Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents

Variability of polygenic prediction for body mass index in Africa

BACKGROUND

Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required.

METHODS

Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions.

RESULTS

Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status.

CONCLUSIONS

Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.

Exploring Maternal Diet-Epigenetic-Gut Microbiome Crosstalk as an Intervention Strategy to Counter Early Obesity Programming

Alterations in a mother's metabolism and endocrine system, due to unbalanced nutrition, may increase the risk of both metabolic and non-metabolic disorders in the offspring's childhood and adulthood. The risk of obesity in the offspring can be determined by the interplay between maternal nutrition and lifestyle, intrauterine environment, epigenetic modifications, and early postnatal factors. Several studies have indicated that the fetal bowel begins to colonize before birth and that, during birth and nursing, the gut microbiota continues to change. The mother's gut microbiota is primarily transferred to the fetus through maternal nutrition and the environment. In this way, it is able to impact the establishment of the early fetal and neonatal microbiome, resulting in epigenetic signatures that can possibly predispose the offspring to the development of obesity in later life. However, antioxidants and exercise in the mother have been shown to improve the offspring's metabolism, with improvements in leptin, triglycerides, adiponectin, and insulin resistance, as well as in the fetal birth weight through epigenetic mechanisms. Therefore, in this extensive literature review, we aimed to investigate the relationship between maternal diet, epigenetics, and gut microbiota in order to expand on current knowledge and identify novel potential preventative strategies for lowering the risk of obesity in children and adults.

Socio-economic differences in body mass index: the contribution of genetic factors

BACKGROUND

Higher mean body mass index (BMI) among lower socioeconomic position (SEP) groups is well established in Western societies, but the influence of genetic factors on these differences is not well characterized.

METHODS

We analyzed these associations using Finnish health surveys conducted between 1992 and 2017 (N = 33 523; 53% women) with information on measured weight and height, polygenic risk scores of BMI (PGS-BMI) and linked data from administrative registers to measure educational attainment, occupation-based social class and personal income.

RESULTS

In linear regressions, largest adjusted BMI differences were found between basic and tertiary educated men (1.4 kg/m2, 95% confidence interval [CI] 1.2; 1.6) and women (2.5 kg/m2, 95% CI 2.3; 2.8), and inverse BMI gradients were also found for social class and income. These SEP differences arose partly because mean PGS-BMI was higher and partly because PGS-BMI predicted BMI more strongly in lower SEP groups. The inverse SEP gradients of BMI were steeper in women than in men, but sex differences were not found in the genetic contributions to these differences.

CONCLUSIONS

Better understanding of the interplay between genes and environment provides insight into the mechanisms explaining SEP differences in BMI.

A genomics perspective of personalized prevention and management of obesity

This review discusses the landscape of personalized prevention and management of obesity from a nutrigenetics perspective. Focusing on macronutrient tailoring, we discuss the impact of genetic variation on responses to carbohydrate, lipid, protein, and fiber consumption. Our bioinformatic analysis of genomic variants guiding macronutrient intake revealed enrichment of pathways associated with circadian rhythm, melatonin metabolism, cholesterol and lipoprotein remodeling and PPAR signaling as potential targets of macronutrients for the management of obesity in relevant genetic backgrounds. Notably, our data-based in silico predictions suggest the potential of repurposing the SYK inhibitor fostamatinib for obesity treatment in relevant genetic profiles. In addition to dietary considerations, we address genetic variations guiding lifestyle changes in weight management, including exercise and chrononutrition. Finally, we emphasize the need for a refined understanding and expanded research into the complex genetic landscape underlying obesity and its management.

New Insights into Polygenic Score-Lifestyle Interactions for Cardiometabolic Risk Factors from Genome-Wide Interaction Analyses

The relationship between lifestyles and cardiometabolic outcomes varies between individuals. In 382,275 UK Biobank Europeans, we investigate how lifestyles interact with polygenic scores (PGS) of cardiometabolic risk factors. We identify six interactions (PGS for body mass index with meat diet, physical activity, sedentary behaviour and insomnia; PGS for high-density lipoprotein cholesterol with sedentary behaviour; PGS for triglycerides with meat diet) in multivariable linear regression models including an interaction term and show stronger associations between lifestyles and cardiometabolic risk factors among individuals with high PGSs than those with low PGSs. Genome-wide interaction analyses pinpoint three genetic variants (FTO rs72805613 for BMI; CETP rs56228609 for high-density lipoprotein cholesterol; TRIB2 rs4336630 for triglycerides; PInteraction < 5 × 10-8). The associations between lifestyles and cardiometabolic risk factors differ between individuals grouped by the genotype of these variants, with the degree of differences being similar to that between individuals with high and low values for the corresponding PGSs. This study demonstrates that associations between lifestyles and cardiometabolic risk factors can differ between individuals based upon their genetic profiles. It further suggests that genetic variants with interaction effects contribute more to such differences compared to those without interaction effects, which has potential implications for developing PGSs for personalised intervention.

General and abdominal obesity and dietary nutrient intake among university students in Bangladesh: A cross-sectional study targeting potential risk factors

BACKGROUND & AIMS

The overall national increase in the prevalence of overweight and obesity has emerged among university students in Bangladesh. Though, poor dietary habits and lifestyle is quite common among university students, their dietary nutrient intake level, obesity prevalence and potential risk factors has hitherto given little priority. This study aimed to understand the prevalence and factors associated with general and abdominal obesity and level of dietary nutrient intake among university students in Bangladesh.

METHODS

Data from 320 unselected tertiary level students (81.6% males, 18.4% females; average age 22.7±3.0, BMI 22.4±3.1 and waist-hip ratio (WHR) 0.88 ± 0.1) was collected randomly, in a single visit, from Islamic University, Kushtia, Bangladesh. Basic demographic and anthropometric information were collected. Twenty-four hour (24H) dietary recall and food frequency questionnaire (FFQ) was used to collect dietary nutrient level retrospectively. Descriptive statistics, chi-square test, t-test, ANOVA, and binomial logistic regression analysis were done.

RESULTS

Around 3% and 42% student were reported to be obese and overweight respectively. Whereas abdominal obesity was prevalent among ∼52% and more than 67% of student were reportedly obese/overweight by either BMI or WHR or WHtR category. Energy and carbohydrate (CHO) intake were reported to be significantly higher (P < 0.05) among overweight who born by C-section delivery and were fed formula milk than those were normal weight and born by vaginal-birth and were breastfed. The overweight individual with a history of preterm birth was reported to intake significantly higher (P < 0.05) carbohydrates compared to normal-weight individuals with a history of term birth. While total fat intake was significantly higher (P < 0.05) among overweight individuals with their mother had gestational diabetes than those with normal weight individuals with mother without gestational diabetes.

CONCLUSIONS

General and abdominal obesity is common among university students and possibly associated with mode of birth, gestational duration, gestational diabetes, and breastfeeding practice.

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort

AIMS/HYPOTHESIS

There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution.

METHODS

Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin.

RESULTS

A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin.

CONCLUSIONS/INTERPRETATION

The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children

Diet modulates the genetic risk of obesity, but the modulation has been rarely studied using genetic risk scores (GRSs) in children. Our objectives were to identify single nucleotide polymorphisms (SNPs) that drive the interaction of specific foods with obesity and combine these into GRSs. Genetic and food frequency data from Finnish Health in Teens study was utilized. In total, 1142 11-year-old subjects were genotyped on the Metabochip array. BMI-GRS with 30 well-known SNPs was computed and the interaction of individual SNPs with food items and their summary dietary scores were examined in relation to age- and sex-specific BMI z-score (BMIz). The whole BMI-GRS interacted with several foods on BMIz. We identified 7-11 SNPs responsible for each interaction and these were combined into food-specific GRS. The most predominant interaction was witnessed for pizza (p < 0.001): the effect on BMIz was b - 0.130 (95% CI - 0.23; - 0.031) in those with low-risk, and 0.153 (95% CI 0.072; 0.234) in high-risk. Corresponding, but weaker interactions were verified for sweets and chocolate, sugary juice drink, and hamburger and hotdog. In total 5 SNPs close to genes NEGR1, SEC16B, TMEM18, GNPDA2, and FTO were shared between these interactions. Our results suggested that children genetically prone to obesity showed a stronger association of unhealthy foods with BMIz than those with lower genetic susceptibility. Shared SNPs of the interactions suggest common differences in metabolic gene-diet interactions, which warrants further investigation.

The Uterine Environment and Childhood Obesity Risk: Mechanisms and Predictions

PURPOSE OF REVIEW

Childhood obesity is a growing health problem in many populations, hence the urgent need to unravel the underlying mechanisms. Some evidence suggests that exposure to suboptimal intrauterine environments can program foetal metabolic health, with adverse consequences in later life, including susceptibility to childhood obesity.

FINDINGS

Factors such as high and low foetal birth weight, excessive gestational-weight-gain, maternal stress and smoking are all associated with increased risk of childhood obesity in observational studies. Animal models, where both genetic background and the postnatal environment can be carefully controlled, suggest that several different mechanisms, including epigenetic changes, dysregulation of adipose tissue development and programming of appetite, may be key drivers of developmental programming of childhood obesity. However, the influence of genetics and the post-natal environment are much more difficult to disentangle as independent effects in human studies, which are also complicated by low follow-up rates. Suboptimal intrauterine environments interact with maternal and foetal genetics and with the postnatal environment to contribute to the risk of childhood obesity. Maternal metabolic challenges, for example obesity and insulin resistance, contribute to the risk of foetal overgrowth and subsequent adiposity in childhood. To protect the long-term health of populations, research focusing on effective means of identifying and intervening in the transgenerational cycle of childhood obesity is required.

Integration of methylation quantitative trait loci (mQTL) on dietary intake on DNA methylation levels: an example of n-3 PUFA and ABCA1 gene

BACKGROUND

Epigenetic studies have reported relationships between dietary nutrient intake and methylation levels. However, genetic variants that may affect DNA methylation (DNAm) pattern, called methylation quantitative loci (mQTL), are usually overlooked in these analyses. We investigated whether mQTL change the relationship between dietary nutrient intake and leukocyte DNAm levels with an example of estimated fatty acid intake and ATP-binding cassette transporter A1 (ABCA1).

METHODS

A cross-sectional study on 231 participants (108 men, mean age: 62.7 y) without clinical history of cancer and no prescriptions for dyslipidemia. We measured leukocyte DNAm levels of 8 CpG sites within ABCA1 gene by pyrosequencing method and used mean methylation levels for statistical analysis. TaqMan assay was used for genotyping a genetic variant of ABCA1 (rs1800976). Dietary fatty acid intake was estimated with a validated food frequency questionnaire and adjusted for total energy intake by using residual methods.

RESULTS

Mean ABCA1 DNAm levels were 5% lower with the number of minor alleles in rs1800976 (CC, 40.6%; CG, 35.9%; GG, 30.6%). Higher dietary n-3 PUFA intake was associated with lower ABCA1 DNAm levels (1st (ref) vs. 4th, β [95% CI]: -2.52 [-4.77, -0.28]). After controlling for rs180076, the association between dietary n-3 PUFA intake and ABCA1 DNAm levels was attenuated, but still showed an independent association (1st (ref) vs. 4th, β [95% CI]: -2.00 [-3.84, -0.18]). The interaction of mQTL and dietary n-3 PUFA intake on DNAm levels was not significant.

CONCLUSIONS

This result suggested that dietary n-3 PUFA intake would be an independent predictor of DNAm levels in ABCA1 gene after adjusting for individual genetic background. Considering mQTL need to broaden into other genes and nutrients for deeper understanding of DNA methylation, which can contribute to personalized nutritional intervention.

Gene-Environment Interplay in the Development of Overweight

PURPOSE

Overweight in youth is influenced by genes and environment. Gene-environment interaction (G×E) has been demonstrated in twin studies and recent developments in genetics allow for studying G×E using individual genetic predispositions for overweight. We examine genetic influence on trajectories of overweight during adolescence and early adulthood and determine whether genetic predisposition is attenuated by higher socioeconomic status and having physically active parents.

METHODS

Latent class growth models of overweight were fitted using data from the TRacking Adolescents' Individual Lives Survey (n = 2720). A polygenic score for body mass index (BMI) was derived using summary statistics from a genome-wide association study of adult BMI (N = ∼700,000) and tested as predictor of developmental pathways of overweight. Multinomial logistic regression models were used to examine effects of interactions of genetic predisposition with socioeconomic status and parental physical activity (n = 1675).

RESULTS

A three-class model of developmental pathways of overweight fitted the data best ("non-overweight", "adolescent-onset overweight", and "persistent overweight"). The polygenic score for BMI and socioeconomic status distinguished the persistent overweight and adolescent-onset overweight trajectories from the non-overweight trajectory. Only genetic predisposition differentiated the adolescent-onset from the persistent overweight trajectory. There was no evidence for G×E.

DISCUSSION

Higher genetic predisposition increased the risk of developing overweight during adolescence and young adulthood and was associated with an earlier age at onset. We did not find that genetic predisposition was offset by higher socioeconomic status or having physically active parents. Instead, lower socioeconomic status and higher genetic predisposition acted as additive risk factors for developing overweight.

Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response

AIMS/HYPOTHESIS

Although insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the probability of successful prevention and intervention. Moreover, treatment efficacy is affected by the genetics of the individual. We used gene expression profiles from a cross-sectional study to identify potential candidate genes for the prediction of diabetes risk and intervention response.

METHODS

Using a multivariate regression model, we linked gene expression profiles of human skeletal muscle and intermuscular adipose tissue (IMAT) to fasting glucose levels and glucose infusion rate. Based on the expression patterns of the top predictive genes, we characterised and compared individual gene expression with clinical classifications using k-nearest neighbour clustering. The predictive potential of the candidate genes identified was validated using muscle gene expression data from a longitudinal intervention study.

RESULTS

We found that genes with a strong association with clinical measures clustered into three distinct expression patterns. Their predictive values for insulin resistance varied substantially between skeletal muscle and IMAT. Moreover, we discovered that individual gene expression-based classifications may differ from classifications based predominantly on clinical variables, indicating that participant stratification may be imprecise if only clinical variables are used for classification. Of the 15 top candidate genes, ST3GAL2, AASS, ARF1 and the transcription factor SIN3A are novel candidates for predicting a refined diabetes risk and intervention response.

CONCLUSION/INTERPRETATION

Our results confirm that disease progression and successful intervention depend on individual gene expression states. We anticipate that our findings may lead to a better understanding and prediction of individual diabetes risk and may help to develop individualised intervention strategies.

Polygenic risk scores enhance prediction of body mass index increase in individuals with a first episode of psychosis

BACKGROUND

Individuals with a first episode of psychosis (FEP) show rapid weight gain during the first months of treatment, which is associated with a reduction in general physical health. Although genetics is assumed to be a significant contributor to weight gain, its exact role is unknown.

METHODS

We assembled a population-based FEP cohort of 381 individuals that was split into a Training (n = 224) set and a Validation (n = 157) set to calculate the polygenic risk score (PRS) in a two-step process. In parallel, we obtained reference genome-wide association studies for body mass index (BMI) and schizophrenia (SCZ) to examine the pleiotropic landscape between the two traits. BMI PRSs were added to linear models that included sociodemographic and clinical variables to predict BMI increase (∆BMI) in the Validation set.

RESULTS

The results confirmed considerable shared genetic susceptibility for the two traits involving 449 near-independent genomic loci. The inclusion of BMI PRSs significantly improved the prediction of ∆BMI at 12 months after the onset of antipsychotic treatment by 49.4% compared to a clinical model. In addition, we demonstrated that the PRS containing pleiotropic information between BMI and SCZ predicted ∆BMI better at 3 (12.2%) and 12 months (53.2%).

CONCLUSIONS

We prove for the first time that genetic factors play a key role in determining ∆BMI during the FEP. This finding has important clinical implications for the early identification of individuals most vulnerable to weight gain and highlights the importance of examining genetic pleiotropy in the context of medically important comorbidities for predicting future outcomes.

Inorganic Pyrophosphate Plasma Levels Are Decreased in Pseudoxanthoma Elasticum Patients and Heterozygous Carriers but Do Not Correlate with the Genotype or Phenotype

Pseudoxanthoma elasticum (PXE) is a rare ectopic calcification disorder affecting soft connective tissues that is caused by biallelic ABCC6 mutations. While the underlying pathomechanisms are incompletely understood, reduced circulatory levels of inorganic pyrophosphate (PPi)-a potent mineralization inhibitor-have been reported in PXE patients and were suggested to be useful as a disease biomarker. In this study, we explored the relation between PPi, the ABCC6 genotype and the PXE phenotype. For this, we optimized and validated a PPi measurement protocol with internal calibration that can be used in a clinical setting. An analysis of 78 PXE patients, 69 heterozygous carriers and 14 control samples revealed significant differences in the measured PPi levels between all three cohorts, although there was overlap between all groups. PXE patients had a ±50% reduction in PPi levels compared to controls. Similarly, we found a ±28% reduction in carriers. PPi levels were found to correlate with age in PXE patients and carriers, independent of the ABCC6 genotype. No correlations were found between PPi levels and the Phenodex scores. Our results suggest that other factors besides PPi are at play in ectopic mineralization, which limits the use of PPi as a predictive biomarker for severity and disease progression.

Familial aggregation of the aging process: biological age measured in young adult offspring as a predictor of parental mortality

Measures of biological age (BA) integrate information across organ systems to quantify "biological aging," i.e., inter-individual differences in aging-related health decline. While longevity and lifespan aggregate in families, reflecting transmission of genes and environments across generations, little is known about intergenerational continuity of biological aging or the extent to which this continuity may be modified by environmental factors. Using data from the Jerusalem Perinatal Study (JPS), we tested if differences in offspring BA were related to mortality in their parents. We measured BA using biomarker data collected from 1473 offspring during clinical exams in 2007-2009, at age 32 ± 1.1. Parental mortality was obtained from population registry data for the years 2004-2016. We fitted parametric survival models to investigate the associations between offspring BA and parental all-cause and cause-specific mortality. We explored potential differences in these relationships by socioeconomic position (SEP) and offspring sex. Participants' BAs widely varied (SD = 6.95). Among those measured to be biologically older, parents had increased all-cause mortality (HR = 1.10, 95% CI: 1.08, 1.13), diabetes mortality (HR = 1.19, 95% CI: 1.08, 1.30), and cancer mortality (HR = 1.07, 95% CI: 1.02, 1.13). The association with all-cause mortality was stronger for families with low compared with high SEP (P_interaction = 0.04) and for daughters as compared to sons (P_interaction < 0.001). Using a clinical-biomarker-based BA estimate, observable by young adulthood prior to the onset of aging-related diseases, we demonstrate intergenerational continuity of the aging process. Furthermore, variation in this familial aggregation according to household socioeconomic position (SEP) at offspring birth and between families of sons and daughters proposes that the environment alters individuals' aging trajectory set by their parents.

Changing genetic architecture of body mass index from infancy to early adulthood: an individual based pooled analysis of 25 twin cohorts

Background

Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height.

Methods

We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age.

Results

The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood.

Conclusions

Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.

Study of the Combined Effect of Maternal Tobacco Smoking and Polygenic Risk Scores on Birth Weight and Body Mass Index in Childhood

Background: Maternal smoking during pregnancy has adverse health effects on the offspring, including lower birth weight and increased risk for obesity. These outcomes are also influenced by common genetic polymorphisms. We aimed to investigate the combined effect of maternal smoking during pregnancy and genetic predisposition on birth weight and body mass index (BMI)-related traits in 1,086 children of the Human Early Life Exposome (HELIX) project.

Methods: Maternal smoking during pregnancy was self-reported. Phenotypic traits were assessed at birth or at the age of 8 years. Ten polygenic risk scores (PRSs) per trait were calculated using the PRSice v2 program. For birth weight, we estimated two sets of PRSs based on two different base GWAS summary statistics: PRS-EGG, which includes HELIX children, and PRS-PanUK, which is completely independent. The best PRS per trait (highest R2) was selected for downstream analyses, and it was treated in continuous or categorized into three groups. Multivariate linear regression models were applied to evaluate the association of the explanatory variables with the traits of interest. The combined effect was evaluated by including an interaction term in the regression models and then running models stratified by the PRS group.

Results: BMI-related traits were correlated among them but not with birth weight. A similar pattern was observed for their PRSs. On average, the PRSs explained ∼4% of the phenotypic variation, with higher PRS values related to higher trait values (p-value &lt;5.55E-08). Sustained maternal smoking was associated with lower birth weight and higher BMI and related traits (p-value &lt;2.99E-02). We identified a gene by environment (GxE) interaction for birth weight between sustained maternal smoking and the PRS-EGG in three groups (p-value interaction = 0.01), which was not replicated with the PRS-PanUK (p-value interaction = 0.341). Finally, we did not find any statistically significant GxE interaction for BMI-related traits (p-value interaction &gt;0.237).

Conclusion: Sustained maternal smoking and the PRSs were independently associated with birth weight and childhood BMI-related traits. There was low evidence of GxE interactions.

Circulating miRNAs Are Associated with Inflammation Biomarkers in Children with Overweight and Obesity: Results of the I.Family Study

Increasing data suggest that overnutrition-induced obesity may trigger an inflammatory process in adipose tissue and upturn in the innate immune system. Numerous players have been involved in governing the inflammatory response, including epigenetics. Among epigenetic players, miRNAs are emerging as crucial regulators of immune cell development, immune responses, autoimmunity, and inflammation. In this study, we aimed at identifying the involvement of candidate miRNAs in relation to inflammation-associated biomarkers in a subsample of European children with overweight and obesity participating in the I.Family study. The study sample included individuals with increased adiposity since this condition contributes to the early occurrence of chronic low-grade inflammation. We focused on the acute-phase reagent C-reactive protein (CRP) as the primary outcome and selected cytokines as plausible biomarkers of inflammation. We found that chronic low-grade CRP elevation shows a highly significant association with miR-26b-3p and hsa-miR-576-5p in boys. Furthermore, the association of CRP with hsa-miR-10b-5p and hsa-miR-31-5p is highly significant in girls. We also observed major sex-related associations of candidate miRNAs with selected cytokines. Except for IL-6, a significant association of hsa-miR-26b-3p and hsa-miR-576-5p with TNF-α, IL1-Ra, IL-8, and IL-15 levels was found exclusively in boys. The findings of this exploratory study suggest sex differences in the association of circulating miRNAs with inflammatory response biomarkers, and indicate a possible role of miRNAs among the candidate epigenetic mechanisms related to the process of low-grade inflammation in childhood obesity.

A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk

Epidemiological and associative research from humans and animals identifies correlations between the environment and health impacts. The environment—health inter-relationship is effected through an individual’s underlying genetic variation and mediated by mechanisms that include the changes to gene regulation that are associated with the diversity of phenotypes we exhibit. However, the causal relationships have yet to be established, in part because the associations are reduced to individual interactions and the combinatorial effects are rarely studied. This problem is exacerbated by the fact that our genomes are highly dynamic; they integrate information across multiple levels (from linear sequence, to structural organisation, to temporal variation) each of which is open to and responds to environmental influence. To unravel the complexities of the genomic basis of human disease, and in particular non-communicable diseases that are also influenced by the environment (e.g., obesity, type II diabetes, cancer, multiple sclerosis, some neurodegenerative diseases, inflammatory bowel disease, rheumatoid arthritis) it is imperative that we fully integrate multiple layers of genomic data. Here we review current progress in integrated genomic data analysis, and discuss cases where data integration would lead to significant advances in our ability to predict how the environment may impact on our health. We also outline limitations which should form the basis of future research questions. In so doing, this review will lay the foundations for future research into the impact of the environment on our health.

Mediterranean Diet and Genetic Determinants of Obesity and Metabolic Syndrome in European Children and Adolescents

Childhood obesity and metabolic syndrome (MetS) are multifactorial diseases influenced by genetic and environmental factors. The Mediterranean Diet (MD) seems to modulate the genetic predisposition to obesity or MetS in European adults. The FTO gene has also been shown to have an impact on the MD benefits to avoid obesity or MetS. Since these interaction effects have been scarcely analyzed in European youth, the aim was to describe the gene–MD interplay, analyzing the impact of the genetic factors to reduce the obesity and MetS risk through MD adherence, and the MD impact in the obesity and MetS genetic profile. From the limited evidence on gene–MD interaction studies in European youth, a study showed that the influence of high MD adherence on adiposity and MetS was only observed with a limited number of risk alleles; the gene–MD interplay showed sex-specific differences, being higher in females. Most results analyzed in European adults elucidate that, the relationship between MD adherence and both obesity and MetS risk, could be modulated by obesity genetic variants and vice versa. Further research is needed, to better understand the inter-individual differences in the association between MD and body composition, and the integration of omics and personalized nutrition considering MD.

Influence of High Energy Diet and Polygenic Predisposition for Obesity on Postpartum Health in Rat Dams

It is estimated that 30% of pregnant women worldwide are overweight or obese, leading to adverse health effects for both mother and child. Women with obesity during pregnancy are at higher risk for developing both metabolic and mental disorders, such as diabetes and depression. Numerous studies have used rodent models of maternal obesity to understand its consequences on the offspring, yet characterization of changes in the dams is rare, and most rodent models rely solely on a high fat diet to induce maternal obesity, without regarding genetic propensity for obesity. Here we present the influence of both peripartum high energy diet (HE) and obesity-proneness on maternal health using selectively bred diet-resistant (DR) and diet-induced obese (DIO) rat dams. Outbred Sprague-Dawley rats were challenged with HE diet prior to mating and bred according to their propensity to gain weight. The original outbred breeding dams (F0) were maintained on low-fat chow during pregnancy and lactation. By comparison, the F1 dams consuming HE diet during pregnancy and lactation displayed higher gestational body weight gain (P < 0.01), and HE diet caused increased meal size and reduced meal frequency (P < 0.001). Sensitivity to the hormone amylin was preserved during pregnancy, regardless of diet. After several rounds of selective breeding, DIO and DR dams from generation F3 were provided chow or HE during pregnancy and lactation and assessed for their postpartum physiology and behaviors. We observed strong diet and phenotype effects on gestational weight gain, with DIO-HE dams gaining 119% more weight than DR-chow (P < 0.001). A high-resolution analysis of maternal behaviors did not detect main effects of diet or phenotype, but a subset of DIO dams showed delayed nursing behavior (P < 0.05). In generation F6/F7 dams, effects on gestational weight gain persisted (P < 0.01), and we observed a main effect of phenotype during a sucrose preference test (P < 0.05), with DIO-chow dams showing lower sucrose preference than DR controls (P < 0.05). Both DIO and DR dams consuming HE diet had hepatic steatosis (P < 0.001) and exhibited reduced leptin sensitivity in the arcuate nucleus (P < 0.001). These data demonstrate that both diet and genetic obesity-proneness have consequences on maternal health.

Parental feeding and childhood genetic risk for obesity: exploring hypothetical interventions with causal inference methods

BACKGROUND

Parental-feeding behaviors are common intervention targets for childhood obesity, but often only deliver small changes. Childhood BMI is partly driven by genetic effects, and the extent to which parental-feeding interventions can mediate child genetic liability is not known. Here we aim to examine how potential interventions on parental-feeding behaviors can mitigate some of the association between child genetic liability and BMI in early adolescence, using causal inference methods.

METHODS

Data from the Avon Longitudinal Study of Parents and Children were used to estimate an interventional disparity measure for a child polygenic score for BMI (PGS-BMI) on BMI at 12 years. The approach compares counterfactual outcomes for different hypothetical interventions on parental-feeding styles applied when children are 10-11 years (n = 4248). Results are presented as adjusted total association (Adj-Ta) between genetic liability (PGS-BMI) and BMI at 12 years, versus the interventional disparity measure-direct effect (IDM-DE), which represents the association that would remain, had we intervened on parental-feeding under different scenarios.

RESULTS

For children in the top quintile of genetic liability, an intervention shifting parental feeding to the levels of children with lowest genetic risk, resulted in a difference of 0.81 kg/m² in BMI at 12 years (Adj-Ta = 3.27, 95% CI: 3.04, 3.49; versus IDM-DE = 2.46, 95% CI: 2.24, 2.67).

CONCLUSIONS

Findings suggest that parental-feeding interventions have the potential to buffer some of the genetic liability for childhood obesity. Further, we highlight a novel way to analyze potential interventions for health conditions only using secondary data analyses, by combining methodology from statistical genetics and social epidemiology.

Effects of a physical activity intervention on schoolchildren fitness

The global prevalence of childhood obesity is high. Obesity main causes are linked to sedentary lifestyles. Increasing physical activity (PA) and reducing sedentary activities are recommended to prevent and treat obesity. This study aimed to evaluate the effectiveness of a 6-month school PA intervention on obesity prevention and healthy behaviors in school-aged children. Participating students (10-11 years of age) were randomly divided into an intervention group and a control group. Children in the intervention group (n = 80) participated in a multicomponent PA that included improvement in extracurricular physical activities (with an additional 40 min per day for 5/6 days per week). Children (n = 80) in the control group participated in usual practice. Participants had mean body mass index of 19.7 ± 2.9 kg/m2 , and 33.7% of them were overweight or with obesity at T0. The change in body mass index in intervention group (-2.4 ± 0.6 kg/m2 ) was significantly different from that in control group (3.01 ± 1.8 kg/m2 ). The effects on waist circumference, waist-to-height ratio, and physic fitness were also significant in intervention group compared with control group (all p < 0.05). Furthermore, there is a significant decrease in overweight or children with obesity in the experimental group (to 17.5%, p < 0.05). These findings suggest that a school-based intervention program represents an effective strategy for decreasing the number of overweight and children with obesity.

Findings from the Hispanic Community Health Study/Study of Latinos on the Importance of Sociocultural Environmental Interactors: Polygenic Risk Score-by-Immigration and Dietary Interactions

Introduction: Hispanic/Latinos experience a disproportionate burden of obesity. Acculturation to US obesogenic diet and practices may lead to an exacerbation of innate genetic susceptibility. We examined the role of gene-environment interactions to better characterize the sociocultural environmental determinants and their genome-scale interactions, which may contribute to missing heritability of obesity. We utilized polygenic risk scores (PRSs) for body mass index (BMI) to perform analyses of PRS-by-acculturation and other environmental interactors among self-identified Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods: PRSs were derived using genome-wide association study (GWAS) weights from a publicly available, large meta-analysis of European ancestry samples. Generalized linear models were run using a set of a priori acculturation-related and environmental factors measured at visit 1 (2008-2011) and visit 2 (2014-2016) in an analytic subsample of 8,109 unrelated individuals with genotypic, phenotypic, and complete case data at both visits. We evaluated continuous measures of BMI and waist-to-hip ratio. All models were weighted for complex sampling design, combined, and sex-stratified. Results: Overall, we observed a consistent increase of BMI with greater PRS across both visits. We found the best-fitting model adjusted for top five principal components of ancestry, sex, age, study site, Hispanic/Latino background genetic ancestry group, sociocultural factors and PRS interactions with age at immigration, years since first arrival to the United States (p < 0.0104), and healthy diet (p < 0.0036) and explained 16% of the variation in BMI. For every 1-SD increase in PRS, there was a corresponding 1.10 kg/m² increase in BMI (p < 0.001). When these results were stratified by sex, we observed that this 1-SD effect of PRS on BMI was greater for women than men (1.45 vs. 0.79 kg/m², p < 0.001). Discussion: We observe that age at immigration and the adoption of certain dietary patterns may play a significant role in modifying the effect of genetic risk on obesity. Careful consideration of sociocultural and immigration-related factors should be evaluated. The role of nongenetic factors, including the social environment, should not be overlooked when describing the performance of PRS or for promoting population health in understudied populations in genomics.

Relationships among Physical Self-Concept, Physical Activity and Mediterranean Diet in Adolescents from the Province of Granada

The aim of the present research was to analyse the relationships among physical self-concept, physical activity engagement and Mediterranean diet adherence in a sample of 1650 secondary school students from the province of Granada. The study design was descriptive-exploratory, cross-sectional and ex post facto. Measurements were taken from a single group. The PSQ, PAQ-A and KIDMED questionnaires were used to measure diet quality. Results showed the presence of a positive relationship among all dimensions of physical self-concept and physical activity engagement, with better outcomes being achieved in this self-perception with increasing engagement in sport. With regard to diet quality and its repercussions on physical self-concept, it was highlighted that the dimensions of the general self-concept, physical attractiveness and strength tended to be more positive as quality improved. In contrast, worse outcomes were produced in those with a low-quality diet. In this way, it was deemed necessary to continue investigating psychosocial factors with the aim of clarifying the relationships with psychological factors and health indicators. This would enable the development of prevention and intervention programs focused on promoting wellbeing in adolescents.

Personalized approach to childhood obesity: Lessons from gut microbiota and omics studies. Narrative review and insights from the 29th European childhood obesity congress

The traditional approach to childhood obesity prevention and treatment should fit most patients, but misdiagnosis and treatment failure could be observed in some cases that lie away from average as part of individual variation or misclassification. Here, we reflect on the contributions that high-throughput technologies such as next-generation sequencing, mass spectrometry-based metabolomics and microbiome analysis make towards a personalized medicine approach to childhood obesity. We hypothesize that diagnosing a child as someone with obesity captures only part of the phenotype; and that metabolomics, genomics, transcriptomics and analyses of the gut microbiome, could add precision to the term "obese," providing novel corresponding biomarkers. Identifying a cluster -omic signature in a given child can thus facilitate the development of personalized prognostic, diagnostic, and therapeutic approaches. It can also be applied to the monitoring of symptoms/signs evolution, treatment choices and efficacy, predisposition to drug-related side effects and potential relapse. This article is a narrative review of the literature and summary of the main observations, conclusions and perspectives raised during the annual meeting of the European Childhood Obesity Group. Authors discuss some recent advances and future perspectives on utilizing a systems approach to understanding and managing childhood obesity in the context of the existing omics data.