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冠心病生物标志物与风险因素性状位点在3p21.31和HLA区域的汇聚。

Convergence of biomarkers and risk factor trait loci of coronary artery disease at 3p21.31 and HLA region.

作者信息

Nikpay Majid, McPherson Ruth

机构信息

Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, ON, Canada.

Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON, Canada.

出版信息

NPJ Genom Med. 2021 Feb 11;6(1):12. doi: 10.1038/s41525-021-00174-z.

Abstract

Here we seek to identify molecular biomarkers that mediate the effect of risk factors on coronary artery disease (CAD). We perform a SNP-based multiomics data analysis to find biomarkers (probes) causally associated with the risk of CAD within known genomic loci for its risk factors. We identify 78 biomarkers, the majority (64%) of which are methylation probes. We detect the convergence of several CNS and lifestyle trait loci and their biomarkers at the 3p21.31 and human leukocyte antigen (HLA) regions. The 3p21.31 locus was the most populated region in the convergence of biomarkers and risk factors. In this region, we noted as the BSN gene becomes methylated the level of stomatin (STOM) in blood increases and this contributes to higher risk of CAD. In the HLA locus, we identify several methylation biomarkers associated with various CAD risk factors. SNPs in the CFB gene display a trans-regulatory impact on the GRIA4 protein level. A methylation site upstream of the APOE gene is associated with a higher protein level of S100A13 which in turn leads to higher LDL-C and greater CAD risk. We find UHRF1BP1 and ILRUN mediate the effect of obesity on CAD whereas methylation sites within NOS3 and CKM mediate the effect of their associated-risk factors on CAD. This study provides further insight into the biology of CAD and identifies a list of biomarkers that mediate the impact of risk factors on CAD. A SNP-based initiative can unite data from various fields of omics into a single network of knowledge.

摘要

在此,我们试图识别介导风险因素对冠状动脉疾病(CAD)影响的分子生物标志物。我们进行了基于单核苷酸多态性(SNP)的多组学数据分析,以在已知基因组位点中寻找与其风险因素相关的、与CAD风险有因果关系的生物标志物(探针)。我们识别出78种生物标志物,其中大多数(64%)是甲基化探针。我们在3p21.31和人类白细胞抗原(HLA)区域检测到几个中枢神经系统和生活方式性状位点及其生物标志物的汇聚。3p21.31位点是生物标志物与风险因素汇聚最多的区域。在该区域,我们注意到随着BSN基因甲基化,血液中血影蛋白(STOM)水平升高,这会导致CAD风险增加。在HLA位点,我们识别出几种与各种CAD风险因素相关的甲基化生物标志物。CFB基因中的单核苷酸多态性对GRIA4蛋白水平有反式调节作用。APOE基因上游的一个甲基化位点与S100A13蛋白水平升高相关,这反过来又导致低密度脂蛋白胆固醇(LDL-C)升高和CAD风险增加。我们发现UHRF1BP1和ILRUN介导肥胖对CAD的影响,而NOS3和CKM内的甲基化位点介导其相关风险因素对CAD的影响。本研究进一步深入了解了CAD的生物学机制,并识别出一系列介导风险因素对CAD影响的生物标志物。基于SNP的研究可以将来自各个组学领域的数据整合到一个单一的知识网络中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8184/7878768/e2ecc3238567/41525_2021_174_Fig1_HTML.jpg

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