Quantile-Dependent Expressivity of Serum Uric Acid Concentrations

Abstract

Objective. “Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., serum uric acid) is high or low relative to its distribution. Analyses were performed to test whether serum uric acid heritability is quantile-specific and whether this could explain some reported gene-environment interactions. Methods. Serum uric acid concentrations were analyzed from 2151 sibships and 12,068 offspring-parent pairs from the Framingham Heart Study. Quantile-specific heritability from offspring-parent regression slopes ( β OP , h 2 = 2 β OP / 1 + r spouse ) and full-sib regression slopes ( β FS , h 2 = 1 + 8 r spouse β FS 0.5 − 1 / 2 r spouse ) was robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. Results. Quantile-specific h 2 (±SE) increased with increasing percentiles of the offspring’s sex- and age-adjusted uric acid distribution when estimated from β OP P trend = 0.001 : 0.34 ± 0.03 at the 10th, 0.36 ± 0.03 at the 25th, 0.41 ± 0.03 at the 50th, 0.46 ± 0.04 at the 75th, and 0.49 ± 0.05 at the 90th percentile and when estimated from β FS P trend = 0.006 . This is consistent with the larger genetic effect size of (1) the SLC2A9 rs11722228 polymorphism in gout patients vs. controls, (2) the ABCG2 rs2231142 polymorphism in men vs. women, (3) the SLC2A9 rs13113918 polymorphism in obese patients prior to bariatric surgery vs. two-year postsurgery following 29 kg weight loss, (4) the ABCG2 rs6855911 polymorphism in obese vs. nonobese women, and (5) the LRP2 rs2544390 polymorphism in heavier drinkers vs. abstainers. Quantile-dependent expressivity may also explain the larger genetic effect size of an SLC2A9/PKD2/ABCG2 haplotype for high vs. low intakes of alcohol, chicken, or processed meats. Conclusions. Heritability of serum uric acid concentrations is quantile-specific.

Quantile-Specific Heritability of Inflammatory and Oxidative Stress Biomarkers Linked to Cardiovascular Disease

“…The statistical analyses have been described elsewhere, [12][13][14][15][16][17][18][19][20][21][22][23][24][25] and summarized briefly here. Individual subject values are the average of the age-and sex-adjusted concentrations over all available exams.…”

“…11 "Quantile-dependent expressivity" refers to the phenotypic expression of a genetic variant being dependent on whether the trait is high or low relative to its distribution. 12 For example, the heritability of total and HDL cholesterol, [13][14][15] triglycerides, 16 leptin, 17 glucose, 18 insulin, 18 uric acid 19 and adiponectin concentrations, 20 coffee and alcohol consumption, 21,22 adiposity, 12,23 and postprandial lipemia 24 increase with increasing quantiles of each trait, whereas intakes of other macronutrients and height do not. 12,22,23 One potential consequence of quantile-dependent expressivity is that sampling by characteristics that distinguish high-vs low-valued phenotypes may produce genetic differences traditionally ascribed to geneenvironment, gene-drug and gene-diet interactions when a simpler explanation of quantile-dependence might suffice.…”