Investigating causality between abnormalities of mineral metabolism and kidney, cardiovascular and bone disease

矿物质代谢异常一直与心血管和骨骼疾病有关， 患有慢性肾病的个体和普通人群。不过，尚不清楚是否 矿物质代谢生物标志物本身代表并发症的因果过程，肾功能如何 影响这些过程，以及哪种生物标志物（如果有的话）可能是最有希望的干预目标。 孟德尔随机化 (MR) 使用遗传变异作为感兴趣暴露的无混杂代理 估计其对结果的因果影响。我们现在已经揭示了与以下因素密切相关的遗传变异： 矿物质代谢标志物的循环水平，并将在 MR 框架内利用这些发现来 增进对矿物质代谢标志物在心血管和骨骼疾病中因果作用的了解。 MR 方法的最新发展也使我们能够检查相互作用并揭示相互作用的异质性。 新疗法的治疗效果或功效。 MR 可以提供关键证据来优先考虑进一步的研究和 临床应用，或者同样重要的是，阻止额外的资源分配给非因果性 途径。该应用程序的目标是全面评估矿物质之间的因果关系 代谢物、肾功能、治疗策略以及心血管的临床和亚临床表型 和骨骼疾病。 我们将基于孟德尔随机化技术，使用基因组数据进行分析，并将 利用公开的全基因组关联数据和两个最大的基于实践的生物库 世界：范德比尔特大学的 BioVU 和百万退伍军人计划 (MVP)。使用新颖的技术和资源， 我们将1）评估矿物质代谢物对心血管和骨骼疾病的因果影响； 2）调查 这些关联中肾功能的相互作用； 3）评估常用处方的可能效果 慢性肾病心血管和骨骼事件的药物和潜在药物靶点。在一起， 这些补充方法将增进对与矿物质代谢相关的病理学的理解 扰，并将为识别新药物和疗法提供一个启动点，以预防 心血管和骨骼疾病。

Abnormalities in mineral metabolism have consistently been associated with cardiovascular and bone disease, among individuals with chronic kidney disease and in the general population. However, it is unknown whether mineral metabolism biomarkers themselves represent causal processes for complications, how kidney function impacts these processes, and which biomarker, if any, may be the most promising interventional target. Mendelian Randomization (MR) employs genetic variants as unconfounded proxies of an exposure of interest to estimate its causal effect on an outcome. We have now revealed genetic variants robustly associated with circulating levels of mineral metabolism markers and will employ these findings, within the framework of MR, to advance knowledge of the causal roles of mineral metabolism marker in cardiovascular and bone disease. Recent developments in MR methods can also enable us to examine interactions and uncover heterogeneity of treatment effect or efficacy of new therapies. MR can provide critical evidence to prioritize further research and clinical applications, or just as importantly, to discourage additional resource allocation towards non-causal pathways. The goal of this application is to comprehensively evaluate causal relationships between mineral metabolites, kidney function, treatment strategies and clinical and subclinical phenotypes of cardiovascular and bone disease. We will conduct analyses using genomic data, based on Mendelian Randomization techniques, and will leverage publicly available genome-wide association data and two of the largest practice-based biobanks in the world: Vanderbilt’s BioVU and the Million Veteran Program (MVP). Using novel techniques and resources, we will 1) evaluate the causal effect of mineral metabolites on cardiovascular and bone disease; 2) investigate the interplay of kidney function in these associations; and 3) assess the likely effect of commonly prescribed medications and potential drug targets on cardiovascular and bone events in chronic kidney disease. Together, these complementary approaches will improve understanding of pathologies related to mineral metabolism disturbances and will provide a launch point for the identification of novel drugs and therapies to prevent cardiovascular and bone disease.