A hybrid design for studying genetic influences on risk of diseases with onset early in life

Abstract

Studies of genetic contributions to risk can be family-based, such as the case-parents design, or population-based, such as the case-control design. Both provide powerful inference regarding associations between genetic variants and risks, but both have limitations. The case-control design requires identifying and recruiting appropriate controls, but it has the advantage that nongenetic risk factors like exposures can be assessed. For a condition with an onset early in life, such as a birth defect, one should also genotype the mothers of cases and the mothers of controls to avoid potential confounding due to maternally mediated genetic effects acting on the fetus during gestation. The case-parents approach is less vulnerable than the case-mother/control-mother approach to biases due to population structure and self-selection. The case-parents approach also allows access to epigenetic phenomena like imprinting, but it cannot evaluate the role of nongenetic cofactors like exposures. We propose a hybrid design based on augmenting a set of affected individuals and their parents with a set of unaffected, unrelated individuals and their parents. The affected individuals and their parents are all genotyped, whereas only the parents of unaffected individuals are genotyped, although exposures are ascertained for both affected and unaffected offspring. The proposed hybrid design, through log-linear, likelihood-based analysis, allows estimation of the relative risk parameters, can provide more power than either the case-parents approach or the case-mother/control-mother approach, permits straightforward likelihood-ratio tests for bias due to mating asymmetry or population stratification, and admits valid alternative analyses when mating is asymmetric or when population stratification is detected.

Figure 1

χ² noncentrality parameters for a likelihood-ratio test of the four genetic risk parameters based on a scenario with an offspring-mediated effect (R₁=2; R₂=3) and no maternally mediated effects (S₁=1=S₂). The calculations assume Hardy-Weinberg equilibrium and use 150 cases for each design. To calculate corresponding noncentrality parameters for a different number, N, of cases, multiply the value shown by N/150. Solid dark curve, hybrid design (Hybrid MS and MA analyses coincide when there are no maternal effects), five individuals genotyped per case. Solid light curve, Epstein et al. (2005) design, four individuals genotyped per case. Dotted curve, case-parents design, three individuals genotyped per case. Dashed curve, case-mother/control-mother design, four individuals genotyped per case. Horizontal reference lines indicate power at α=0.05.

Figure 2

χ² noncentrality parameters for a likelihood-ratio test of the four genetic risk parameters based on a scenario with an offspring-mediated recessive effect (R₁=1, R₂=3) and no maternally mediated effects (S₁=1=S₂). The calculations assume Hardy-Weinberg equilibrium and use 150 cases for each design. To calculate corresponding noncentrality parameters for a different number, N, of cases, multiply the value shown by N/150. Solid dark curve, hybrid design (Hybrid MS and MA analyses coincide when there are no maternal effects), five individuals genotyped per case. Solid light curve, Epstein et al. (2005) design, four individuals genotyped per case. Dotted curve, case-parents design, three individuals genotyped per case. Dashed curve, case-mother/control-mother design, four individuals genotyped per case. Horizontal reference lines indicate power at α=0.05.

Figure 3

χ² noncentrality parameters for a likelihood-ratio test of the four genetic risk parameters based on a scenario with an offspring-mediated recessive effect (R₁=1; R₂=2) and a maternally mediated recessive effect (S₁=1; S₂=3). The calculations assume Hardy-Weinberg equilibrium and use 150 cases for each design. To calculate corresponding noncentrality parameters for a different number, N, of cases, multiply the value shown by N/150. Solid dark curve, Hybrid MS, five individuals genotyped per case. Long dash curve, Hybrid MA. Solid light curve, Epstein et al. (2005) design, four individuals genotyped per case. Dotted curve, case-parents design, three individuals genotyped per case. Dashed curve, case-mother/control-mother design, four individuals genotyped per case. Horizontal reference lines indicate power at α=0.05.

Figure 4

χ² noncentrality parameters for a likelihood-ratio test of the four genetic risk parameters based on a scenario with an offspring-mediated recessive effect (R₁=1; R₂=3) and a maternally mediated dominant effect (S₁=2; S₂=2). The calculations assume Hardy-Weinberg equilibrium and use 150 cases for each design. To calculate corresponding noncentrality parameters for a different number, N, of cases, multiply the value shown by N/150. Solid dark curve, Hybrid MS, five individuals genotyped per case. Long dash curve, Hybrid MA. Solid light curve, Epstein et al. (2005) design, four individuals genotyped per case. Dotted curve, case-parents design, three individuals genotyped per case. Dashed curve, case-mother/control-mother design, four individuals genotyped per case. Horizontal reference lines indicate power at α=0.05.