110 research outputs found
Genetic Contribution to Variation in Body Configuration in Belgian Nuclear Families: A Closer Look at Body Lengths and Circumferences
The purpose of the current study was to evaluate the contribution of genetic factors on body configuration related phenotypes. The sample consisted of 119 Belgian nuclear families including 231 males and 229 females. Factor analysis with varimax rotation was carried out to analyse 13 length and circumference measures and the resulting two synthetic traits (LF and CF; linear and circumference factors, respectively) were used as summary variables. Univariate quantitative genetic analysis indicated that variation in anthropometric as well as in synthetic traits was significantly dependent on additive genetic effects, with heritabilities ranging from 0.55 to 0.88. Narrow sense heritability estimates were higher for measurements principally characterizing skeletal mass than in variables that also involve soft-tissues. Sex, age and their interactions explained 11â67% of the total phenotypic variance. This report also examined the covariations between pairs of anthropometric and synthetic traits (length measurements and LF vs. height; circumference measures and CF vs. weight and BMI; LF vs. CF). Significant genetic correlations among all the studied traits (except for middle finger length vs. height) confirmed the influence of pleiotropy on genetic determination of these phenotypes. Bivariate analysis showed that pleiotropic effects had a great influence in determining body traits variation within body length measurements, as well as between body circumferences and weight or BMI. In relation to the two synthetic traits, even the variation of body lengths and circumferences was highly determined by genetic factors, shared genetic influences were unlikely to explain much of the observed variation between LF and CF. The results of the present study allow us to conclude that in this population body configuration related traits are subject to a strong genetic control and that shared genes also contribute to this genetic structure
A statistical investigation into the sharing of common genetic factors between blood pressure and obesity phenotypes in nuclear families from the Greater Bilbao (Spain)
Objectives: Several obesity phenotypes (e.g. body mass and fat, fat distribution) have been suggested to be a risk for elevated blood pressure. This study was undertaken to determine the heritability of four blood pressure phenotypes: SBP, DBP, pulse pressure (PP) and mean arterial pressure (MAP) and to assess the strength of genetic and environmental correlations among these phenotypes, and also between blood pressure and the different obesity-related traits.
Methods: The studied sample consisted of 429 nuclear families living in the Greater Bilbao (Spain) and included 1302 individuals aged 4-61 years. Univariate and bivariate quantitative genetic analyses were performed using a variance components procedure implemented in Sequential Oligogenic Linkage Analysis Routines software.
Results: SBP, DBP, PP and MAP were significantly influenced by genetic factors with heritability estimates of 0.25, 0.28, 0.14 and 0.31, respectively, and presented high genetic and environmental correlations between them (except DBP-PP). On the contrary, whereas SBP, DBP and MAP showed common environmental factors with almost all body mass and fat-related traits, pleiotropic effects were only detected for some pairs, especially for those phenotypes that included skinfolds. In contrast, PP did not exhibit common genetic or environmental factors with obesity phenotypes in the studied population
Conclusion: Blood pressure and obesity phenotypes do not share, in general, a substantial influence of common genetic and environmental effects. Finally, the results obtained revealed the importance of the amount of adipose tissue in the genetic correlations with SBP, DBP and MAP, at least, during the growth period
A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes
Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.</p
Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries.
AIMS/HYPOTHESIS: Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes. METHODS: We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (Nâ=â21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution. RESULTS: No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2 range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined. CONCLUSIONS/INTERPRETATION: Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions
Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
Lifestyle and precision diabetes medicine: will genomics help optimise the prediction, prevention and treatment of type 2 diabetes through lifestyle therapy?
Gene-Educational attainment interactions in a Multi-Population Genome-Wide Meta-Analysis Identify Novel Lipid Loci
Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension
High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention
Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci
Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: âSome Collegeâ (yes/no, for any education beyond high school) and âGraduated Collegeâ (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 Ă 10â8) and suggestive (p < 1 Ă 10â6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.</p
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