DMRdb: a disease-centric Mendelian randomization database for systematically assessing causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases

Abstract

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.

Graphical Abstract

Figure 1.

Schematic overview of DMRdb. This figure presents a detailed workflow and data processing pipeline for DMRdb. In the ‘Data Collection and Curation’ phase, 6640 high-quality disease GWAS datasets were filtered and standardized from sources including FinnGen, GWAS Catalog, MRC IEU and UK Biobank. During the ‘Data Processing Pipeline’ phase, SNPs underwent rigorous filtering, followed by MR and sensitivity analyses. This process generated over 497 million results, comprising 43 million disease–disease MR results, 29 million pQTL–disease MR results, 267 million eQTL–disease MR results, 142 million mQTL–disease MR results and 16 million metabolite–disease MR results. Additionally, over 380 thousand causal relationship pairs were collected from 1223 literature sources relevant to MR analyses. In the ‘Database Construction’ phase, a user-friendly online database was developed, enabling users to query, search, and download all the results.

Figure 2.

Screenshots of DMRdb web pages. (A) The search function on the homepage allows users to search quickly for MR results across multiple modules, including diseases, genes, and proteins. (B) The Search page provides an advanced search function to further refine the MR results. (C) Browse page mainly consists of sidebar and data table. The list of MR analysis results could be viewed in an interactive table on this page. On the sidebar, users can customize filters to search for MR analysis results on the basis of various exposures, such as diseases, genes and proteins. (D) Detailed information on the MR results is displayed when users click the Study ID. (E) On the Disease GWAS page, users can browse basic information about disease trait GWAS datasets. They can download GWAS data by clicking the download button. (F) Detailed information about a disease GWAS dataset is displayed when users click the Study ID.

Figure 3.

Potential causal associations of type 2 diabetes and coronary heart disease in two-sample bidirectional Mendelian randomization (MR) analyses.