed using RNA-seq by STRT technique with GlobinLock technology.

RESULTS

Following the 20-week exercise intervention program, 161 genes were differentially expressed between the exercise and the control groups among boys, and 121 genes among girls (p-value <0.05), while after multiple correction, no significant difference between exercise and control groups persisted in gene expression profiles (FDR >0.05). Genes enriched in GO processes and molecular pathways showed different immune response in boys (antigen processing and presentation, infections, and T cell receptor complex) and in girls (Fc epsilon RI signaling pathway) (FDR <0.05).

CONCLUSION

These results suggest that 20-week exercise intervention program alters the molecular pathways involved in immune processes in children with overweight/obesity.

Beyond the single-outcome approach: A comparison of outcome-wide analysis methods for exposome research

Outcome-wide analysis can offer several benefits, including increased power to detect weak signals and the ability to identify exposures with multiple effects on health, which may be good targets for preventive measures. Recently, advanced statistical multivariate techniques for outcome-wide analysis have been developed, but they have been rarely applied to exposome analysis. In this work, we provide an overview of a selection of methods that are well-suited for outcome-wide exposome analysis and are implemented in the R statistical software. Our work brings together six different methods presenting innovative solutions for typical problems arising from outcome-wide approaches in the context of the exposome, including dependencies among outcomes, high dimensionality, mixed-type outcomes, missing data records, and confounding effects. The identified methods can be grouped into four main categories: regularized multivariate regression techniques, multi-task learning approaches, dimensionality reduction approaches, and bayesian extensions of the multivariate regression framework. Here, we compare each technique presenting its main rationale, strengths, and limitations, and provide codes and guidelines for their application to exposome data. Additionally, we apply all selected methods to a real exposome dataset from the Human Early-Life Exposome (HELIX) project, demonstrating their suitability for exposome research. Although the choice of the best method will always depend on the challenges to be faced in each application, for an exposome-like analysis we find dimensionality reduction and bayesian methods such as reduced rank regression (RRR) or multivariate bayesian shrinkage priors (MBSP) particularly useful, given their ability to deal with critical issues such as collinearity, high-dimensionality, missing data or quantification of uncertainty.

Statistical Approaches to Study Exposome-Health Associations in the Context of Repeated Exposure Data: A Simulation Study

The exposome concept aims to consider all environmental stressors simultaneously. The dimension of the data and the correlation that may exist between exposures lead to various statistical challenges. Some methodological studies have provided insight regarding the efficiency of specific modeling approaches in the context of exposome data assessed once for each subject. However, few studies have considered the situation in which environmental exposures are assessed repeatedly. Here, we conduct a simulation study to compare the performance of statistical approaches to assess exposome-health associations in the context of multiple exposure variables. Different scenarios were tested, assuming different types and numbers of exposure-outcome causal relationships. An application study using real data collected within the INMA mother-child cohort (Spain) is also presented. In the simulation experiment, assessed methods showed varying performance across scenarios, making it challenging to recommend a one-size-fits-all strategy. Generally, methods such as sparse partial least-squares and the deletion-substitution-addition algorithm tended to outperform the other tested methods (ExWAS, Elastic-Net, DLNM, or sNPLS). Notably, as the number of true predictors increased, the performance of all methods declined. The absence of a clearly superior approach underscores the additional challenges posed by repeated exposome data, such as the presence of more complex correlation structures and interdependencies between variables, and highlights that careful consideration is essential when selecting the appropriate statistical method. In this regard, we provide recommendations based on the expected scenario. Given the heightened risk of reporting false positive or negative associations when applying these techniques to repeated exposome data, we advise interpreting the results with caution, particularly in compromised contexts such as those with a limited sample size.

Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression

BACKGROUND AND OBJECTIVE

Prostate cancer is one of the most prevalent forms of cancer in men worldwide. Traditional screening strategies such as serum PSA levels, which are not necessarily cancer-specific, or digital rectal exams, which are often inconclusive, are still the screening methods used for the disease. Some studies have focused on identifying biomarkers of the disease but none have been reported for diagnosis in routine clinical practice and few studies have provided tools to assist the pathologist in the decision-making process when analyzing prostate tissue. Therefore, a classifier is proposed to predict the occurrence of PCa that provides physicians with accurate predictions and understandable explanations.

METHODS

A selection of 47 genes was made based on differential expression between PCa and normal tissue, GO gene ontology as well as the literature to be used as input predictors for different machine learning methods based on eXplainable Artificial Intelligence. These methods were trained using different class-balancing strategies to build accurate classifiers using gene expression data from 550 samples from 'The Cancer Genome Atlas'. Our model was validated in four external cohorts with different ancestries, totaling 463 samples. In addition, a set of SHapley Additive exPlanations was provided to help clinicians understand the underlying reasons for each decision.

RESULTS

An in-depth analysis showed that the Random Forest algorithm combined with majority class downsampling was the best performing approach with robust statistical significance. Our method achieved an average sensitivity and specificity of 0.90 and 0.8 with an AUC of 0.84 across all databases. The relevance of DLX1, MYL9 and FGFR genes for PCa screening was demonstrated in addition to the important role of novel genes such as CAV2 and MYLK.

CONCLUSIONS

This model has shown good performance in 4 independent external cohorts of different ancestries and the explanations provided are consistent with each other and with the literature, opening a horizon for its application in clinical practice. In the near future, these genes, in combination with our model, could be applied to liquid biopsy to improve PCa screening.

Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in children with obesity

Obesity in children is related to the development of cardiometabolic complications later in life, where molecular changes of visceral adipose tissue (VAT) and skeletal muscle tissue (SMT) have been proven to be fundamental. The aim of this study is to unveil the gene expression architecture of both tissues in a cohort of Spanish boys with obesity, using a clustering method known as weighted gene co-expression network analysis. For this purpose, we have followed a multi-objective analytic pipeline consisting of three main approaches; identification of gene co-expression clusters associated with childhood obesity, individually in VAT and SMT (intra-tissue, approach I); identification of gene co-expression clusters associated with obesity-metabolic alterations, individually in VAT and SMT (intra-tissue, approach II); and identification of gene co-expression clusters associated with obesity-metabolic alterations simultaneously in VAT and SMT (inter-tissue, approach III). In both tissues, we identified independent and inter-tissue gene co-expression signatures associated with obesity and cardiovascular risk, some of which exceeded multiple-test correction filters. In these signatures, we could identify some central hub genes (e.g., NDUFB8, GUCY1B1, KCNMA1, NPR2, PPP3CC) participating in relevant metabolic pathways exceeding multiple-testing correction filters. We identified the central hub genes PIK3R2, PPP3C and PTPN5 associated with MAPK signaling and insulin resistance terms. This is the first time that these genes have been associated with childhood obesity in both tissues. Therefore, they could be potential novel molecular targets for drugs and health interventions, opening new lines of research on the personalized care in this pathology. This work generates interesting hypotheses about the transcriptomics alterations underlying metabolic health alterations in obesity in the pediatric population.

Serum levels of the novel adipokine isthmin-1 are associated with obesity in pubertal boys

OBJECTIVES

To evaluate whether there is an association between the serum levels of the novel insulin-like adipokine isthmin-1 (ISM1) and obesity-related phenotypes in a population of Spanish children and to investigate the plausible molecular alterations behind the alteration of the serum levels of this protein in children with obesity.

METHODS

The study population is a sub-cohort of the PUBMEP research project, consisting of a cross-sectional population of 119 pubertal children with overweight (17 boys, 19 girls), obesity (20 boys, 25 girls), and normal weight (17 boys, 21 girls). All subjects were classified into experimental groups according to their sex, obesity, and insulin resistance (IR) status. They were counted anthropometry, glucose and lipid metabolism, inflammation and cardiovascular biomarkers as well as isthmin-1 (ISM1) serum levels. This population was intended as a discovery population to elucidate the relationship between obesity and ISM1 levels in children. Furthermore, the study population had blood whole-genome DNA methylation examined, allowing deepening into the obesity-ISM1 molecular relationship.

RESULTS

Higher serum ISM1 levels were observed in boys with obesity than in normal weight (P = 0.004) and overweight (P = 0.007) boys. ISM1 serum levels were positively associated with body mass index (BMI) Z-score (P = 0.005) and fat mass (P = 0.058) and negatively associated with myeloperoxidase (MPO) (P = 0.043) in boys. Although we did not find associations between ISM1 serum levels and metabolic outcomes in girls, which may indicate a putative sexual dimorphism, fat mass was positively associated in all children, including boys and girls (P = 0.011). DNA methylation levels in two-enhancer-related CpG sites of ISM1 (cg03304641 and cg14269097) were associated with serum levels of ISM1 in children.

CONCLUSIONS

ISM1 is associated with obesity in boys at the pubertal stage, elucidating how this protein might be of special relevance as a new biomarker of obesity in children. Further studies including a longitudinal design during puberty are needed.

Environmental exposures in early-life and general health in childhood

BACKGROUND

Early-life environmental exposures are suspected to be involved in the development of chronic diseases later in life. Most studies conducted so far considered single or few exposures and single-health parameter. Our study aimed to identify a childhood general health score and assess its association with a wide range of pre- and post-natal environmental exposures.

METHODS

The analysis is based on 870 children (6-12 years) from six European birth cohorts participating in the Human Early-Life Exposome project. A total of 53 prenatal and 105 childhood environmental factors were considered, including lifestyle, social, urban and chemical exposures. We built a general health score by averaging three sub-scores (cardiometabolic, respiratory/allergy and mental) built from 15 health parameters. By construct, a child with a low score has a low general health status. Penalized multivariable regression through Least Absolute Shrinkage and Selection Operator (LASSO) was fitted in order to identify exposures associated with the general health score.

FINDINGS

The results of LASSO show that a lower general health score was associated with maternal passive and active smoking during pregnancy and postnatal exposure to methylparaben, copper, indoor air pollutants, high intake of caffeinated drinks and few contacts with friends and family. Higher child's general health score was associated with prenatal exposure to a bluespace near residency and postnatal exposures to pets, cobalt, high intakes of vegetables and more physical activity. Against our hypotheses, postnatal exposure to organochlorine compounds and perfluorooctanoate were associated with a higher child's general health score.

CONCLUSION

By using a general health score summarizing the child cardiometabolic, respiratory/allergy and mental health, this study reinforced previously suspected environmental factors associated with various child health parameters (e.g. tobacco, air pollutants) and identified new factors (e.g. pets, bluespace) warranting further investigations.

Longitudinal associations between cardiovascular biomarkers and metabolic syndrome during puberty: the PUBMEP study

Puberty has been described as a life stage of considerable metabolic risk specially for those with obesity. The low-grade systemic inflammatory status associated with obesity could be one of the connections with metabolic syndrome (MetS). Thus, we aimed to assess the relationship between inflammatory and cardiovascular biomarkers and the development of MetS during puberty. Seventy-five children from the PUBMEP study (33 females), aged 4-18 years, were included. Cardiovascular and inflammatory biomarkers were measured in the prepubertal and pubertal stage, including high-sensitivity C-reactive protein (CRP), leptin, tumor necrosis factor-alpha (TNFα), interleukin 8 (IL8), monocyte chemoattractant protein 1 (MCP-1), total plasminogen activator inhibitor-1 (tPAI), resistin, adiponectin, myeloperoxidase (MPO), and soluble intercellular adhesion molecule-1 (sICAM-1). MetS was diagnosed at each measurement point. Mixed-effects and logistic regressions were performed. Those children with MetS in puberty presented higher prepubertal values of several cardiometabolic biomarkers in comparison to those without MetS (z-score body mass index (zBMI), waist circumference, insulin, HOMA-IR, leptin, and tPAI (p < 0.05)). For prepubertal children with obesity, the odds of developing MetS in puberty were significantly higher in those having high zBMI (OR = 4.27; CI: 1.39-22.59) or high concentrations of tPAI (OR = 1.19; CI: 1.06-1.43).

CONCLUSION

Those with obesity with higher prepubertal tPAI plasma levels had 19% higher odds of having MetS at puberty highlighting the existence of association between MetS, obesity, and inflammation already in puberty. Thus, assessing cardiometabolic and inflammatory status in children with obesity already at prepuberty is key to avoiding future comorbidities.

WHAT IS KNOWN

• Inflammation, metabolic syndrome, and obesity may have their onset in childhood. • Puberty is a life stage characterized for an increased cardiovascular risk.

WHAT IS NEW

• Prepuberty state could be an early indicator of future cardiometabolic risk. • Children with obesity and high total plasminogen have higher odds of future metabolic syndrome.

Prepubertal Children With Metabolically Healthy Obesity or Overweight Are More Active Than Their Metabolically Unhealthy Peers Irrespective of Weight Status: GENOBOX Study

Background and Aim

The association of a metabolically healthy status with the practice of physical activity (PA) remains unclear. Sedentarism and low PA have been linked to increased cardiometabolic risk. The aim of this study was to evaluate the PA levels in metabolically healthy (MH) or unhealthy (MU) prepubertal children with or without overweight/obesity.

Methods

A total 275 children (144 boys) with 9 ± 2 years old were selected for the GENOBOX study. PA times and intensities were evaluated by accelerometry, and anthropometry, blood pressure, and blood biochemical markers were analyzed. Children were considered to have normal weight or obesity, and further classified as MH or MU upon fulfillment of the considered metabolic criteria.

Results

Classification resulted in 119 MH children (21% with overweight/obesity, referred to as MHO) and 156 MU children (47% with overweight/obesity, referred to as MUO). Regarding metabolic profile, MHO showed lower blood pressure levels, both systolic and diastolic and biochemical markers levels, such as glucose, Homeostatic Model Assessment of Insulin Resistance, triglycerides and higher HDL-c levels than MUO (P < 0.001). In addition, MHO children spent more time in PA of moderate intensity compared with MUO children. In relation to vigorous PA, MH normal weight (MHN) children showed higher levels than MUO children. Considering sex, boys spent more time engaged in moderate, vigorous, and moderate–vigorous (MV) PA than girls, and the number of boys in the MH group was also higher.

Conclusion

Prepubertal MHO children are less sedentary, more active, and have better metabolic profiles than their MUO peers. However, all children, especially girls, should increase their PA engagement, both in terms of time and intensity because PA appears to be beneficial for metabolic health status itself.

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.

Progression of metabolic syndrome and associated cardiometabolic risk factors from prepuberty to puberty in children: The PUBMEP study

INTRODUCTION

Metabolic syndrome (MetS) is a cluster of clinical and metabolic alterations related to the risk of cardiovascular diseases (CVD). Metabolic changes occurring during puberty, especially in children with overweight and obesity, can influence the risk of developing chronic diseases, especially CVD.

METHODS

Longitudinal study based on the follow-up until puberty of a cohort of 191 prepubertal Spanish boys and girls without congenital, chronic, or inflammatory diseases: undernutrition: or intake of any drug that could alter blood glucose, blood pressure, or lipid metabolism. The following parameters were used to determine the presence of MetS: obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-c.

RESULTS

A total of 75·5% of participants stayed in the same BMI category from prepuberty to puberty, whereas 6·3% increased by at least one category. The prevalence of MetS was 9·1% (prepubertal stage) and 11·9% (pubertal stage). The risk of presenting alterations in puberty for systolic blood pressure (SBP), plasma triacylglycerols, HDL cholesterol (HDL-c), and HOMA-IR was significantly higher in those participants who had the same alterations in prepuberty. MetS prevalence in puberty was predicted by sex and levels of HOMA-IR, BMI-z, and waist circumference in the prepubertal stage, in the whole sample: in puberty, the predictors were levels of HOMA-IR, BMI-z, and diastolic blood pressure in participants with obesity. Two fast-and-frugal decision trees were built to predict the risk of MetS in puberty based on prepuberty HOMA-IR (cutoff 2·5), SBP (cutoff 106 mm of Hg), and TAG (cutoff 53 mg/dl).

DISCUSSION

Controlling obesity and cardiometabolic risk factors, especially HOMA-IR and blood pressure, in children during the prepubertal stage appears critical to preventing pubertal MetS effectively.

The Vitamin D Decrease in Children with Obesity Is Associated with the Development of Insulin Resistance during Puberty: The PUBMEP Study

Obesity and cardiometabolic risk have been associated with vitamin D levels even in children. The objective of the present study was to evaluate the association between insulin resistance (IR), cardiometabolic risk factors, and vitamin D in children from prepubertal to pubertal stages. A total of 76 children from the PUBMEP study, aged 4–12 years at baseline, were included. Children were evaluated in prepubertal and pubertal stages. Anthropometric measurements and selected cardiometabolic risk biomarkers, such as plasma glucose, blood lipids, insulin, adiponectin, leptin, and blood pressure, and serum 25-hydroxyvitamin D (25(OH)D) were determined. Children were categorized by obesity degree and IR status combined before and after puberty. Paired t-test and multivariate linear regression analyses were conducted. During puberty, the increase in triacylglycerols, insulin, and HOMA-IR and the decrease in QUICKI were significantly associated with the reduction in 25(OH)D (B = −0.274, p = 0.032; B = −0.219, p = 0.019; B = −0.250, p = 0.013; B = 1.574, p = 0.013, respectively) after adjustment by BMI-z, sex, and pubertal stage. Otherwise, prepubertal non-IR children with overweight/obesity that became IR during puberty showed a significant decrease in 25(OH)D and HDL-c, and an increase in waist circumference and triacylglycerol concentrations (p < 0.05 for all) over time. These results suggest that changes in IR seem to be associated with an effect on 25(OH)D levels during puberty, especially in children with overweight.

Association of Diet, Physical Activity Guidelines and Cardiometabolic Risk Markers in Children

The aim was to identify different dietary and physical activity (PA) patterns in 5- to 14-year-old children with a high prevalence of overweight and obesity using cluster analysis based on their adherence to the Spanish Society of Community Nutrition dietary guidelines and levels of PA, and to determine their associations with age, sex, body composition, and cardiometabolic risk markers. In 549 children, hierarchical cluster analysis was used to identify subgroups with similar adherence to dietary recommendations and level of PA. Three clusters were identified: Cluster 1, with the lowest level of vigorous PA and adherence to dietary recommendations; Cluster 2, with the lowest levels of moderate and vigorous PA and the highest adherence to dietary recommendations; and Cluster 3, with the highest level of PA, especially vigorous PA and a medium level adherence to dietary recommendations. Cluster 3 had lower total body fat and higher lean body mass percentages than Cluster 2. Cluster 2 had lower high-density lipoprotein cholesterol and higher low-density lipoprotein cholesterol levels than Cluster 1. The results from our study suggest that it is important to consider adherence to PA recommendations together with adherence to dietary guidelines to understand patterns of obesogenic habits in pediatric populations with high prevalence of overweight and obesity.

Changes in Physical Activity Patterns from Childhood to Adolescence: Genobox Longitudinal Study

Longitudinal changes of physical activity (PA) from childhood into adolescence have not been accurately described yet for the Spanish population. The aim of this study is to evaluate the changes of PA, assessed by accelerometry and anthropometric measures in a cohort of 213 children from the prepubertal to pubertal period, focusing on those with valid data from both time points (n = 75). Sedentary time (ST) increased about 50%, while all PA intensities declined from the pre-pubertal to pubertal period. Light PA (LPA) was the major contributor, decreasing by about 30%. Boys were more active than girls in both periods, but they showed a higher decline in PA, especially moderate-to-vigorous PA (MVPA). The proportion who reached the recommendation of 60 min of MVPA decreased by 33.3% in boys and 4.6% in girls. Children with obesity or overweight had lower MVPA than those with normal-weight in the pre-pubertal period, but no differences were found in the pubertal period. This study shows a decrease of PA and an increase of sedentarism in the transition from childhood to adolescence, particularly in boys. Regardless of body weight, adolescents tend to be less active. Therefore, prevention programs should be implemented to achieve optimal PA and reduce sedentarism during infancy considering the differences found by sex.

Genetics of Lactose Intolerance: An Updated Review and Online Interactive World Maps of Phenotype and Genotype Frequencies

In humans the ability to digest milk lactose is conferred by a β-galactosidase enzyme called lactase-phlorizin hydrolase (LPH). While in some humans (approximately two-thirds of humankind) the levels of this enzyme decline drastically after the weaning phase (a trait known as lactase non-persistence (LNP)), some other individuals are capable of maintaining high levels of LPH lifelong (lactase persistence (LP)), thus being able to digest milk during adulthood. Both lactase phenotypes in humans present a complex genetic basis and have been widely investigated during the last decades. The distribution of lactase phenotypes and their associated single nucleotide polymorphisms (SNPs) across human populations has also been extensively studied, though not recently reviewed. All available information has always been presented in the form of static world maps or large dimension tables, so that it would benefit from the newly available visualization tools, such as interactive world maps. Taking all this into consideration, the aims of the present review were: (1) to gather and summarize all available information on LNP and LP genetic mechanisms and evolutionary adaptation theories, and (2) to create online interactive world maps, including all LP phenotype and genotype frequency data reported to date. As a result, we have created two online interactive resources, which constitute an upgrade over previously published static world maps, and allow users a personalized data exploration, while at the same time accessing complete reports by population or ethnicity.

Cluster Analysis of Physical Activity Patterns, and Relationship with Sedentary Behavior and Healthy Lifestyles in Prepubertal Children: Genobox Cohort

Sedentary habits during childhood are associated with adverse health outcomes. The aim of this work was to cluster lifestyle behaviors and metabolic biomarkers to establish different patterns in children. Their physical and sedentary activities were evaluated by accelerometry, and questionnaires that included lifestyle behaviors, such as adherence to a Mediterranean diet, anthropometry and blood biochemical markers. Cluster analysis was performed to establish different groups based on physical activity levels. A total of 489 children were finally selected. Cluster 1 included children with a mostly sedentary state, whereas Cluster 3 included the most active children and Cluster 2 included children that did not fit into either the sedentary or the highly active groups. In Cluster 3, 56% of children were in a sports club, and a lower percentage used electronic devices in their rooms compared to the other groups. Cluster 1 children exhibited higher insulin, HOMA-IR and triacylglycerides with respect to the other groups. No differences were found regarding adherence to a Mediterranean diet. The choice to practice an extracurricular sport could be an influencing factor to increase exercise and ensure an active lifestyle in children. Reducing or limiting screen time mainly in children’s rooms could contribute to an active lifestyle.

The protein S100A4 as a novel marker of insulin resistance in prepubertal and pubertal children with obesity

BACKGROUND

S100A4 is a metastasis-associated protein also reported as a promising marker for dysfunctional white adipose tissue (WAT) and insulin resistance (IR) in adult and adolescent populations.

OBJECTIVE

We aimed to evaluate the association between the protein S100A4 and obesity and IR in children and during pubertal development.

DESIGN AND METHODS

The study design consisted of three cross-sectional populations of 249, 11 and 19 prepubertal children respectively (named study population 1, 2 and 3), and a longitudinal population of 53 girls undergoing sexual maturation (study population 4). All subjects were classified into experimental groups according to their sex, obesity and IR status. All study populations counted on anthropometry, glucose, and lipid metabolism, inflammation and cardiovascular biomarkers as well as S100A4 plasma levels measured. The study population 1 was intended as the discovery population in which to elucidate the relationship between Obesity-IR and S100A4 plasma levels in prepubertal children. The cross-sectional populations 2 and 3 further counted on WAT gene expression data for investigating the molecular basis of this association. Instead, the longitudinal study population 4 presented blood whole-genome DNA methylation data at each temporal record, allowing deepening into the Obesity-IR-S1004 relationship during puberty as well as deciphering plausible epigenetic mechanisms altering S100A4 plasma levels.

RESULTS

S100A4 plasma levels were strongly associated with several metabolic and anthropometric outcomes, namely IR, in prepubertal non-diabetic obese children. We also found highly significant positive associations during the course of puberty between the increase in S100A4 levels and the increase in HOMA-IR (P = 0.0003, FDR = 0.005) and insulin levels (P = 0.0003, FDR = 0.005). Methylation in two-enhancer related CpG sites of the S100A4 region (cg07245635 and cg10447638) was associated with IR biomarkers at the prepubertal stage and with longitudinal changes in these measurements. We further reported an association between visceral WAT (vWAT) S100A4 expression and HOMA-IR, insulin levels and BMI Z-Score, but not with circulating S100A4.

CONCLUSIONS

We report for the first time the association of S100A4 with IR and WAT dysfunction in prepubertal populations as well as how the change in plasma S100A4 levels accompanies longitudinal trajectories of IR in children during pubertal development. Moreover, we propose epigenetic changes in two methylation sites and an altered S100A4 vWAT expression as plausible molecular mechanisms underlying this disturbance in obesity.

eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research

Until date, several machine learning approaches have been proposed for the dynamic modeling of temporal omics data. Although they have yielded impressive results in terms of model accuracy and predictive ability, most of these applications are based on "Black-box" algorithms and more interpretable models have been claimed by the research community. The recent eXplainable Artificial Intelligence (XAI) revolution offers a solution for this issue, were rule-based approaches are highly suitable for explanatory purposes. The further integration of the data mining process along with functional-annotation and pathway analyses is an additional way towards more explanatory and biologically soundness models. In this paper, we present a novel rule-based XAI strategy (including pre-processing, knowledge-extraction and functional validation) for finding biologically relevant sequential patterns from longitudinal human gene expression data (GED). To illustrate the performance of our pipeline, we work on in vivo temporal GED collected within the course of a long-term dietary intervention in 57 subjects with obesity (GSE77962). As validation populations, we employ three independent datasets following the same experimental design. As a result, we validate primarily extracted gene patterns and prove the goodness of our strategy for the mining of biologically relevant gene-gene temporal relations. Our whole pipeline has been gathered under open-source software and could be easily extended to other human temporal GED applications.

X chromosome genetic data in a Spanish children cohort, dataset description and analysis pipeline

X chromosome genetic variation has been proposed as a potential source of missing heritability for many complex diseases, including obesity. Currently, there is a lack of public available genetic datasets incorporating X chromosome genotype data. Although several X chromosome-specific statistics have been developed, there is also a lack of readily available implementations for routine analysis. Here, we aimed: (1) to make public and describe a dataset incorporating phenotype and X chromosome genotype data from a cohort of 915 normal-weight, overweight and obese children, and (2) to deeply describe a whole implementation of the special X chromosome analytic process in genetics. Datasets and pipelines like this are crucial to get familiar with the steps in which X chromosome requires special attention and may raise awareness of the importance of this genomic region.

Design Type(s)	disease analysis objective • factorial design • genetic structural variation analysis objective • genotyping design
Measurement Type(s)	genotyping assay
Technology Type(s)	genotyping
Factor Type(s)	sex • experimental condition
Sample Characteristic(s)	Homo sapiens • blood

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Role of Functional Fortified Dairy Products in Cardiometabolic Health: A Systematic Review and Meta-analyses of Randomized Clinical Trials

There is insufficient evidence on the role of functional fortified dairy products in improving health and in preventing risk factors associated with noncommunicable chronic diseases. This systematic review was conducted to summarize effects of the consumption of fortified dairy products on biomarkers of cardiometabolic risk. MEDLINE and SCOPUS databases were used to perform searches to include studies published up to 30 April 2018. Randomized clinical trials with human subjects consuming dairy products fortified with phytosterols, FAs, vitamins or minerals and relating this consumption with cardiometabolic health were included in this review. Risk of bias assessment according to Cochrane guidelines was performed to determine the quality of the trials. Forty-one studies were finally selected for this synthesis; the selected studies tested dairy products fortified with the following nutrients and bioactive components: phytosterols (n = 31), FAs (n = 8), and vitamin D (n = 2). We found that the consumption of phytosterol-fortified dairy, led to an overall LDL cholesterol reduction of -0.36 (-0.41, -0.31) mmol/L, P < 0.001; this decrease was mainly related to the dosage. Likewise, consumption of ω-3 FA-fortified dairy products resulted in a plasma LDL cholesterol reduction of -0.18 (-0.27, -0.09) mmol/L as well as a decrease of -0.18 (-0.32, -0.05) mmol/L in triacylglycerols (TG). Performing meta-analyses of the consumption of dairy products fortified with vitamin D or FAs other than ω-3 FAs and biomarkers of cardiometabolic risk was not possible because of the few available publications. Our results indicate that consumption of dairy products fortified with phytosterols and ω-3 FAs can lead to a reduction of LDL cholesterol and consumption of fortified dairy products fortified with ω-3 FAs can reduce TG concentration. However, more studies with homogeneous designs are needed to determine the advantages of using dairy products as fortification vehicles to prevent cardiometabolic risk.

Effects of X-chromosome Tenomodulin Genetic Variants on Obesity in a Children's Cohort and Implications of the Gene in Adipocyte Metabolism

Tenomodulin (TNMD) is a type II transmembrane glycoprotein that has been recently linked to obesity, and it is highly expressed in obese adipose tissue. Several sex-dependent associations have been observed between single-nucleotide polymorphisms (SNPs) of the TNMD gene, which is located in the X-chromosome, and obesity, type 2 diabetes mellitus (T2DM), and metabolic syndrome in adults. On the other hand, results are lacking for children. We aimed (i) to study the association between TNMD genetic variants and metabolic complications related to childhood obesity and (ii) to investigate the function of TNMD in human adipocytes. We conducted a case-control, multicenter study in 915 Spanish children and demonstrated significant positive associations between TNMD genetic variants and BMI z-score, waist circumference, fasting glucose, and insulin resistance in boys, highlighting the SNP rs4828038. Additionally, we showed a BMI-adjusted inverse association with waist circumference in girls. Second, in vitro experiments revealed that TNMD is involved in adipogenesis, along with glucose and lipid metabolism in differentiated adipocytes, and these effects may be mediated through AMPK activation. Hence, these results suggest that TNMD genetic variants could be potentially useful as early life risk indicators for obesity and T2DM. In addition, we support the fact that TNMD exhibits significant metabolic functions in adipocytes.

Genetic Factors and Molecular Mechanisms of Vitamin D and Obesity Relationship

Vitamin D (vitD) deficiency is associated with a wide range of chronic diseases and conditions, including obesity, and with an increasing severity of metabolic dysregulation, such as insulin resistance, hyperlipidemia, liver disease, and hypertension, both in children and adults. However, the nature of the association between low vitD status and obesity remains unclear. This fact has motivated the scientific community to conduct genetic association analyses between 25-hydroxyvitamin D (25[OH]D)-related genes and obesity traits. In this line, the variation in the vitD receptor (VDR) gene represents the bulk of the findings. Specifically, polymorphisms in the VDR gene have been associated with obesity traits in some but not all, studies. Thus, results regarding this matter remain inconclusive. Other genes aside from VDR have also been investigated in relation to obesity-related traits. However, again, findings have been inconsistent. In general, results point to the fact that the DBP/GC gene could be an important protein-linking obesity and vitD status. On the other hand, several studies have attempted to determine the molecular mechanism of the relationship between 25(OH)-D levels and obesity. Some of these studies suggest that vitD, due to its fat-soluble characteristic, is retained by the adipose tissue and has the capacity to metabolize 25(OH)-D locally, and this can be altered during obesity. Additionally, vitD is capable of regulating the gene expression related to adipogenesis process, inflammation, oxidative stress, and metabolism in mature adipocytes. Therefore, the aim of the present review was to evaluate the association between obesity and vitD deficiency describing the main molecular mechanism of the relationship and the link with genetic factors. Key Messages: Low serum 25(OH)-D is positively associated with obesity or BMI in adults and children. Circulating vitD concentrations are, at least, partially determined by genetic factors. VitD plays an important role in the adipogenesis process and inflammation status in adipocytes and adipose tissue.