Evidence map›Paper›PMID 42598191›Full record

ReviewJournal of translational autoimmunity2026

Resetting immunometabolic set points in autoimmune disease.

Xiao Yu, Yidan Zhang, Anquan Shang

Abstract readReview
In one paragraph

Review in Journal of translational autoimmunity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

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

3 authors.

Xiao YuDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yidan ZhangDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Anquan ShangDepartment of Laboratory Medicine, Affiliated Lianyungang Clinical College of Nantong University, Lianyungang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoimmune diseases often persist despite effective suppression of overt inflammation, and many patients experience relapse after treatment tapering or withdrawal. This clinical pattern raises the possibility that disease activity is influenced not only by ongoing immune stimulation, but also by relatively stable biological states that preserve inflammatory potential. In this Review, we propose immunometabolic set points as an integrative framework for examining how immune-cell metabolic programs, tissue metabolic niches, metabolite signaling, and immune or metabolic memory may interact in chronic autoimmune disease. Rather than representing a single pathway or biomarker, an immunometabolic set point is proposed to describe a potentially reversible multicompartment state shaped by immune and tissue interactions. Experimental studies support important roles for cellular metabolism, local nutrient and oxygen conditions, mitochondrial stress, stromal activation, and metabolites such as lactate, succinate, and itaconate in regulating immune function. However, their integration into a unified disease-maintaining state has not been directly established. We therefore distinguish evidence-supported mechanisms from broader conceptual inferences concerning relapse-prone remission and therapeutic reset. We further discuss how longitudinal single-cell profiling, spatial omics, metabolomics, and metabolic flux analysis may be used to test the framework and determine whether treatment produces transient inflammatory suppression or more durable biological reconfiguration.

Indexed as

Autoimmune diseaseImmune toleranceImmunometabolic set pointImmunometabolismMetabolic memoryTherapeutic reset

Identifiers

PMID42598191
PMCPMC13470438

What OpenQuestion holds

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Registered trials

None linked

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.