整合分析优先考虑慢性静脉疾病的相关基因和风险因素。

Integrative analysis prioritizes the relevant genes and risk factors for chronic venous disease.

机构信息

Division of Vascular Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China; National-Guangdong Joint Engineering Laboratory for Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou, Guangdong, China.

Department of Ophthalmology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China; Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China.

出版信息

J Vasc Surg Venous Lymphat Disord. 2022 May;10(3):738-748.e5. doi: 10.1016/j.jvsv.2022.02.006. Epub 2022 Feb 24.

DOI:10.1016/j.jvsv.2022.02.006

PMID:35218958

Abstract

OBJECTIVE

Chronic venous disease (CVD) refers to a range of symptoms resulting from long-term morphological and functional abnormalities of the venous system. However, the mechanism of CVD development remains largely unknown. Here, we aim to provide more information on CVD pathogenesis, prevention strategies, and therapy development through the integrative analysis of large-scale genetic data.

METHODS

Genetic data were obtained from publicly accessible databases. We used different approaches, including Functional Mapping and Annotation, DEPICT, Sherlock, SMR/HEIDIS, DEPICT, and NetWAS to identify possible causal genes for CVD. Candidate genes were prioritized to further literature-based review. The differential expression of prioritized genes was validated by microarray from the Gene Expression Omnibus, a public genomics data repository and real-time quantitative polymerase chain reaction of varicose vein specimens. The causal relationships between risk factors and CVD were assessed using the two-sample Mendelian randomization approach.

RESULTS

We identified 46 lead single-nucleotide polymorphisms and 26 plausible causal genes for CVD. Microarray data indicated differential expression of possible causal genes in CVD when compared with controls. The expression levels of WDR92, RSPO3, LIMA, ABCB10, DNAJC7, C1S, and CXCL1 were significantly downregulated (P < .05). PHLDA1 and SERPINE1 were significantly upregulated (P < .05). Dysregulated expression of WDR92, RSPO3, and CASZ1 was also found in varicose vein specimens by quantitative polymerase chain reaction. Two-sample Mendelian randomization suggested causative effects of body mass index (odds ratio [OR], 1.008; 95% confidence interval [CI], 1.005-1.010), standing height (OR, 1.009; 95% CI, 1.007-1.011), college degree (OR, 0.983; 95% CI, 0.991-0.976), insulin (OR, 0.858; 95% CI, 0.794-0.928), and metformin (OR, 0.944; 95% CI, 0.904-0.985) on CVD.

CONCLUSIONS

Our study integrates genetic and gene expression data to make an effective risk gene prediction and etiological inferences for CVD. Prioritized candidate genes provide more insights into CVD pathogenesis, and the causative effects of risk factors on CVD that deserve further investigation.

摘要

目的

慢性静脉疾病（CVD）是指由于静脉系统长期形态和功能异常而引起的一系列症状。然而，CVD 发展的机制在很大程度上仍然未知。在这里，我们旨在通过对大规模遗传数据的综合分析，提供更多关于 CVD 发病机制、预防策略和治疗开发的信息。

方法

遗传数据来自公开可访问的数据库。我们使用了不同的方法，包括功能映射和注释、DEPICT、Sherlock、SMR/HEIDIS、DEPICT 和 NetWAS，以识别 CVD 的可能因果基因。候选基因被优先排序，以便进一步进行基于文献的综述。通过 Gene Expression Omnibus（一个公共基因组学数据存储库）中的微阵列和静脉曲张标本的实时定量聚合酶链反应，验证了优先基因的差异表达。使用两样本 Mendelian 随机化方法评估风险因素与 CVD 之间的因果关系。

结果

我们确定了 46 个 CVD 的 lead single-nucleotide polymorphisms 和 26 个可能的因果基因。与对照组相比，微阵列数据表明 CVD 中可能的因果基因表达存在差异。WDR92、RSPO3、LIMA、ABCB10、DNAJC7、C1S 和 CXCL1 的表达水平显著下调（P<.05）。PHLDA1 和 SERPINE1 的表达水平显著上调（P<.05）。通过定量聚合酶链反应还发现静脉曲张标本中 WDR92、RSPO3 和 CASZ1 的表达失调。两样本 Mendelian 随机化表明体重指数（OR，1.008；95%置信区间[CI]，1.005-1.010）、站立身高（OR，1.009；95%CI，1.007-1.011）、大学学历（OR，0.983；95%CI，0.991-0.976）、胰岛素（OR，0.858；95%CI，0.794-0.928）和二甲双胍（OR，0.944；95%CI，0.904-0.985）对 CVD 有因果作用。