Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis.
Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis.
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DOI：
10.1093/ehjopen/oeab043
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发表时间：
2022-01
期刊：
影响因子：
--
通讯作者：
Mokry M
中科院分区：
文献类型：
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作者：
Slenders L;Landsmeer LPL;Cui K;Depuydt MAC;Verwer M;Mekke J;Timmerman N;van den Dungen NAM;Kuiper J;de Winther MPJ;Prange KHM;Ma WF;Miller CL;Aherrahrou R;Civelek M;de Borst GJ;de Kleijn DPV;Asselbergs FW;den Ruijter HM;Boltjes A;Pasterkamp G;van der Laan SW;Mokry M
全基因组关联研究 (GWAS) 发现了数百种动脉粥样硬化疾病和心血管危险因素的常见遗传变异。将易感位点转化为药物发现的生物机制和靶标仍然具有挑战性。交叉遗传和基因表达数据导致了候选基因的识别。然而，先前研究的组织通常是无病的且细胞组成异质，这阻碍了准确的候选优先级排序。因此，我们分析了动脉粥样硬化斑块的单细胞转录组学的细胞类型特异性表达，以确定与动脉粥样硬化相关的候选基因-细胞对。我们利用 GWAS 汇总统计数据对 46 种动脉粥样硬化和心血管疾病、危险因素和其他特征进行了基于基因的分析。然后，我们将这些候选基因与单细胞 RNA 测序 (scRNA-seq) 数据相交叉，以确定动脉粥样硬化斑块中单个细胞（亚）群的特异性基因。冠状动脉疾病 (CAD) 基因座在斑块平滑肌细胞 (SMC)（SKI、KANK2 和 SORT1）P-adj 中显示出显着信号。 = 0.0012，以及内皮细胞 (EC) (SLC44A1、ATP2B1) P-adj。 = 0.0011。最后，我们使用肝脏来源的 scRNA-seq 数据，显示了与血清脂质水平有关的基因的肝细胞特异性富集。我们发现了新的和已知的基因-细胞对，指出了动脉粥样硬化疾病的新生物学机制。我们强调与 CAD 相关的位点揭示了主要在斑块 SMC 和 EC 群体中显着的关联水平。我们提出了一种直观的单细胞转录组驱动的工作流程，植根于人类大规模遗传研究，以识别与心血管特征相关的假定候选基因和受影响的细胞。总的来说，我们的工作流程可以识别与动脉粥样硬化相关的细胞特异性靶点，并且可以普遍应用于其他复杂的遗传疾病和性状。
Genome-wide association studies (GWASs) have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analysed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene–cell pairs. We applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with single-cell RNA sequencing (scRNA-seq) data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease (CAD) loci demonstrated a prominent signal in plaque smooth muscle cells (SMCs) (SKI, KANK2, and SORT1) P-adj. = 0.0012, and endothelial cells (ECs) (SLC44A1, ATP2B1) P-adj. = 0.0011. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels. We discovered novel and known gene–cell pairs pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with CAD reveal prominent association levels in mainly plaque SMC and EC populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.