277 resultados para Fat mass, blood pressure, aerobics, body mass index, weight
Resumo:
To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.
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Hypertension is an important determinant of cardiovascular morbidity and mortality and has a substantial heritability, which is likely of polygenic origin. The aim of this study was to assess to what extent multiple common genetic variants contribute to blood pressure regulation in both adults and children and to assess overlap in variants between different age groups, using genome-wide profiling. Single nucleotide polymorphism sets were defined based on a meta-analysis of genome-wide association studies on systolic blood pressure and diastolic blood pressure performed by the Cohort for Heart and Aging Research in Genome Epidemiology (n=29 136), using different P value thresholds for selecting single nucleotide polymorphisms. Subsequently, genetic risk scores for systolic blood pressure and diastolic blood pressure were calculated in an independent adult population (n=2072) and a child population (n=1034). The explained variance of the genetic risk scores was evaluated using linear regression models, including sex, age, and body mass index. Genetic risk scores, including also many nongenome-wide significant single nucleotide polymorphisms, explained more of the variance than scores based only on very significant single nucleotide polymorphisms in adults and children. Genetic risk scores significantly explained ≤1.2% (P=9.6*10(-8)) of the variance in adult systolic blood pressure and 0.8% (P=0.004) in children. For diastolic blood pressure, the variance explained was similar in adults and children (1.7% [P=8.9*10(-10)] and 1.4% [P=3.3*10(-5)], respectively). These findings suggest the presence of many genetic loci with small effects on blood pressure regulation both in adults and children, indicating also a (partly) common polygenic regulation of blood pressure throughout different periods of life.
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Candidate gene and genome-wide association studies have not identified common variants, which are reliably associated with depression. The recent identification of obesity predisposing genes that are highly expressed in the brain raises the possibility of their genetic contribution to depression. As variation in the intron 1 of the fat mass- and obesity-associated (FTO) gene contributes to polygenic obesity, we assessed the possibility that FTO gene may contribute to depression in a cross-sectional multi-ethnic sample of 6561 depression cases and 21 932 controls selected from the EpiDREAM, INTERHEART, DeCC (depression case-control study) and Cohorte Lausannoise (CoLaus) studies. Major depression was defined according to DSM IV diagnostic criteria. Association analyses were performed under the additive genetic model. A meta-analysis of the four studies showed a significant inverse association between the obesity risk FTO rs9939609 A variant and depression (odds ratio=0.92 (0.89, 0.97), P=3 × 10(-4)) adjusted for age, sex, ethnicity/population structure and body-mass index (BMI) with no significant between-study heterogeneity (I(2)=0%, P=0.63). The FTO rs9939609 A variant was also associated with increased BMI in the four studies (β 0.30 (0.08, 0.51), P=0.0064) adjusted for age, sex and ethnicity/population structure. In conclusion, we provide the first evidence that the FTO rs9939609 A variant may be associated with a lower risk of depression independently of its effect on BMI. This study highlights the potential importance of obesity predisposing genes on depression.
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Objective: Blood pressure is known to aggregate in families. Yet, heritability estimates are population-specific and no Swiss data have been published so far. Moreover, little is known on the heritability of the white-coat effect. We investigated the heritability of various blood pressure (BP) traits in a Swiss population-based sample. Methods: SKIPOGH (Swiss Kidney Project on Genes in Hypertension) is a family-based multi-centre (Lausanne, Bern, Geneva) cross-sectional study that examines the role of genes in determining BP levels. Office and 24-hour ambulatory BP were measured using validated devices (A&D UM-101 and Diasys Integra). We estimated the heritability of systolic BP (SBP), diastolic BP (DBP), heart rate (HR), pulse pressure (PP), proportional white-coat effect (i.e. [office BP-mean ambulatory daytime BP]/mean ambulatory daytime BP), and nocturnal BP dipping (difference between mean ambulatory daytime and night-time BP) using a maximum likelihood method implemented in the SAGE software. Analyses were adjusted for age, sex, body mass index (BMI), and study centre. Analyses involving PP were additionally adjusted for DBP. Results: The 517 men and 579 women included in this analysis had a mean (}SD) age of 46.8 (17.8) and 47.8 (17.1) years and a mean BMI of 26.0 (4.2) and 24.2 (4.6) kg/m2, respectively. Heritability estimates (}SE) for office SBP, DBP, HR, and PP were 0.20}0.07, 0.20}0.07, 0.39}0.08, and 0.16}0.07 (all P<0.01). Heritability estimates for 24-hour ambulatory SBP, DBP, HR, and PP were, respectively, 0.39}0.07, 0.30}.08, 0.19}0.09, and 0.25}0.08 (all P<0.05). The heritability of the white-coat effect was 0.29}0.07 for SBP and 0.31}0.07 for DBP (both P<0.001). The heritability of nocturnal BP dipping was 0.15}0.08 for SBP and 0.22}0.07 for DBP (both P<0.05). Conclusions: We found that the white-coat effect is significantly heritable. Our findings show that BP traits are moderately heritable in a multi-centric study in Switzerland, in line with previous population-based studies, justifying the ongoing search for genetic determinants in this field.
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RESUME L'obésité et l'hypertension atteignent des niveaux épidémiques aussi bien dans les pays industrialisés que dans ceux en voie de développement. La coexistence de ces deux pathologies est associée à un risque cardiovasculaire augmenté. Traditionnellement on mesure la pression artérielle (PA) au bras au moyen d'un brassard qui détermine la pression systolique et diastolique en utilisant soit la méthode auscultatoire ou oscillométrique. L'utilisation d'un brassard de taille standard chez le patient avec un tour de bras augmenté peut surestimer la pression artérielle. Il semble même qu'il existe un rapport idéal entre le tour de bras, et la taille du brassard La mesure à domicile de la pression artérielle avec des appareils validés donne des valeurs de la PA valables. Plusieurs appareils existent sur le marché et depuis quelques années les appareils de mesure de la PA au poignet font leur apparition sur le marché. Cette étude vise à comparer chez des sujets sains et obèses les valeurs de PA obtenues au poignet avec celles obtenues au bras en utilisant deux appareils validés l'OMRON HEM 705-CP et l'OMRON R6. L'OMRON HEM 705-CP permet l'utilisation soit d'un brassard standard (13x30 cm) ou d'un brassard large (16x38 cm), et l'OMRON R6 mesure la PA au poignet. Nous avons comparé un groupe de sujets obèses [Body Mass Index (BMI) >35kg/m2] avec un groupe de sujets sains (BMI <25kg/m2). Ont été exclues de l'étudé les personnes prenant un traitement antihypertenseur ainsi que celles souffrant d'arythmies. La PA a été mesurée en position assise avec le bras gauche sur une table à hauteur du coeur. Un brassard large a été employé pour les sujets obèses et un brassard standard pour les sujets sains. Trois mesures ont été effectuées, la première après une pause de 5 min et chacune des suivantes avec un intervalle de 2 min. La pression d'inflation maximale a été fixée à 170 mmHg. Nous avons utilisé la formule proposée par Marks LA et al pour déterminer si le rapport entre la taille des brassards fournis avec l'OMRON .HEM 705-CP et le tour de bras de nos sujets était optimal (taille du brassard = 9.34 x log10 taille du bras). Nos résultats ne montrent pas de différence statistiquement significative de la PA diastolique entre les deux groupes, qu'elle soit mesurée au bras ou au poignet. La PA systolique mesurée au bras s'est par contre avérée significativement plus basse chez les sujets obèses que chez les sujets sains. Aucune différence n'a été trouvée lorsque la mesure est effectuée au poignet. En utilisant la formule fournie par Marks le rapport entre taille du brassard (large chez les obèses) et tour de bras a été de 10.30±30 chez les sujets obèses et 9.630.45 chez les sujets sains (p<0.001). Le rapport entre tour de bras et brassard chez les sujets obèses est nettement au-dessus de la valeur optimale, ce qui suggère une possible sous-estimation de la PA systolique chez ces sujets. Ces résultats suggèrent qu'il existe un risque de sous-estimer la PA chez le patient obèse lors de l'utilisation d'un brassard large. Cette erreur pourrait être réduite par l'utilisation d'appareils de mesure au poignet. validés chez le sujet obèse.
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BACKGROUND: Head and neck cancer (HNC) risk is elevated among lean people and reduced among overweight or obese people in some studies; however, it is unknown whether these associations differ for certain subgroups or are influenced by residual confounding from the effects of alcohol and tobacco use or by other sources of biases. METHODS: We pooled data from 17 case-control studies including 12 716 cases and the 17 438 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for associations between body mass index (BMI) at different ages and HNC risk, adjusted for age, sex, centre, race, education, tobacco smoking and alcohol consumption. RESULTS: Adjusted ORs (95% CIs) were elevated for people with BMI at reference (date of diagnosis for cases and date of selection for controls) 25.0-30.0 kg/m(2) (0.52, 0.44-0.60) and BMI >/=30 kg/m(2) (0.43, 0.33-0.57), compared with BMI >18.5-25.0 kg/m(2). These associations did not differ by age, sex, tumour site or control source. Although the increased risk among people with BMI 25 kg/m(2) was present only in smokers and drinkers. CONCLUSIONS: In our large pooled analysis, leanness was associated with increased HNC risk regardless of smoking and drinking status, although reverse causality cannot be excluded. The reduced risk among overweight or obese people may indicate body size is a modifier of the risk associated with smoking and drinking. Further clarification may be provided by analyses of prospective cohort and mechanistic studies.
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AIM: The resting metabolic rate (RMR) varies among pregnant women. The factors responsible for this variability are unknown. This study aimed to assess the influence of the prepregnancy body mass index (BMI) on the RMR during late pregnancy. METHODS: RMR, height, weight, and total (TEE) and activity (AEE) energy expenditures were measured in 46 healthy women aged 31 ± 5 years (mean ± SD) with low (<19.8), normal (19.8-26.0), and high (>26.0) prepregnancy BMI at 38.2 ± 1.5 weeks of gestation (t(gest)) and 40 ± 7 weeks postpartum (t(post)) (n = 27). RESULTS: The mean t(gest) RMR for the low-, normal-, and high-BMI groups was 1,373, 1,807, and 2,191 kcal/day, respectively (p = 0.001). The overall mean t(gest) RMR was 316 ± 183 kcal/day (21%), higher than the overall mean t(post) value and this difference was correlated with gestational weight gain (r = 0.78, p < 0.001). The scaled metabolic rate by allometry (RMR/kilograms⁰·⁷³) was similar in the low-, normal-, and high-BMI groups, respectively (p = 0.45). Changes in t(gest) TEE closely paralleled changes in t(gest) RMR (r = 0.84, p < 0.001). AEE was similar among the BMI groups. CONCLUSION: The RMR is significantly increased in the third trimester of pregnancy. The absolute gestational RMR is higher in women with high prepregnancy BMI due to increased body weight. The scaled metabolic rate (RMR/kilograms⁰·⁷³) is similar among the BMI groups of pregnant women.
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Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
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BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.
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We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.
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Weight gain is a major health problem among psychiatric populations. It implicates several receptors and hormones involved in energy balance and metabolism. Phosphoenolpyruvate carboxykinase 1 is a rate-controlling enzyme involved in gluconeogenesis, glyceroneogenesis and cataplerosis and has been related to obesity and diabetes phenotypes in animals and humans. The aim of this study was to investigate the association of phosphoenolpyruvate carboxykinase 1 polymorphisms with metabolic traits in psychiatric patients treated with psychotropic drugs inducing weight gain and in general population samples. One polymorphism (rs11552145G > A) significantly associated with body mass index in the psychiatric discovery sample (n = 478) was replicated in 2 other psychiatric samples (n1 = 168, n2 = 188), with AA-genotype carriers having lower body mass index as compared to G-allele carriers. Stronger associations were found among women younger than 45 years carrying AA-genotype as compared to G-allele carriers (-2.25 kg/m, n = 151, P = 0.009) and in the discovery sample (-2.20 kg/m, n = 423, P = 0.0004). In the discovery sample for which metabolic parameters were available, AA-genotype showed lower waist circumference (-6.86 cm, P = 0.008) and triglycerides levels (-5.58 mg/100 mL, P < 0.002) when compared to G-allele carriers. Finally, waist-to-hip ratio was associated with rs6070157 (proxy of rs11552145, r = 0.99) in a population-based sample (N = 123,865, P = 0.022). Our results suggest an association of rs11552145G > A polymorphism with metabolic-related traits, especially in psychiatric populations and in women younger than 45 years.