Genetic Insights Into Smooth Muscle Cell Contributions to Coronary Artery Disease.
Genetic Insights Into Smooth Muscle Cell Contributions to Coronary Artery Disease.
复制标题
DOI：
10.1161/atvbaha.119.312141
复制
发表时间：
2019-06
期刊：
影响因子：
--
通讯作者：
Miller CL
中科院分区：
文献类型：
--
作者：
Wong D;Turner AW;Miller CL
冠状动脉疾病是一种复杂的心血管疾病，涉及一生中遗传和环境影响的相互作用。虽然在了解生活方式风险因素方面取得了相当大的进展，但从全基因组关联研究中确定的遗传因素可能会捕获传统临床测试未发现的其他隐藏风险。这些遗传学发现突出了血管壁中失调的许多候选基因和途径，包括涉及平滑肌细胞表型调节和损伤反应的那些。在这里，我们总结了一些全基因组的重要位点支持其在平滑肌细胞生物学和疾病中的作用的实验证据。我们还讨论了分子数量性状基因定位作为一个强大的发现和精细定位方法应用于平滑肌细胞和冠状动脉疾病相关组织。我们强调替代遗传策略的迫切需要，包括顺式/反式调控网络分析，基因组编辑和扰动，以及在正常和疾病状态下平滑肌细胞组织和模式生物的单细胞测序。通过整合多种实验和分析模式，这些多维数据集应该改善冠状动脉疾病全基因组关联研究和分子数量性状位点信号的解释，并为治疗干预或风险预测提供候选靶点。
Coronary artery disease is a complex cardiovascular disease involving an interplay of genetic and environmental influences over a lifetime. Although considerable progress has been made in understanding lifestyle risk factors, genetic factors identified from genome-wide association studies may capture additional hidden risk undetected by traditional clinical tests. These genetic discoveries have highlighted many candidate genes and pathways dysregulated in the vessel wall, including those involving smooth muscle cell phenotypic modulation and injury responses. Here, we summarize experimental evidence for a few genome-wide significant loci supporting their roles in smooth muscle cell biology and disease. We also discuss molecular quantitative trait locus mapping as a powerful discovery and fine-mapping approach applied to smooth muscle cell and coronary artery disease-relevant tissues. We emphasize the critical need for alternative genetic strategies, including cis/trans-regulatory network analysis, genome editing, and perturbations, as well as single-cell sequencing in smooth muscle cell tissues and model organisms, under both normal and disease states. By integrating multiple experimental and analytical modalities, these multidimensional datasets should improve the interpretation of coronary artery disease genome-wide association studies and molecular quantitative trait locus signals and inform candidate targets for therapeutic intervention or risk prediction.