Advanced

Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations

Salanti, Georgia; Southam, Lorraine; Altshuler, David; Ardlie, Kristin; Barroso, Ines; Boehnke, Michael; Cornelis, Marilyn C.; Frayling, Timothy M.; Grallert, Harald and Grarup, Niels, et al. (2009) In American Journal of Epidemiology 170(5). p.537-545
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
@article{d35d31e7-399a-45bb-910f-acc17762fa09,
  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.},
  author       = {Salanti, Georgia and Southam, Lorraine and Altshuler, David and Ardlie, Kristin and Barroso, Ines and Boehnke, Michael and Cornelis, Marilyn C. and Frayling, Timothy M. and Grallert, Harald and Grarup, Niels and Groop, Leif and Hansen, Torben and Hattersley, Andrew T. and Hu, Frank B. and Hveem, Kristian and Illig, Thomas and Kuusisto, Johanna and Laakso, Markku and Langenberg, Claudia and Lyssenko, Valeriya and McCarthy, Mark I. and Morris, Andrew and Morris, Andrew D. and Palmer, Colin N. A. and Payne, Felicity and Platou, Carl G. P. and Scott, Laura J. and Voight, Benjamin F. and Wareham, Nicholas J. and Zeggini, Eleftheria and Ioannidis, John P. A.},
  issn         = {0002-9262},
  keyword      = {Bayes theorem,type 2,meta-analysis,models,polymorphism,genetic,diabetes mellitus,population characteristics},
  language     = {eng},
  number       = {5},
  pages        = {537--545},
  publisher    = {Oxford University Press},
  series       = {American Journal of Epidemiology},
  title        = {Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations},
  url          = {http://dx.doi.org/10.1093/aje/kwp145},
  volume       = {170},
  year         = {2009},
}