Mendelian randomization studies of periodontitis: Understanding benefits and natural limitations in an applied context

孟德尔随机化 背景(考古学) 观察研究 医学 风险分析(工程) 清晰 因果推理 混淆 口译(哲学) 介绍(产科) 推论 计算机科学 特质 管理科学 数据科学 生物 人工智能 病理 遗传变异 工程类 外科 基因 程序设计语言 古生物学 基因型 生物化学
作者
Simon Haworth,Nicholas J. Timpson,Kimon Divaris
出处
期刊:Journal of Clinical Periodontology [Wiley]
卷期号:51 (10): 1258-1266
标识
DOI:10.1111/jcpe.14029
摘要

Mendelian randomization (MR) is a flexible analytical tool that has been widely applied to strengthen causal inference in observational epidemiology and is now gaining attention in many areas including periodontal research. The interpretation of results drawn from MR is based on a series of assumptions, which can be unrealistic or difficult to meet faithfully in some settings. However, we argue that with care, this does not necessarily prevent valuable deployment of the approach. We argue that clarity of presentation as well as careful assessment of specific analytical conditions is a fundamental part of all MR analyses. To that end, awareness of its limitations should also guide the design of MR investigations and the presentation of results rather than rule out its use altogether. Notably, considerations similar to those known to be important in conventional epidemiological settings apply to MR. While MR studies are valuable in their contrast to other study limitations, the application of this technique must be carefully cross-examined. Specific considerations include possible confounders, recruitment strategy and phenotypic measurement and differential analysis properties across studies. In the case of periodontal research, current MR applications are limited by the available evidence base for genetic contributions to periodontitis; however, this sets a specific scene for the strategic use of MR and shines light on a need for greater research emphasis on the genetics of the condition and intermediaries. This article provides a perspective on the uses and inherent limitations of MR studies and the importance of adhering to basic epidemiological principles when designing them.
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