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Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease.

Lanktree MB, Hegele RA - Genome Med (2009)

Bottom Line: In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions.For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies.Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departments of Medicine and Biochemistry, Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8, Canada.

ABSTRACT
Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

No MeSH data available.


Related in: MedlinePlus

Putative gene-environment interactions. For even the simplest case, a dichotomous genetic risk factor (for example, carriers versus non-carriers) and a dichotomous environmental risk factor (for example, present versus absent), several types of interactions are possible. If both the gene and environment have main effects (odds ratios > 1), and thus could be identified independently, a synergistic interaction would result in an effect size larger than a simple additive effect. A second possibility is that an environmental factor could have no main effect but could modify the effect of a genetic factor that does have a main effect, creating a larger than expected combined effect. The inverse is also possible, in which a modifier gene with no main effect of its own increases the effect size of an environmental risk factor. A fourth possibility is that neither the gene nor the environment has a detectable main effect, and interaction is required to produce a measurable effect. A fifth possibility is for a gene and an environmental factor to have redundant effects, in which case the combination of factors produces no increase in risk. These types of interactions can be extended to include different effect sizes or gene-gene interactions.
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Figure 2: Putative gene-environment interactions. For even the simplest case, a dichotomous genetic risk factor (for example, carriers versus non-carriers) and a dichotomous environmental risk factor (for example, present versus absent), several types of interactions are possible. If both the gene and environment have main effects (odds ratios > 1), and thus could be identified independently, a synergistic interaction would result in an effect size larger than a simple additive effect. A second possibility is that an environmental factor could have no main effect but could modify the effect of a genetic factor that does have a main effect, creating a larger than expected combined effect. The inverse is also possible, in which a modifier gene with no main effect of its own increases the effect size of an environmental risk factor. A fourth possibility is that neither the gene nor the environment has a detectable main effect, and interaction is required to produce a measurable effect. A fifth possibility is for a gene and an environmental factor to have redundant effects, in which case the combination of factors produces no increase in risk. These types of interactions can be extended to include different effect sizes or gene-gene interactions.

Mentions: Broadly defined, interactions are differences in the strength of association between a gene and phenotype on the basis of the presence of, absence of or quantitative differences in an additional factor, which could be another genetic variant or an environmental exposure. There are several putative models for gene-environment interactions, including synergy, modification of effects and redundancy (Figure 2). For a gene-gene interaction, the additional factor might be dichotomous, such as carrier versus non-carrier status, or additive, such as zero, one or two copies of the minor allele. For a gene-environment interaction, the additional factor can similarly be dichotomous, such as presence or absence of smoking history, or it can be a continuous variable, such as number of pack-years smoked.


Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease.

Lanktree MB, Hegele RA - Genome Med (2009)

Putative gene-environment interactions. For even the simplest case, a dichotomous genetic risk factor (for example, carriers versus non-carriers) and a dichotomous environmental risk factor (for example, present versus absent), several types of interactions are possible. If both the gene and environment have main effects (odds ratios > 1), and thus could be identified independently, a synergistic interaction would result in an effect size larger than a simple additive effect. A second possibility is that an environmental factor could have no main effect but could modify the effect of a genetic factor that does have a main effect, creating a larger than expected combined effect. The inverse is also possible, in which a modifier gene with no main effect of its own increases the effect size of an environmental risk factor. A fourth possibility is that neither the gene nor the environment has a detectable main effect, and interaction is required to produce a measurable effect. A fifth possibility is for a gene and an environmental factor to have redundant effects, in which case the combination of factors produces no increase in risk. These types of interactions can be extended to include different effect sizes or gene-gene interactions.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2664961&req=5

Figure 2: Putative gene-environment interactions. For even the simplest case, a dichotomous genetic risk factor (for example, carriers versus non-carriers) and a dichotomous environmental risk factor (for example, present versus absent), several types of interactions are possible. If both the gene and environment have main effects (odds ratios > 1), and thus could be identified independently, a synergistic interaction would result in an effect size larger than a simple additive effect. A second possibility is that an environmental factor could have no main effect but could modify the effect of a genetic factor that does have a main effect, creating a larger than expected combined effect. The inverse is also possible, in which a modifier gene with no main effect of its own increases the effect size of an environmental risk factor. A fourth possibility is that neither the gene nor the environment has a detectable main effect, and interaction is required to produce a measurable effect. A fifth possibility is for a gene and an environmental factor to have redundant effects, in which case the combination of factors produces no increase in risk. These types of interactions can be extended to include different effect sizes or gene-gene interactions.
Mentions: Broadly defined, interactions are differences in the strength of association between a gene and phenotype on the basis of the presence of, absence of or quantitative differences in an additional factor, which could be another genetic variant or an environmental exposure. There are several putative models for gene-environment interactions, including synergy, modification of effects and redundancy (Figure 2). For a gene-gene interaction, the additional factor might be dichotomous, such as carrier versus non-carrier status, or additive, such as zero, one or two copies of the minor allele. For a gene-environment interaction, the additional factor can similarly be dichotomous, such as presence or absence of smoking history, or it can be a continuous variable, such as number of pack-years smoked.

Bottom Line: In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions.For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies.Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departments of Medicine and Biochemistry, Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8, Canada.

ABSTRACT
Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

No MeSH data available.


Related in: MedlinePlus