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BACKGROUND Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity. OBJECTIVE This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for body mass index (BMI) and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity. METHODS This cross-sectional study included 750 participants (56.3% women, age 41.5 ± 14.9 years, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on > 500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-day food record from which a diet quality score (i.e., Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach. RESULTS : The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64) and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC. CONCLUSIONS The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.

Background and aim Circulating level of glutamate, a by-product of the catabolism of branched-chain amino acids, has been positively correlated with visceral adipose tissue accumulation and waist circumference (WC). The aim of the present study was to assess the potential of using glutamate level to identify individuals with abdominal obesity and a high cardiometabolic risk. Methods and results The study sample included 99 men and 99 women. Fasting serum glutamate was measured using the Biocrates p180 kit. Anthropometric and metabolic variables were used to identify individuals with abdominal obesity (WC ≥ 95 cm in both sexes), the hypertriglyceridemic waist (HTW) phenotype and the metabolic syndrome (MetS). Mean (±SD) age was 34.1 ± 10.1 years, mean BMI was 29.0 ± 6.2 kg/m2 and mean WC was 92.7 ± 16.5 cm. Glutamate was strongly correlated with WC (r = 0.66 for men; r = 0.76 for women, both p Conclusion Glutamate level may represent an interesting potential biomarker of abdominal obesity and metabolic risk.

Introduction: Carotenoids, which are a reliable biomarker of fruit and vegetable consumption, are positively associated with the lipid profile. Circulating carotenoid concentrations may interact with several omics profiles including genome, transcriptome, and epigenome. Few studies have used multi-omics approaches, and they rarely include environmental factors, such as diet. Objective: The objective of this observational study was to examine the potential role of multi-omics data in the interconnection between diet, represented by total carotenoids, and lipid profile using weighted gene correlation network analysis (WGCNA). Methods: Blood leukocyte DNA methylation levels of 472,245 CpG sites and whole blood gene expression levels of 18,160 transcripts were tested for associations with total carotenoid concentrations using regressions in 48 healthy subjects. WGCNA was used to identify co-omics modules and hub genes related to the lipid profile. Results: Among genes associated with total carotenoid concentrations, a total of 236 genes were identified at both DNA methylation and gene expression levels. Using WGCNA, six modules, consisting of groups of highly correlated genes represented by colors, were identified and linked to the lipid profile. Probes clustered in the turquoise and green modules correlated with plasma lipid concentrations. A total of 28 hub genes were identified. Conclusions: Genome-wide DNA methylation and gene expression levels were both associated with plasma total carotenoid concentrations. Several hub genes, mostly involved in lipid metabolism and inflammatory response with several genetic variants associated with plasma lipid concentrations, came out of the integrative analysis. This provides a comprehensive understanding of the interactive molecular system between carotenoids, omics, and plasma lipid profile.

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10(−6)) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.

Background Considering the implication of gene expression in the susceptibility of chronic diseases and the familial clustering of chronic diseases, the study of familial resemblances in gene expression levels is then highly relevant. Few studies have considered the contribution of both genetic and common environmental effects to familial resemblances in whole blood gene expression levels. The objective is to quantify the contribution of genetic and common environmental effects in the familial resemblances of whole blood genome-wide gene expression levels. We also make comparisons with familial resemblances in blood leukocytes genome-wide DNA methylation levels in the same cohort in order to further investigate biological mechanisms. Results Maximal heritability, genetic heritability, and common environmental effect were computed for all probes (20.6%, 15.6%, and 5.0% respectively) and for probes showing a significant familial effect (78.1%, 60.1%, and 18.0% respectively). Pairwise phenotypic correlations between gene expression and DNA methylation levels adjusted for blood cell heterogeneity were computed for probes showing significant familial effect. A total of 78 probe pairs among the 7,618,401 possible pairs passed Bonferroni correction (corrected P-value = 6.56 × 10− 9). Significant genetic correlations between gene expression and DNA methylation levels were found for 25 probe pairs (absolute genetic correlation of 0.97). Conclusions Familial resemblances in gene expression levels were mainly attributable to genetic factors, but common environmental effect also played a role especially in probes showing a significant familial effect. Probes and CpG sites with familial effect seem to be under a strong shared genetic control. Electronic supplementary material The online version of this article (10.1186/s12864-018-4698-6) contains supplementary material, which is available to authorized users.

Variability in plasma carotenoids may be attributable to several factors including genetic variants and lipid profile. Until now, the impact of DNA methylation on this variability has not been widely studied. Weighted gene correlation network analysis (WGCNA) is a systems biology method used for finding gene clusters (modules) with highly correlated methylation levels and for relating them to phenotypic traits. The objective of the present study was to examine the role of DNA methylation in the relationship between plasma total carotenoid concentrations and lipid profile using WGCNA in 48 healthy subjects. Genome-wide DNA methylation levels of 20,687 out of 472,245 CpG sites in blood leukocytes were associated with total carotenoid concentrations. Using WGCNA, nine co-methylation modules were identified. A total of 2734 hub genes (17 unique top hub genes) were potentially related to lipid profile. This study provides evidence for the potential implications of gene co-methylation in the relationship between plasma carotenoids and lipid profile. Further studies and validation of the hub genes are needed.

Epigenetic factors such as DNA methylation are DNA alterations affecting gene expression that can convey environmental information through generations. Only a few studies have demonstrated epigenetic inheritance in humans. Our objective is to quantify genetic and common environmental determinants of familial resemblances in DNA methylation levels, using a family based sample. DNA methylation was measured in 48 French Canadians from 16 families as part of the GENERATION Study. We used the Illumina HumanMethylation450 BeadChip array to measure DNA methylation levels in blood leukocytes on 485,577 CpG sites. Heritability was assessed using the variance components method implemented in the QTDT software, which partitions the variance into polygenic (G), common environmental (C), and non-shared environmental (E) effects. We computed maximal heritability, genetic heritability, and common environmental effect for all probes (12.7%, 8.2%, and 4.5%, respectively) and for statistically significant probes (81.8%, 26.9%, and 54.9%, respectively). Higher maximal heritability was observed in the Major Histocompatibility Complex region on chromosome 6. In conclusion, familial resemblances in DNA methylation levels are mainly attributable to genetic factors when considering the average across the genome, but common environmental effect plays an important role when considering statistically significant probes. Further epigenome-wide studies on larger samples combined with genome-wide genotyping studies are needed to better understand the underlying mechanisms of DNA methylation heritability.

BACKGROUND The extent of weight loss among patients undergoing bariatric surgery is highly variable. Herein, we tested the contribution of genetic background to such interindividual variability after biliopancreatic diversion with duodenal switch. METHODS Percentage of excess body weight loss (%EBWL) was monitored in 865 patients over a period of 48 months after bariatric surgery, and two polygenic risk scores were constructed with 186 and 11 (PRS186 and PRS11) single nucleotide polymorphisms previously associated with body mass index (BMI). RESULTS The accuracy of the %EBWL logistic prediction model - including initial BMI, age, sex, and surgery modality, and assessed as the area under the receiver operating characteristics (ROC) curve adjusted for optimism (AUCadj = 0.867) - significantly increased after the inclusion of PRS186 (ΔAUCadj = 0.021; 95% CI of the difference [95% CIdiff] = 0.005-0.038) but not PRS11 (ΔAUCadj= 0.008; 95% CIdiff= -0.003-0.019). The overall fit of the longitudinal linear mixed model for %EBWL showed a significant increase after addition of PRS186 (-2 log-likelihood = 12.3; P = 0.002) and PRS11 (-2 log-likelihood = 9.9; P = 0.007). A significant interaction with postsurgery time was found for PRS186 (β = -0.003; P = 0.008) and PRS11 (β = -0.008; P = 0.03). The inclusion of PRS186 and PRS11 in the model improved the cost-effectiveness of bariatric surgery by reducing the percentage of false negatives from 20.4% to 10.9% and 10.2%, respectively. CONCLUSION These results revealed that genetic background has a significant impact on weight loss after biliopancreatic diversion with duodenal switch. Likewise, the improvement in weight loss prediction after addition of polygenic risk scores is cost-effective, suggesting that genetic testing could potentially be used in the presurgical assessment of patients with severe obesity. FUNDING Heart and Stroke Foundation of Canada (G-17-0016627) and Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health (no. 950-231-580).

Carotenoids have shown an interindividual variability that may be due to genetic factors. The only study that has reported heritability of serum &alpha, and &beta, carotene has not considered the environmental component. This study aimed to estimate the contribution of both genetic and common environmental effects to the variance of carotenoid concentrations and to test whether their phenotypic correlations with cardiometabolic risk factors are explained by shared genetic and environmental effects. Plasma carotenoid concentrations (&alpha, carotene, &beta, cryptoxanthin, lutein, lycopene, zeaxanthin, and total carotenoids) of 48 healthy subjects were measured. Heritability estimates of carotenoid concentrations were calculated using the variance component method. Lutein and lycopene showed a significant familial effect (p = 6 &times, 10&minus, 6 and 0.0043, respectively). Maximal heritability, genetic heritability, and common environmental effect were computed for lutein (88.3%, 43.8%, and 44.5%, respectively) and lycopene (45.2%, 0%, and 45.2%, respectively). Significant phenotypic correlations between carotenoid concentrations and cardiometabolic risk factors were obtained for &beta, cryptoxanthin, lycopene, and zeaxanthin. Familial resemblances in lycopene concentrations were mainly attributable to common environmental effects, while for lutein concentrations they were attributable to genetic and common environmental effects. Common genetic and environmental factors may influence carotenoids and cardiometabolic risk factors, but further studies are needed to better understand the potential impact on disease development.

Evidence suggests that industrial trans fatty acids (iTFA) impair lipid profiles while ruminant trans fatty acids (rTFA) may lower insulin resistance and blood pressure. The objective of this article was to determine if the plasma phospholipid percentage of rTFA is associated with a favorable cardiometabolic profile. We collected fasting blood samples from 200 individuals from Quebec city (QC, Canada) aged from 18 to 55 years old, including 100 obese (BMI ≥ 30 kg m(-2)) and 100 non-obese (BMI30 kg m(-2)) men and women. Fatty acid levels in plasma phospholipids were determined using gas chromatography. After separating the subjects into two groups, according to the median percentage of rTFA in plasma phospholipids, participants in the group with higher percentages of rTFA (0.86 ± 0.24 %) had higher adiponectin levels (p = 0.01) and a lower blood pressure (systolic, p = 0.005; diastolic, p = 0.04). In contrast, concentrations in plasma phospholipids of elaidic acid, a major iTFA, are positively correlated with glycemia in non-obese subjects (p = 0.01) and with both triacylglycerol (TAG) (p = 0.0007) and total cholesterol (TC) (p = 0.009) in obese subjects. These data suggest that rTFA may have beneficial effects on cardiometabolic risk factors conversely to their counterpart iTFA. Dietary sources of TFA should be taken into account in future cardiometabolic studies.

Metabolites are of great importance for understanding the pathogenesis of several diseases. Understanding the genetic contribution to metabolite concentrations may provide insights into mechanisms of complex diseases. Several studies have investigated heritability of metabolites but none investigated potential influences of genetic and environmental factors on the relationship between metabolites and cardiometabolic (CM) risk factors. Thus, we tested the hypothesis that both genetic and common environmental effects contribute to the variance of plasma metabolite concentrations and that shared genetic and environmental effects explain their phenotypic correlations with CM risk factors. To test this hypothesis, variance component method and bivariate genetic analysis were performed in a family-based sample of 48 French Canadians from 16 families. Familial resemblances were computed for all 147 detected metabolites and 9 (acetylornithine, acylcarnitine C9, arginine, phosphatidylcholine acyl-alkyl C36:4, serotonin, lysophosphatidylcholine acyl C20:4, citrulline, asymmetric dimethylarginine, phosphatidylcholine acyl-alkyl C36:5) showed a significant familial effect (55.7%, 18.7%, and 37.0% for maximal heritability, genetic heritability, and common environmental effect, respectively). Citrulline, phosphatidylcholine acyl-alkyl C36:4, phosphatidylcholine acyl-alkyl C36:5, and serotonin had significant phenotypic correlations with CM risk factors. Citrulline had a positive genetic correlation with apolipoprotein B100, while phosphatidylcholine acyl-alkyl C36:5 had a positive environmental correlation with total cholesterol. In conclusion, familial resemblances in metabolite concentrations were mainly attributable to common environmental effect when considering metabolites with a significant familial effect. Common genetic and environmental factors may also influence the relationship between metabolites and CM risk factors.

To examine whether yogurt consumption is associated with a healthier dietary pattern and with a better cardio-metabolic risk profile among healthy individuals classified on the basis of their body mass index (BMI).A 91-item food frequency questionnaire, including data on yogurt consumption, was administered to 664 subjects from the INFOGENE study. After principal component analysis, two factors were retained, thus classified as the Prudent and Western dietary patterns.Yogurt was a significant contributor to the Prudent dietary pattern. Moreover, yogurt consumption was associated with lower body weight, waist-to-hip ratio, and waist circumference and tended to be associated with a lower BMI. Consumers had lower levels of fasting total cholesterol and insulin. Consumers of yogurt had a positive Prudent dietary pattern mean score, while the opposite trend was observed in non-consumers of yogurt. Overweight/obese individuals who were consumers of yogurts exhibited a more favorable cardio-metabolic profile characterized by lower plasma triglyceride and insulin levels than non-consumers within the same range of BMI. There was no difference in total yogurt consumption between normal-weight individuals and overweight/obese individuals. However, normal-weight subjects had more daily servings of high-fat yogurt and less daily servings of fat-free yogurt compared to overweight/obese individuals.Being a significant contributor to the Prudent dietary pattern, yogurt consumption may be associated with healthy eating. Also, yogurt consumption may be associated with lower anthropometric indicators and a more beneficial cardio-metabolic risk profile in overweight/obese individuals.

Excessive activation of complement is associated with many diseases including schizophrenia. Investigation of C3 polymorphisms, circulating C3, cleavage product ASP/C3adesArg, and lipid metabolism. Cross-sectional analysis. C3 genotyping (CC vs GG for R102L) was performed on 434 Tunisian people consisting of 272 schizophrenic (SZ) patients and 162 control subjects. In a age- and gender-matched subgroups of the three genotypes (131 SZ and 112 NOR), plasma triglycerides, total cholesterol (C), LDL-C, HDL-C, ASP, and complement C3 were measured. C3 gene polymorphism influences BMI and plasma C3, ASP, triglyceride, total cholesterol, LDL-C and HDL-C among SZ patients (p0.05-0.0001), with increasing values demonstrated from CC (common form) to CG (heterozygote form) to GG (rare homozygote) forms. Significant correlations between plasma C3 and BMI, triglyceride, HDL-C and ASP (p0.05-0.0001) were observed, while ASP correlated with BMI and LDL-C (p = 0.005, p = 0.001, respectively) in SZ patients. Further, proportional conversion of C3 to ASP (%ASP/C3) also increased (p0.0001, GGCGCC). C3 polymorphisms and plasma C3, ASP and %ASP/C3 correlated with lipid parameters in this SZ population, suggesting that factors predisposing patients to schizophrenia are permissive for complement pathway activation and dyslipidemic influences.

The concern about the current epidemic of obesity is heightened by recent data showing an increase in the prevalence of overweight and obesity in children and adolescents. As obese children are at increased risk of becoming obese adults, early identification of individuals at risk of becoming obese is important for the implementation of preventive measures. In that context, it is important to assess the role of genetic and nongenetic factors in childhood obesity as well as in susceptibility to dietary variations. This paper reviews recent data regarding the prevalence of obesity in childhood as well as the role of genetic factors in phenotypes related to obesity, with emphasis on studies conducted on children, when available. The existence of severe cases of obesity, such as those encountered in Mendelian syndromes of obesity or those caused by mutations in single genes, provides strong evidence for a role of genetic factors in the aetiology of childhood obesity. Furthermore, results from family studies suggest that the maximal heritability of obesity phenotypes ranges from about 30% to 50% and that the major affectors of body fat content, energy intake and energy expenditure are also influenced by genetic factors. Finally, there is increasing evidence that responsiveness to dietary intervention is genetically determined.

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10-105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10-107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10-16), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10-9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 × 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 × 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery., The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (102318; 104781, 120315, 123885, 129619, 286284, 134309, 126925, 121584, 124282, 129378, 117787, 250207, 258753, 41071, 77299, 124243, 1114194, 24300796); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la Recherche; Agency for Health Care Policy Research (HS06516); Age UK Research into Ageing Fund; Åke Wiberg Foundation; ALF/LUA Research Grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S (Hørsholm, Denmark); American Heart Association (13POST16500011, 10SDG269004); Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; AstraZeneca; Australian Associated Brewers; Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498); Avera Research Institute; Bayer Diagnostics; Becton Dickinson; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007); Biocentrum Helsinki; Boston Obesity Nutrition Research Center (DK46200); British Heart Foundation (RG/10/12/28456, SP/04/002); Canada Foundation for Innovation; Canadian Institutes of Health Research (FRN-CCT-83028); Cancer Research UK; Cardionics; Center for Medical Systems Biology; Center of Excellence in Complex Disease Genetics and SALVECenter of Excellence in Genomics (EXCEGEN); Chief Scientist Office of the Scottish Government; City of Kuopio; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF–1333-00124, DFF–1331-007308); Danish Diabetes Academy; Danish Medical Research Council; Department of Psychology and Education of the VU University Amsterdam; Diabetes Hilfs- und Forschungsfonds Deutschland; Dutch Brain Foundation; Dutch Ministry of Justice; Emil Aaltonen Foundation; Erasmus Medical Center; Erasmus University; Estonian Government (IUT20-60, IUT24-6); Estonian Ministry of Education and Research (3.2.0304.11-0312); European Commission (230374, 284167, 323195, 692145, FP7 EurHEALTHAgeing-277849, FP7 BBMRI-LPC 313010, nr 602633, HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, FP6 LSHM-CT-2004-005272, FP5 QLG2-CT-2002-01254, FP6 LSHG-CT-2006-01947, FP7 HEALTH-F4-2007-201413, FP7 279143, FP7 201668, FP7 305739, FP6 LSHG-CT-2006-018947, HEALTH-F4-2007-201413, QLG1-CT-2001-01252); European Regional Development Fund; European Science Foundation (EuroSTRESS project FP-006, ESF, EU/QLRT-2001-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, 01ZZ0403, 03ZIK012, 03IS2061A); Federal State of Mecklenburg - West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Food Standards Agency; Fondation de France; Fonds Santé; Genetic Association Information Network of the Foundation for the National Institutes of Health; German Diabetes Association; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); German Research Council (SFB-1052, SPP 1629 TO 718/2-1); GlaxoSmithKline; Göran Gustafssons Foundation; Göteborg Medical Society; Health and Safety Executive; Heart Foundation of Northern Sweden; Icelandic Heart Association; Icelandic Parliament; Imperial College Healthcare NHS Trust; INSERM, Réseaux en Santé Publique, Interactions entre les déterminants de la santé; Interreg IV Oberrhein Program (A28); Italian Ministry of Economy and Finance; Italian Ministry of Health (ICS110.1/RF97.71); John D and Catherine T MacArthur Foundation; Juho Vainio Foundation; King's College London; Kjell och Märta Beijers Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); Leiden University Medical Center; Lilly; LMUinnovativ; Lundbeck Foundation; Lundberg Foundation; Medical Research Council of Canada; MEKOS Laboratories (Denmark); Merck Santé; Mid-Atlantic Nutrition Obesity Research Center (P30 DK72488); Ministère de l’Économie, de l’Innovation et des Exportations; Ministry for Health, Welfare and Sports of the Netherlands; Ministry of Cultural Affairs of the Federal State of Mecklenburg-West Pomerania; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science of the Netherlands; MRC Human Genetics Unit; MRC-GlaxoSmithKline Pilot Programme Grant (G0701863); Municipality of Rotterdam; Netherlands Bioinformatics Centre (2008.024); Netherlands Consortium for Healthy Aging (050-060-810); Netherlands Genomics Initiative; Netherlands Organisation for Health Research and Development (904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192); Netherlands Organisation for Health Research and Development (2010/31471/ZONMW); Netherlands Organisation for Scientific Research (10-000-1002, GB-MW 940-38-011, 100-001-004, 60-60600-97-118, 261-98-710, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MaGW 452-04-314, GB-MaGW 452-06-004, 175.010.2003.005, 175.010.2005.011, 481-08-013, 480-05-003, 911-03-012); Neuroscience Campus Amsterdam; NHS Foundation Trust; Novartis Pharmaceuticals; Novo Nordisk; Office National Interprofessionel des Vins; Paavo Nurmi Foundation; Påhlssons Foundation; Päivikki and Sakari Sohlberg Foundation; Pierre Fabre; Republic of Croatia Ministry of Science, Education and Sport (108-1080315-0302); Research Centre for Prevention and Health, the Capital Region for Denmark; Research Institute for Diseases in the Elderly (014-93-015, RIDE2); Roche; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Executive Health Department (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du Diabète; State of Bavaria; Stroke Association; Swedish Diabetes Association; Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20140543); Swedish Research Council (2015-03657); Swedish Medical Research Council (K2007-66X-20270-01-3, 2011-2354); Swedish Society for Medical Research; Swiss National Science Foundation (33CSCO-122661, 33CS30-139468, 33CS30-148401); Tampere Tuberculosis Foundation; The Marcus Borgström Foundation; The Royal Society; The Wellcome Trust (084723/Z/08/Z, 088869/B/09/Z); Timber Merchant Vilhelm Bangs Foundation; Topcon; Torsten and Ragnar Söderberg's Foundation; UK Department of Health; UK Diabetes Association; UK Medical Research Council (MC_U106179471, G0500539, G0600705, G0601966, G0700931, G1002319, K013351, MC_UU_12019/1); UK National Institute for Health Research BioResource Clinical Research Facility and Biomedical Research Centre; UK National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre; UK National Institute for Health Research (RP-PG-0407-10371); Umeå University Career Development Award; United States – Israel Binational Science Foundation Grant (2011036); University Hospital Oulu (75617); University Medical Center Groningen; University of Tartu (SP1GVARENG); National Institutes of Health (AG13196, CA047988, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSC271201100004C, HHSN268200900041C, HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268201500001I, HL36310, HG002651, HL034594, HL054457, HL054481, HL071981, HL084729, HL119443, HL126024, N01-AG12100, N01-AG12109, N01-HC25195, N01-HC55015, N01-HC55016, N01-HC55018, N01-HC55019, N01-HC55020, N01-HC55021, N01-HC55022, N01-HD95159, N01-HD95160, N01-HD95161, N01-HD95162, N01-HD95163, N01-HD95164, N01-HD95165, N01-HD95166, N01-HD95167, N01-HD95168, N01-HD95169, N01-HG65403, N02-HL64278, R01-HD057194, R01-HL087641, R01-HL59367, R01HL-086694, R01-HL088451, R24-HD050924, U01-HG-004402, HHSN268200625226C, UL1-RR025005, UL1-RR025005, UL1-TR-001079, UL1-TR-00040, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, DA12854, MH081802, MH66206, R01-D004215701A, R01-DK075787, R01-DK089256, R01-DK8925601, R01-HL088451, R01-HL117078, R01-DK062370, R01-DK072193, DK091718, DK100383, DK078616, 1Z01-HG000024, HL087660, HL100245, R01DK089256, 2T32HL007055-36, U01-HL072515-06, U01-HL84756, NIA-U01AG009740, RC2-AG036495, RC4-AG039029, R03 AG046389, 263-MA-410953, 263-MD-9164, 263-MD-821336, U01-HG004802, R37CA54281, R01CA63, P01CA33619, U01-CA136792, U01-CA98758, RC2-MH089951, MH085520, R01-D0042157-01A, MH081802, 1RC2-MH089951, 1RC2-MH089995, 1RL1MH08326801, U01-HG007376, 5R01-HL08767902, 5R01MH63706:02, HG004790, N01-WH22110, U01-HG007033, UM1CA182913, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, 44221); USDA National Institute of Food and Agriculture (2007-35205-17883); Västra Götaland Foundation; Velux Foundation; Veterans Affairs (1 IK2 BX001823); Vleugels Foundation; VU University’s Institute for Health and Care Research (EMGO+, HEALTH-F4-2007-201413) and Neuroscience Campus Amsterdam; Wellcome Trust (090532, 091551, 098051, 098381); Wissenschaftsoffensive TMO; and Yrjö Jahnsson Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Parental eating behavior traits have been shown to be related to the adiposity of their young children. It is unknown whether this relationship persists in older offspring or whether rigid or flexible control are involved. The objective of this study was to test the hypothesis that parental eating behavior traits, as measured by the Three-Factor Eating Questionnaire (TFEQ), are related to offspring body weight. Cross-sectional anthropometric and TFEQ data from phase 2 and 3 of the Quebec Family Study generated 192 parent–offspring dyads (offspring age range: 10–37 years). Relationships were adjusted for offspring age, sex and reported physical activity, number of offspring per family and parent body mass index (BMI). In all parent–offspring dyads, parental rigid control and disinhibition scores were positively related to offspring BMI (r=0.17, P=0.02; r=0.18, P

A genetic influence on methylation levels has been reported and methylation quantitative trait loci (meQTL) have been identified in various tissues. The contribution of genetic and epigenetic factors in the development of the metabolic syndrome (MetS) has also been noted. To pinpoint candidate genes for testing the association of SNPs with MetS and its components, we aimed to evaluate the contribution of genetic variations to differentially methylated CpG sites in severely obese men discordant for MetS. A genome-wide differential methylation analysis was conducted in visceral adipose tissue (VAT) of 31 severely obese men discordant for MetS (16 with and 15 without MetS) and identified ∼17,800 variable CpG sites. The genome-wide association study conducted to identify the SNPs (meQTL) associated with methylation levels at variable CpG sites revealed 2292 significant associations ( P −11 ) involving 2182 unique meQTLs regulating the methylation levels of 174 variable CpG sites. Two meQTLs disrupting CpG sites located within the collagen-encoding COL11A2 gene were tested for associations with MetS and its components in a cohort of 3021 obese individuals. Rare alleles of these meQTLs showed association with plasma fasting glucose levels. Further analysis conducted on these meQTL suggested a biological impact mediated through the disruption of transcription factor (TF)–binding sites based on the prediction of TF-binding affinities. The current study identified meQTL in the VAT of severely obese men and revealed associations of two COL11A2 meQTL with fasting glucose levels.

Summary Physical activity is often avoided or practised at a low-intensity level because of the limited ability of patients with heart disease (HD) to provide sustained effort. Immersible training has been suggested as a possible alternative as hydrostatic pressure can modify some hemodynamic parameters in healthy patients and potentially increase the exercise capacity in patients with HD. The purpose of this study was to examine the acute cardiorespiratory adaptations at different levels of immersion using an immersible ergometer (IE) in patients with HD. Twenty-one patients and 13 healthy controls (HC) participated in this study. Several cardiorespiratory parameters were assessed at two levels of immersion (hips and xiphoid) for five different pedalling rates (40, 50, 60, 70 and peak rpm). At submaximal intensity, HD and HC participants did not differ significantly for most variables. However, for nearly and/or maximal workload, HD participants showed significantly lower values for VO2 and higher values for VE/VO2 and VE/VCO2 for both immersion levels. The increase in immersion level from hips to xiphoid resulted in a significant decrease in VO2 in both HC and HD groups at the same exercise intensity. In addition, the increase in the effects of size values based on the exercise workload indicates that group differences are accentuated with the highest pedalling rates. Our data suggest that participants with HD may benefit from the hydrostatic effect during IE cycling by allowing them to alleviate their submaximal efforts and increasing their maximal cardiorespiratory capacity during hip immersion.

We aimed to determine the effect of aquatic cycling and different levels of immersion on respiratory responses in healthy and heart disease (HD) volunteers. Thirty-four age matched volunteers, 21 HD and 13 healthy controls (HC) took part in this study. The ventilatory pattern, phase 1 VE and steady-state ventilatory responses to progressive exercise from 40 to peak rpm, were measured while participants exercised on a water stationary bike (WSB) at different levels of immersion. No effect of immersion was observed on steady-state respiratory responses in the HD group, but immersion reduced VE phase 1 by ∼79% at pedaling cadences of 40, 50 and 60 rpm. In conclusion, immersion at hips and xiphoid process blunted the fast drive to breathe in the HD group. This transient effect on the respiratory response to immersed exercise cannot be considered a contraindication for exercise in HD individuals.

The lipase A, lysosomal acid, cholesterol esterase enzyme (LIPA) is involved in the hydrolysis of triglycerides (TGs) and cholesteryl esters (CEs) delivered to lysosomes. LIPA deficiency in human causes two distinct phenotypes characterized by intracellular storage of CE and derangements in the control of cholesterol production, namely the Wolman disease (WD) and the CE storage disease (CESD). To test the potential association of LIPA gene polymorphisms with obesity-related metabolic complications, promoter, exons, and intronic flanking regions of the LIPA gene were first sequenced in 25 individuals. From the 14 common polymorphisms identified, 12 tagging single-nucleotide polymorphisms (tSNPs) were genotyped in a cohort of 1,751 obese individuals. After adjustments for the effect of age, sex, diabetes, and medication, the C allele of SNP rs1051338 was associated with lower blood pressure (BP; systolic (SBP) P = 0.004; diastolic (DBP) P = 0.006). Three of the tested SNPs were associated with modifications of the plasma lipid profile. The G/G genotype of rs2071509 was associated with higher high-density lipoprotein cholesterol (HDL-C) levels (P = 0.009) and minor allele of rs1131706 was also associated with higher HDL-C (P = 0.004) and an association between rs3802656 and total cholesterol (total-C)/HDL-C ratio was identified (P = 0.04). These results thus suggest that LIPA polymorphisms contribute to the interindividual variability observed in obesity-related metabolic complications.

The prevalence and familial patterns of night eating syndrome (NES) in families enrolled in the Quebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) study was examined. Families (n = 395; one child, mother, and father for whom at least one parent was obese or had abdominal obesity) completed the Night Eating Questionnaire (NEQ) as part of a longitudinal study on the development of metabolic disease in children at risk for obesity. Responses on the NEQ were used to establish a diagnosis of NES and to determine the correlation and heritability of NES symptoms in families. Using comprehensive research diagnostic criteria, full threshold NES was rare: 0% of children, 0.5% of mothers, and 0.3% of fathers met criteria. When controlling for age, sex, and BMI, NEQ scores of spouses were not significantly correlated, but mothers' NEQ scores were significantly correlated with the scores of both sons (r = 0.19, P < 0.001) and daughters (r = 0.15, P = 0.05). The heritability of NEQ scores was 0.24 when controlling for age, sex, and BMI. These findings replicate previous research suggesting a low prevalence of night eating behavior in children and the aggregation of NES in families.

Context: Both excess visceral adipose tissue (VAT) and low cardiorespiratory fitness (CRF) levels are associated with a deteriorated cardiometabolic risk profile. Objective: The aim of the study was to examine the respective contributions of changes in VAT accumulation vs. changes in CRF to 6-yr longitudinal changes in cardiometabolic risk markers. Design, Settings, and Participants: We conducted a prospective, population-based study with an average follow-up of 5.9 ± 0.8 yr. We followed 132 middle-aged participants from the Quebec Family Study (mean age, 35.3 ± 13.9 yr). VAT was measured by computed tomography, whereas the level of CRF was assessed by a submaximal physical working capacity test at baseline and at follow-up. A complete cardiometabolic risk profile, including systolic and diastolic blood pressure, fasting glucose and insulin levels, C-reactive protein (n = 72), as well as a standard lipoprotein-lipid profile, was obtained at baseline and at follow-up. Main Outcome Measures: We measured changes in CRF, VAT, and cardiometabolic risk profile over 6 yr. Results: After adjusting for age and sex, 6-yr changes in VAT were negatively correlated with changes in CRF (r = −0.38; P < 0.001). In a multivariate model that included age, sex, changes in VAT, changes in CRF, as well as baseline levels of the above cardiometabolic risk factors, 6-yr changes in VAT were the most important predictor of the change in the metabolic syndrome score (R2 = 13.2%; P < 0.001). Adding 6-yr changes in CRF levels significantly improved the predictability of the model (R2 = 19.7%; P = 0.002). Conclusions: Changes in both VAT and CRF levels observed over 6 yr are associated with changes in parameters of the lipoprotein-lipid profile, glucose-insulin homeostasis, and inflammatory markers. Thus, maintaining a low level of VAT and a high level of CRF are important targets for maintenance of cardiometabolic health.

This review of the exercise genomics literature emphasizes the strongest papers published in 2010 as defined by sample size, quality of phenotype measurements, quality of the exercise program or physical activity exposure, study design, adjustment for multiple testing, quality of genotyping, and other related study characteristics. One study on voluntary running wheel behavior was performed in 448 mice from 41 inbred strains. Several quantitative trait loci for running distance, speed, and duration were identified. Several studies on the alpha-3 actinin (ACTN3) R577X nonsense polymorphism and the angiotensin converting enzyme (ACE) I/D polymorphism were reported with no clear evidence for a joint effect, but the studies were generally underpowered. Skeletal muscle RNA abundance at baseline for 29 transcripts and 11 single nucleotide polymorphisms (SNPs) were both found to be predictive of the VO2max response to exercise training in one report from multiple laboratories. None of the 50 loci associated with adiposity traits is known to influence physical activity behavior. However, physical activity appears to reduce the obesity-promoting effects of at least 12 of these loci. Evidence continues to be strong for a role of gene-exercise interaction effects on the improvement in insulin sensitivity following exposure to regular exercise. SNPs in the cAMP responsive element binding position 1 (CREB1) gene were associated with training-induced heart rate response, in the C-reactive protein (CRP) gene with training-induced changes in left ventricular mass, and in the methylenetetrahydrofolate reductase (MTHFR) gene with carotid stiffness in low-fit individuals. We conclude that progress is being made but that high-quality research designs and replication studies with large sample sizes are urgently needed.

Background: The small, dense LDL phenotype is associated with an increased cardiovascular disease risk. A genome-wide scan performed on the Quebec Family Study (QFS) revealed a quantitative trait locus for LDL peak particle diameter (LDL-PPD) on the 17q21 region. A positional candidate gene – the fatty acid synthase gene (FASN) – encodes a key enzyme in the biogenesis of membrane lipids. FASN may play a role in the regulation of feeding and may be a potential therapeutic target for obesity and insulin resistance. Methods: Analyses were performed on 592 subjects of the QFS. Dietary fat was estimated by a 3-day food record. LDL-PPD was measured by gradient gel electrophoresis on polyacrylamide gradient gels. Results: Five single nucleotide polymorphisms were genotyped in FASN gene. FASN rs4246444 was associated with LDL-PPD, but only when fat intake was taken into account (p = 0.001). High and low lipid consumers were defined using a cutoff of 35% of dietary fat intake. Carriers of the variant allele showed smaller LDL-PPD only when consuming a high amount of fat. This association remained significant after adjustments for age, sex, body mass index and plasma triglyceride levels. Conclusion: The results suggest that dietary fat intake may modify the effect of the FASN rs4246444 polymorphism on LDL-PPD.

Homozygosity for a premature stop codon at amino acid position 577 in the alpha-actinin-3 (ACTN3) gene leads to α-actinin-3 deficiency. This genotype is observed in approximately 18% of Caucasians. The ACTN3 R577X polymorphism has been previously associated with indicators of physical performance in several, but not all, studies. We examined the prevalence of R577X (rs1815739) and two additional haplotype tagging single nucleotide polymorphisms (htSNPs) of the ACTN3 gene (rs1791690 and rs2275998) in the Genathlete study comprising 316 male elite endurance athletes (VO2max 79.0+3.5 ml · kg(-1) · min(-1); mean +/- s) from North America, Finland, and Germany and 304 sedentary controls (VO2max 40.1+7.0 ml · kg(-1) · min(-1) matched by country of origin. The distribution of genotype and allele frequencies between the two groups was tested by Pearson chi-square and/or Fischer exact test. The prevalence of the 577X homozygote genotype was similar in endurance athletes and controls (20% and 17.5%, respectively). The resulting odds ratio for endurance performance in 577X homozygotes compared with 577R-allele carriers was 1.24 (95%CI 0.82-1.87, P = 0.3). The genotype distribution of the two htSNPs and haplotype frequencies did not differ significantly between athletes and controls. In conclusion, our findings indicate that ACTN3 R577X and other SNPs in ACTN3 are not genetic determinants of endurance performance in Caucasian males.

Hypoxia-inducible factor-1α ( HIF1A) is a transcription factor regulating several genes in response to hypoxic stimuli. HIF1A target genes code for proteins involved in oxygen transport, glycolytic enzymes, and glucose transporters. We investigated whether single-nucleotide polymorphisms and haplotypes in the HIF1A gene are associated with endurance performance in the Genathlete cohort, which includes 316 Caucasian male elite endurance athletes (EEA) with a maximal oxygen uptake of 79.0 ± 3.5 ml·kg−1·min−1 (mean ± SD) and 304 Caucasian male sedentary controls with a maximal oxygen uptake of 40.1 ± 7.0 ml·kg−1·min−1. Six single-nucleotide polymorphisms (rs1951795, rs11158358, rs2301113, rs11549465, rs115494657, rs17099207) were genotyped with the TaqMan system. We found a nominal significant tendency for a difference between the two groups for HIF1A Pro582Ser (rs11549465) genotype distributions ( P χ2 = 0.017). Homozygotes of the Pro genotype were slightly more frequent in athletes than in controls (84 vs. 75%). Compared with Ser carriers, the odds ratio (OR) of being an EEA in Pro/Pro homozygotes was 1.77 [95% confidence interval (CI): 1.18–2.67, P = 0.006] compared with the other genotypes. A common HIF1A haplotype (frequency: 15%), including the rs11549465 Pro allele and the minor A allele of rs17099207 in the 3′ flanking region of the gene, showed a significant association with EEA status (OR: 2.37, 95% CI: 1.21–4.66, P = 0.012), whereas the most prevalent haplotype (frequency: 59%) comprising the rs11549465 Pro allele and the major G allele of rs1709920 showed no association with EEA status (OR: 0.93, 95% CI: 0.58–1.50, P = 0.769). We found preliminary evidence that the HIF1A Pro582Ser polymorphism and a common haplotype of the HIF1A gene may be associated with EEA status in Caucasian men.

Eating behaviour traits are associated with body weight variations in adults. The Three-Factor Eating Questionnaire (TFEQ) measures cognitive restraint, disinhibition and hunger, as well as their corresponding subscales, e.g. rigid and flexible control. The TFEQ has not been widely used in adolescents to investigate eating behaviour traits associated with body weight. The aim of the present study was to assess whether eating behaviour traits were associated with BMI in male and female adolescents. Sixty adolescents (thirty females and thirty males; mean age 15·0 (sd 2·4) years) from the Québec Family Study completed the TFEQ and 3 d dietary records. There were no sex differences in the TFEQ scores. Rigid control, disinhibition and emotional susceptibility (to overeat) were positively related to BMI z-scores for the entire sample (r 0·3, P z-scores and rigid control (r 0·39, P z-scores were positively related to emotional susceptibility (r 0·42, P r 0·41, P z-scores than those by both low disinhibition and low rigid control. There were no significant differences in BMI z-scores between the flexible control categories. Dietary macronutrient content was not consistently related to eating behaviour traits. These results show that the eating behaviour traits of disinhibition and rigid control are independently related to BMI z-scores in this group of adolescents.

The glutamate decarboxylase 2 (GAD2) gene encodes for the glutamic acid decarboxylase enzyme (GAD65), which is implicated in the formation of the gamma-aminobutyric acid (GABA), a neurotransmitter involved in the regulation of food intake. The objective of the present study was to test for association between GAD2 single-nucleotide polymorphisms (SNPs) and eating behaviors, dietary intake and obesity in subjects (n=873) from the Quebec Family Study (QFS). Energy and macronutrient intakes were measured using a 3-day dietary record and eating behaviors were assessed using the Three-Factor Eating Questionnaire (TFEQ). Six SNPs capturing about 90% of GAD2 gene variability were genotyped and tested for association with age- and BMI- adjusted phenotypes. No evidence of association was found in men. In women, a SNP (rs992990; c.61450 C>A) was associated with disinhibition (p=0.028), emotional susceptibility to disinhibition (p=0.0005) and susceptibility to hunger (p=0.028). Another SNP (rs7908975; c.8473A>C) was associated with carbohydrate (p=0.021) and lipid (p=0.021) intakes, disinhibition (p=0.011) and two of its subscales (emotional and situational susceptibility) as well as with avoidance of fattening foods (p=0.036). Six-year weight gain was two times higher in women carrying the variants associated with eating behaviors: 4.2kg (vs 2.1kg in non-carriers) in A-allele carriers of c.61450 C>A (p=0.038) and 4.9kg (vs 2.5kg in non-carriers) in C-allele carriers of c. 8473 A>C (p=0.013). The results suggest a role for the GAD2 gene in determining food intake, eating behaviors and weight gain over time in women.

As visceral adipose tissue (AT) accumulation and inflammatory markers are known to increase with age, we examined whether this age-related change in regional AT distribution could contribute to the increase in the concentration of some inflammatory markers found with age. Two hundred eight healthy men aged 18.6 to 72.2 years and covering a wide range of adiposity values (body mass index, 18.5-39.3 kg/m(2)) were studied. Plasma C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha) levels were measured by enzyme-linked immunosorbent assay. Anthropometric characteristics such as height, weight, and waist girth were measured; and body mass index was calculated. Cross-sectional areas of abdominal AT were obtained at L4-L5 by computed tomography. Fasting blood samples were collected to determine a complete lipoprotein lipid profile, and a 75-g oral glucose tolerance test was performed. Overall, visceral AT accumulation was positively correlated with age (r = 0.51, P.0001) as well as with plasma CRP (r = 0.39, P.0001), IL-6 (r = 0.32, P.0001), and TNF-alpha (r = 0.14, P.05) levels. A significant positive relationship was also observed between age and CRP (r = 0.36, P.0001), IL-6 (r = 0.39, P.0001), or TNF-alpha (r = 0.15, P.05) concentrations. As middle-aged men were characterized by higher CRP (1.32 [25th percentile, 0.71; 75th percentile, 2.71] vs 0.66 [0.36, 1.62] mg/L, P.0001) and IL-6 (1.60 [1.09, 2.28] vs 1.12 [0.77, 1.60] pg/mL, P.0001) levels as well as by a greater amount of visceral AT (P.0001) than young men, we have individually matched 43 young men (age, 28.6 +/- 5.82 years) with 43 middle-aged men (age, 57.6 +/- 5.15 years) on the basis of their visceral AT. Matching for visceral AT eliminated the difference between middle-aged men and younger adult men in inflammatory markers. These results suggest that the age-related variation in CRP and IL-6 is largely explained by differences in visceral AT.

To examine whether dietary patterns are associated with obesity phenotypes.Cross-sectional study.We recruited 664 participants aged between 18 and 55 years. Dietary data were collected from a food frequency questionnaire. A factor analysis was performed to derive dietary patterns. Body mass index (BMI), weight and waist girth were recorded using standard procedures. Fat mass and fat-free mass were assessed by electrical bioimpedance. Obesity was defined as having a BMIor =30 kg m(-2) and a positive FHO (FHO+) as having at least one obese first-degree relative.Two dietary patterns were identified; Western and Prudent. The Western pattern was mainly characterized by a higher consumption of refined grains, French fries, red meats, condiments, processed meats and regular soft drinks whereas the Prudent pattern was mainly characterized by a higher consumption of non-hydrogenated fat, vegetables, eggs and fish and seafood. Subjects in the top tertile of the Western pattern had higher BMI, weight, waist girth, waist-to-hip ratio and fat mass than those in the lower tertile. In contrast, subjects in the top tertile of the Prudent pattern had lower BMI, weight, waist girth, fat mass, HDL-cholesterol levels, and lower triglyceride levels than those in the lowest tertile. Individuals in the upper tertile of the Western pattern were more likely to be obese (obesity was defined as having a BMIor =30 kg m(-2)) (OR=1.82, 95% CI 1.16-2.87) whereas those in the upper tertile of the Prudent pattern were less likely to be obese (OR=0.62, 95% CI 0.40-0.96). These latter significant associations were only observed among those with FHO+. No such association was observed among FHO- individuals.Individuals having a high score of Western pattern were more likely to be obese and those having a high score of the Prudent pattern were less likely to be obese, and this is particularly among individuals with an FHO+.

The prevalence of morbid obesity and its associated metabolic complications has risen rapidly in the past decade. Recently, we have established the transcriptome of the visceral adipose tissue of nondiabetic severely obese men with and without metabolic syndrome (MetS) that provided new candidate genes for cardiovascular disease (CVD) risk factors. The oxysterol-binding protein–like protein 11 (OSBPL11) that belongs to the OSBP family of intracellular receptors was one of the genes found to be significantly overexpressed in the MetS group. To determine whether OSBPL11 gene polymorphisms are associated with CVD risk factors and diabetes, OSBPL11 gene promoter and coding regions were sequenced in 25 individuals and six tagging single-nucleotide polymorphisms (SNPs) capturing 85% of gene sequence–derived common genetic variability (minor allele frequency (MAF) > 5%) were genotyped in two samples for a total of 962 obese individuals. Using a multistage experimental design, χ2-tests and logistic regressions were applied to compare genotype frequencies and to compute odds ratios (ORs) for low and high CVD risk groups. Significant associations between rs1055419 and diastolic blood pressure (OR = 0.53; P = 0.01) were found whereas IVS12+95 T>C, a newly discovered SNP, was associated with low-density lipoprotein–cholesterol levels (OR = 1.63; P < 0.001), hyperglycemia/diabetes (OR = 1.48; P < 0.004) as well as with MetS per se (OR = 1.56; P < 0.01). These results suggest that the OSBPL11 gene is involved in cholesterol and glucose metabolism in obese individuals.

The objective of the present study was to determine the respective contributions of visceral adipose tissue (AT) accumulation and cardiorespiratory fitness to variation of inflammatory markers in men and women. Circulating levels of C-reactive protein, tumor necrosis factor-alpha, interleukin-6, and adiponectin were obtained with visceral AT (computed tomography) and fitness (physical working capacity test) levels in a sample of healthy men (n = 120) and women (n = 152) covering a wide range of adiposity. An inflammation score was developed based on gender-specific percentile values of each inflammatory marker (0 or 1), which yielded a score ranging from 0 (low) to 4 (high). Visceral AT was positively associated with C-reactive protein and interleukin-6 levels (ror =0.35, p0.0001), but negatively associated with adiponectin (r = -0.29, por =0.0003) after adjustment for fitness. After adjusting for visceral AT, fitness was not associated with variation in inflammatory markers in women and only with adiponectin in men (r = -0.20, p = 0.03). In participants with low visceral AT (130 cm(2) for men and100 cm(2) for women), prevalences of participants with an increased inflammation score were 23.9% and 28.0%, respectively, for participants with high and low fitness, whereas in subjects with increased visceral AT, prevalences of a high inflammation score were 60.0% and 61.7%, respectively, for participants with high and low fitness. In conclusion, these results suggest that the previously reported association between poor fitness and low-grade inflammation may be largely attributable to increased visceral AT accumulation and its associated state of insulin resistance, conditions frequently observed in subjects with poor cardiorespiratory fitness.

The aims of this study were to identify (i) what cognitions predict leisure-time physical activity and (ii) the moderators of cognition-behavior relationships among obese individuals. A sample of 91 adults (BMIor=30 kg/m(2)) completed a baseline questionnaire assessing variables of the theory of planned behavior (TPB). Biological measures and socio-demographic variables were also obtained. Behavior was assessed 3 months later. Multiple hierarchical regression analyses indicated that significant variables predicting behavior were past behavior (beta = 0.39; P = 0.0001), intention (beta = 0.27; P = 0.03), and the interaction term "perceived behavioral control (PBC) x perceived built environment" (beta = 0.17; P = 0.05). The PBC-behavior relation was better when the built environment was perceived as favorable to physical activity. The model explained 41% of variance in behavior. The determinants explaining intention were PBC (beta = 0.55; P0.0001), anticipated regret (beta = 0.26; P = 0.0007), and past behavior (beta = 0.22; P = 0.005), accounting for 59% of variance. Participation in leisure-time physical activity is explained primarily by a person's intentions to perform this behavior. The results also suggest that people are more able to translate their perception of control into action if they perceive the built environment as favorable, although this additional gain in prediction is small relative to intention. Nonetheless, both cognitions and aspects of the built environment should be given consideration in the promotion of leisure-time physical activity among obese individuals.

Aim: To evaluate whether familial history of obesity (FHO) interacts with dietary fat intake (DFI) on obesity-related phenotypes. Methods: We recruited 664 participants aged between 18 and 55 years. A positive FHO (FHO+) was defined as having at least 1 obese first-degree relative and a negative FHO (FHO–) as no obese first-degree relative. Dietary intakes were collected from a food-frequency questionnaire. Body mass index, weight and waist girth were recorded using standard procedures. Fat mass and fat-free mass were assessed by electrical bioimpedance. Results: Significant interaction effects (FHO·DFI) were observed for body mass index, weight, waist girth and fat mass (p interaction = 0.05, 0.04, 0.04, 0.02, respectively). Among FHO+ individuals, indices of obesity increased with an increasing amount of DFI, whereas these associations were not observed in FHO– individuals. We also found that FHO+ individuals consuming a high-fat diet were at higher risk of obesity than FHO– individuals consuming a low-fat diet (3.6, CI 2.1–6.2). Conclusion: These results suggest a stronger relationship between DFI and obesity-related phenotypes in individuals with FHO+.

A large body of evidence suggests that the environment plays an important role in the development of obesity. The hormone-sensitive lipase (encoded by the LIPE gene) is an intracellular enzyme that mobilises fat stores in a hormone-stimulated manner. The aim of the present study was to determine the effects of the LIPE C-60G polymorphism on body fat and plasma lipid and lipoprotein concentrations, and to test for its interaction with physical activity. The LIPE C-60G polymorphism was genotyped in 862 subjects from the Quebec Family Study. Body mass index (BMI), fat mass, percentage body fat, abdominal fat areas assessed by computed tomography, and detailed fasting plasma lipid and lipoprotein profiles were measured. Levels of physical activity were estimated using a three-day diary, and a moderate to strenuous physical activity score was retained for this study. The main effects of the LIPE C-60G polymorphism, physical activity and their interaction were determined by regression analyses separately in men and women using the MIXED model procedure. In men, we observed significant gene-physical activity interactions for BMI (p = 0.006), fat mass (p = 0.04), abdominal visceral fat area (p = 0.005) and plasma cholesterol (C) high-density lipoprotein cholesterol (HDL-C) ratio (p = 0.003). A high level of physical activity was associated with reduced adiposity and a lower plasma-C/HDL-C ratio, but only in non-carriers of the genetic variant (G-60 allele). In women, no evidence of a gene by physical activity interaction was observed, except for subcutaneous abdominal fat (p = 0.05). These results suggest that the associations between physical activity and body fat and plasma lipoprotein/lipid concentrations in men are dependent on the LIPE C-60G polymorphism, and highlight the importance of taking into account the role of gene-physical activity interactions in candidate gene studies of obesity and obesity-related traits.

Introduction: Complex traits such as obesity are modulated by genetic and environmental factors and lead to varied clinical presentations.The aim of this study was to investigate associations between candidate genes and obesity-related phenotypes using a sample of 252 lumberjacks issued from a founder population and sharing a common and circumscribed environment. Methods: Thirty-seven variants in 18 genes were genotyped. The restriction fragment length polymorphism method and the template-directed dye-terminator incorporation assay with fluorescence polarization detection were employed for the genotyping assays. Multivariate logistic regression models were built in order to calculate the relative odds of exhibiting obesity-related phenotypes associated with the presence of the studied polymorphism. Among them, 21 single nucleotide polymorphisms were tested for associations with obesity phenotypes. Results: Significant associations were found between carriers of the minor alleles of APOE-ε2, FABP2-A54T, UCP1-L229M, LPL-HindIII, LPL-S447X and LPL-T1973C, patients bearing a combination of LPL-D9N, LPL-N291S and LPL-P207L and obesity-related phenotypes. Conclusion: The present results suggest that a particular population such as lumberjacks, sharing the same environment, could help target genes involved in complex traits.

Several single nucleotide polymorphisms (SNPs) for type 2 diabetes mellitus (T2DM) risk have been identified by genome wide association studies (GWAS). The objective of the present study was to investigate the impact of these SNPs on T2DM intermediate phenotypes in order to clarify the physiological mechanisms through which they exert their effects on disease etiology. We analysed 23 SNPs in 9 T2DM genes (CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8, TCF2, TCF7L2 and WFS1) in a maximum of 712 men and women from the Quebec Family Study. The participants underwent a 75 g oral glucose tolerance test (OGTT) and were measured for glucose, insulin and C-peptide levels. Indices of insulin sensitivity and insulin secretion were derived from fasting and OGTT measurements. We confirmed the significant associations of variants in CDKAL1, CDKN2B, HHEX/IDE, KCNJ11 and TCF7L2 with insulin secretion and also found associations of some of these variants with insulin sensitivity and glucose tolerance. IGF2BP2 and SLC30A8 SNPs were not associated with insulin secretion but were with insulin sensitivity and glucose tolerance (0.002 ≤ P ≤ 0.02). To examine the joint effects of these variants and their contribution to T2DM endophenotypes variance, stepwise regression models were used and the model R 2 was computed. The variance in the phenotypes explained by combinations of variants ranged from 2.0 to 8.5%. Diabetes-associated variants in CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8 and TCF7L2 are associated with physiological alterations leading to T2DM, such as glucose intolerance, impaired insulin secretion or insulin resistance, supporting their role in the disease aetiology. These variants were found to account for 2.0–8.5% of the variance of T2DM-related traits.

Purpose: To compare dietary intakes of individuals with and without familial history of obesity (FHO) with recommendations from Canada’s Food Guide to Healthy Eating (CFGHE). Methods: This cross-sectional study recruited 197 women and 129 men with a body mass index of less than 30kg/m2 from the Quebec City metropolitan area. A dietitian obtained their dietary intakes, using a food frequency questionnaire. Results: Daily energy, macronutrient, and fibre intakes were not significantly different between individuals with and without FHO. No significant differences in the proportion of individuals who achieved the minimum CFGHE recommendations were observed between individuals with and without FHO. Conclusions: Findings of our study suggest that individuals with and without FHO have comparable dietary intakes when compared to Canadian dietary guidelines.

Adipose tissue synthesizes and secretes a wide range of biologically active molecules considered as inflammatory markers whose dysregulation in obesity plays a role in the development of insulin resistance and vascular disorders. Thus, finding genes that influence circulating levels of inflammatory biomarkers may provide insights into the genetic determinants of obesity-related metabolic diseases. We performed linkage analyses for fasting plasma levels of adiponectin, C-reactive protein (CRP), interleukin-6 (IL-6) and tumor-necrosis factor-alpha (TNF-alpha) in 764 subjects enrolled in the Quebec family study (QFS). A maximum of 393 pairs of siblings from 211 nuclear families were available for analyses. A total of 443 markers spanning the 22 autosomal chromosomes with an average inter-marker distance of 6.24 Mb were genotyped. Linkage was tested using both allele-sharing (SIBPAL) and variance component linkage methods (MERLIN). We showed suggestive evidence of linkage for plasma adiponectin levels on chromosome 15q21.1 [D15S659; logarithm of the odds (LOD) score = 2.23], 3q13.33 (D3S3023; LOD = 2.09), 20q13.2 (D20S197; LOD = 1.96) and 14q32.2 (D14S1426; LOD = 1.79). Evidence of linkage (SIBPAL) was also found for CRP on 12p11.23 (P = 0.001) and 12q15 (P = 0.0005) and for IL-6 on 14q12 (P = 0.002). None of these linkages remained significant after adjustment for body mass index. No evidence of linkage was found for TNF-alpha plasma levels. These results suggest that several QTLs can influence plasma levels of adiponectin and CRP, partly via their effects on adiposity.

OBJECTIVE—A genome-wide association study conducted by the Wellcome Trust Case Control Consortium recently associated single nucleotide polymorphisms (SNPs) in the FTO (fatso/fat mass and obesity associated) gene with type 2 diabetes. These associations were shown to be mediated by obesity. Other research groups found similar results in Europeans and Hispanics but not African Americans. The mechanism by which FTO influences obesity and type 2 diabetes is currently unknown. The present study investigated the role of two FTO SNPs (rs17817449 and rs1421085) in adiposity, insulin sensitivity, and body weight regulation, including energy intake and expenditure. RESEARCH DESIGN AND METHODS—We genotyped 908 individuals from the Quebec City metropolitan area that participated in the Quebec Family Study, a long-term study of extensively phenotyped individuals designed to investigate factors involved in adiposity. RESULTS—We found significant associations for both SNPs with several obesity-related phenotypes. In particular, rs17817449 was associated with BMI (P = 0.0014), weight (P = 0.0059), and waist circumference (P = 0.0021) under an additive model. In addition, this FTO SNP influenced fasting insulin (P = 0.011), homeostasis model assessment of insulin resistance (P = 0.038), and an insulin sensitivity index derived from an oral glucose tolerance test (P = 0.0091). Associations were also found with resting metabolic rate (RMR) (P = 0.042) and plasma leptin levels (P = 0.036). Adjustment for BMI abolished the associations with insulin sensitivity, RMR, and plasma leptin levels. CONCLUSIONS—These results confirm that genetic variation at the FTO locus contributes to the etiology of obesity, insulin resistance, and increased plasma leptin levels.

Aims Studies suggest that adiponectin (APM1) and its receptors 1 and 2 (AdipoR1 and AdipoR2) play an important role in the development of insulin resistance (IR). Our objective was to examine associations between APM1 (+45T>G, +276G>T and –3971A>G), AdipoR1 (−100G>T and −3882T>C) and AdipoR2 (−35361A>G and –1352G>A) genes single-nucleotide polymorphisms (SNPs) and adiponectin plasma levels, indicators of glucose tolerance, insulin sensitivity (IS) and insulin secretion. Methods Six hundred and twenty-two non-diabetic subjects from the Quebec Family Study (QFS) underwent a 75-g oral glucose tolerance test (OGTT), with measurement of fasting adiponectin, glucose, insulin and C-peptide levels. Indices of glucose tolerance, IS and insulin secretion were derived from fasting and OGTT measurements. Results Significant evidence of association was found between indices of IS and APM1 and AdipoR1 SNPs. The APM1 –3971G/G homozygotes exhibited a reduced area under the curve of insulin during the OGTT (P = 0.007) and higher Cederholm index (P = 0.01) compared to the A/A homozygotes. The APM1+45T>G variant was also associated with fasting (P = 0.002) and 2-h (P = 0.007) glucose values as well as with higher Cederholm index (P = 0.04) and disposition index (P = 0.02). Finally, the AdipoR1−3882T>C SNP was associated with fasting glucose (P = 0.03), the homeostasis model assessment for insulin resistance (P = 0.04) and an index of insulin secretion (P30/G30, P = 0.02). No evidence of association was found with plasma adiponectin levels. Conclusions These results provide evidence for an influence of common SNPs in the APM1 and AdipoR1 genes on different phenotypes of glucose and insulin metabolism associated with increased risk of type 2 diabetes.

Article, Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P, published version, peerReviewed

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases. Fondo de Investigaciones Sanitarias (grant # PI12/00914). Research in sports genetics to A. Lucia in Spain was funded by grants from the Consejo Superior de Deportes (CSD) 2.806 JCR (2016) Q1, 15/64 Multidisciplinary Sciences No data SJR 2016 No data IDR 2016 UEM

Objective: In the present study, we undertook a two-step fine mapping of a 20-megabase region around a quantitative trait locus previously reported on chromosome 15q26 for abdominal subcutaneous fat (ASF) in an extended sample of 707 subjects from 202 families from the Quebec Family Study. Research Methods and Procedure: First, 19 microsatellites (in addition to the 7 markers initially available on 15q24-q26; total = 26) were genotyped and tested for linkage with abdominal total fat, abdominal visceral fat, and ASF assessed by computed tomography and with fat mass (FM) using variance component-based approach on age- and sex-adjusted phenotypes. Second, 16 single nucleotide polymorphisms (SNPs) were genotyped and tested for association using family-based association tests. Results: After the fine mapping, the peak logarithm of odds ratio (LOD) score (marker D15S1004) increased from 2.79 to 3.26 for ASF and from 3.52 to 4.48 for FM, whereas for abdominal total fat, the peak linkage (marker D15S996) decreased from 2.22 to 1.53. No evidence of linkage was found for abdominal visceral fat. Overall, for genotyped SNPs, three variants located in the putative MCTP2 gene were significantly associated with FM and the three abdominal fat phenotypes (p ≤ 0.05). The major allele and genotype of rs1424695 were associated with higher adiposity values (p < 0.004). The same trend was found for the two other polymorphisms (p < 0.05). None of the other SNPs was associated with adiposity phenotypes. The linkage for FM became non-significant (LOD = 0.84) after adjustment for the MCTP2 polymorphisms, whereas the one for ASF remained unchanged. Discussion: These results suggest that the MCTP2 gene, located on chromosome 15q26, influences adiposity. Other studies will be needed to investigate the function of the MCTP2 gene and its role in obesity.

Several candidate genes have been associated with obesity, but very few studies have tested more than one gene simultaneously.In this study, 15 polymorphisms in 10 candidate genes of obesity were tested for association with changes in adiposity measured over a period of 6-10 years in a maximum of 332 adult subjects with a wide range of adiposity (17.5body mass index (BMI)55.6 kg/m2) from the Québec Family Study. Stepwise regression models were used to identify the combination of genes explaining changes in adiposity after adjustment for age (initial value), gender, initial value of the adiposity variable and duration of follow-up. Analyses were carried out in the whole sample and repeated while stratifying on age (40 andor=40 years).In the whole sample, the variance in age-related adiposity changes explained by the candidate gene polymorphisms ranged from 3.1% (BMI, P0.05) to 8.5% (fat mass (FM), Por=0.0005). The genes retained in the prediction model for changes in FM were leptin (Por=0.05), guanine nucleotide binding protein beta3 (Por=0.05), adrenergic receptor beta3 (Por=0.05), neuromedin beta (Por=0.05) and peroxisome proliferator-activated receptor-gamma2 (Por=0.10). The effects of the genes were significant in both age groups, but the genes contributing to adiposity changes were different and their effects were stronger in the younger than in the older age group.This study suggests that models including genetic information from several candidate gene polymorphisms can significantly contribute to the changes in adiposity over time, that different genes may act at different ages and that genetic information could be useful for the identification of individuals at high risk for gaining body fat over time.

Genetic and nutritional factors interact together and modulate the plasma lipid profile. We identified variations in the gene encoding the liver X receptor α (LXRα) and investigated their effects on the plasma lipoprotein/lipid profile. We also examined whether the association between cholesterol intake and plasma lipid profile was modulated by LXRα variants. The LXRα gene was sequenced in thirty-five French-Canadian men with high plasma total cholesterol (>5·0 mmol/l) and LDL-cholesterol (>3·5 mmol/l) concentrations. Dietary cholesterol was obtained from a food-frequency questionnaire. The LXRα c.-115G>A, c.-840C>A and c.-1830T>C genotypes were determined by direct sequencing in 732 subjects. Molecular screening of the LXRα gene revealed sixteen variants. Genotypes c.-115G>A, c.-840C>A and c.-1830T>C (rare allele frequency of 14·3 %, 14·2 % and 11·0 %, respectively) were analysed further. Plasma total cholesterol concentrations were higher in carriers of the -115A, -840A and -1830C allele, compared with the -115G/G, -840C/C and -1830T/T homozygotes (P ≤ 0·05). In a model including the c.-115G>A polymorphism, cholesterol intake, the interaction term c.-115G>A × cholesterol intake (mg/d) and covariates, LXRα-115G>A explained 1·8 % and 2·1 % of the variance in total cholesterol and LDL-cholesterol concentrations (P = 0·02 andP = 0·01), whereas the interaction term explained 2·9 % (P = 0·002) and 2·8 % (P = 0·005), respectively. When subjects were divided into four groups according to the median of cholesterol (290·8 mg) and -115G>A genotypes, high cholesterol intake was associated with higher cholesterol levels in -115A carriers. Similar results were observed for c.-840C>A and c.-1830T>C. These results suggest that cholesterol intake interacts with LXRα variants to modulate the plasma lipid profile.

Objectives: The purpose of this project was to evaluate the potential of the downward hierarchical clustering analysis (DHCA) for studying genetic heterogeneity, i.e. differences in allele frequency in subpopulations, such as the 15 public health regions of the province of Québec (Canada). Methods: The study relied on an anonymized sample of 1,680 individuals who had participated in the Québec Heart Health Survey in 1990–1991. The genotyping of 11 variants in 8 candidate genes known to be involved in chronic inflammatory diseases, namely asthma and cardiovascular diseases, was performed using the amplification refractory mutation system and restriction fragment length polymorphism techniques. Only variants showing an allelic frequency >2% in the Québec Heart Health Survey (n = 8) were selected. DHCA techniques were then applied to model the geographical distribution of these 8 genetic variants in 15 Québec public health regions and to study genetic heterogeneity. Results: The DHCA allowed to group public health regions and gene variants on the basis of genetic variability. For both asthma and cardiovascular diseases, 3 significant clusters of public health regions and 1 cluster of gene variants were identified. Discussion: This study suggests that DHCA might be useful in studying genetic heterogeneity at the population level and for public health activities.

To test the potential association of cytosine-phosphate-guanine dinucleotides (CpG)-single-nucleotide polymorphisms (SNPs) located within actin-related protein 2/3 complex subunit 3 (ARPC3), a gene recently linked to adipogenesis and lipid accumulation, with metabolic syndrome (MetS) features in severely obese patients.Prioritized SNPs within the ARPC3 locus were genotyped and tested for associations with MetS features in a cohort of 1,749 obese patients with and without MetS. Association testing with CpG methylation levels was performed in a methylation sub-cohort of 16 obese men.A significant association was found between the CpG-SNP rs3759384 (CT) and plasma triglyceride (TG) levels (false discovery rate-corrected p = 3.5 × 10-2), with 0.6% of the phenotypic variance explained by the CpG-SNP, and with TT homozygotes showing the highest plasma TG levels (1.89 mmol/l). The carriers of the rs3759384 T allele also showed a significant decrease in methylation levels of the ARPC3 promoter-associated CpG site cg10738648 in both visceral adipose tissue and blood. ARPC3 expression levels showed a strong correlation with plasma TG levels (r = 0.70; p = 0.02).The increased plasma TG levels found in homozygous rs3759384 T allele carriers argue for a relevant role of this CpG-SNP in lipid management among obese individuals, which may be driven by an epigenetic-mediated mechanism.