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Zhu X, Yang Y, Lorincz-Comi N, Li G, Bentley AR, de Vries PS, Brown M, Morrison AC, Rotimi CN, Gauderman WJ, Rao DC, Aschard H. An approach to identify gene-environment interactions and reveal new biological insight in complex traits. Nat Commun 2024; 15:3385. [PMID: 38649715 PMCID: PMC11035594 DOI: 10.1038/s41467-024-47806-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 04/10/2024] [Indexed: 04/25/2024] Open
Abstract
There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genetic Epidemiology Consortium has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identify and confirm 5 loci (6 independent signals) interacted with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrate that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated heritability is significant (P < 0.02) for low-density lipoprotein cholesterol and triglycerides in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Yihe Yang
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Gen Li
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Michael Brown
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Dabeeru C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Hugues Aschard
- Institut Pasteur, Université Paris Cité, Department of Computational Biology, F-75015, Paris, France
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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Nienaber-Rousseau C. Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings. Nutr Rev 2024:nuae015. [PMID: 38442341 DOI: 10.1093/nutrit/nuae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024] Open
Abstract
Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.
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Affiliation(s)
- Cornelie Nienaber-Rousseau
- Centre of Excellence for Nutrition, North-West University, Potchefstroom, South Africa
- SAMRC Extramural Unit for Hypertension and Cardiovascular Disease, Faculty of Health Sciences, North-West University, Potchefstroom, South Africa
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Zhu X, Yang Y, Lorincz-Comi N, Li G, Bentley A, de Vries PS, Brown M, Morrison AC, Rotimi C, James Gauderman W, Rao DC, Aschard H. A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits. RESEARCH SQUARE 2023:rs.3.rs-3338723. [PMID: 37886448 PMCID: PMC10602131 DOI: 10.21203/rs.3.rs-3338723/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identified and confirmed 5 loci (6 independent signals) interacting with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrated that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated contribution ranges from 1.76% to 14.05% of SNP heritability of serum lipids in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yihe Yang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Gen Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Amy Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Michael Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - W. James Gauderman
- Biostatistics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - DC Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Hugues Aschard
- Institut Pasteur, Université Paris Cité, Department of Computational Biology, F-75015 Paris, France
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Dietrich E, Jomard A, Osto E. Crosstalk between high-density lipoproteins and endothelial cells in health and disease: Insights into sex-dependent modulation. Front Cardiovasc Med 2022; 9:989428. [PMID: 36304545 PMCID: PMC9594152 DOI: 10.3389/fcvm.2022.989428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/16/2022] [Indexed: 11/19/2022] Open
Abstract
Atherosclerotic cardiovascular disease is the leading cause of death worldwide. Intense research in vascular biology has advanced our knowledge of molecular mechanisms of its onset and progression until complications; however, several aspects of the patho-physiology of atherosclerosis remain to be further elucidated. Endothelial cell homeostasis is fundamental to prevent atherosclerosis as the appearance of endothelial cell dysfunction is considered the first pro-atherosclerotic vascular modification. Physiologically, high density lipoproteins (HDLs) exert protective actions for vessels and in particular for ECs. Indeed, HDLs promote endothelial-dependent vasorelaxation, contribute to the regulation of vascular lipid metabolism, and have immune-modulatory, anti-inflammatory and anti-oxidative properties. Sex- and gender-dependent differences are increasingly recognized as important, although not fully elucidated, factors in cardiovascular health and disease patho-physiology. In this review, we highlight the importance of sex hormones and sex-specific gene expression in the regulation of HDL and EC cross-talk and their contribution to cardiovascular disease.
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Affiliation(s)
- Elisa Dietrich
- Institute for Clinical Chemistry, University of Zurich and University Hospital Zurich, Zurich, Switzerland
| | - Anne Jomard
- Institute for Clinical Chemistry, University of Zurich and University Hospital Zurich, Zurich, Switzerland
| | - Elena Osto
- Institute for Clinical Chemistry, University of Zurich and University Hospital Zurich, Zurich, Switzerland
- Department of Cardiology, Heart Center, University Hospital Zurich, Zurich, Switzerland
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Kardiovaskuläre Prävention in Peri- und Postmenopause – Herz und Kreislauf gesund erhalten. GYNAKOLOGISCHE ENDOKRINOLOGIE 2022. [DOI: 10.1007/s10304-022-00458-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Williams PT. Quantile-specific heritability of plasma fibrinogen concentrations. PLoS One 2022; 17:e0262395. [PMID: 34995330 PMCID: PMC8741049 DOI: 10.1371/journal.pone.0262395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 12/21/2021] [Indexed: 11/30/2022] Open
Abstract
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 (βOP, h2 = 2βOP/(1+rspouse)) and full-sib regression slopes (βFS, h2 = {(1+8rspouseβFS)0.05–1}/(2rspouse)) 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 βOP (Ptrend = 5.5x10-6): 0.30±0.05 at the 10th, 0.37±0.04 at the 25th, 0.48±0.05 at the 50th, 0.61±0.06 at the 75th, and 0.65±0.08 at the 90th percentile, and when estimated from βFS (Ptrend = 0.008): 0.28±0.04 at the 10th, 0.31±0.04 at the 25th, 0.36±0.03 at the 50th, 0.41±0.05 at the 75th, and 0.50±0.06 at the 90th 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.
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Affiliation(s)
- Paul T. Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, Berkeley, CA, United States of America
- * E-mail:
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Williams PT. Quantile-Dependent Expressivity of Serum Interleukin-6 Concentrations as a Possible Explanation of Gene-Disease Interactions, Gene-Environment Interactions, and Pharmacogenetic Effects. Inflammation 2022; 45:1059-1075. [PMID: 34993731 DOI: 10.1007/s10753-021-01601-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 11/15/2021] [Indexed: 12/01/2022]
Abstract
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.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
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Williams PT. Quantile-Specific Heritability of Inflammatory and Oxidative Stress Biomarkers Linked to Cardiovascular Disease. J Inflamm Res 2022; 15:85-103. [PMID: 35023945 PMCID: PMC8743501 DOI: 10.2147/jir.s347402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 12/16/2021] [Indexed: 11/23/2022] Open
Abstract
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.
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Affiliation(s)
- Paul T Williams
- Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Lee YH, Chang YS, Hsieh CC, Wang RT, Chang JG, Chen CJ, Chang SJ. APOE and KLF14 genetic variants are sex-specific for low high-density lipoprotein cholesterol identified by a genome-wide association study. Genet Mol Biol 2022; 45:e20210280. [PMID: 35238325 PMCID: PMC8892272 DOI: 10.1590/1678-4685-gmb-2021-0280] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/28/2021] [Indexed: 11/22/2022] Open
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Williams PT. Quantile-specific heritability of 8-isoprostane and the modulating effects of smoking, alcohol, cardiovascular disease and diabetes on 8-isoprostane-gene interactions. Free Radic Biol Med 2022; 178:262-270. [PMID: 34883250 PMCID: PMC10101173 DOI: 10.1016/j.freeradbiomed.2021.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 10/19/2022]
Abstract
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 (βOP) and full-sib regression slopes (βFS) 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 = 2βOP/(1+rspouse) and h2 = {(1+8rspouseβFS)0.5-1}/(2rspouse)). RESULTS Spouse 8-isoprostane concentrations were weakly concordant (rspouse = 0.06). 8-isoprostane heritability (h2±SE) increased significantly with increasing percentiles of its distribution (Plinear trend = 0.0009, Pquadratic trend = 0.0007, Pcubic trend = 0.003) when estimated from βOP, and when estimated from βFS (Plinear trend = 0.005, Pquadratic trend = 0.09, Pcubic trend = 0.06). Compared to the 10th percentile, βOP-estimated h2 was over 22-fold greater at the 90th percentile (Pdifference = 9.2 × 10-5), and 5.3-fold greater when estimated from βFS (Pdifference = 0.004). Significantly higher 8-isoprostane heritability in smokers than nonsmokers (0.352 ± 0.147 vs. 0.061 ± 0.036, Pdifference = 0.01), and heavier than lighter drinkers (0.449 ± 0.216 vs. 0.078 ± 0.037, Pdifference = 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.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
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Williams PT. Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin. Lifestyle Genom 2021; 15:10-34. [PMID: 34872092 PMCID: PMC8766916 DOI: 10.1159/000519382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/01/2021] [Indexed: 01/03/2023] Open
Abstract
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.
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Affiliation(s)
- Paul T Williams
- Division of Molecular Biophysics & Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California, USA
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Williams PT. Quantile-specific heritability of monocyte chemoattractant protein-1, and relevance to rs1024611-disease interactions. Cytokine 2021; 149:155722. [PMID: 34624603 PMCID: PMC10124179 DOI: 10.1016/j.cyto.2021.155722] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 09/20/2021] [Accepted: 09/22/2021] [Indexed: 12/19/2022]
Abstract
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 (βOP) and full-sib regression slopes (βFS) 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 = 2βOP/(1 + rspouse) and h2={(1 + 8rspouseβFS)0.5-1}/(2rspouse)). 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 (Plinear trend = 2.4 × 10-5) when estimated from βOP, and (Plinear trend = 7.7 × 10-9) when estimated from βFS. Compared to the 10th percentile, βOP-estimated h2 was 3-fold greater at the 90th percentile (Pdifference = 0.0003), and 6.9-fold greater when estimated from βFS (Pdifference = 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.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, 1 Cyclotron Road, Berkeley, CA 94720, United States.
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Williams PT. Quantile-specific heritability of plasminogen activator inhibitor type-1 (PAI-1, aka SERPINE1) and other hemostatic factors. J Thromb Haemost 2021; 19:2559-2571. [PMID: 34273240 DOI: 10.1111/jth.15468] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 07/07/2021] [Accepted: 07/16/2021] [Indexed: 11/27/2022]
Abstract
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.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, Berkeley, CA, USA
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Quantile-Dependent Expressivity of Serum Uric Acid Concentrations. Int J Genomics 2021; 2021:3889278. [PMID: 34545327 PMCID: PMC8448993 DOI: 10.1155/2021/3889278] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 08/11/2021] [Accepted: 08/14/2021] [Indexed: 11/29/2022] Open
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 (βOP, h2 = 2βOP/(1 + rspouse)) and full-sib regression slopes (βFS, h2 = {(1 + 8rspouseβFS)0.5 − 1}/(2rspouse)) 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 βOP (Ptrend = 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 βFS (Ptrend = 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.
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Giammanco A, Noto D, Barbagallo CM, Nardi E, Caldarella R, Ciaccio M, Averna MR, Cefalù AB. Hyperalphalipoproteinemia and Beyond: The Role of HDL in Cardiovascular Diseases. Life (Basel) 2021; 11:life11060581. [PMID: 34207236 PMCID: PMC8235218 DOI: 10.3390/life11060581] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/11/2021] [Accepted: 06/16/2021] [Indexed: 12/16/2022] Open
Abstract
Hyperalphalipoproteinemia (HALP) is a lipid disorder characterized by elevated plasma high-density lipoprotein cholesterol (HDL-C) levels above the 90th percentile of the distribution of HDL-C values in the general population. Secondary non-genetic factors such as drugs, pregnancy, alcohol intake, and liver diseases might induce HDL increases. Primary forms of HALP are caused by mutations in the genes coding for cholesteryl ester transfer protein (CETP), hepatic lipase (HL), apolipoprotein C-III (apo C-III), scavenger receptor class B type I (SR-BI) and endothelial lipase (EL). However, in the last decades, genome-wide association studies (GWAS) have also suggested a polygenic inheritance of hyperalphalipoproteinemia. Epidemiological studies have suggested that HDL-C is inversely correlated with cardiovascular (CV) risk, but recent Mendelian randomization data have shown a lack of atheroprotective causal effects of HDL-C. This review will focus on primary forms of HALP, the role of polygenic inheritance on HDL-C, associated risk for cardiovascular diseases and possible treatment options.
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Affiliation(s)
- Antonina Giammanco
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
| | - Davide Noto
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
| | - Carlo Maria Barbagallo
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
| | - Emilio Nardi
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
| | - Rosalia Caldarella
- Department of Laboratory Medicine, Unit of Laboratory Medicine CoreLab, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (R.C.); (M.C.)
| | - Marcello Ciaccio
- Department of Laboratory Medicine, Unit of Laboratory Medicine CoreLab, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (R.C.); (M.C.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90127 Palermo, Italy
| | - Maurizio Rocco Averna
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
| | - Angelo Baldassare Cefalù
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties–University of Palermo, Via del Vespro, 129, 90127 Palermo, Italy; (A.G.); (D.N.); (C.M.B.); (E.N.); (M.R.A.)
- Correspondence:
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Williams PT. Quantile-dependent expressivity of serum C-reactive protein concentrations in family sets. PeerJ 2021; 9:e10914. [PMID: 33628645 PMCID: PMC7894107 DOI: 10.7717/peerj.10914] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/18/2021] [Indexed: 12/12/2022] Open
Abstract
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 (βFS, h2 ={(1 + 8rspouseβFS)0.5 − 1}/(2rspouse)) and offspring-parent regression slopes (βOP, h2 = 2βOP/(1 + rspouse)) 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 βOP (Ptrend = 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 βFS (Ptrend = 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.
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Affiliation(s)
- Paul T Williams
- Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Williams PT. Quantile-specific heritability of serum growth factor concentrations. Growth Factors 2021; 39:45-58. [PMID: 35312415 PMCID: PMC10101221 DOI: 10.1080/08977194.2022.2049261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
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 (Ptrend<10-16), HGF (Ptrend=0.0004), angiopoietin-2 (Ptrend=0.0002), sTie-2 (Ptrend=1.2 × 10-5), and sFlt-1 distributions (Ptrend=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.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, Berkeley, CA, USA
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Quantile-specific heritability of sibling leptin concentrations and its implications for gene-environment interactions. Sci Rep 2020; 10:22152. [PMID: 33335207 PMCID: PMC7747738 DOI: 10.1038/s41598-020-79116-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 12/03/2020] [Indexed: 12/18/2022] Open
Abstract
"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 (βFS) regression slopes were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. The analyses showed βFS increased significantly with increasing percentiles of the offspring's age- and sex-adjusted leptin distribution (Plinear = 0.0001), which was accelerated at the higher concentrations (Pquadratic = 0.0003). βFS at the 90th percentile (0.418 ± 0.066) was 4.7-fold greater than at the 10th percentile (0.089 ± 0.032, Pdifference = 3.6 × 10-6). Consistent with quantile-dependent expressivity, the βFS 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. βFS for leptin receptor concentrations and free leptin index also increased significantly with increasing percentiles of their distributions (Plinear = 0.04 and Plinear = 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.
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Quantile-specific heritability of total cholesterol and its pharmacogenetic and nutrigenetic implications. Int J Cardiol 2020; 327:185-192. [PMID: 33296721 DOI: 10.1016/j.ijcard.2020.11.070] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 11/30/2020] [Indexed: 12/23/2022]
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.
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