Evidence map›Paper›PMID 41563353›Full record

ReviewJournal of the American Society of Nephrology : JASN2026

Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.

Yiming Li, Tingkun Ma, Hao Lu, Yiping Yan, Yucheng Xue, Jinmeng Suo, Yusheng Chen, Zhiyong Peng

Abstract readReview
In one paragraph

Review in Journal of the American Society of Nephrology : JASN, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Yiming LiDepartment of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.ORCID 0000-0003-0236-9840
Tingkun MaDepartment of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.ORCID 0009-0005-4263-9536
Hao LuDepartment of Critical Care Medicine, Xiaogan First People's Hospital, Hubei, China.
Yiping YanDepartment of Critical Care Medicine, Xiaogan First People's Hospital, Hubei, China.
Yucheng XueZhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Jinmeng SuoDepartment of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Yusheng ChenDepartment of Emergency and Critical Care Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China.ORCID 0009-0000-2628-8362
Zhiyong PengDepartment of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.ORCID 0000-0002-0849-5648

Funding

Fundamental Research Funds for the Central Universities 2042025kf0070Hubei Provincial Natural Science Foundation Project 2024AFB775National Natural Science Foundation of China 81971816National Natural Science Foundation of China 82102273National Natural Science Foundation of China 82241039National Natural Science Foundation of China 82272208National Natural Science Foundation of China 82472197Sanming Project of Medicine in Shenzhen Guangming szgmtd2025003Wu Jieping Medical Foundation 320.6750.2023-02-4Xiangyang Central Hospital Young Talents Cultivation Program 2025RCYC-005
6 · The paper itself

Abstract

Kidney disease represents a growing global health crisis, demanding a deeper understanding of its underlying pathophysiology. Current mechanistic efforts are often focused on discrete cell states identified by single-cell sequencing, which remains the standard for characterizing the human kidney. Crucially, these molecular atlases fail to explain how individual cell states organize and interact in specific spatial contexts to drive collective, systems-level organ failure. This Review introduces the conceptual and clinical utility of "functional communities"-spatially constrained, interacting multicellular neighborhoods-as the definitive pathologic units of kidney disease. We first outline recent advances in spatial and multiomic technologies that are essential for resolving the composition and communication networks of these communities in situ . This is followed by a deconstruction of three archetypal pathologic communities: the maladaptive repair niche linked to chronic injury, the profibrotic niche driven by specific fibroblast subtypes, and the tissue-destructive immune niche. Moreover, by integrating artificial intelligence and multiomics data, it is possible to build virtual models capable of simulating and predicting dynamic intercellular interactions in kidney diseases. Finally, we discuss key challenges and future directions for translating this community-centric view into novel diagnostics and therapeutics. This framework offers a robust, integrated strategy for identifying vulnerable microenvironments, thereby guiding the development of next-generation diagnostics and targeted therapeutic interventions.

Indexed as

Kidney DiseasesHumansKidneyMultiomicsacute renal failureAKIartificial intelligencebiostatisticsepithelial

Identifiers

PMID41563353
PMCPMC13143460

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.