ArticleNucleic acids research2026
Spatial2GWAS: a database for linking spatial transcriptomic regions with GWAS traits.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The 2026 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2026Article
- Cardio-Vascular Extracellular Matrix: The Unmet Enigma.International journal of molecular sciences · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Spatial heterogeneity of gene expression within tissue regions has a critical influence on biological functions, thereby affecting disease pathogenesis. However, systematic associations between spatially resolved transcriptomes and phenotypes, especially in complex diseases, remain underexplored. Here, we developed spatial2GWAS (http://www.spatial2gwas.cn), a comprehensive resource linking spatial transcriptomic (ST) regions with GWAS traits. In the database, we collected 1196 ST slices (human and mouse) from five technologies and 812 GWAS traits spanning 18 phenotype categories and identified 29 701 ST slice-GWAS trait pairs containing 47 492 significant regions. Functional analyses reveal distinct patterns of cell type composition, gene expression, GO/KEGG pathway activation, and cell-cell communication direction between trait-related and unrelated spatial regions. The database provides a user-friendly interface for visualization of spatial regions and GWAS trait associations, supporting advanced queries by slice and GWAS information, genes co-expressed with GWAS trait-associated genes, and spatial regions. Spatial2GWAS aims to enable systematic exploration of spatial mechanisms underlying complex traits and offer insights into region-specific biological functions and potential therapeutic targets. This database bridges ST and high-level phenotypes, advancing the understanding of tissue heterogeneity in complex human diseases.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.