Genome-based prediction of common diseases: methodological considerations for future research.
Genome-based prediction of common diseases: methodological considerations for future research.
复制标题
DOI：
10.1186/gm20
复制
发表时间：
2009-02-18
期刊：
影响因子：
12.3
通讯作者：
van Duijn CM
中科院分区：
文献类型：
--
作者：
Janssens AC;van Duijn CM
将新兴的基因组知识转化为公共卫生和临床护理是未来几十年的主要挑战之一。目前，基于基因组的常见疾病预测，如2型糖尿病，冠心病和癌症，仍然没有信息。我们对多因素疾病的遗传基础的理解正在提高，但目前确定的易感性变异对疾病的发展贡献很小。与此同时，越来越多的公司正在根据个人基因图谱提供个性化的生活方式和健康建议。遗传图谱有限的预测价值与商业可用性之间的这种差异凸显了对基于基因组的应用在临床和公共卫生保健中的有用性进行严格评估的必要性。预计在不久的将来会发现大量的遗传变异，我们需要准备一个框架，用于设计和分析旨在评估基因检测的临床有效性和实用性的研究。在这篇文章中，我们回顾了最近的研究，从方法学的角度来看，遗传谱的预测价值和解决问题周围的选择的研究人群，遗传谱的建设，预测值的测量，校准和验证的预测模型，并评估临床效用。仔细考虑这些问题将有助于知识基础，需要确定有用的基因组为基础的应用程序在临床和公共卫生实践中的实施。
The translation of emerging genomic knowledge into public health and clinical care is one of the major challenges for the coming decades. At the moment, genome-based prediction of common diseases, such as type 2 diabetes, coronary heart disease and cancer, is still not informative. Our understanding of the genetic basis of multifactorial diseases is improving, but the currently identified susceptibility variants contribute only marginally to the development of disease. At the same time, an increasing number of companies are offering personalized lifestyle and health recommendations on the basis of individual genetic profiles. This discrepancy between the limited predictive value and the commercial availability of genetic profiles highlights the need for a critical appraisal of the usefulness of genome-based applications in clinical and public health care. Anticipating the discovery of a large number of genetic variants in the near future, we need to prepare a framework for the design and analysis of studies aiming to evaluate the clinical validity and utility of genetic tests. In this article, we review recent studies on the predictive value of genetic profiling from a methodological perspective and address issues around the choice of the study population, the construction of genetic profiles, the measurement of the predictive value, calibration and validation of prediction models, and assessment of clinical utility. Careful consideration of these issues will contribute to the knowledge base that is needed to identify useful genome-based applications for implementation in clinical and public health practice.
登录
查看更多内容
评估18种常见遗传变异的综合遗传变异对2型糖尿病风险的综合影响。
影响因子：
7.7
作者：
Lango H;UK Type 2 Diabetes Genetics Consortium;Palmer CN;Morris AD;Zeggini E;Hattersley AT;McCarthy MI;Frayling TM;Weedon MN
通讯作者：
Weedon MN
影响因子：
7.7
作者：
van Hoek M;Dehghan A;Witteman JC;van Duijn CM;Uitterlinden AG;Oostra BA;Hofman A;Sijbrands EJ;Janssens AC
通讯作者：
Janssens AC
影响因子：
8.8
作者：
Janssens, A. Cecile J. W.;Moonesinghe, Ramal;Khoury, Muin J.
通讯作者：
Khoury, Muin J.
影响因子：
37.8
作者：
Cook, Nancy R.
通讯作者：
Cook, Nancy R.
影响因子：
3.5
作者：
Janssens, A. Cecile J. W.;van Duijn, Cornelia M.
通讯作者：
van Duijn, Cornelia M.