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Sökning: WFRF:(Grallert Harald) > (2006-2009) > (2009)

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  • Huth, Cornelia, et al. (författare)
  • Joint analysis of individual participants' data from 17 studies on the association of the IL6 variant -174G>C with circulating glucose levels, interleukin-6 levels, and body mass index.
  • 2009
  • Ingår i: Annals of medicine. - 1365-2060. ; 41:2, s. 128-38
  • Tidskriftsartikel (refereegranskat)abstract
    • Background. Several studies have investigated associations between the -174GC single nucleotide polymorphism (rs1800795) of the IL6 gene and phenotypes related to type 2 diabetes mellitus (T2DM) but presented inconsistent results. Aims. This joint analysis aimed to clarify whether IL6 -174GC was associated with glucose and circulating interleukin-6 concentrations as well as body mass index (BMI). Methods. Individual-level data from all studies of the IL6-T2DM consortium on Caucasian subjects with available BMI were collected. As study-specific estimates did not show heterogeneity (P0.1), they were combined by using the inverse-variance fixed-effect model. Results. The main analysis included 9440, 7398, 24,117, or 5659 non-diabetic and manifest T2DM subjects for fasting glucose, 2-hour glucose, BMI, or circulating interleukin-6 levels, respectively. IL6 -174 C-allele carriers had significantly lower fasting glucose (-0.091 mmol/L, P=0.014). There was no evidence for association between IL6 -174GC and BMI or interleukin-6 levels, except in some subgroups. Conclusions. Our data suggest that C-allele carriers of the IL6 -174GC polymorphism have lower fasting glucose levels on average, which substantiates previous findings of decreased T2DM risk of these subjects.
  • Lindgren, Cecilia M, et al. (författare)
  • Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.
  • 2009
  • Ingår i: PLoS genetics. - 1553-7404. ; 5:6, s. e1000508
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.</p>
  • Salanti, Georgia, et al. (författare)
  • Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations
  • 2009
  • Ingår i: American Journal of Epidemiology. - Oxford University Press. - 0002-9262. ; 170:5, s. 537-545
  • Forskningsöversikt (refereegranskat)abstract
    • For most associations of common single nucleotide polymorphisms (SNPs) with common diseases, the genetic model of inheritance is unknown. The authors extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations with type 2 diabetes. For 13 SNPs, the data fitted very well to an additive model of inheritance for the diabetes risk allele; for 4 SNPs, the data were consistent with either an additive model or a dominant model; and for 2 SNPs, the data were consistent with an additive or recessive model. Results were robust to the use of different priors and after exclusion of data for which index SNPs had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that were very similar to those previously reported based on fixed- or random-effects models, but uncertainty about several of the effects was substantially larger. The authors also examined the extent of between-study heterogeneity in the genetic model and found generally small between-study deviation values for the genetic model parameter. Heterosis could not be excluded for 4 SNPs. Information on the genetic model of robustly replicated association signals derived from genome-wide association studies may be useful for predictive modeling and for designing biologic and functional experiments.
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