SynthesisThe Journal of international medical research2026
Mendelian randomization identifies multiple immune cell surface markers as potential causal contributors and drug targets in rheumatoid arthritis.
Synthesis in The Journal of international medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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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.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Causal risk and protective factors for rheumatoid arthritis: a comprehensive mendelian randomization systematic review and meta-analysis.Frontiers in genetics · 2026Pooled it
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ObjectiveAlthough biologic therapies targeting cytokines have revolutionized the treatment of rheumatoid arthritis, immune cell surface markers remain underexplored as therapeutic targets. We combined Mendelian randomization with clinical evidence to identify causal immune cell phenotypes as potential causal contributors to rheumatoid arthritis and as candidate drugs and therapeutic targets.MethodsWe analyzed genome-wide association study summary statistics from rheumatoid arthritis cohorts (discovery: 12,555 cases/240,862 controls; replication: 14,361 cases/43,923 controls) as well as 731 immune cell traits. The primary analysis used inverse-variance weighted Mendelian randomization. Clinical trial evidence was further used to explore the therapeutic potential of identified targets. Associations with p < 0.05 were considered nominally significant, while Bonferroni correction was applied to determine statistical significance (p < 6.83 × 10
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