Zheng Xiao, Tian Zhihao, Che Xiaohui, Zhang Xu, Xiang Yu, Ge Zhijian, Zhai Zhaoyu, Ma Qinfeng, Pan Jianbo
Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China.
Nucleic Acids Res. 2025 Jan 6;53(D1):D1363-D1371. doi: 10.1093/nar/gkae853.
Exploring the causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases is fundamental to the life sciences. However, large-scale research using Mendelian randomization (MR) analysis is currently lacking. To address this, we introduce DMRdb (http://www.inbirg.com/DMRdb/), a disease-centric Mendelian randomization database, designed to systematically assess causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases. The database consists of three main components: (i) 6640 high-quality disease genome-wide association studies (GWASs) from public sources that were subjected to rigorous quality filtering and standardization; (ii) over 497 billion results from MR analyses involving 6640 disease GWAS datasets, 16 238 expression quantitative trait loci (eQTLs) data, 2564 protein quantitative trait loci (pQTLs) data, 12 000 methylation quantitative trait locus (meQTLs) data and 825 metabolites data and (iii) over 380 000 causal relationship pairs from 1223 literature sources relevant to MR analyses. A user-friendly online database was developed to allow users to query, search, and download all the results. In summary, we anticipate that DMRdb will be a valuable resource for advancing our understanding of disease mechanisms and identifying new biomarkers and therapeutic targets.
探索疾病与基因、蛋白质、CpG位点、代谢物及其他疾病之间的因果关系是生命科学的基础。然而，目前缺乏使用孟德尔随机化（MR）分析的大规模研究。为了解决这一问题，我们引入了DMRdb（http://www.inbirg.com/DMRdb/），这是一个以疾病为中心的孟德尔随机化数据库，旨在系统评估疾病与基因、蛋白质、CpG位点、代谢物及其他疾病之间的因果关系。该数据库由三个主要部分组成：（i）来自公共来源的6640项高质量疾病全基因组关联研究（GWAS），这些研究经过了严格的质量筛选和标准化；（ii）超过4970亿条MR分析结果，涉及6640个疾病GWAS数据集、16238个表达数量性状位点（eQTL）数据、2564个蛋白质数量性状位点（pQTL）数据、12000个甲基化数量性状位点（meQTL）数据和825个代谢物数据；（iii）来自1223个与MR分析相关的文献来源的超过380000个因果关系对。开发了一个用户友好的在线数据库，允许用户查询、搜索和下载所有结果。总之，我们预计DMRdb将成为推动我们对疾病机制的理解以及识别新的生物标志物和治疗靶点的宝贵资源。
