Evidence mapPaperPMID 41585231Full record

ArticleFrontiers in medicine2025

Baricitinib in chronic kidney disease: an exploratory analysis integrating network toxicology, molecular docking and pharmacovigilance.

Rubin Zheng, Jing Lu, Miao Deng, Jiayi Lyu, Jinfen Han, Jiaxi Chen, Qin Wang, Ye Liu, Liangdong Yuan, Zhixun Bai

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Rubin Zheng *Department of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Jing Lu *Department of Nursing, Southwest Guizhou Vocational and Technical College Nationalities, Xingyi, Guizhou, China.
Miao Deng *Department of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Jiayi Lyu *Department of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Jinfen HanDepartment of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Jiaxi ChenDepartment of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Qin WangDepartment of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Ye LiuDepartment of Nephrology, Qianxinan Affiliated Hospital of Zunyi Medical University, Xingyi, Guizhou, China.
Liangdong YuanDepartment of Nephrology, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
Zhixun BaiDepartment of Nephrology, People's Hospital of Qianxinan Prefecture, Xingyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic kidney disease (CKD) presents a major global health challenge due to ineffective therapies against progressive renal fibrosis. Baricitinib, a selective JAK1/JAK2 inhibitor, has anti-inflammatory and anti-fibrotic potential, yet its mechanistic basis and safety implications in CKD require further exploration. Methods: An integrated strategy was employed, combining network toxicology across multiple databases, protein-protein interaction network analysis and molecular docking. Real-world safety was evaluated by analyzing adverse event (AE) reports from FDA Adverse Event Reporting System (FAERS) (2018-2024), capturing safety data across all approved indications for baricitinib by calculating reporting odds ratios (RORs) and proportional reporting ratios (PRRs). Results: Predictive toxicology indicated potential respiratory and acute toxicity risks. Network analysis identified 229 shared targets; core hubs (AKT1, SRC, STAT3, EGFR, ESR1) showed high-affinity docking, suggesting potentially stronger theoretical binding affinity than JAK1. Pathway enrichment suggested potential suppression of JAK-STAT/MAPK and TGF-β/Smad3 pathways. FAERS analysis of 6,006 reports from its broader clinical use showed significantly elevated RORs for infections and thromboembolic events, alongside the absence of a disproportionate signal for renal AEs. This finding aligns with the mechanistic profile derived from intersecting baricitinib's predicted targets with CKD-related genes, highlighting the need to systematically evaluate renal safety in prospective CKD trials. Conclusion: Baricitinib has computational and mechanistic potential to modulate key pathways in CKD. Pharmacovigilance data confirm risks of infection and thrombosis but show no disproportionate renal safety signal. These exploratory findings generate a testable hypothesis for its use in CKD, underscoring the necessity of prospective, renal-function-stratified trials.

Indexed as

baricitinibchronic kidney diseasemolecular dockingnetwork toxicologypharmacovigilance

Identifiers

PMID41585231
PMCPMC12827112

What Socratic holds

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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.