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Peer-reviewedCC BY-NC 4.0Nucleic Acids Research

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

  • Siyu Pan1,2
  • Ziyang Wang1,2,3
  • Peilin Jia1,2,3,4
4 affiliations
  1. 1China National Center for Bioinformation , Beijing 100101 ,
  2. 2Beijing Institute of Genomics, Chinese Academy of Sciences , Beijing 100101 ,
  3. 3College of Life Sciences, University of Chinese Academy of Sciences , Beijing 101408 ,
  4. 4Beijing Key Laboratory of Intelligent Governance and Application of Biological Big Data, China National Center for Bioinformation , Beijing 100101 ,
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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.

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Cite

BibTeXRIS
BibTeX
@article{pan2026scmrdb,
  title = {{scMRdb: a comprehensive resource for cell-type-resolved Mendelian randomization of complex traits}},
  author = {Siyu Pan and Ziyang Wang and Peilin Jia},
  journal = {Nucleic Acids Research},
  year = {2026},
  month = oct,
  doi = {10.1093/nar/gkag1063},
  url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1063/9004250},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - scMRdb: a comprehensive resource for cell-type-resolved Mendelian randomization of complex traits
AU  - Siyu Pan
AU  - Ziyang Wang
AU  - Peilin Jia
PY  - 2026
DA  - 2026/10/29
JO  - Nucleic Acids Research
DO  - 10.1093/nar/gkag1063
UR  - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1063/9004250
AB  - 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.
SN  - 0305-1048
SN  - 1362-4962
ER  -