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RCM: A novel association approach to search for coronary artery disease genetic related metabolites based on SNPs and metabolic network

机译：RCM：一种基于SNP和代谢网络的新型关联方法，用于搜索冠状动脉疾病的遗传相关代谢物

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Integration of genetic and metabolic network holds promise for providing insight into human disease. Coronary artery disease (CAD) is strongly heritable, but the heritability of metabolic compounds has not been evaluated in human metabolic context. Here we performed a genetic-based computational approach within eight sub-cellular networks from Edinburgh Human Metabolic Network to identify significant genetic risk compounds (SGRCs) of CAD. Our results provide the evidence that the high heritabilities of SGRCs played an important role in CAD pathogenesis. Besides, SGRCs were discovered to be strongly associated with lipid metabolism. We also established a possible disease-causing reference table to decipher genetic associations of SGRCs with CAD. Comparing with traditional method, RCM experienced better performance in CAD genetic risk compounds' identification. These findings provided novel insights into CAD pathogenesis from a genetic perspective.
机译：遗传和代谢网络的整合有望为人类疾病提供见识。冠状动脉疾病（CAD）具有很强的遗传性，但尚未在人类代谢环境中评估代谢化合物的遗传性。在这里，我们从爱丁堡人类代谢网络的八个亚细胞网络中进行了基于遗传的计算方法，以识别出CAD的重要遗传风险化合物（SGRC）。我们的结果提供了证据，表明SGRCs的高遗传力在CAD发病机理中起着重要作用。此外，发现SGRCs与脂质代谢密切相关。我们还建立了可能的致病参考表，以破译SGRC与CAD的遗传关联。与传统方法相比，RCM在CAD遗传风险化合物的鉴定中表现出更好的性能。这些发现从遗传学的角度为CAD发病机理提供了新颖的见解。

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