Leyden Genevieve M, Sobczyk Maria K, Richardson Tom G, Gaunt Tom R
MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK.
Genome Med. 2025 May 15;17(1):54. doi: 10.1186/s13073-025-01472-2.
Mendelian randomization (MR) leverages trait associated genetic variants as instrumental variables (IVs) to determine causal relationships in epidemiology. However, genetic IVs for complex traits are typically highly heterogeneous and, at a molecular level, exert effects on different biological processes. Exploration of the biological underpinnings of such heterogeneity can enhance our understanding of disease mechanisms and inform therapeutic strategies. Here, we introduce a new approach to instrument partitioning based on enrichment of Mendelian disease categories (pathway-partitioned) and compare it to an existing method based on genetic colocalization in contrasting tissues (tissue-partitioned).
We employed individual- and summary-level MR methodologies using SNPs grouped by pathway informed by proximity to Mendelian disease genes affecting the renal system or vasculature (for blood pressure (BP)), or mental health and metabolic disorders (for body mass index (BMI)). We compared the causal effects of pathway-partitioned SNPs on cardiometabolic outcomes with those derived using tissue-partitioned SNPs informed by colocalization with gene expression in kidney, artery (BP), or adipose and brain tissues (BMI). Additionally, we assessed the likelihood that estimates observed for partitioned exposures could emerge by chance using random SNP sampling.
Our pathway-partitioned findings suggest the causal relationship between systolic BP and heart disease is predominantly driven by vessel over renal pathways. The stronger effect attributed to kidney over artery tissue in our tissue-partitioned MR hints at a multifaceted interplay between pathways in the disease aetiology. We consistently identified a dominant role for vessel (pathway) and artery (tissue) driving the negative directional effect of diastolic BP on left ventricular stroke volume and positive directional effect of systolic BP on type 2 diabetes. We also found when dissecting the BMI pathway contribution to atrial fibrillation that metabolic-pathway and brain-tissue IVs predominantly drove the causal effects relative to mental health and adipose in pathway- and tissue-partitioned MR analyses, respectively.
This study presents a novel approach to dissecting heterogeneity in MR by integrating clinical phenotypes associated with Mendelian disease. Our findings emphasize the importance of understanding pathway-/tissue-specific contributions to complex exposures when interpreting causal relationships in MR. Importantly, we advocate caution and robust validation when interpreting pathway-partitioned effect size differences.
孟德尔随机化(MR)利用与性状相关的基因变异作为工具变量(IVs)来确定流行病学中的因果关系。然而,复杂性状的基因IVs通常高度异质,并且在分子水平上对不同的生物过程产生影响。探索这种异质性的生物学基础可以增进我们对疾病机制的理解,并为治疗策略提供信息。在此,我们引入一种基于孟德尔疾病类别富集的工具划分新方法(通路划分法),并将其与现有的基于不同组织中基因共定位的方法(组织划分法)进行比较。
我们采用个体水平和汇总水平的MR方法,使用根据与影响肾脏系统或血管系统(针对血压(BP))的孟德尔疾病基因的接近程度分组的单核苷酸多态性(SNPs),或针对心理健康和代谢紊乱(针对体重指数(BMI))的SNPs。我们将通路划分的SNPs对心脏代谢结局的因果效应与使用通过与肾脏、动脉(针对BP)或脂肪和脑组织(针对BMI)中的基因表达共定位得出的组织划分的SNPs得出的因果效应进行比较。此外,我们使用随机SNP抽样评估了观察到的划分暴露估计值可能偶然出现的可能性。
我们通路划分的研究结果表明,收缩压与心脏病之间的因果关系主要由血管途径而非肾脏途径驱动。在我们组织划分的MR中,归因于肾脏组织而非动脉组织的更强效应暗示了疾病病因中各途径之间的多方面相互作用。我们一致确定血管(通路)和动脉(组织)在驱动舒张压对左心室每搏输出量的负向作用以及收缩压对2型糖尿病的正向作用方面起主导作用。我们还发现,在剖析BMI通路对心房颤动的贡献时,在通路划分和组织划分的MR分析中,代谢通路和脑组织IVs分别相对于心理健康和脂肪组织主要驱动了因果效应。
本研究提出了一种通过整合与孟德尔疾病相关的临床表型来剖析MR异质性的新方法。我们的研究结果强调了在解释MR中的因果关系时理解通路/组织特异性对复杂暴露的贡献的重要性。重要的是,我们主张在解释通路划分的效应大小差异时要谨慎并进行有力验证。