ArticleFrontiers in immunology2026
Cross-phenotype integration of eQTL-based Mendelian randomization and transcriptomics prioritizes
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To prioritize candidate genes and compounds potentially associated with IgA vasculitis with nephritis (IgAVN) by integrating genetic and transcriptomic evidence across IgAVN, IgA vasculitis (IgAV), and IgA nephropathy (IgAN), followed by preliminary cellular and pharmacological validation. Methods: Expression quantitative trait locus (eQTL)-based two-sample Mendelian randomization (MR) was performed using FinnGen summary statistics for IgAVN, IgAV, and IgAN. MR-prioritized genes were integrated with differentially expressed genes from the IgAVN transcriptomic dataset GSE102114. Fisher's method was used to combine convergent evidence, and exploratory immune cell-specific single-cell eQTL-based MR was conducted to identify potential cell-type-relevant signals. Candidate compounds were screened using drug-signature analysis and evaluated by molecular docking. Results: MR analysis identified 124 genes with nominally significant risk-increasing associations with IgAVN, 132 with IgAV, and 119 with IgAN. Integration with IgAVN transcriptomic data prioritized four candidate genes: Conclusion: Integrative genetic, transcriptomic, and preliminary experimental evidence prioritized
Indexed as
Identifiers
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.