基于全基因组关联研究预测个体疾病遗传风险
Prediction of individual genetic risk to disease from genome-wide association studies.
作者信息
Wray Naomi R, Goddard Michael E, Visscher Peter M
机构信息
Genetic Epidemiology, Queensland Institute of Medical Research, Queensland 4029, Brisbane, Australia.
出版信息
Genome Res. 2007 Oct;17(10):1520-8. doi: 10.1101/gr.6665407. Epub 2007 Sep 4.
Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex genetic diseases are small, with most genotype relative risks in the range of 1.1-2.0. Although the increased risk of disease for a carrier is small for any single locus, knowledge of multiple-risk alleles throughout the genome could allow the identification of individuals that are at high risk. In this study, we investigate the number and effect size of risk loci that underlie complex disease constrained by the disease parameters of prevalence and heritability. Then we quantify the value of prediction of genetic risk to disease using a range of realistic combinations of the number, size, and distribution of risk effects that underlie complex diseases. We propose an approach to assess the genetic risk of a disease in healthy individuals, based on dense genome-wide SNP panels. We test this approach using simulation. When the number of loci contributing to the disease is >50, a large case-control study is needed to identify a set of risk loci for use in predicting the disease risk of healthy people not included in the case-control study. For diseases controlled by 1000 loci of mean relative risk of only 1.04, a case-control study with 10,000 cases and controls can lead to selection of approximately 75 loci that explain >50% of the genetic variance. The 5% of people with the highest predicted risk are three to seven times more likely to suffer the disease than the population average, depending on heritability and disease prevalence. Whether an individual with known genetic risk develops the disease depends on known and unknown environmental factors.
实证研究表明,复杂遗传疾病所涉及的单个因果风险等位基因的效应量较小,大多数基因型相对风险在1.1至2.0范围内。尽管对于任何单个基因座而言,携带者患疾病的风险增加幅度较小,但了解整个基因组中的多个风险等位基因可以识别出高风险个体。在本研究中,我们调查了受疾病患病率和遗传力等疾病参数限制的复杂疾病所涉及的风险基因座数量和效应量。然后,我们使用一系列复杂疾病所涉及的风险效应数量、大小和分布的实际组合,来量化遗传风险对疾病预测的价值。我们提出了一种基于密集全基因组SNP面板来评估健康个体疾病遗传风险的方法。我们通过模拟对该方法进行了测试。当导致疾病的基因座数量>50时,需要进行大规模病例对照研究,以识别出一组风险基因座,用于预测未纳入病例对照研究的健康人群的疾病风险。对于由1000个平均相对风险仅为1.04的基因座控制的疾病,一项包含10000例病例和对照的病例对照研究可导致选择大约75个解释>50%遗传变异的基因座。预测风险最高的5%人群患该病的可能性是总体平均水平的三到七倍,这取决于遗传力和疾病患病率。具有已知遗传风险的个体是否会患上该疾病取决于已知和未知的环境因素。