PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-3 (3)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
Document Types
1.  FTO, Type 2 Diabetes, and Weight Gain Throughout Adult Life 
Diabetes  2011;60(5):1637-1644.
OBJECTIVE
FTO is the most important polygene identified for obesity. We aimed to investigate whether a variant in FTO affects type 2 diabetes risk entirely through its effect on BMI and how FTO influences BMI across adult life span.
RESEARCH DESIGN AND METHODS
Through regression models, we assessed the relationship between the FTO single nucleotide polymorphisms rs9939609, type 2 diabetes, and BMI across life span in subjects from the Norwegian population-based HUNT study using cross-sectional and longitudinal perspectives. For replication and meta-analysis, we used data from the Malmö Diet and Cancer (MDC) and Malmö Preventive Project (MPP) cohorts, comprising a total sample of 41,504 Scandinavians.
RESULTS
The meta-analysis revealed a highly significant association for rs9939609 with both type 2 diabetes (OR 1.13; P = 4.5 × 10−8) and the risk to develop incident type 2 diabetes (OR 1.16; P = 3.2 × 10−8). The associations remained also after correction for BMI and other anthropometric measures. Furthermore, we confirmed the strong effect on BMI (0.28 kg/m2 per risk allele; P = 2.0 × 10−26), with no heterogeneity between different age-groups. We found no differences in change of BMI over time according to rs9939609 risk alleles, neither overall (∆BMI = 0.0 [−0.05, 0.05]) nor in any individual age stratum, indicating no further weight gain attributable to FTO genotype in adults.
CONCLUSIONS
We have identified that a variant in FTO alters type 2 diabetes risk partly independent of its observed effect on BMI. The additional weight gain as a result of the FTO risk variant seems to occur before adulthood, and the BMI difference remains stable thereafter.
doi:10.2337/db10-1340
PMCID: PMC3292341  PMID: 21398525
2.  Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations 
American Journal of Epidemiology  2009;170(5):537-545.
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.
doi:10.1093/aje/kwp145
PMCID: PMC2732984  PMID: 19602701
Bayes theorem; diabetes mellitus, type 2; meta-analysis; models, genetic; polymorphism, genetic; population characteristics
3.  Underlying genetic models of inheritance in established type 2 diabetes associations 
American journal of epidemiology  2009;170(5):537-545.
For most associations of common polymorphisms with common diseases, the genetic model of inheritance is unknown. We extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations for type 2 diabetes. For 13 polymorphisms, the data fit very well to an additive model, for 4 polymorphisms the data were consistent with either an additive or dominant model, and for 2 polymorphisms with an additive or recessive model of inheritance for the diabetes risk allele. Results were robust to using different priors and after excluding data where index polymorphisms had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that are very similar to those previously reported based on fixed or random effects models, but uncertainty about several of the effects was substantially larger. We also examined the extent of between-study heterogeneity in the genetic model and found generally small values of the between-study deviation for the genetic model parameter. Heterosis could not be excluded in 4 SNPs. Information on the genetic model of robustly replicated GWA-derived association signals may be useful for predictive modeling, and for designing biological and functional experiments.
doi:10.1093/aje/kwp145
PMCID: PMC2732984  PMID: 19602701

Results 1-3 (3)