Aslibekyan Stella, Demerath Ellen W, Mendelson Michael, Zhi Degui, Guan Weihua, Liang Liming, Sha Jin, Pankow James S, Liu Chunyu, Irvin Marguerite R, Fornage Myriam, Hidalgo Bertha, Lin Li-An, Thibeault Krista Stanton, Bressler Jan, Tsai Michael Y, Grove Megan L, Hopkins Paul N, Boerwinkle Eric, Borecki Ingrid B, Ordovas Jose M, Levy Daniel, Tiwari Hemant K, Absher Devin M, Arnett Donna K
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
Obesity (Silver Spring). 2015 Jul;23(7):1493-501. doi: 10.1002/oby.21111.
To conduct an epigenome-wide analysis of DNA methylation and obesity traits.
DNA methylation was quantified in CD4+ T-cells using the Illumina Infinium HumanMethylation450 array in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network. Methylation at individual cytosine-phosphate-guanine (CpG) sites as a function of body mass index (BMI) and waist circumference (WC), adjusting for age, gender, study site, T-cell purity, smoking, and family structure, was modeled.
Epigenome-wide significant associations between eight CpG sites and BMI and five CpG sites and WC, successfully replicating the top hits in whole blood samples from the Framingham Heart Study (n = 2,377) and the Atherosclerosis Risk in Communities study (n = 2,097), were found. Top findings were in CPT1A (meta-analysis P = 2.7 × 10(-43) for BMI and 9.9 × 10(-23) for WC), PHGDH (meta-analysis P = 2.0 × 10(-15) for BMI and 4.0 × 10(-9) for WC), CD38 (meta-analysis P = 6.3 × 10(-11) for BMI and 1.6 × 10(-12) for WC), and long intergenic non-coding RNA 00263 (meta-analysis P = 2.2 × 10(-16) for BMI and 8.9 × 10(-14) for WC), regions with biologically plausible relationships to adiposity.
This large-scale epigenome-wide study discovered and replicated robust associations between DNA methylation at CpG loci and obesity indices, laying the groundwork for future diagnostic and/or therapeutic applications.
对DNA甲基化与肥胖特征进行全表观基因组分析。
在降脂药物与饮食网络遗传学研究的991名参与者中，使用Illumina Infinium HumanMethylation450芯片对CD4 + T细胞中的DNA甲基化进行定量分析。建立了个体胞嘧啶-磷酸-鸟嘌呤（CpG）位点甲基化与体重指数（BMI）和腰围（WC）之间的函数关系模型，并对年龄、性别、研究地点、T细胞纯度、吸烟情况和家庭结构进行了校正。
发现8个CpG位点与BMI以及5个CpG位点与WC之间存在全表观基因组显著关联，这些关联在弗雷明汉心脏研究（n = 2377）和社区动脉粥样硬化风险研究（n = 2097）的全血样本中成功得到了验证。主要发现集中在CPT1A基因（BMI的荟萃分析P = 2.7×10^(-43)，WC的荟萃分析P = 9.9×10^(-23)）、PHGDH基因（BMI的荟萃分析P = 2.0×10^(-15)，WC的荟萃分析P = 4.0×10^(-9)）、CD38基因（BMI的荟萃分析P = 6.3×10^(-11)，WC的荟萃分析P = 1.6×10^(-12)）以及长链基因间非编码RNA 00263（BMI的荟萃分析P = 2.2×10^(-16)，WC的荟萃分析P = 8.9×10^(-14)），这些区域与肥胖具有生物学上合理的关系。
这项大规模的全表观基因组研究发现并验证了CpG位点的DNA甲基化与肥胖指数之间的强关联，为未来的诊断和/或治疗应用奠定了基础。
