Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution

Abstract

Background “Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and the FEV1/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h2) is constant over all quantiles of their distribution. Methods Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (βOP), offspring-midparent (βOM), and full-sib regression slopes (βFS). Nonparametric significance levels were obtained from 1,000 bootstrap samples. βOPs were used as simple indicators of quantile-specific heritability (i.e., h2 = 2βOP/(1+rspouse), where rspouse was the correlation between spouses). Results βOP ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV1/FVC, i.e., βOP ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV1/FVC distribution, respectively. These correspond to h2 ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV1/FVC ratio. Maximum mid-expiratory flow (MMEF) h2 ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h2 increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h2, i.e., greater heritability in individuals with lower FEV1/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals. Conclusion Heritabilities of FEV1/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity.

Quantile-specific heritability of sibling leptin concentrations and its implications for gene-environment interactions

“…The methods have been described previously [25][26][27][28][29][30][31][32][33] , but are repeated here for completeness. The data were obtained from the National Institutes of Health FRAMCOHORT, GEN3, FRAMOFFSPRING Research Materials obtained from the National Heart Lung and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center.…”

Quantile-dependent expressivity of plasma adiponectin concentrations may explain its sex-specific heritability, gene-environment interactions, and genotype-specific response to postprandial lipemia

“…The methods have been described previously (Williams, 2020c;Williams, 2020e;Williams, 2020a;Williams, 2020g), but are repeated here for completeness. The data were obtained from the National Institutes of Health FRAMCOHORT, GEN3, FRAMOFFSPRING Research Materials obtained from the National Heart Lung and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center.…”

“…This is in contrast to the traditional estimate of a genetic effect size that is assumed to be constant across all population percentiles. Quantile-dependent expressivity has been demonstrated for adiposity ( Williams, 2012 ; Williams, 2020c ), lipoproteins ( Williams, 2012 ; Williams, 2020e ; Williams, 2020a ), pulmonary function ( Williams, 2020g ), coffee intake ( Williams, 2020d ), and alcohol intake ( Williams, 2020f ). Moreover, the genetic effect sizes of single nucleotide polymorphisms (SNPs) affecting triglycerides have been shown to increase and decrease within individuals in accordance with increasing and decreasing postprandial triglyceride concentrations, consistent with quantile-dependent expressivity ( Williams, 2020b ).…”

Quantile-dependent expressivity of serum C-reactive protein concentrations in family sets

“…“Quantile-dependent expressivity” postulates that the effects of genetic variants on phenotypes may depend on the whether the phenotype (e.g., CRP concentration) is high or low relative to its distribution. The heritability of adiposity ( Williams, 2012 , 2020a ); plasma concentrations of triglyceride ( Williams, 2012 , 2020b ), high-density lipoproteins ( Williams, 2012 , 2020c , 2020d ), total cholesterol ( Williams, 2020e ), leptin ( Williams, 2020f ), and adiponection ( Williams, 2020g ); pulmonary function ( Williams, 2020h ); and intakes of alcohol ( Williams, 2020i ) and coffee ( Williams, 2020j ) are quantile dependent, whereas height and the intakes of other macronutrients are not ( Williams, 2012 , 2020a , 2020i ). Others have also demonstrated increasing genetic effect size with increasing BMI levels ( Rokholm et al, 2011 ; Abadi et al, 2012 ; Beyerlein et al, 2011 ; Mitchell et al, 2013 ).…”