Background. Previous studies have shown that heart failure (HF) and chronic kidney disease (CKD) have common genetic mechanisms, overlapping pathophysiological pathways, and therapeutic drug—sodium-glucose cotransporter 2 (SGLT2) inhibitors. Methods. The genetic pleiotropy metaCCA method was applied on summary statistics data from two independent meta-analyses of GWAS comprising more than 1 million people to identify shared variants and pleiotropic effects between HF and CKD. Targets of SGLT2 inhibitors were predicted by SwissTargetPrediction and DrugBank databases. To refine all genes, we performed using versatile gene-based association study 2 (VEGAS2) and transcriptome-wide association studies (TWAS) for HF and CKD, respectively. Gene enrichment and KEGG pathway analyses were used to explore the potential functional significance of the identified genes and targets. Results. After metaCCA analysis, 4,624 SNPs and 1,745 genes were identified to be potentially pleiotropic in the univariate and multivariate SNP-multivariate phenotype analyses, respectively. 21 common genes were detected in both metaCCA and SGLT2 inhibitors’ target prediction. In addition, 169 putative pleiotropic genes were identified, which met the significance threshold both in metaCCA analysis and in the VEGAS2 or TWAS analysis for at least one disease. Conclusion. We identified novel variants associated with HF and CKD using effectively incorporating information from different GWAS datasets. Our analysis may provide new insights into HF and CKD therapeutic approaches based on the pleiotropic genes, common targets, and mechanisms by integrating the metaCCA method, TWAS and VEGAS2 analyses, and target prediction of SGLT2 inhibitors.

中文翻译：

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通过整合 metaCCA 和 SGLT2 抑制剂的靶点预测，探索与心力衰竭和慢性肾脏病相关的多效基因和治疗靶点

背景。以往的研究表明，心力衰竭 (HF) 和慢性肾脏病 (CKD) 具有共同的遗传机制、重叠的病理生理途径和治疗药物——钠-葡萄糖协同转运蛋白 2 (SGLT2) 抑制剂。方法. 遗传多效性 metaCCA 方法应用于来自超过 100 万人的 GWAS 的两项独立荟萃分析的汇总统计数据，以确定 HF 和 CKD 之间的共享变异和多效性效应。SGLT2 抑制剂的靶点由 SwissTargetPrediction 和 DrugBank 数据库预测。为了完善所有基因，我们分别对 HF 和 CKD 使用通用的基于基因的关联研究 2 (VEGAS2) 和转录组范围的关联研究 (TWAS)。基因富集和 KEGG 通路分析用于探索已识别基因和靶标的潜在功能意义。结果. 在 metaCCA 分析后，分别在单变量和多变量 SNP-多变量表型分析中鉴定出 4,624 个 SNP 和 1,745 个基因具有潜在的多效性。在 metaCCA 和 SGLT2 抑制剂的靶点预测中检测到 21 个共同基因。此外，鉴定了 169 个推定的多效性基因，这些基因在 metaCCA 分析和至少一种疾病的 VEGAS2 或 TWAS 分析中均满足显着性阈值。结论. 我们通过有效整合来自不同 GWAS 数据集的信息，确定了与 HF 和 CKD 相关的新变体。我们的分析可以通过整合 metaCCA 方法、TWAS 和 VEGAS2 分析以及 SGLT2 抑制剂的靶点预测，为基于多效基因、共同靶点和机制的 HF 和 CKD 治疗方法提供新的见解。