Evidence map›Paper›PMID 41657733›Full record

ReviewFrontiers in molecular biosciences2026

S100A12 drives inflammatory and metabolic reprogramming in sepsis-associated acute kidney injury.

Huanqin Liu, Yanan Lv, Qingjie Xue, Jikui Shi

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

4 authors.

Huanqin LiuDepartment of Critical Care Medicine, Jining No.1 People's Hospital, Jining, Shandong, China.
Yanan LvSchool of Clinical Medicine, Jining Medical University, Jining, Shandong, China.
Qingjie XueSchool of Basic Medicine, Jining Medical University, Jining, Shandong, China.
Jikui ShiDepartment of Critical Care Medicine, Jining No.1 People's Hospital, Jining, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis-associated acute kidney injury (SA-AKI) is a severe complication of sepsis characterized by dysregulated inflammation, endothelial injury, and metabolic reprogramming. Among the numerous inflammatory mediators involved, S100 calcium-binding protein A12 (S100A12), a neutrophil-derived alarmin, has emerged as a key amplifier of receptor for advanced glycation end-products (RAGE) and toll-like receptor 4 (TLR4) signaling in this context. Through activation of these pathways, S100A12 drives inflammatory amplification, promotes cytokine release, pyroptotic and apoptotic cell death, endothelial dysfunction, and impaired tubular repair, thereby exacerbating renal injury. Experimental studies demonstrate that inhibition of S100A12 or blockade of its downstream signaling attenuates inflammation and tissue damage, whereas clinical evidence associates elevated circulating and urinary S100A12 levels with disease severity and adverse prognosis in sepsis. Collectively, current evidence positions S100A12 as both a mechanistic driver of inflammatory and metabolic reprogramming and a clinically actionable biomarker in SA-AKI. This review summarizes recent advances in the molecular biology and immunometabolic roles of S100A12 in SA-AKI, emphasizes its systemic versus kidney-specific effects, and discusses its translational potential as a biomarker and therapeutic target, highlighting opportunities and challenges for precision diagnostics and targeted therapies in sepsis-related organ injury.

Indexed as

biomarkerinflammationmetabolic reprogrammingRAGES100A12sepsissepsis-associated acute kidney injuryTLR4

Identifiers

PMID41657733
PMCPMC12875965

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Registered trials

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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 OpenQuestion graph.