Evaluation of risk prediction updates from commercial genome-wide scans
Evaluation of risk prediction updates from commercial genome-wide scans
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DOI：
10.1097/gim.0b013e3181b13a4f
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发表时间：
2009-08-01
影响因子：
8.8
通讯作者：
Janssens, A. Cecile J. W.
中科院分区：
文献类型：
--
作者：
Mihaescu, Raluca;van Hoek, Mandy;Janssens, A. Cecile J. W.
目的：基于互联网的商业公司提供全基因组扫描来预测常见疾病的风险，并提供个性化的营养和生活方式建议。这些风险估计随着每一个新基因的发现而更新。方法：为了评估在商业全基因组扫描中更新风险信息的益处，我们比较了单独基于TCF7L2、单独基于18个多态性和18个多态性加年龄、性别和体重指数的2型糖尿病风险预测。使用鹿特丹研究的数据进行分析，这是一项针对55岁及以上个体的前瞻性、基于人群的研究。数据来自5297名参与者。结果：研究人群中2型糖尿病的实际患病率为20%。TCF7L2 CC基因型携带者的预测风险低于平均水平（预测风险为17.6%），而CT和TT基因型携带者的预测风险高于平均水平（20.8%和28.0%）。加上其他17个多态性导致34%的参与者被重新分类（即在低于和高于平均水平之间切换）：24%的CC携带者改变为风险增加，52%和6%的CT和TT携带者改变为风险降低。包括年龄、性别和身体质量指数的信息导致29%的人改变了分类（CC、CT和TT携带者分别为27%、31%和19%）。总的来说，39%的参与者在风险因素更新时改变了一次类别，11%的参与者改变了两次，即回到他们最初的风险类别。结论：随着时间的推移，更新风险因素可能会产生关于个人风险状况的相互矛盾的信息，如果生活方式和营养建议相应变化，这是不可取的。中华医学杂志，2009,11(8):588-594。
Purpose: Commercial internet-based companies offer genome-wide scans to predict the risk of common diseases and personalize nutrition and lifestyle recommendations. These risk estimates are updated with every new gene discovery. Methods: To assess the benefits of updating risk information in commercial genome-wide scans, we compared type 2 diabetes risk predictions based on TCF7L2 alone, 18 polymorphisms alone, and 18 polymorphisms plus age, sex, and body mass index. Analyses were performed using data from the Rotterdam study, a prospective, population-based study among individuals aged 55 years and older. Data were available from 5297 participants. Results: The actual prevalence of type 2 diabetes in the study population was 20%. Predicted risks were below average for carriers of the TCF7L2 CC genotype (predicted risk 17.6%) and above average for the CT and TT genotypes (20.8% and 28.0%). Adding the other 17 polymorphisms caused 34% of participants to be reclassified (i.e., switched between below and above average): 24% of the CC carriers changed to increased risk, 52% and 6% of the CT and TT carriers changed to decreased risk. Including information on age, sex, and body mass index caused 29% to change categories (27%, 31%, and 19% for CC, CT, and TT carriers, respectively). In total, 39% of participants changed categories once when risk factors were updated, and 11% changed twice, i.e., back to their initial risk category. Conclusion: Updating risk factors may produce contradictory information about an individual's risk status over time, which is undesirable if lifestyle and nutritional recommendations vary accordingly. Genet Med 2009:11(8):588-594.