Abstract
The heritability of a phenotype is an estimation of the percent of variance in that phenotype that is attributable to additive genetic factors. Heritability is optimally estimated in family-based sample populations. Traditionally, this involves use of a pedigree-based kinship coefficient generated from the collected genealogical relationships between family members. An alternative, when dense genotype data are available, is to directly measure the empirical kinship between samples. This study compares the use of pedigree and empirical kinships in the GAW20 data set. Two phenotypes were assessed: triglyceride levels and high-density lipoprotein cholesterol (HDL-C) levels pre- and postintervention with the cholesterol-reducing drug fenofibrate. Using SOLAR (Sequential Oligogenic Linkage Analysis Routines), pedigree-based kinships and empirically calculated kinships (using IBDLD and LDAK) were used to calculate phenotype heritability. In addition, a genome-wide association study was conducted using each kinship model for each phenotype to identify genetic variants significantly associated with phenotypic variation. The variant rs247617 was significantly associated with HDL-C levels both pre- and post-fenofibrate intervention. Overall, the phenotype heritabilities calculated using pedigree based kinships or either of the empirical kinships generated using IBDLD or LDAK were comparable. Phenotype heritabilities estimated from empirical kinships generated using IBDLD were closest to the pedigree-based estimations. Given that there was not an appreciable amount of unknown relatedness between the pedigrees in this data set, a large increase in heritability in using empirical kinship was not expected, and our calculations support this. Importantly, these results demonstrate that when sufficient genotypic data are available, empirical kinship estimation is a practical alternative to using pedigree-based kinships.
Highlights
SOLAR (Sequential Oligogenic Linkage Analysis Routines) [1], software developed for the genetic analysis of pedigrees, can be used to calculate the heritability (h2) of a phenotype
Measured genotype analysis Single-variant association testing was conducted using measured genotype analysis (MGA) in SOLAR for the 718,407 single-nucleotide polymorphism (SNP) available for analysis in the GAW20 data set. This analysis takes into account the nonindependence of participants, using the kinship matrix, incorporating each SNP separately into the analysis model as a covariate measured as a genotype dosage (0, 1, 2) and evaluating the genotype-specific difference in the phenotype means
Heritability of triglyceride and high-density lipoprotein cholesterol (HDL-C) levels pre- and post-fenofibrate intervention, using SOLAR with pedigree-based and empirical kinship Heritability estimates using SOLAR identified that both triglyceride levels and HDL-C were significantly and highly heritable pre- and post-fenofibrate intervention (Table 2), regardless of whether IBDLD, LDAK, or pedigree kinship was used
Summary
SOLAR (Sequential Oligogenic Linkage Analysis Routines) [1], software developed for the genetic analysis of pedigrees, can be used to calculate the heritability (h2) of a phenotype. This calculation requires the phenotype measurement, relevant covariates, and a kinship matrix. The kinship matrix is derived from a carefully curated pedigree (or pedigrees) joining together the individuals with phenotypes by their self-reported genealogical relationships. The use of self-reported genealogical relationships has one Accurate biological relationships are necessary for the calculation of phenotype heritability. Where individuals are unrelated in a pedigree kinship matrix, some level of empirical kinship can be calculated for all pairs in the data set
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