Paul T Williams1. 1. Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA. Electronic address: ptwilliams@lbl.gov.
Abstract
BACKGROUND: "Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. cholesterol) is high or low relative to its distribution. We have previously shown that the effect of a 52-SNP genetic-risk score was 3-fold larger at the 90th percentile of the total cholesterol distribution than at its 10th percentile. The objective of this study is to assess quantile-dependent expressivity for total cholesterol in 7006 offspring with parents and 2112 sibships from Framingham Heart Study. METHODS: Quantile-specific heritability (h2) was estimated as twice the offspring-parent regression slope as robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. RESULTS: Quantile-specific h2 increased linearly with increasing percentiles of the offspring's cholesterol distribution (P = 3.0 × 10-9), i.e. h2 = 0.38 at the 10th percentile, h2 = 0.45 at the 25th percentile, h2 = 0.52 at the 50th, h2 = 0.61 at the 75th percentile, and h2 = 0.65 at the 90th percentile of the total cholesterol distribution. Average h2 decreased from 0.55 to 0.34 in 3564 offspring who started cholesterol-lowering medications, but this was attributable to quantile-dependent expressivity and the offspring's 0.94 mmol/L average drop in total cholesterol. Quantile-dependent expressivity likely explains the reported effect of the CELSR2/PSRC1/SORT1 rs646776 and APOE rs7412 gene loci on statin efficacy. Specifically, a smaller genetic effect size at the lower (post-treatment) than higher (pre-treatment) cholesterol concentrations mandates that the trajectories of the genotypes cannot move in parallel when cholesterol is decreased pharmacologically. CONCLUSION: Cholesterol concentrations exhibit quantile-dependent expressivity, which may provide an alternative interpretation to pharmacogenetic and nutrigenetic interactions. Published by Elsevier B.V.
BACKGROUND: "Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. cholesterol) is high or low relative to its distribution. We have previously shown that the effect of a 52-SNP genetic-risk score was 3-fold larger at the 90th percentile of the total cholesterol distribution than at its 10th percentile. The objective of this study is to assess quantile-dependent expressivity for total cholesterol in 7006 offspring with parents and 2112 sibships from Framingham Heart Study. METHODS: Quantile-specific heritability (h2) was estimated as twice the offspring-parent regression slope as robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. RESULTS: Quantile-specific h2 increased linearly with increasing percentiles of the offspring's cholesterol distribution (P = 3.0 × 10-9), i.e. h2 = 0.38 at the 10th percentile, h2 = 0.45 at the 25th percentile, h2 = 0.52 at the 50th, h2 = 0.61 at the 75th percentile, and h2 = 0.65 at the 90th percentile of the total cholesterol distribution. Average h2 decreased from 0.55 to 0.34 in 3564 offspring who started cholesterol-lowering medications, but this was attributable to quantile-dependent expressivity and the offspring's 0.94 mmol/L average drop in total cholesterol. Quantile-dependent expressivity likely explains the reported effect of the CELSR2/PSRC1/SORT1 rs646776 and APOE rs7412 gene loci on statin efficacy. Specifically, a smaller genetic effect size at the lower (post-treatment) than higher (pre-treatment) cholesterol concentrations mandates that the trajectories of the genotypes cannot move in parallel when cholesterol is decreased pharmacologically. CONCLUSION: Cholesterol concentrations exhibit quantile-dependent expressivity, which may provide an alternative interpretation to pharmacogenetic and nutrigenetic interactions. Published by Elsevier B.V.
Authors: L Pisciotta; A Cantafora; A Piana; P Masturzo; R Cerone; G Minniti; A Bellocchio; E Reggiani; U Armani; S Bertolini Journal: Nutr Metab Cardiovasc Dis Date: 2003-08 Impact factor: 4.222