Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution
Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution
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DOI：
10.1016/j.ajhg.2017.10.007
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发表时间：
2017-12-07
影响因子：
9.8
通讯作者：
Meyre, David
中科院分区：
文献类型：
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作者：
Abadi, Arkan;Alyass, Akram;Meyre, David
越来越多的单核苷酸多态性（snp）与体重指数（BMI）和肥胖有关，但这些肥胖易感位点的影响在BMI分布中是否一致仍不清楚。通过条件分位数回归（CQR）和元回归（MR）模型，研究了75,230名欧洲血统成年人中37个BMI相关snp对BMI百分位数的影响。9个snp (24%)-rs1421085 （FTO; p = 8.69 × 10(-15)）、rs6235 （PCSK1; p = 7.11 × 10(-6)）、rs7903146 （TCF7L2; p = 9.60 × 10(-6)）、rs11873305 （MC4R; p = 5.08 × 10(-5)）、rs12617233 （FANCL; p = 5.30 × 10(-5)）、rs11672660 （GIPR; p = 1.64 × 10(-4)）、rs6499653 （MAP2K5; p = 6.23 × 10(-4)）、rs3824755 (NT5C2; p = 7.90 × 10(-4))-的影响在样本BMI分布中显著增加。我们发现，这种增加源于未调整的基因相互作用，这种相互作用增强了高BMI人群中snp的影响。当分析125个身高相关snp进行比较时，只有一个（< 1%）rs6219 （IGF1, p = 1.80 x 10(-4)）在身高百分位数上显示出显著差异。这些snp （GS-BMI和GS-height）的累积基因评分显示，在整个样本分布中，只有GS-BMI的影响显著增加(BMI: p = 7.03 × 10(-37)；高度：p = 0.499)。总的来说，这些发现强调了基因-基因和基因-环境相互作用在塑造BMI遗传结构中的重要性，并提出了一种仅使用样本结果分布来检测这种相互作用的方法。
A growing number of single-nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effects of these obesity-susceptibility loci are uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI-associated SNPs in 75,230 adults of European ancestry across BMI percentiles by using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of nine SNPs (24%)-rs1421085 (FTO; p = 8.69 x 10(-15)), rs6235 (PCSK1; p = 7.11 x 10(-6)), rs7903146 (TCF7L2; p = 9.60 x 10(-6)), rs11873305 (MC4R; p = 5.08 x 10(-5)), rs12617233 (FANCL; p = 5.30 x 10(-5)), rs11672660 (GIPR; p = 1.64 x 10(-4)), rs997295 (MAP2K5; p = 3.25 x 10(-4)), rs6499653 (FTO; p = 6.23 x 10(-4)), and rs3824755 (NT5C2; p = 7.90 x 10(-4))-increased significantly across the sample BMI distribution. We showed that such increases stemmed from unadjusted gene interactions that enhanced the effects of SNPs in persons with a high BMI. When 125 height-associated SNPs were analyzed for comparison, only one (< 1%), rs6219 (IGF1, p = 1.80 x 10(-4)), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-height) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p = 7.03 x 10(-37); height: p = 0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.