Relationship between self-reported dietary intake and physical activity levels among adolescents: The HELENA study

Background Evidence suggests possible synergetic effects of multiple lifestyle behaviors on health risks like obesity and other health outcomes. Therefore it is important to investigate associations between dietary and physical activity behavior, the two most important lifestyle behaviors influencing our energy balance and body composition. The objective of the present study is to describe the relationship between energy, nutrient and food intake and the physical activity level among a large group of European adolescents. Methods The study comprised a total of 2176 adolescents (46.2% male) from ten European cities participating in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. Dietary intake and physical activity were assessed using validated 24-h dietary recalls and self-reported questionnaires respectively. Analyses of covariance (ANCOVA) were used to compare the energy and nutrient intake and the food consumption between groups of adolescents with different physical activity levels (1st to 3rd tertile). Results In both sexes no differences were found in energy intake between the levels of physical activity. The most active males showed a higher intake of polysaccharides, protein, water and vitamin C and a lower intake of saccharides compared to less active males. Females with the highest physical activity level consumed more polysaccharides compared to their least active peers. Male and female adolescents with the highest physical activity levels, consumed more fruit and milk products and less cheese compared to the least active adolescents. The most active males showed higher intakes of vegetables and meat, fish, eggs, meat substitutes and vegetarian products compared to the least active ones. The least active males reported the highest consumption of grain products and potatoes. Within the female group, significantly lower intakes of bread and cereal products and spreads were found for those reporting to spend most time in moderate to vigorous physical activity. The consumption of foods from the remaining food groups, did not differ between the physical activity levels in both sexes. Conclusion It can be concluded that dietary habits diverge between adolescents with different self-reported physical activity levels. For some food groups a difference in intake could be found, which were reflected in differences in some nutrient intakes. It can also be concluded that physically active adolescents are not always inclined to eat healthier diets than their less active peers.The HELENA study took place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD-CT: 2005-007034). This work was also partially supported by the European Union, in the framework of the Public Health Programme (ALPHA project, Ref: 2006120), the Swedish Council for Working Life and Social Research (FAS), the Spanish Ministry of Education (EX-2007-1124, and EX-2008-0641), and the Spanish Ministry of Health, Maternal, Child Health and Development Network (number RD08/0072) (JPRL, LAM)

Les formes tardivesde la maladie d’Alzheimer : de la génétique à la biologie

A ce jour, quatre déterminants génétiques de la maladie d’Alzheimer ont été identifiés. Cependant, dans les formes tardives de cette maladie, survenant au-delà de 65 ans, le gène de l’apoli-poprotéine E constitue le seul facteur de susceptibilité génétique reconnu. Plusieurs hypothèses expliqueraient le risque conféré à l’allèle ε4 de ce gène en favorisant la formation des dépôts amyloïdes (une des caractéristiques neuropathologiques de la maladie), à travers ses liens avec le métabolisme des lipides ou bien par le développement d’une réponse inflammatoire. Afin d’identifier d’autres gènes de susceptibilité de cette maladie, des criblages génomiques ont été entrepris. Certaines régions chromosomiques ont été sélectionnées, notamment sur les chromosomes 12 et 10. Ces données récentes soulignent l’hétérogénéité génétique de la maladie d’Alzheimer et la difficulté d’identifier les autres gènes de susceptibilité de cette maladie multi-factorielle

Effects of established BMI-associated loci on obesity-related traits in a French representative population sample

International audienceBackgroundGenome-wide association studies have identified variants associated with obesity-related traits, such as the body mass index (BMI). We sought to determine how the combination of 31 validated, BMI-associated loci contributes to obesity- and diabetes-related traits in a French population sample. The MONA LISA Lille study (1578 participants, aged 35-74) constitutes a representative sample of the population living in Lille (northern France). Genetic variants were considered both individually and combined into a genetic predisposition score (GPS).ResultsIndividually, 25 of 31 SNPs showed directionally consistent effects on BMI. Four loci (FTO, FANCL, MTIF3 and NUDT3) reached nominal significance (p ≤ 0.05) for their association with anthropometric traits. When considering the combined effect of the 31 SNPs, each additional risk allele of the GPS was significantly associated with an increment in the mean [95% CI] BMI of 0.13 [0.07-0.20] kg/m2 (p = 6.3x10-5) and a 3% increase in the risk of obesity (p = 0.047). The GPS explained 1% of the variance in the BMI. Furthermore, the GPS was associated with higher fasting glycaemia (p = 0.04), insulinaemia (p = 0.008), HbA1c levels (p = 0.01) and HOMA-IR scores (p = 0.0003) and a greater risk of type 2 diabetes (OR [95% CI] = 1.06 [1.00-1.11], p = 0.03). However, these associations were no longer statistically significant after adjustment for BMI.ConclusionOur results show that the GPS was associated with a higher BMI and an insulin-resistant state (mediated by BMI) in a population in northern France

Dietary saturated fat, gender and genetic variation at the TCF7L2 locus predict the development of metabolic syndrome

International audienceTranscription factor 7-like 2 (TCF7L2) is the strongest genetic determinant of type 2 diabetes (TDM) and insulin-related phenotypes to date. Dietary fat is a key environmental factor which may interact with genotype to affect risk of metabolic syndrome (MetS) and T2DM. This study investigated the relationship between the TCF7L2 rs7903146 polymorphism, insulin sensitivity/resistance and MetS in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n=1754) and determined potential interactions with dietary fat intake. Female minor T allele carriers of rs7903146 had increased MetS risk (odds ratio [OR] 1.66, confidence interval [CI] 1.02-2.70, P=.04) and displayed elevated insulin concentrations (P=.005), impaired insulin sensitivity (P=.011), increased abdominal obesity (P=.008) and body mass index (P=.001) and higher blood pressure (P= 15.5% energy) exacerbated MetS risk (OR 2.35, 95% CI 1.29-4.27, P=.005) and was associated with further impaired insulin sensitivity in the T allele carriers relative to the CC homozygotes (P=.025) and particularly to the T allele carriers with the lowest SFA intake (P=.008). No significant genotype effect on MetS risk or insulin sensitivity was evident among low-SFA consumers. In conclusion, the TCF7L2 rs7903146 polymorphism influences MetS risk, which is augmented by both gender and dietary SFA intake, suggesting novel gene-diet-gender interactions. (C) 2012 Elsevier Inc. All rights reserved

Gene-nutrient interactions and gender may modulate the association between ApoA1 and ApoB gene polymorphisms and metabolic syndrome risk

International audienceObjective: Dyslipidemia is a key feature of the metabolic syndrome (MetS), which is determined by both genetic and dietary factors. Methods: We determined the relationships between ApoA1 and ApoB polymorphisms and MetS risk, and whether dietary fat modulates this in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1754). Results: ApoB rs512535 and ApoA1 rs670 major G allele homozygotes had increased MetS risk (OR 1.65 [CI 1.24, 2.20], P = 0.0006; OR 1.42 [CI 1.08, 1.87], P = 0.013), which may be, partly, explained by their increased abdominal obesity and impaired insulin sensitivity (P 35% energy) (ApoB rs512535 OR 2.00 [CI 1.14, 3.51], P = 0.015; OR 1.58 [CI 1.11, 2.25], P = 0.012 for ApoA1 rs670). In addition a high monounsaturated fat (MUFA) intake (>14% energy) increased MetS risk (OR 1.89 [CI 1.08, 3.30], P = 0.026 and OR 1.57 [CI 1.10, 2.40], P = 0.014 for ApoB rs512535 and ApoA1 rs670, respectively). MetS risk was abolished among the habitual low-fat consumers (<35% energy). Saturated and polyunsaturated fat intake did not modulate MetS risk. Conclusion: ApoB rs512535 and ApoA1 rs670 may influence MetS risk. Apparent modulation of these associations by gender and dietary fat composition suggests novel gene-gender-diet interactions. (C) 2010 Elsevier Ireland Ltd. All rights reserved

Plasma fatty acid composition patterns may provide predictive factors for metabolic syndrome: Preliminary results from LIPGENE-SU.VI.MAX study

National audienc

Association between angiopoietin-like 6 (ANGPTL6) gene polymorphisms and metabolic syndrome-related phenotypes in the French MONICA Study

AIM: Although the ANGPTL6 (angiopoietin-like 6) gene product is now known to be involved in the regulation of fat mass and insulin sensitivity in mice, its physiological functions in humans have yet to be determined. METHODS: Subjects from the population-based French MONICA Study (n=3402) were genotyped for single nucleotide polymorphisms (SNPs) in ANGPTL6, and associations with anthropometric or biochemical phenotypes were looked for. RESULTS: On evaluating the frequency of 17 ANGPTL6 SNPs in 100 randomly selected subjects on the basis of linkage disequilibrium mapping, four SNPs (rs6511435, rs8112063, rs11671983 and rs15723) were found to cover more than 95% of the known ANGPTL6 genetic variability. Subjects from the entire MONICA Study were then genotyped for these four SNPs. No significant association was detected for rs11671983 and rs15723. In contrast, the G allele of rs8112063 was associated with lower plasma glucose levels (P=0.009). Also, obese subjects carrying the G allele of rs6511435 had higher plasma insulin levels than AA subjects (P=0.0055). Moreover, the G allele of rs6511435 tended to be associated with a 20% higher risk of the metabolic syndrome (P=0.034). However, when false discovery rate testing (40 tests) was applied, these associations were no longer statistically significant. CONCLUSION: These findings constitute the first study in humans of ANGPTL6 genetic variability. Although there was no evidence that polymorphisms in ANGPTL6 might be significantly associated with the metabolic syndrome-related phenotypes, a weak association of these polymorphisms with these parameters cannot be excluded. Further association studies are needed to arrive at any definite conclusions

Bayesian Network Analysis of plasma microRNA sequencing data in patients with venous thrombosis

International audienceMicroRNAs (miRNAs) are small regulatory RNAs participating to several biological processes and known to be involved in various pathologies. Measurable in body fluids, miRNAs have been proposed to serve as efficient biomarkers for diseases and/or associated traits. We here performed a next-generation-sequencing based profiling of plasma miRNAs in 344 patients with venous thrombosis (VT) and assessed the association of plasma miRNA levels with several haemostatic traits and the risk of VT recurrence. Among the most significant findings, we detected an association between hsa-miR-199b-3p and hematocrit 2 levels (p = 0.0016), these two markers having both been independently reported to associate with VT risk. We also observed suggestive evidence for association of hsa-miR-370-3p (p = 0.019), hsa-miR-27b-3p (p = 0.016) and hsa-miR-222-3p (p = 0.049) with VT recurrence, the observations at the latter two miRNAs confirming the recent findings of Wang et al. (Clin Epigenetics 2019). Besides, by conducting Genome Wide Association Studies on miRNA levels and meta-analyzing our results with some publicly available, we identified 21 new associations of SNP with plasma miRNA levels at the statistical significance threshold of p < 5 × 10-8 , some of these associations pertaining to thrombosis associated mechanisms. In conclusion, this study provides novel data about the impact of miRNAs' variability in haemostasis and new arguments supporting the association of few miRNAs with the risk of recurrence in patients with venous thrombosis

Explainable Artificial Neural Network for Recurrent Venous Thromboembolism Based on Plasma Proteomics

Venous thromboembolism (VTE) is the third most common cardiovascular disease, affecting ∼ 1,000,000 individuals each year in Europe. VTE is characterized by an annual recurrent rate of ∼ 6%, and ∼ 30% of patients with unprovoked VTE will face a recurrent event after a six-month course of anticoagulant treatment. Even if guidelines recommend life-long treatment for these patients, about ∼ 70% of them will never experience a recurrence and will receive unnecessary lifelong anti-coagulation that is associated with increased risk of bleeding and is highly costly for the society. There is then urgent need to identify biomarkers that could distinguish VTE patients with high risk of recurrence from low-risk patients. Capitalizing on a sample of 913 patients followed up for the risk of VTE recurrence during a median of ∼ 10 years and profiled for 376 plasma proteomic antibodies, we here develop an artificial neural network (ANN) based strategy to identify a proteomic signature that helps discriminating patients at low and high risk of recurrence. In a first stage, we implemented a Repeated Editing Nearest Neighbors algorithm to select a homogeneous sub-sample of VTE patients. This sub-sample was then split in a training and a testing sets. The former was used for training our ANN, the latter for testing its discriminatory properties. In the testing dataset, our ANN led to an accuracy of 0.86 that compared to an accuracy of 0.79 as provided by a random forest classifier. We then applied a Deep Learning Important FeaTures (DeepLIFT) – based approach to identify the variables that contribute the most to the ANN predictions. In addition to sex, the proposed DeepLIFT strategy identified 6 important proteins (DDX1, HTRA3, LRG1, MAST2, NFATC4 and STXBP5) whose exact roles in the etiology of VTE recurrence now deserve further experimental validations. © 2021, Springer Nature Switzerland AG