Quantile-specific heritability of high-density lipoproteins with implications for precision medicine

Quantile-Dependent Expressivity of Serum Interleukin-6 Concentrations as a Possible Explanation of Gene-Disease Interactions, Gene-Environment Interactions, and Pharmacogenetic Effects

Interleukin 6 (IL-6) is a moderately heritable pleiotropic cytokine whose elevated concentrations in coronary artery disease, peripheral arterial disease, pulmonary arterial hypertension, Eales' disease, Sjògren's syndrome, osteoarthritis, adenocarcinoma, neuroblastoma, polymyalgia rheumatica, pulmonary tuberculosis, and enterovirus 71 infection, and following coronary artery bypass graft show larger genetic effects than in unaffected low IL-6 controls. We hypothesize that genetic effects may depend upon whether average IL-6 concentrations are high or low, i.e., quantile-dependent expressivity. Quantile-specific offspring-parent (βOP) and full-sib regression slopes (βFS) were estimated by applying quantile regression to the age- and sex-adjusted serum IL-6 concentrations in families surveyed in the Framingham Heart Study. Quantile-specific heritabilities were calculated as h2 = 2βOP / (1 + rspouse) and h2 = {(1 + 8rspouseβFS)0.5 -1} / (2rspouse)). Heritability (h2 ± SE) of IL-6 concentrations increased from 0.01 ± 0.01 at the 10th percentile (NS), 0.02 ± 0.01 at the 25th (P = 0.009), 0.03 ± 0.01 at the 50th (P = 0.007), 0.04 ± 0.02 at the 75th (P = 0.004), and 0.13 ± 0.05 at the 90th percentile (P = 0.03), or 0.0005 ± 0.0002 for each 1% increase in the offspring's phenotype distribution (Plinear trend = 0.02) when estimated from βOP and from 0.02 ± 0.02 at the 10th (NS), 0.02 ± 0.02 at the 25th (NS), 0.06 ± 0.02 at the 50th (P = 0.01), 0.12 ± 0.04 at the 75th (P = 0.001), and 0.30 ± 0.03 at the 90th percentile (P < 10-16), or 0.0015 ± 0.0007 for each 1% increase in the sibling phenotype distribution (Plinear trend = 0.02) when estimated from βFS. Thus the heritability of serum IL-6 concentrations is quantile dependent, which may contribute in part to the larger genetic effect size reported for diseases and environmental conditions that elevate IL-6 concentrations vis-à-vis unaffected controls.

Quantile-specific heritability of plasma fibrinogen concentrations

Background

Fibrinogen is a moderately heritable blood protein showing different genetic effects by sex, race, smoking status, pollution exposure, and disease status. These interactions may be explained in part by “quantile-dependent expressivity”, where the effect size of a genetic variant depends upon whether the phenotype (e.g. plasma fibrinogen concentration) is high or low relative to its distribution.

Purpose

Determine whether fibrinogen heritability (h²) is quantile-specific, and whether quantile-specific h² could account for fibrinogen gene-environment interactions.

Methods

Plasma fibrinogen concentrations from 5689 offspring-parent pairs and 1932 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β_OP, h² = 2β_OP/(1+r_spouse)) and full-sib regression slopes (β_FS, h² = {(1+8r_spouseβ_FS)^0.05–1}/(2r_spouse)) were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples.

Results

Quantile-specific h² (±SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted fibrinogen distribution when estimated from β_OP (P_trend = 5.5x10^-6): 0.30±0.05 at the 10^th, 0.37±0.04 at the 25^th, 0.48±0.05 at the 50^th, 0.61±0.06 at the 75^th, and 0.65±0.08 at the 90^th percentile, and when estimated from β_FS (P_trend = 0.008): 0.28±0.04 at the 10^th, 0.31±0.04 at the 25^th, 0.36±0.03 at the 50^th, 0.41±0.05 at the 75^th, and 0.50±0.06 at the 90^th percentile. The larger genetic effect at higher average fibrinogen concentrations may contribute to fibrinogen’s greater heritability in women than men and in Blacks than Whites, and greater increase from smoking and air pollution for the FGB -455G>A A-allele. It may also explain greater fibrinogen differences between: 1) FGB -455G>A genotypes during acute phase reactions than usual conditions, 2) GTSM1 and IL-6 -572C>G genotypes in smokers than nonsmokers, 3) FGB -148C>T genotypes in untreated than treated diabetics, and LPL PvuII genotypes in macroalbuminuric than normoalbuminuric patients.

Conclusion

Fibrinogen heritability is quantile specific, which may explain or contribute to its gene-environment interactions. The analyses do not disprove the traditional gene-environment interpretations of these examples, rather quantile-dependent expressivity provides an alternative explanation that warrants consideration.

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

PURPOSE

Heritability (h2 , the proportion of the phenotypic variance attributable to additive genetic effects) is traditionally assumed to be constant throughout the distribution of the phenotype. However, the heritabilities of circulating C-reactive protein, interleukin-6, plasminogen activator inhibitor type-1 (PAI-1), and monocyte chemoattractant protein-1 (MCP-1) concentrations depend upon whether the phenotype is high or low relative to their distributions (quantile-dependent expressivity), which may account for apparent gene-environment interactions. Whether the heritabilities of other inflammatory biomarkers linked to cardiovascular disease are quantile-dependent remain to be determined.

PATIENTS AND METHODS

Quantile-specific offspring-parent (βOP) and full-sib regression slopes (βFS) were estimated by applying quantile regression to the age- and sex-adjusted phenotypes of families surveyed as part of the Framingham Heart Study. Quantile-specific heritabilities were calculated as: h2 =2βOP/(1+rspouse) and h2 ={(1+8rspouseβFS)0.5-1}/(2rspouse).

RESULTS

Heritability (h2 ± SE) of lipoprotein-associated phospholipase A2 (Lp-PLA2) mass concentrations increased from 0.11 ± 0.03 at the 10th percentile, 0.08 ± 0.03 at the 25th, 0.12 ± 0.03 at the 50th, 0.20 ± 0.04 at the 75th, and 0.26 ± 0.06 at the 90th percentile, or 0.0023 ± 0.0006 per each one-percent increase in the phenotype distribution (Plinear trend= 0.0004). Similarly, h2 increased 0.0029 ± 0.0011 (Plinear trend= 0.01) for sP-selectin, 0.0032 ± 0.0009 (Plinear trend= 0.0001) for soluble intercellular adhesion molecule 1 (sICAM-1), and 0.0026 ± 0.0006 for tumor necrosis factor receptor 2 (TNFR2) (Plinear trend= 5.0 × 10-6) per each one-percent increase in their distributions when estimated from βOP. Osteoprotegerin and soluble ST2 heritability also increased significantly with increasing percentiles of their distributions when estimated from βFS. Lp-PLA2 activity, CD40 ligand, TNFα, interleukin-18, and myeloperoxidase heritability showed no significant quantile-dependence.

CONCLUSION

The heritabilities of circulating Lp-PLA2-mass, sP-selectin, sICAM-1, TNFR2, osteoprotegerin and soluble ST2 concentrations are quantile-dependent, which may contribute to purported genetic modulations of: 1) sP-selectin's relationships to venous thrombosis, pulmonary hypertension, type 2 diabetes and atorvastatin treatment; 2) sICAM-I's relationships to brain abscess and atorvastatin treatment; and 3) Lp-PLA2's relationships to myocardial infarction and preeclampsia.

Quantile-specific heritability of 8-isoprostane and the modulating effects of smoking, alcohol, cardiovascular disease and diabetes on 8-isoprostane-gene interactions

BACKGROUND

Urinary 8-isoprostane provides a significantly heritable measure of oxidative stress. Prior reports suggest that genetic variants may modulate oxidative stress due to smoking, other environmental factors, and disease. Alternatively, these apparent modulations may reflect a dependence of genetic effects on 8-isoprostane concentrations.

METHOD

To test whether genetic effects on 8-isoprostane concentrations are quantile-dependent, quantile-specific offspring-parent (β_OP) and full-sib regression slopes (β_FS) were estimated by applying quantile regression to the age- and sex-adjusted creatinine-standardized urinary 8-isoprostane concentrations of Framingham Heart Study families. Quantile-specific heritabilities were calculated as h² = 2β_OP/(1+r_spouse) and h² = {(1+8r_spouseβ_FS)^0.5-1}/(2r_spouse)).

RESULTS

Spouse 8-isoprostane concentrations were weakly concordant (r_spouse = 0.06). 8-isoprostane heritability (h²±SE) increased significantly with increasing percentiles of its distribution (P_{linear trend} = 0.0009, P_{quadratic trend} = 0.0007, P_{cubic trend} = 0.003) when estimated from β_OP, and when estimated from β_FS (P_{linear trend} = 0.005, P_{quadratic trend} = 0.09, P_{cubic trend} = 0.06). Compared to the 10th percentile, β_OP-estimated h² was over 22-fold greater at the 90th percentile (P_difference = 9.2 × 10^-5), and 5.3-fold greater when estimated from β_FS (P_difference = 0.004). Significantly higher 8-isoprostane heritability in smokers than nonsmokers (0.352 ± 0.147 vs. 0.061 ± 0.036, P_difference = 0.01), and heavier than lighter drinkers (0.449 ± 0.216 vs. 0.078 ± 0.037, P_difference = 0.01) were eliminated when corrected for the higher 8-isoprostane concentrations of the smokers and heavier drinkers.

CONCLUSION

Heritability of oxidative stress as measured by 8-isoprostane is quantile-dependent, which may contribute to the larger reported effects on oxidative stress by UCP2 -866G > A, IL6 -572C > G and LTA 252A > G polymorphisms in smokers than nonsmokers, by the UCP2 -866G > A polymorphism in coronary heart disease patients, by the ESRRG rs1890552 A > G polymorphism in type 2 diabetics, by the CYBA 242C > T polymorphism after exercise training, by the PLIN 11482G > A/14995A > T haplotype before weight loss, and by the CYBA -930A > G and GSTP1 I105V haplotypes in patients with pulmonary edema.

Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin

BACKGROUND

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution.

METHODS

Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study.

RESULTS

Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), increased 0.0045 ± 0.0007 (p = 8.8 × 10-14) for each 1% increment in the fasting glucose distribution, that is, h2 ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (p = 1.2 × 10-6), homeostatic model assessment of insulin resistance (HOMA-IR, p = 5.3 × 10-5), insulin/glucose ratio (p = 3.9 × 10-5), proinsulin (p = 1.4 × 10-6), proinsulin/insulin ratio (p = 2.7 × 10-5), and glucose concentrations during a glucose tolerance test (p = 0.001), and their logarithmically transformed values.

DISCUSSION/CONCLUSION

These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between ACE, ADRB3, PPAR-γ2, and TNF-α polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2), gene-exercise (INS), gene-diet (ACSL1, ELOVL6, IRS-1, PLIN, S100A9), and gene-socioeconomic interactions.

Quantile-specific heritability of monocyte chemoattractant protein-1, and relevance to rs1024611-disease interactions

BACKGROUND

Monocyte chemoattractant protein-1 (MCP-1) concentrations are 34% to 47% heritable. Larger -2518 G/A (rs1024611) genotypes differences are reported for: 1) MCP-1 production in stimulated vs. basal cells; and 2) MCP-1 concentrations in diseased (sepsis, brain abscess, hepatitis B virus, Alzheimer's disease, Behcet's disease, and systemic lupus erythematosus) vs. healthy patients. Those results suggest that the -2518 G/A effect size may depend on whether the phenotype is high or low relative to its distribution (quantile-dependent expressivity).

METHOD

To test whether quantile-dependent expressivity applies more broadly to genetic influences on MCP-1 concentrations, quantile-specific offspring-parent (β_OP) and full-sib regression slopes (β_FS) were estimated by applying quantile regression to the age- and sex-adjusted serum MCP-1 concentrations of Framingham Heart Study families. Quantile-specific heritabilities were calculated as h² = 2β_OP/(1 + r_spouse) and h²={(1 + 8r_spouseβ_FS)^0.5-1}/(2r_spouse)).

RESULTS

Heritability (h² ± SE) of MCP-1 concentrations increased from 0.15 ± 0.05 at the 10th percentile of the MCP-1 distribution, 0.23 ± 0.04 at the 25th, 0.32 ± 0.05 at the 50th, 0.43 ± 0.07 at the 75th, and 0.44 ± 0.07 at the 90th percentile, or an 0.0041 ± 0.0009 increase for each one-percent increment in the MCP-1 distribution (P_{linear trend} = 2.4 × 10^-5) when estimated from β_OP, and (P_{linear trend} = 7.7 × 10^-9) when estimated from β_FS. Compared to the 10th percentile, β_OP-estimated h² was 3-fold greater at the 90th percentile (P_difference = 0.0003), and 6.9-fold greater when estimated from β_FS (P_difference = 3.3 × 10^-6). Re-analysis of in vivo comparison of MCP-1 concentrations in controls vs. patients with MCP-1-elevating conditions, and in vitro studies of MCP-1 production in basal vs. stimulated cells, show rs1024611 genotypes differences that were consistent with quantile-dependent expressivity.

CONCLUSION

The heritability of circulating MCP-1 concentrations is quantile-dependent.

Genetics and regulation of HDL metabolism

The inverse association between plasma HDL cholesterol (HDL-C) levels and risk for cardiovascular disease (CVD) has been demonstrated by numerous epidemiological studies. However, efforts to reduce CVD risk by pharmaceutically manipulating HDL-C levels failed and refused the HDL hypothesis. HDL-C levels in the general population are highly heterogeneous and are determined by a combination of genetic and environmental factors. Insights into the causes of HDL-C heterogeneity came from the study of monogenic HDL deficiency syndromes but also from genome wide association and Μendelian randomization studies which revealed the contribution of a large number of loci to low or high HDL-C cases in the general or in restricted ethnic populations. Furthermore, HDL-C levels in the plasma are under the control of transcription factor families acting primarily in the liver including members of the hormone nuclear receptors (PPARs, LXRs, HNF-4) and forkhead box proteins (FOXO1-4) and activating transcription factors (ATFs). The effects of certain lipid lowering drugs used today are based on the modulation of the activity of specific members of these transcription factors. During the past decade, the roles of small or long non-coding RNAs acting post-transcriptionally on the expression of HDL genes have emerged and provided novel insights into HDL regulation and new opportunities for therapeutic interventions. In the present review we summarize recent progress made in the genetics and the regulation (transcriptional and post-transcriptional) of HDL metabolism.

Quantile-specific heritability of plasminogen activator inhibitor type-1 (PAI-1, aka SERPINE1) and other hemostatic factors

BACKGROUND

Plasminogen activator inhibitor type-1 (PAI-1, aka SERPINE1) is a moderately heritable glycoprotein that regulates fibrin clot dissolution (fibrinolysis).

OBJECTIVES

Test whether the heritabilities (h2 ) of PAI-1 and other hemostatic factors are constant throughout their distribution or whether they are quantile-specific (i.e., a larger or smaller h2 depending on whether their concentrations are high or low).

METHODS

Quantile regression was applied to 5606 parent-offspring pairs and 5310 full siblings of the Framingham Heart Study. Quantile-specific heritability was estimated from the parent-offspring regression slope (βPO , h2  = 2βPO /(1+rspouse )) and the full-sib regression slope (βFS , h2  = {(1+8rspouse βFS )0.5 -1}/(2rspouse )).

RESULTS

Heritability (h2  ± SE) increased significantly with increasing percentiles of the offspring's age- and sex-adjusted PAI-1 distribution when estimated from βPO (plinear trend  = 0.0001): 0.09 ± 0.02 at the 10th, 0.09 ± 0.02 at the 25th, 0.16 ± 0.02 at the 50th, 0.29 ± 0.04 at the 75th, and 0.26 ± 0.08 at the 90th percentile of the PAI-1 distribution, and when estimated from βFS (plinear trend  = 6.5x10-7 ). There was no significant evidence for quantile-specific heritability for factor VII (plinear trend  = 0.35), D-dimer (plinear trend  = 0.08), tPA (plinear trend  = 0.74), or von Willebrand factor (plinear trend  = 0.79).

CONCLUSION

Higher mean plasma PAI-1 antigen concentrations tend to accentuate genetic effects (quantile-dependent expressivity), which is consistent with the greater reported differences in PAI-1 concentrations between rs1799889 SERPINE1 (4G/5G) genotypes in patients with osteonecrosis, meningococcal sepsis, obesity, prior myocardial infarction, deep vein thrombosis, and polycystic ovarian syndrome than in healthy controls. It is also consistent with the greater increases in PAI-1 concentrations in 4G-allele carriers than 5G/5G homozygotes following fibrinolytic treatment, low-salt intake, and high saturated fat intake.

Quantile-Dependent Expressivity of Serum Uric Acid Concentrations

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, h² = 2β_OP/(1 + r_spouse)) and full-sib regression slopes (β_FS, h² = {(1 + 8r_spouseβ_FS)^0.5 − 1}/(2r_spouse)) was robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples.

Results

Quantile-specific h² (±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 10^th, 0.36 ± 0.03 at the 25^th, 0.41 ± 0.03 at the 50^th, 0.46 ± 0.04 at the 75^th, and 0.49 ± 0.05 at the 90^th 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-dependent expressivity of serum C-reactive protein concentrations in family sets

Background

“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., C-reactive protein, CRP) is high or low relative to its distribution. We have previously shown that the heritabilities (h²) of coffee and alcohol consumption, postprandial lipemia, lipoproteins, leptin, adiponectin, adiposity, and pulmonary function are quantile-specific. Whether CRP heritability is quantile-specific is currently unknown.

Methods

Serum CRP concentrations from 2,036 sibships and 6,144 offspring-parent pairs were analyzed from the Framingham Heart Study. Quantile-specific heritability from full-sib (β_FS, h² ={(1 + 8r_spouseβ_FS)^0.5 − 1}/(2r_spouse)) and offspring-parent regression slopes (β_OP, h² = 2β_OP/(1 + r_spouse)) were estimated robustly by quantile regression with nonparametric significance determined from 1,000 bootstrap samples.

Results

Quantile-specific h² (±SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted CRP distribution when estimated from β_OP (P_trend = 0.0004): 0.02 ± 0.01 at the 10th, 0.04 ± 0.01 at the 25th, 0.10 ± 0.02 at the 50th, 0.20 ± 0.05 at the 75th, and 0.33 ± 0.10 at the 90th percentile, and when estimated from β_FS (P_trend = 0.0008): 0.03±0.01 at the 10th, 0.06 ± 0.02 at the 25th, 0.14 ± 0.03 at the 50th, 0.24 ± 0.05 at the 75th, and 0.53 ± 0.21 at the 90th percentile.

Conclusion

Heritability of serum CRP concentration is quantile-specific, which may explain or contribute to the inflated CRP differences between CRP (rs1130864, rs1205, rs1800947, rs2794521, rs3091244), FGB (rs1800787), IL-6 (rs1800795, rs1800796), IL6R (rs8192284), TNF-α (rs1800629) and APOE genotypes following CABG surgery, stroke, TIA, curative esophagectomy, intensive periodontal therapy, or acute exercise; during acute coronary syndrome or Staphylococcus aureus bacteremia; or in patients with chronic rheumatoid arthritis, diabetes, peripheral arterial disease, ankylosing spondylitis, obesity or inflammatory bowel disease or who smoke.

Quantile-specific heritability of serum growth factor concentrations

BACKGROUND

"Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. growth factor concentration) is high or low relative to its distribution.

METHODS

Quantile-regression analysis was applied to family sets from the Framingham Heart Study to determine whether the heritability (h²) of vascular endothelial growth factor (VEGF), hepatocyte growth factor (HGF), angiopoietin-2, and angiopoietin-2 (sTie-2) and VEGFR1 (sFlt-1) receptor concentrations were quantile-specific.

RESULTS

Quantile-specific h² (±SE) increased with increasing percentiles of the age- and sex-adjusted VEGF (P_trend<10^-16), HGF (P_trend=0.0004), angiopoietin-2 (P_trend=0.0002), sTie-2 (P_trend=1.2 × 10^-5), and sFlt-1 distributions (P_trend=0.04).

CONCLUSION

Heritabilities of VEGF, HGF, angiopoitein-2, sTie-2 and sFlt-1 concentrations are quantile dependent. This may explain reported interactions of genetic loci (rs10738760, rs9472159, rs833061, rs3025039, rs2280789, rs1570360, rs2010963) with metabolic syndrome, diet, recurrent miscarriage, hepatocellular carcinoma, erysipelas, diabetic retinopathy, and bevacizumab treatment in their effect on VEGF concentrations.

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

"Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., leptin) is high or low relative to its distribution. Leptin concentrations are strongly related to adiposity, whose heritability is quantile dependent. Whether inheritance of leptin concentrations is quantile dependent, and whether this explains the greater heritability in women than men in accordance with their greater adiposity, and explains other gene-environment interactions, remains to be determined. Therefore, leptin and leptin receptor concentrations from 3068 siblings in 1133 sibships from the Framingham Heart Study Third Generation Cohort were analyzed. Free leptin index (FLI) was calculated as the ratio of leptin to soluble leptin receptor concentrations. Full-sib (β_FS) regression slopes were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. The analyses showed β_FS increased significantly with increasing percentiles of the offspring's age- and sex-adjusted leptin distribution (P_linear = 0.0001), which was accelerated at the higher concentrations (P_quadratic = 0.0003). β_FS at the 90th percentile (0.418 ± 0.066) was 4.7-fold greater than at the 10th percentile (0.089 ± 0.032, P_difference = 3.6 × 10^-6). Consistent with quantile-dependent expressivity, the β_FS was greater in female sibs, which was attributable to their higher leptin concentrations. Reported gene-environment interactions involving adiposity and LEP, LEPR, MnSOD, PPARγ, PPARγ2, and IRS-1 polymorphisms were consistent with quantile-dependent expressivity of leptin concentrations. β_FS for leptin receptor concentrations and free leptin index also increased significantly with increasing percentiles of their distributions (P_linear = 0.04 and P_linear = 8.5 × 10^-6, respectively). In conclusion, inherited genetic and shared environmental effects on leptin concentrations were quantile dependent, which likely explains male-female differences in heritability and some gene-environment interactions.

Quantile-Dependent Expressivity and Gene-Lifestyle Interactions Involving High-Density Lipoprotein Cholesterol

BACKGROUND

The phenotypic expression of a high-density lipoprotein (HDL) genetic risk score has been shown to depend upon whether the phenotype (HDL-cholesterol) is high or low relative to its distribution in the population (quantile-dependent expressivity). This may be due to the effects of genetic mutations on HDL-metabolism being concentration dependent.

METHOD

The purpose of this article is to assess whether some previously reported HDL gene-lifestyle interactions could potentially be attributable to quantile-dependent expressivity.

SUMMARY

Seventy-three published examples of HDL gene-lifestyle interactions were interpreted from the perspective of quantile-dependent expressivity. These included interactive effects of diet, alcohol, physical activity, adiposity, and smoking with genetic variants associated with the ABCA1, ADH3, ANGPTL4, APOA1, APOA4, APOA5, APOC3, APOE, CETP, CLASP1, CYP7A1, GALNT2, LDLR, LHX1, LIPC, LIPG, LPL, MVK-MMAB, PLTP, PON1, PPARα, SIRT1, SNTA1,and UCP1genes. The selected examples showed larger genetic effect sizes for lifestyle conditions associated with higher vis-à-vis lower average HDL-cholesterol concentrations. This suggests these reported interactions could be the result of selecting subjects for conditions that differentiate high from low HDL-cholesterol (e.g., lean vs. overweight, active vs. sedentary, high-fat vs. high-carbohydrate diets, alcohol drinkers vs. abstainers, nonsmokers vs. smokers) producing larger versus smaller genetic effect sizes. Key Message: Quantile-dependent expressivity provides a potential explanation for some reported gene-lifestyle interactions for HDL-cholesterol. Although overall genetic heritability appears to be quantile specific, this may vary by genetic variant and environmental exposure.

Quantile-specific heritability of total cholesterol and its pharmacogenetic and nutrigenetic implications

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.

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

Background

"Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution. We have previously shown that the heritability (h² ) of adiposity, lipoproteins, postprandial lipemia, pulmonary function, and coffee and alcohol consumption are quantile-specific. Whether adiponectin heritability is quantile specific remains to be determined.

Methods

Plasma adiponectin concentrations from 4,182 offspring-parent pairs and 1,662 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β _OP,h² = 2β _OP/(1 + r_spouse)) and full-sib regression slopes (β _FS, h² = {(1 + 8r_spouse β _FS)^0.05-1}/(2r_spouse)) were robustly estimated by quantile regression with nonparametric significance assigned from 1,000 bootstrap samples.

Results

Quantile-specific h² (± SE) increased with increasing percentiles of the offspring's age- and sex-adjusted adiponectin distribution when estimated from β _OP (P _trend = 2.2 × 10^-6): 0.30 ± 0.03 at the 10th, 0.33 ± 0.04 at the 25th, 0.43 ± 0.04 at the 50th, 0.55 ± 0.05 at the 75th, and 0.57 ± 0.08 at the 90th percentile, and when estimated from β _FS (P _trend = 7.6 × 10^-7): 0.42 ± 0.03 at the 10th, 0.44 ± 0.04 at the 25th, 0.56 ± 0.05 at the 50th, 0.73 ± 0.08 at the 75th, and 0.79 ± 0.11 at the 90th percentile. Consistent with quantile-dependent expressivity, adiponectin's: (1) heritability was greater in women in accordance with their higher adiponection concentrations; (2) relationships to ADIPOQ polymorphisms were modified by adiposity in accordance with its adiponectin-lowering effect; (3) response to rosiglitazone was predicted by the 45T> G ADIPOQ polymorphism; (4) difference by ADIPOQ haplotypes increased linearly with increasing postprandial adiponectin concentrations.

Conclusion

Adiponectin heritability is quantile dependent, which may explain sex-specific heritability, gene-environment and gene-drug interactions, and postprandial response by haplotypes.

Quantile-Specific Heritability of Intakes of Alcohol but not Other Macronutrients

Genetic heritability (h²) of alcohol use is reported to be greater in rural dwellers, distressed marriages, low socioeconomic status, in girls who are unmarried or lacking closeness with their parents or religious upbringing, in less-educated men, and in adolescents with peers using alcohol. However, these are all risk factors for heavy drinking, and the greater heritability could be due to quantile-dependent expressivity, i.e., h² dependent upon whether the phenotype (alcohol intake) is high or low relative to its distribution. Quantile regression showed that h² estimated from the offspring-parent regression slope increased significantly from lowest to highest gram/day of alcohol consumption (0.006 ± 0.001 per percent, P = 1.1 × 10^-7). Heritability at the 90th percentile of the sample distribution (0.557 ± 0.116) was 4.5-fold greater than at the 10th percentile (0.122 ± 0.037). Heritabilities for intakes of other macronutrients were not quantile-dependent. Thus quantile-dependent expressivity may explain the higher estimated heritability associated with risk factors for high alcohol consumption.