Edland Steven D, Slager Susan, Farrer Matthew
Division of Clinical Epidemiology, Department of Health Science Research, Mayo Clinic and Foundation, Rochester, MN 55905, USA.
Stat Med. 2004 Jan 30;23(2):169-78. doi: 10.1002/sim.1706.
Genetic association studies have identified important risk factors for Alzheimer's disease and other diseases. However, the ease with which these methods can be applied and the shear number of polymorphisms in the human genome has led to a well-characterized multiple comparison problem-given the number of genetic variants being tested, it is likely that many of the positive findings reported in the literature to date will prove to be false positive findings explained simply by random fluctuation in data and type I error. The disparity of findings in initial positive reports versus subsequent negative replication studies observed in the Alzheimer's disease literature underscores this problem. The problem of a high false positive rate can be addressed in part by using statistical correction for multiple comparisons in larger and statistically more powerful samples and in meta-analyses of smaller samples. National initiatives are now being considered to address this problem by encouraging sharing of genetic material. Of equal concern in planning future initiatives are methodological issues that are the domain of the epidemiologist. In fact, it is possible that disparate findings across case-control studies reported to date may be explained in part by problems in the design, analysis and interpretation of these studies. The involvement of epidemiologists may improve the situation in this regard. For example, population stratification bias, control selection bias and prevalent case bias can be minimized by careful study design and by appropriate statistical analysis. Regarding interpretation of case-control studies, a more careful consideration of the strength of evidence for a given genetic variant may help to temper enthusiasm for, or appropriately qualify, positive findings. Epidemiologists have well-developed causal criteria for this purpose. This paper reviews the current state of case-control studies of genetic variants in Alzheimer's disease from the epidemiological perspective. The problem of multiple comparisons and a high false positive rate is reviewed. The potential for bias in case-control studies of Alzheimer's disease is reviewed by way of example. Future initiatives to promote case-control studies of genetic variants in Alzheimer's disease can only benefit from increased awareness the tools of epidemiology.
基因关联研究已经确定了阿尔茨海默病和其他疾病的重要风险因素。然而,鉴于人类基因组中多态性的数量众多,这些方法的易用性导致了一个特征明显的多重比较问题——鉴于所测试的基因变异数量众多,迄今为止文献中报道的许多阳性结果很可能是假阳性结果,仅仅是由数据中的随机波动和I型错误造成的。阿尔茨海默病文献中观察到的初始阳性报告与后续阴性重复研究结果之间的差异凸显了这一问题。通过在更大且统计效力更强的样本中进行多重比较的统计校正以及对较小样本进行荟萃分析,可以部分解决假阳性率高的问题。目前正在考虑国家层面的举措,通过鼓励基因材料的共享来解决这一问题。在规划未来举措时,同样值得关注的是属于流行病学家领域的方法学问题。事实上,迄今为止不同病例对照研究中出现的不同结果,可能部分是由这些研究的设计、分析和解释中的问题所导致的。流行病学家的参与可能会改善这方面的情况。例如,通过精心的研究设计和适当的统计分析,可以将人群分层偏倚、对照选择偏倚和现患病例偏倚降至最低。关于病例对照研究的解释,对特定基因变异证据强度进行更仔细的考虑,可能有助于抑制对阳性结果的过度热情,或对其进行适当限定。流行病学家为此制定了完善的因果标准。本文从流行病学角度综述了阿尔茨海默病基因变异病例对照研究的现状。回顾了多重比较和高假阳性率的问题。通过举例回顾了阿尔茨海默病病例对照研究中存在偏倚的可能性。未来促进阿尔茨海默病基因变异病例对照研究的举措,只有通过提高对流行病学工具的认识才能受益。