Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations

Georgia Salanti, Lorraine Southam, David Altshuler, Kristin Ardlie, Ines Barroso, Michael Boehnke, Marilyn C. Cornelis, Timothy M. Frayling, Harald Grallert, Niels Grarup, Leif Groop, Torben Hansen, Andrew T. Hattersley, Frank B. Hu, Kristian Hveem, Thomas Illig, Johanna Kuusisto, Markku Laakso, Claudia Langenberg, Valeriya Lyssenko & 11 others Mark I. McCarthy, Andrew Morris, Andrew D. Morris, Colin N. A. Palmer, Felicity Payne, Carl G. P. Platou, Laura J. Scott, Benjamin F. Voight, Nicholas J. Wareham, Eleftheria Zeggini, John P. A. Ioannidis

    Research output: Contribution to journalReview article

    45 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)537-545
    Number of pages9
    JournalAmerican Journal of Epidemiology
    Volume170
    Issue number5
    DOIs
    Publication statusPublished - 1 Sep 2009

    Keywords

    • Bayes theorem
    • diabetes mellitus
    • type 2
    • meta-analysis
    • models
    • genetic
    • polymorphism
    • genetic
    • population characteristics
    • GENOME-WIDE ASSOCIATION
    • MOLECULAR ASSOCIATION
    • METAANALYSIS
    • REPLICATION
    • LOCI
    • POLYMORPHISMS
    • EPIDEMIOLOGY
    • CHALLENGES
    • VARIANTS
    • DISEASE

    Cite this

    Salanti, G., Southam, L., Altshuler, D., Ardlie, K., Barroso, I., Boehnke, M., ... Ioannidis, J. P. A. (2009). Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations. American Journal of Epidemiology, 170(5), 537-545. https://doi.org/10.1093/aje/kwp145
    Salanti, Georgia ; Southam, Lorraine ; Altshuler, David ; Ardlie, Kristin ; Barroso, Ines ; Boehnke, Michael ; Cornelis, Marilyn C. ; Frayling, Timothy M. ; Grallert, Harald ; Grarup, Niels ; Groop, Leif ; Hansen, Torben ; Hattersley, Andrew T. ; Hu, Frank B. ; Hveem, Kristian ; Illig, Thomas ; Kuusisto, Johanna ; Laakso, Markku ; Langenberg, Claudia ; Lyssenko, Valeriya ; McCarthy, Mark I. ; Morris, Andrew ; Morris, Andrew D. ; Palmer, Colin N. A. ; Payne, Felicity ; Platou, Carl G. P. ; Scott, Laura J. ; Voight, Benjamin F. ; Wareham, Nicholas J. ; Zeggini, Eleftheria ; Ioannidis, John P. A. / Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations. In: American Journal of Epidemiology. 2009 ; Vol. 170, No. 5. pp. 537-545.
    @article{75e1ed28c7d143edae06df174706d217,
    title = "Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations",
    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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    author = "Georgia Salanti and Lorraine Southam and David Altshuler and Kristin Ardlie and Ines Barroso and Michael Boehnke and Cornelis, {Marilyn C.} and Frayling, {Timothy M.} and Harald Grallert and Niels Grarup and Leif Groop and Torben Hansen and Hattersley, {Andrew T.} and Hu, {Frank B.} and Kristian Hveem and Thomas Illig and Johanna Kuusisto and Markku Laakso and Claudia Langenberg and Valeriya Lyssenko and McCarthy, {Mark I.} and Andrew Morris and Morris, {Andrew D.} and Palmer, {Colin N. A.} and Felicity Payne and Platou, {Carl G. P.} and Scott, {Laura J.} and Voight, {Benjamin F.} and Wareham, {Nicholas J.} and Eleftheria Zeggini and Ioannidis, {John P. A.}",
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    Salanti, G, Southam, L, Altshuler, D, Ardlie, K, Barroso, I, Boehnke, M, Cornelis, MC, Frayling, TM, Grallert, H, Grarup, N, Groop, L, Hansen, T, Hattersley, AT, Hu, FB, Hveem, K, Illig, T, Kuusisto, J, Laakso, M, Langenberg, C, Lyssenko, V, McCarthy, MI, Morris, A, Morris, AD, Palmer, CNA, Payne, F, Platou, CGP, Scott, LJ, Voight, BF, Wareham, NJ, Zeggini, E & Ioannidis, JPA 2009, 'Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations', American Journal of Epidemiology, vol. 170, no. 5, pp. 537-545. https://doi.org/10.1093/aje/kwp145

    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; Grarup, Niels; Groop, Leif; Hansen, Torben; Hattersley, Andrew T.; Hu, Frank B.; Hveem, Kristian; Illig, Thomas; Kuusisto, Johanna; Laakso, Markku; Langenberg, Claudia; Lyssenko, Valeriya; McCarthy, Mark I.; Morris, Andrew; Morris, Andrew D.; Palmer, Colin N. A.; Payne, Felicity; Platou, Carl G. P.; Scott, Laura J.; Voight, Benjamin F.; Wareham, Nicholas J.; Zeggini, Eleftheria; Ioannidis, John P. A.

    In: American Journal of Epidemiology, Vol. 170, No. 5, 01.09.2009, p. 537-545.

    Research output: Contribution to journalReview article

    TY - JOUR

    T1 - Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations

    AU - Salanti, Georgia

    AU - Southam, Lorraine

    AU - Altshuler, David

    AU - Ardlie, Kristin

    AU - Barroso, Ines

    AU - Boehnke, Michael

    AU - Cornelis, Marilyn C.

    AU - Frayling, Timothy M.

    AU - Grallert, Harald

    AU - Grarup, Niels

    AU - Groop, Leif

    AU - Hansen, Torben

    AU - Hattersley, Andrew T.

    AU - Hu, Frank B.

    AU - Hveem, Kristian

    AU - Illig, Thomas

    AU - Kuusisto, Johanna

    AU - Laakso, Markku

    AU - Langenberg, Claudia

    AU - Lyssenko, Valeriya

    AU - McCarthy, Mark I.

    AU - Morris, Andrew

    AU - Morris, Andrew D.

    AU - Palmer, Colin N. A.

    AU - Payne, Felicity

    AU - Platou, Carl G. P.

    AU - Scott, Laura J.

    AU - Voight, Benjamin F.

    AU - Wareham, Nicholas J.

    AU - Zeggini, Eleftheria

    AU - Ioannidis, John P. A.

    PY - 2009/9/1

    Y1 - 2009/9/1

    N2 - 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.

    AB - 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.

    KW - Bayes theorem

    KW - diabetes mellitus

    KW - type 2

    KW - meta-analysis

    KW - models

    KW - genetic

    KW - polymorphism

    KW - genetic

    KW - population characteristics

    KW - GENOME-WIDE ASSOCIATION

    KW - MOLECULAR ASSOCIATION

    KW - METAANALYSIS

    KW - REPLICATION

    KW - LOCI

    KW - POLYMORPHISMS

    KW - EPIDEMIOLOGY

    KW - CHALLENGES

    KW - VARIANTS

    KW - DISEASE

    U2 - 10.1093/aje/kwp145

    DO - 10.1093/aje/kwp145

    M3 - Review article

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    SP - 537

    EP - 545

    JO - American Journal of Epidemiology

    JF - American Journal of Epidemiology

    SN - 0002-9262

    IS - 5

    ER -

    Salanti G, Southam L, Altshuler D, Ardlie K, Barroso I, Boehnke M et al. Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations. American Journal of Epidemiology. 2009 Sep 1;170(5):537-545. https://doi.org/10.1093/aje/kwp145