以懲罰迴歸法來檢定基因環境交互作用

基因-環境交互作用（G×E）已被發現影響許多複雜疾病。然而，由於多重檢定校正的嚴苛懲罰，迄今，許多G×E之效果仍無法被檢測出來。本研究探討二階段分析策略的候選基因與環境交互作用檢定方法。首先，以「脊迴歸」（RIDGE），「彈性網」（ENET）或「最小絕對值收斂與選擇算子」（LASSO）篩選具邊際效應的單核苷酸多型性（SNP），來建構出「基因風險分數」（GRS）。而後檢測GRS與E之間的交互作用。吾人以模擬來評估上述方法和常見的五種G×E檢測方法之統計檢定力。在實際數據分析中，吾人將本法應用於臺灣人體生物資料庫中18,424位個案。針對每個SNP與身體質量指數（BMI）進行迴歸，調整性別、年齡（以年計）、教育程度、飲酒狀況、抽菸狀況、規律運動狀況及前10個代表祖源的主成分。最後檢測出達到全基因組顯著水準（即p值<5×〖10〗^(-8)）的15個SNPs皆位於「脂肪質量與肥胖關聯基因」（FTO）中。本文進一步探討FTO基因與三種環境因子間的交互作用，包括規律運動、抽菸與飲酒。檢測出FTO基因與規律運動存在交互作用（p值= 0.0039）。在不運動族群，GRS的增加對應到更高量的BMI上升。本研究的結果證明，規律運動可降低FTO基因對肥胖的不利影響。

關鍵字

基因-環境交互作用；脊迴歸；彈性網；最小絕對值收斂與選擇算子；臺灣人體生物資料庫；身體質量指數； FTO基因

並列摘要

Gene-environment (GxE) interactions have been found to play a role in many complex diseases. However, due to the harsh penalty of multiple-testing correction, the detection of GxE is underpowered and many GxE interactions have remained hidden to date. The aim of this study is to explore powerful candidate-gene-based GxE interaction tests by using a two-stage analysis strategy. First, we constructed a genetic risk scores (GRS) by filtering the marginal effects of single-nucleotide polymorphisms (SNPs) with the ridge regression (RIDGE), elastic net (ENET), or the least absolute shrinkage and selection operator (LASSO). Second, we tested the interaction between the GRS and E. Moreover, statistical power of our methods and five existing gene-based GxE methods was evaluated with simulations. In real data analysis, we applied our methods to 18,424 unrelated subjects in the Taiwan Biobank. Body mass index (BMI) was regressed on each SNP, while adjusting for sex, age (in years), educational attainment, drinking status, smoking status, regular exercise, and the first 10 ancestry principal components. A total of 15 SNPs located in the fat mass and obesity associated gene (FTO) reached the genome-wide significance level (i.e., p-value<5×〖10〗^(-8)). We further explored interactions between the variants in the FTO gene and three environmental factors, including performing regular exercise, cigarette smoking, and alcohol consumption. We found strong evidence that the FTO gene interacts with regular exercise (p = 0.0039). GRSs elevate more BMI in non-exercisers than in exercisers. Our results indicate that performing regular exercise can attenuate the adverse influence of the FTO variants on obesity.

並列關鍵字

gene-environment interaction ； ridge regression ； elastic net ； least absolute shrinkage and selection operator ； Taiwan Biobank ； body mass index ； FTO gene

參考文獻

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以懲罰迴歸法來檢定基因環境交互作用

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