Recent methodological developments offer alternatives to estimate heritability via SNPs. Thus, contributions from both C and D components might very well coexist but “mask” each other, so that the net effect appears as contribution from neither. Positive contributions to this deviance will stem from dominance (interactions between alleles within the same locus), epistasis (interactions between different loci), as well as other types of higher-order interactions, whereas negative contributions will arise from shared environmental factors. With this follows that whenever D is indicated in the twin model, it does lend support to contribution from D, but the magnitude will represent the total net deviance from a pure additive genetic model. This is because the model is under-informed to allow quantification of more than one source to deviance from pure additivity, even if it exists. As in any family-based modeling, classic twin studies rely on certain important assumptions, the most debated being that MZ and DZ twins share their raising environment to the same extent.Ī further complication in the classic twin model is that C and D cannot be estimated simultaneously. 2, 5 The sum of additive and dominant genetic proportions of variance is often referred to as the broad-sense heritability.
Observed intra-pair correlations among genetically identical, monozygotic (MZ) twins and fraternal, dizygotic (DZ) twins are contrasted in order to partition the phenotypic variance into additive (A) genetic variance-so called narrow-sense heritability (h 2), dominant genetic variance (D), and shared (C) and non-shared (E) environmental variance. 3, 4 The classic twin study, often implemented using structural equation modeling (SEM), is the most commonly used family-based approach. They are based either on modeling of family correlations in related subjects 2 (distributions of trait similarities among various types of relatives) or on molecular measurements in related or unrelated subjects. 1 Several methods can be used to estimate heritability. Heritability is a concept used to denote the relative importance of genetic influences to variability of diseases or complex traits and is loosely defined as the proportion of the phenotypic variance attributed to inherited genetic effects. The risk of erroneously attributing all inherited genetic influences (additive and dominant) to the h 2 in too-small twin studies might also lead to exaggerated “missing heritability” (the proportion of h 2 that remains unexplained by SNPs). We conclude that despite the fact that additive genetics appear to constitute the bulk of genetic influences for most complex traits, dominant genetic variation might often be masked by shared environment in twin and family studies and might therefore have a more prominent role than what family-based estimates often suggest. Independent evidence for contribution from shared environment, also in ADE-fitted traits, was obtained from self-reported within-pair contact frequency and age at separation. On average, the proportion of h 2 SNP/h 2 twin was 70% for ADE-fitted traits (for which the best-fitting model included additive and dominant genetic and unique environmental components) and 31% for AE-fitted traits (for which the best-fitting model included additive genetic and unique environmental components). Contributions of δ 2 were evident for 14 traits in twin models (average δ 2 twin = 0.25, range 0.14–0.49), two of which also displayed significant δ 2 in the GREMLd analyses (triglycerides δ 2 SNP = 0.28 and waist circumference δ 2 SNP = 0.19). Within the same study base (10,682 Swedish twins), we calculated and compared the estimates from classic twin-based structural equation model with SNP-based genomic-relatedness-matrix restricted maximum likelihood method. In order to further illuminate the potential role of dominant genetic variation in the “missing heritability” debate, we investigated the additive (narrow-sense heritability, h 2) and dominant (δ 2) genetic variance for 18 human complex traits.