scMRdb: a comprehensive resource for cell-type-resolved Mendelian randomization of complex traits

Clicks: 16
ID: 337711
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #1,205 of 1,306 articles by views in Nucleic Acids Research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,306 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Mendelian randomization (MR) is a powerful analytical approach to infer putative causal links between gene expression and human disease, using genetic variants as instrumental variables to mitigate confounding and reverse causation. However, existing MR resources predominantly rely on bulk-tissue expression quantitative trait loci (eQTLs), which mask cell-type-specific transcriptional effects by averaging expression across cellular populations. Furthermore, cell-type-resolved causal evidence from single-cell eQTL (sc-eQTL) MR analyses remains fragmented across individual studies with inconsistent workflows, prohibiting standardized cross-cell-type comparisons. Here we present scMRdb (https://ngdc.cncb.ac.cn/scmrdb), a comprehensive resource for cell-type-resolved MR of human complex traits and diseases. scMRdb harmonizes 5206 genome-wide association study (GWAS) summary statistics of European and East Asian ancestry with 585 sc-eQTL datasets spanning 11 tissues and cell systems, including 110 cell types. A uniform pipeline evaluates all gene-trait pairs via MR followed by Steiger directionality testing. Significant associations are assessed by colocalization, and results are stratified into six confidence tiers with integrated drug-target annotation. scMRdb enables systematic recovery of candidate causal genes supported by cell-type-resolved regulatory evidence that is often diluted or obscured in bulk-tissue analyses. We expect scMRdb to serve as a user-friendly portal for generating cell-type-informed mechanistic hypotheses and prioritizing actionable therapeutic targets for complex human diseases.
Reference Key
openalex_W7224479526 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Siyu Pan, Ziyang Wang, Peilin Jia
Are you one of these authors? Claim your profile
Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1063
URL
https://doi.org/10.1093/nar/gkag1063
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.