葡萄糖、胰岛素、胰岛素原、胰岛素抵抗和糖化血红蛋白的分位数依赖性遗传力。

IF 2 4区 医学 Q3 GENETICS & HEREDITY Lifestyle Genomics Pub Date : 2022-01-01 Epub Date: 2021-12-06 DOI:10.1159/000519382
Paul T Williams
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引用次数: 5

摘要

背景:“数量依赖性表达”是遗传效应对表型(如胰岛素抵抗)相对于其分布是高还是低的依赖性。方法:通过Framingham心脏研究6453对后代-父母对空腹血糖浓度的分位数回归估计分位数特异性后代-父母回归斜率(βOP)。结果:空腹血糖分布每增加1%,分位数特异遗传力(h2)(以2βOP/(1+rspouse)估计)增加0.0045±0.0007(p=8.8×10-14),在空腹血糖分布的第10、25、50、75和90个百分位数,h2±SE分别为0.057±0.021、0.095±0.024、0.146±0.019、0.293±0.038和0.456±0.061。空腹胰岛素(p=1.2×10-6)、胰岛素抵抗稳态模型评估(HOMA-IR,p=5.3×10-5)、胰岛素/葡萄糖比率(p=3.9×10-5,以及它们的对数变换值。讨论/结论:这些发现为精准医学和基因-环境相互作用提供了替代解释,包括ACE、ADRB3、PPAR-γ2和TNF-α多态性之间协同作用的替代解释,以及出生小于胎龄对成人胰岛素抵抗的影响(胎儿起源理论),和基因肥胖(APOE、ENPP1、GCKR、IGF2BP2、IL-6、IRS-1、KIAA0280、LEPR、MFHAS1、RETN、TCF7L2)、基因锻炼(INS)、基因饮食(ACSL1、ELOVL6、IRS-1、PLIN、S100A9)和基因社会经济相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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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.

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来源期刊
Lifestyle Genomics
Lifestyle Genomics Agricultural and Biological Sciences-Food Science
CiteScore
4.00
自引率
7.70%
发文量
11
审稿时长
28 weeks
期刊介绍: Lifestyle Genomics aims to provide a forum for highlighting new advances in the broad area of lifestyle-gene interactions and their influence on health and disease. The journal welcomes novel contributions that investigate how genetics may influence a person’s response to lifestyle factors, such as diet and nutrition, natural health products, physical activity, and sleep, amongst others. Additionally, contributions examining how lifestyle factors influence the expression/abundance of genes, proteins and metabolites in cell and animal models as well as in humans are also of interest. The journal will publish high-quality original research papers, brief research communications, reviews outlining timely advances in the field, and brief research methods pertaining to lifestyle genomics. It will also include a unique section under the heading “Market Place” presenting articles of companies active in the area of lifestyle genomics. Research articles will undergo rigorous scientific as well as statistical/bioinformatic review to ensure excellence.
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