Mendelian Randomization Studies of Coffee and Caffeine Consumption.
Mendelian Randomization Studies of Coffee and Caffeine Consumption.
复制标题
DOI：
10.3390/nu10101343
复制
发表时间：
2018-09-20
期刊：
影响因子：
5.9
通讯作者：
Munafo MR
中科院分区：
文献类型：
--
作者：
Cornelis MC;Munafo MR
据报道，习惯性咖啡和咖啡因消费与许多健康结果有关。这种观点的重点是孟德尔随机化（MR）的方法来确定这种关联是否是因果关系。咖啡和咖啡因消费的遗传工具，沿着MR的关键概念和特殊的挑战时，应用这种方法来研究咖啡和咖啡因。迄今为止，至少有15项MR研究调查了咖啡或咖啡因使用对2型糖尿病，心血管疾病，阿尔茨海默病，帕金森病，痛风，骨关节炎，癌症，睡眠障碍和其他物质使用风险的因果关系。大多数研究都没有一致的支持咖啡或咖啡因对这些健康结果的因果作用。常见的研究局限性包括统计功效低、潜在的多效性和对撞机偏倚风险。因此，在许多情况下，因果关系的作用不能完全排除。概念上的挑战也来自于目前基因仪器所捕获的咖啡和咖啡因使用的不同方面。然而，随着对咖啡和咖啡因相关基因座的持续全基因组搜索沿着先进的统计方法和MR设计，MR有望成为了解咖啡和咖啡因对人类健康的因果影响的有价值的方法。
Habitual coffee and caffeine consumption has been reported to be associated with numerous health outcomes. This perspective focuses on Mendelian Randomization (MR) approaches for determining whether such associations are causal. Genetic instruments for coffee and caffeine consumption are described, along with key concepts of MR and particular challenges when applying this approach to studies of coffee and caffeine. To date, at least fifteen MR studies have investigated the causal role of coffee or caffeine use on risk of type 2 diabetes, cardiovascular disease, Alzheimer’s disease, Parkinson’s disease, gout, osteoarthritis, cancers, sleep disturbances and other substance use. Most studies provide no consistent support for a causal role of coffee or caffeine on these health outcomes. Common study limitations include low statistical power, potential pleiotropy, and risk of collider bias. As a result, in many cases a causal role cannot confidently be ruled out. Conceptual challenges also arise from the different aspects of coffee and caffeine use captured by current genetic instruments. Nevertheless, with continued genome-wide searches for coffee and caffeine related loci along with advanced statistical methods and MR designs, MR promises to be a valuable approach to understanding the causal impact that coffee and caffeine have in human health.
登录
查看更多内容
影响因子：
2.1
作者：
Bowden J;Davey Smith G;Haycock PC;Burgess S
通讯作者：
Burgess S
DOI：
10.1097/ede.0000000000000559
发表时间：
2017-01
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Burgess S;Bowden J;Fall T;Ingelsson E;Thompson SG
通讯作者：
Thompson SG
影响因子：
6.1
作者：
Andrzejewski, D;Roach, JAG;Musser, SM
通讯作者：
Musser, SM
影响因子：
7.7
作者：
Bjørngaard JH;Nordestgaard AT;Taylor AE;Treur JL;Gabrielsen ME;Munafò MR;Nordestgaard BG;Åsvold BO;Romundstad P;Davey Smith G
通讯作者：
Davey Smith G
影响因子：
7.7
作者：
Burgess S;Daniel RM;Butterworth AS;Thompson SG;EPIC-InterAct Consortium
通讯作者：
EPIC-InterAct Consortium