Khoury Muin J, Yang Quanhe, Gwinn Marta, Little Julian, Dana Flanders W
Office of Genomics and Disease Prevention, Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Genet Med. 2004 Jan-Feb;6(1):38-47. doi: 10.1097/01.gim.0000105751.71430.79.
The current clinical value of genomic profiling (testing for genotypes at multiple loci) for assessing susceptibility to common diseases and targeting behavioral and medical interventions is questionable. As common diseases result from many gene-environment interactions, epidemiologic studies should be used to examine the value of genomic profiling in terms of clinical validity (future disease positive and negative predictive value stratified by exposure), clinical utility (targeted interventions to reduce disease risk among persons with the profile) and public health utility (comparing reduction of disease burden in the population based on genomic profiling to population-wide interventions).
We investigate these parameters for a hypothetical common disease (5% lifetime risk), for which 3 genetic variants at different loci and one environmental exposure are risk factors.
We show that even for modest effects of each variant alone (risk ratios from 1.5-3.0) and modest interactions between the exposure and the genes, the disease predictive value for people with 2 or more variants (especially 3) can be quite high (50-100%) in the presence of a modifiable exposure. Individual risks can then be reduced by targeted exposure intervention among persons with the genotype. However, the predictive value for multiple genotypes is much lower for rarer diseases (< 1 per 1000). Also, with increasing number of genes in a profile, the population impact of disease reduction for targeted intervention based on genotype will be smaller, especially for rare genotypes, weak associations, and weak interactions.
To assess the value of genomic profiling, well-designed epidemiologic studies are needed to quantify disease risks, in addition to costs, benefits, and risks for testing and interventions.
基因组分析（对多个基因座的基因型进行检测）在评估常见疾病易感性以及指导行为和医学干预方面的当前临床价值存在疑问。由于常见疾病是由多种基因 - 环境相互作用导致的，因此应通过流行病学研究来检验基因组分析在临床有效性（按暴露分层的未来疾病阳性和阴性预测值）、临床实用性（针对具有该特征的人群进行有针对性的干预以降低疾病风险）和公共卫生实用性（将基于基因组分析的人群疾病负担减轻情况与全人群干预措施进行比较）方面的价值。
我们针对一种假设的常见疾病（终生风险为5%）研究这些参数，该疾病有3个位于不同基因座的遗传变异和一种环境暴露作为风险因素。
我们发现，即使每个变异单独的影响较小（风险比为1.5 - 3.0）且暴露与基因之间的相互作用较弱，在存在可改变的暴露情况下，对于具有2个或更多变异（尤其是3个变异）的人群，疾病预测值可能相当高（50 - 100%）。然后，对于具有该基因型的人群，通过有针对性的暴露干预可以降低个体风险。然而，对于更罕见的疾病（每1000人中少于1例），多种基因型的预测值要低得多。此外，随着基因谱中基因数量的增加，基于基因型的靶向干预对疾病减少的人群影响将更小，特别是对于罕见基因型、弱关联和弱相互作用的情况。
为了评估基因组分析的价值，除了检测和干预的成本、益处及风险外，还需要精心设计的流行病学研究来量化疾病风险。
