Jiesisibieke Zhu Liduzi, Cronjé Héléne Toinét, Schooling C Mary, Burgess Stephen
School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, China.
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Eur J Epidemiol. 2025 Jun 9. doi: 10.1007/s10654-025-01246-5.
Ketogenic diets are popular among people aiming for weight management. Ketone supplementation has been linked to improved cognitive performance and increased risk of insulin resistance. We aim to identify common genetic variants that allow Mendelian randomization investigations into further potential effects of ketone metabolism. We set four premises that we believe any valid instrument for ketone metabolism should satisfy. These are: (1) location in a gene region relevant to ketone metabolism, (2) association with all three primary ketone bodies (acetone, acetoacetate, and beta-hydroxybutyrate), (3) no pleiotropic associations, (4) associations with positive control variables (cognitive performance, two-hour glucose, and insulin fold change). We considered gene regions containing variants previously associated with acetone. Four of these regions had biological relevance to ketone metabolism. Lead variants for three of these four regions (SLC2A4, HMGCS2, OXCT1) were associated with all three primary ketone bodies. One region (SLC2A4) was associated with two-hour glucose and insulin fold change; however, this region had strong pleiotropic associations with blood pressure. One region (OXCT1) showed an association with cognitive performance, and thus satisfied all our premises to be a valid instrument for ketone metabolism. In a complementary agnostic approach considering all genome-wide significant predictors of the three primary ketone bodies in turn, genetically predicted acetoacetate based on seven variants was associated with improved cognitive performance. However, several variants selected in this approach were not located in biologically relevant gene regions and were pleiotropic. Causal claims from Mendelian randomization will be most reliable when the instrumental variable assumptions are plausibly satisfied. We illustrate a framework to identify candidate instruments based on biological considerations.
生酮饮食在旨在控制体重的人群中很受欢迎。补充酮已被证明与认知能力的改善以及胰岛素抵抗风险的增加有关。我们旨在识别常见的基因变异，以便通过孟德尔随机化研究进一步探究酮代谢的潜在影响。我们设定了四个前提条件，我们认为任何用于酮代谢的有效工具都应满足这些条件。这些条件是：（1）位于与酮代谢相关的基因区域；（2）与所有三种主要酮体（丙酮、乙酰乙酸和β-羟基丁酸）相关；（3）无多效性关联；（4）与阳性对照变量（认知能力、两小时血糖和胰岛素倍数变化）相关。我们考虑了包含先前与丙酮相关的变异的基因区域。其中四个区域与酮代谢具有生物学相关性。这四个区域中的三个区域（SLC2A4、HMGCS2、OXCT1）的主要变异与所有三种主要酮体相关。一个区域（SLC2A4）与两小时血糖和胰岛素倍数变化相关；然而，该区域与血压存在强烈的多效性关联。一个区域（OXCT1）与认知能力相关，因此满足我们所有前提条件，可作为酮代谢的有效工具。在一种互补的无假设方法中，依次考虑所有全基因组范围内三种主要酮体的显著预测因子，基于七个变异进行遗传预测的乙酰乙酸与认知能力的改善相关。然而，这种方法中选择的几个变异并不位于生物学相关的基因区域，并且具有多效性。当工具变量假设合理满足时，孟德尔随机化得出的因果关系声明将最为可靠。我们阐述了一个基于生物学考虑来识别候选工具的框架。
