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Carcinogenesis. 2014 Jul;35(7):1528-35. doi: 10.1093/carcin/bgu076. Epub 2014 Mar 22.
3
Evidence of gene-environment interaction for two genes on chromosome 4 and environmental tobacco smoke in controlling the risk of nonsyndromic cleft palate.4号染色体上两个基因与环境烟草烟雾在控制非综合征性腭裂风险方面的基因-环境相互作用证据。
PLoS One. 2014 Feb 6;9(2):e88088. doi: 10.1371/journal.pone.0088088. eCollection 2014.
4
Gene-education interactions identify novel blood pressure loci in the Framingham Heart Study.基因与教育的相互作用在弗雷明汉心脏研究中确定了新的血压基因座。
Am J Hypertens. 2014 Mar;27(3):431-44. doi: 10.1093/ajh/hpt283. Epub 2014 Jan 28.
5
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Is the gene-environment interaction paradigm relevant to genome-wide studies? The case of education and body mass index.基因-环境相互作用范式与全基因组研究相关吗?以教育和体重指数为例。
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Genome-wide interaction study identifies RCBTB1 as a modifier for smoking effect on carotid intima-media thickness.全基因组交互研究发现 RCBTB1 可修饰吸烟对颈动脉内膜中层厚度的影响。
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Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: a GWAS data analysis.肥胖和糖尿病相关胰腺癌的基因-环境相互作用:GWAS 数据分析。
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Empirical hierarchical bayes approach to gene-environment interactions: development and application to genome-wide association studies of lung cancer in TRICL.经验层次贝叶斯方法在基因-环境交互作用中的应用:TRICL 肺癌全基因组关联研究中的开发与应用。
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基因与年龄在血压调节中的相互作用:CHARGE、Global BPgen 和 ICBP 联盟的大规模研究。

Gene-age interactions in blood pressure regulation: a large-scale investigation with the CHARGE, Global BPgen, and ICBP Consortia.

机构信息

Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA.

Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA.

出版信息

Am J Hum Genet. 2014 Jul 3;95(1):24-38. doi: 10.1016/j.ajhg.2014.05.010. Epub 2014 Jun 19.

DOI:10.1016/j.ajhg.2014.05.010
PMID:24954895
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4085636/
Abstract

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.

摘要

虽然已有研究报道了血压(BP)的年龄依赖性效应,但在大规模全基因组关联研究(GWAS)中尚未对其进行系统研究。我们利用三个成熟的联盟(CHARGE、GBPgen 和 ICBP)的基础设施以及一种非标准方法(年龄分层和荟萃回归),对与收缩压(SBP)、舒张压(DBP)、平均动脉压(MAP)和脉搏压(PP)的年龄依赖性效应相关的常见变异进行了全基因组搜索。在一项使用 99241 名欧洲血统个体的两阶段设计中,我们通过联合检验 SNP 主效应和 SNP-年龄相互作用,确定了 20 个全基因组显著(p ≤ 5 × 10(-8)) 位点。在单独检验相互作用的情况下,有 9 个显著位点表现出 BP 的年龄依赖性效应的名义证据。EHBP1L1(DBP 和 MAP)、CASZ1(SBP 和 MAP)和 GOSR2(PP)基因座中的索引 SNP 表现出最大的年龄相互作用,其在年轻和年老个体中的作用方向相反。遗传效应随时间的变化虽然很小但不容忽视(在 60 年内高达 1.58 毫米汞柱)。EHBP1L1 基因座仅通过基因-年龄相互作用在白种人中被发现,但在来自新加坡的 8682 名亚洲人中,DBP 主要效应得到了复制(p = 8.3 × 10(-4)),表明存在潜在的种族间异质性。二次分析显示了 22 个具有年龄特异性效应的位点(例如,仅在 20 至 29 岁的人群中)。年龄可以用于选择具有更大遗传效应大小和更同质表型的样本,这可能会增加统计效力。通过新的统计方法确定的年龄依赖性效应可以深入了解 BP 关联背后的生物学和时间调节。