利用韩国哮喘患者的哮喘血液 eQTL 鉴定哮喘相关基因。

Identification of asthma-related genes using asthmatic blood eQTLs of Korean patients.

机构信息

Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.

Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Korea.

出版信息

BMC Med Genomics. 2023 Oct 24;16(1):259. doi: 10.1186/s12920-023-01677-7.

DOI:10.1186/s12920-023-01677-7

PMID:37875944

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10599017/

Abstract

BACKGROUND

More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects.

METHODS

We performed a blood eQTL analysis using transcriptomic and genotypic data from 433 Korean asthma patients. To identify asthma-related genes, we carried out colocalization, Summary-based Mendelian Randomization (SMR) analysis, and Transcriptome-Wide Association Study (TWAS) using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study.

RESULTS

We identified 340,274 cis-eQTL and 2,875 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 64.1% of the 2,875 eGenes overlapped with the GTEx eGenes and 39.0% with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 15 asthma-related genes specific to the Korean asthmatic eQTL data.

CONCLUSIONS

We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.

摘要

背景

在全基因组关联研究（GWAS）中已经发现了 200 多个与哮喘相关的遗传变异。表达数量性状基因座（eQTL）数据资源有助于识别 GWAS 信号的因果基因，但由于大多数 eQTL 数据是从正常健康受试者中获得的，因此很难找到反映疾病状态的 eQTL。

方法

我们使用来自 433 名韩国哮喘患者的转录组和基因型数据进行血液 eQTL 分析。为了鉴定与哮喘相关的基因，我们使用哮喘 GWAS 结果和 eQTL 数据进行 colocalization、基于汇总的孟德尔随机化（SMR）分析和转录组全基因组关联研究（TWAS）。此外，我们将疾病 eQTL 数据和哮喘相关基因的结果与来自 Genotype-Tissue Expression（GTEx）项目和日本研究的两项正常血液 eQTL 数据进行了比较。

结果

我们从哮喘 eQTL 分析中鉴定出 340,274 个 cis-eQTL 和 2,875 个 eGenes。我们将疾病 eQTL 结果与 GTEx 和日本研究进行了比较，发现 2,875 个 eGenes 中有 64.1%与 GTEx 的 eGenes 重叠，39.0%与日本的 eGenes 重叠。通过将哮喘 eQTL 数据与哮喘 GWAS 进行综合分析，使用 colocalization 和 SMR 方法，我们鉴定出了 15 个仅与韩国哮喘 eQTL 数据相关的哮喘相关基因。