Whitcomb David C
Department of Medicine, University of Pittsburgh, GI Administration, UPMC Presbyterian, Mezzanine Level 2, C Wing, 200 Lothrop Street, Pittsburgh, PA 15213, USA.
Endocrinol Metab Clin North Am. 2006 Jun;35(2):255-69, viii. doi: 10.1016/j.ecl.2006.02.010.
Rapid advances in information and technology provide opportunities to discover the risks or causes for various disorders within individual patients. The availability of new data and new technology has outstripped the conceptual framework of simple disorders,however, and challenges current statistical approaches. The author addresses the issues surrounding study design and sample size for complex genetic traits with special attention to meta-analysis and systems biology. The author concludes that meta-analysis should play a limited role in evaluating studies of complex genetic diseases. Instead, systems biology-based approaches should be developed to integrate multiple, focused, and mechanistic association studies, with the goal of assisting in the risk assessment of patients on a person-by-person basis.
信息与技术的飞速发展为发现个体患者各种病症的风险或病因提供了契机。然而，新数据和新技术的可得性已超越了简单病症的概念框架，对当前的统计方法构成了挑战。作者探讨了围绕复杂遗传性状的研究设计和样本量的问题，特别关注荟萃分析和系统生物学。作者得出结论，荟萃分析在评估复杂遗传疾病的研究中应发挥有限作用。相反，应开发基于系统生物学的方法，以整合多个有针对性的机制性关联研究，目标是在个体层面协助对患者进行风险评估。
