Transcriptome analysis in blood cells from children reveals potential early biomarkers of metabolic alterations

OBJECTIVES: The development of effective strategies to prevent childhood obesity and its comorbidities requires new, reliable early biomarkers. Here, we aimed to identify in peripheral blood cells potential transcript-based biomarkers of unhealthy metabolic profile associated to overweight/obesity in children. METHODS: We performed a whole-genome microarray analysis in blood cells to identify genes differentially expressed between overweight and normal weight children to obtain novel transcript-based biomarkers predictive of metabolic complications. RESULTS: The most significant enriched pathway of differentially expressed genes was related to oxidative phosphorylation, for which most of genes were downregulated in overweight versus normal weight children. Other genes were involved in carbohydrate metabolism/glucose homoeostasis or in lipid metabolism (for example, TCF7L2, ADRB3, LIPE, GIPR), revealing plausible mechanisms according to existing biological knowledge. A set of differentially expressed genes was identified to discriminate in overweight children those with high or low triglyceride levels. CONCLUSIONS: Functional microarray analysis has revealed a set of potential blood-cell transcript-based biomarkers that may be a useful approach for early identification of children with higher predisposition to obesity-related metabolic alterations

Longitudinal association of inflammatory markers with markers of glycaemia and insulin resistance in European children

Purpose: Subclinical systemic inflammation may lead to development of type 2 diabetes, but there has been no investigation into its relationship with early progression of glycaemic deterioration and insulin resistance, especially in younger population. In this study we assessed longitudinal associations of pro- and anti-inflammatory markers with markers that evaluate glycaemia and insulin resistance. Methods: This study includes 6537 initially nondiabetic children (mean age at baseline = 6.2 years) with repeated measurements from the IDEFICS/I.Family cohort study (mean follow-up = 5.3 years) from eight European countries. Markers of inflammation were used as independent variables and markers of glycaemia/insulin resistance as dependent variables. Associations were examined using two-level growth model. Models were adjusted for sex, age, major lifestyle, metabolic risk factors, early life markers, and other inflammatory markers in final model. Results: Children with 6 years of follow-up showed that a one-unit increase in z-score of leptin level was associated with 0.38 (95% CI = 0.32 to 0.44) unit increase in HOMA-IR z-scores. Leptin continued to be associated with HOMA-IR even when analysis was limited to children with no overall obesity, no abdominal obesity, and low to normal triglyceride levels. An inverse association was observed between IL-15 and HOMA-IR (ß = -0.11, 95% CI = -0.15 to -0.07). Conclusions: IL-15 should be evaluated further in the prevention or treatment of prediabetes whereas leptin may prove to be useful in early detection of prediabetes via their association with markers of insulin resistance in European children

Neural networks for modeling gene-gene interactions in association studies

<p>Abstract</p> <p>Background</p> <p>Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence, one is a multiplicative model, and three models are epistatic. For each data set, six neural networks (with up to five hidden neurons) and five logistic regression models (the null model, three main effect models, and the full model) with two different codings for the genotype information are fitted. Additionally, the multifactor dimensionality reduction approach is applied.</p> <p>Results</p> <p>The results show that neural networks are more successful in modeling the structure of the underlying disease model than logistic regression models in most of the investigated situations. In our simulation study, neither logistic regression nor multifactor dimensionality reduction are able to correctly identify biological interaction.</p> <p>Conclusions</p> <p>Neural networks are a promising tool to handle complex data situations. However, further research is necessary concerning the interpretation of their parameters.</p

Behavioural Susceptibility Theory: Professor Jane Wardle and the Role of Appetite in Genetic Risk of Obesity

Purpose of Review: There is considerable variability in human body weight, despite the ubiquity of the 'obesogenic' environment. Human body weight has a strong genetic basis and it has been hypothesised that genetic susceptibility to the environment explains variation in human body weight, with differences in appetite being implicated as the mediating mechanism; so-called 'behavioural susceptibility theory' (BST), first described by Professor Jane Wardle. This review summarises the evidence for the role of appetite as a mediator of genetic risk of obesity. Recent Findings: Variation in appetitive traits is observable from infancy, drives early weight gain and is highly heritable in infancy and childhood. Obesity-related common genetic variants identified through genome-wide association studies show associations with appetitive traits, and appetite mediates part of the observed association between genetic risk and adiposity. Summary: Obesity results from an interaction between genetic susceptibility to overeating and exposure to an 'obesogenic' food environment

Reference values of whole-blood fatty acids by age and sex from European children aged 3-8 years

OBJECTIVES: To establish reference values for fatty acids (FA) especially for n-3 and n-6 long-chain polyunsaturated FAs (LC PUFA) in whole-blood samples from apparently healthy 3-8-year-old European children. The whole-blood FA composition was analysed and the age-and sex-specific distribution of FA was determined. DESIGN AND SUBJECTS: Blood samples for FA analysis were taken from 2661 children of the IDEFICS (identification and prevention of dietary-and lifestyle-induced health effects in children and infants) study cohort. Children with obesity (n = 454) and other diseases that are known to alter the FA composition (n = 450) were excluded leaving 1653 participants in the reference population. MEASUREMENTS: The FA composition of whole blood was analysed from blood drops by a rapid, validated gas chromatographic method. RESULTS: Pearson correlation coefficients showed an age-dependent increase of C18:2n-6 and a decrease of C18:1n-9 in a subsample of normal weight boys and girls. Other significant correlations with age were weak and only seen either in boys or in girls, whereas most of the FA did not show any age dependence. For age-dependent n-3 and n-6 PUFA as well as for other FA that are correlated with age (16:0, C18:0 and C18:1n-9) percentiles analysed with the general additive model for location scale and shape are presented. A higher median in boys than in girls was observed for C20:3n-6, C20:4n-6 and C22:4n-6. CONCLUSIONS: Given the reported associations between FA status and health-related outcome, the provision of FA reference ranges may be useful for the interpretation of the FA status of children in epidemiological and clinical studies

Variation in the Heritability of Child Body Mass Index by Obesogenic Home Environment

Importance: The early obesogenic home environment is consistently identified as a key influence on child weight trajectories, but little research has examined the mechanisms of that influence. Such research is essential for the effective prevention and treatment of overweight and obesity. Objective: To test behavioral susceptibility theory’s hypothesis that the heritability of body mass index (BMI) is higher among children who live in more obesogenic home environments. Design, Setting, and Participants: This study was a gene-environment interaction twin study that used cross-sectional data from 925 families (1850 twins) in the Gemini cohort (a population-based prospective cohort of twins born in England and Wales between March and December 2007). Data were analyzed from July to October 2013 and in June 2018. Exposures: Parents completed the Home Environment Interview, a comprehensive measure of the obesogenic home environment in early childhood. Three standardized composite scores were created to capture food, physical activity, and media-related influences in the home; these were summed to create an overall obesogenic risk score. The 4 composite scores were split on the mean, reflecting higher-risk and lower-risk home environments. Main Outcomes and Measures: Quantitative genetic model fitting was used to estimate heritability of age-adjusted and sex-adjusted BMI (BMI SD score, estimated using British 1990 growth reference data) for children living in lower-risk and higher-risk home environments. Results: Among 1850 twins (915 [49.5%] male and 935 [50.5%] female; mean [SD] age, 4.1 [0.4] years), the heritability of BMI SD score was significantly higher among children living in overall higher-risk home environments (86%; 95% CI, 68%-89%) compared with those living in overall lower-risk home environments (39%; 95% CI, 21%-57%). The findings were similar when examining the heritability of BMI in the separate food and physical activity environment domains. Conclusions and Relevance: These findings support the hypothesis that obesity-related genes are more strongly associated with BMI in more obesogenic home environments. Modifying the early home environment to prevent weight gain may be particularly important for children genetically at risk for obesity

The Generation R Study: design and cohort update 2010

The Generation R Study is a population-based prospective cohort study from fetal life until young adulthood. The study is designed to identify early environmental and genetic causes of normal and abnormal growth, development and health during fetal life, childhood and adulthood. The study focuses on four primary areas of research: (1) growth and physical development; (2) behavioural and cognitive development; (3) diseases in childhood; and (4) health and healthcare for pregnant women and children. In total, 9,778 mothers with a delivery date from April 2002 until January 2006 were enrolled in the study. General follow-up rates until the age of 4 years exceed 75%. Data collection in mothers, fathers and preschool children included questionnaires, detailed physical and ultrasound examinations, behavioural observations, and biological samples. A genome wide association screen is available in the participating children. Regular detailed hands on assessment are performed from the age of 5 years onwards. Eventually, results forthcoming from the Generation R Study have to contribute to the development of strategies for optimizing health and healthcare for pregnant women and children