Considering the high prevalence and poor prognosis of cardiometabolic multimorbidity (CMM), identifying causal factors and actively implementing preventive measures is crucial. However, Mendelian randomization (MR), a key method for identifying the causal factors of CMM, requires knowledge of the effects of SNPs on CMM, which remain unknown. We first analyzed the genetic overlap of single cardiometabolic diseases (CMDs) using the latest genome‐wide association study (GWAS) for evidential support and comparison. We observed strong positive genetic correlations and shared loci among all CMDs. Further, GWAS and post‐GWAS analyses of CMM were performed in 407 949 European ancestry individuals from the UK Biobank. Eleven loci and 12 lead SNPs were identified. By comparison, we found these SNPs were a subset of SNPs associated with CMDs, including both shared and non‐shared SNPs. Then, the polygenic risk score model predicted the risk of CMM (C‐index = 0.62) and we identified candidate genes related to lipid metabolism and immune function. Finally, as an example, two‐sample MR analysis based on the GWAS revealed potential causal effects of total cholesterol, serum urate, body mass index, and smoking on CMM. These results provide a basis for future MR research and inspire future studies on the mechanism and prevention of CMM.

中文翻译：

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英国生物银行心脏代谢多发病的全基因组关联研究

考虑到心脏代谢多病（CMM）的高患病率和不良预后，识别病因并积极采取预防措施至关重要。然而，孟德尔随机化 (MR) 作为识别 CMM 致病因素的关键方法，需要了解 SNP 对 CMM 的影响，而这一点目前尚不清楚。我们首先使用最新的全基因组关联研究（GWAS）分析了单一心脏代谢疾病（CMD）的遗传重叠，以进行证据支持和比较。我们观察到所有 CMD 之间存在很强的正遗传相关性和共享基因座。此外，对英国生物银行的 407 949 名欧洲血统个体进行了 CMM 的 GWAS 和 GWAS 后分析。确定了 11 个基因座和 12 个先导 SNP。通过比较，我们发现这些 SNP 是与 CMD 相关的 SNP 的子集，包括共享和非共享 SNP。然后，多基因风险评分模型预测了 CMM 的风险（C 指数 = 0.62），并确定了与脂质代谢和免疫功能相关的候选基因。最后，作为一个例子，基于 GWAS 的双样本 MR 分析揭示了总胆固醇、血清尿酸、体重指数和吸烟对 CMM 的潜在因果影响。这些结果为未来MR研究提供了基础，并为未来CMM发病机制和预防的研究提供了启发。