Evidence map›Paper›PMID 40200175›Full record

ReviewBMC nephrology2025

Novel insights into kidney disease: the scRNA-seq and spatial transcriptomics approaches: a literature review.

Mingming Ma, Qiao Luo, Liangmei Chen, Fanna Liu, Lianghong Yin, Baozhang Guan

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. 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

6 authors.

Mingming MaInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China.
Qiao LuoInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China.
Liangmei ChenInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China.
Fanna LiuInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China.
Lianghong YinInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China. Jnufu09@126.com.
Baozhang GuanInstitute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, No. 613, West Huangpu Avenue, Guangzhou, 510632, China. Guanbaozhang130@163.com.

Funding

Basic and Applied Basic Research Project of the Municipal and University Joint Funding Program, Guangzhou Science and Technology Plan Project 202201020068
6 · The paper itself

Abstract

Over the past decade, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have revolutionized biomedical research, particularly in understanding cellular heterogeneity in kidney diseases. This review summarizes the application and development of scRNA-seq combined with ST in the context of kidney disease. By dissecting cellular heterogeneity at an unprecedented resolution, these advanced techniques have identified novel cell subpopulations and their dynamic interactions within the renal microenvironment. The integration of scRNA-seq with ST has been instrumental in elucidating the cellular and molecular mechanisms underlying kidney development, homeostasis, and disease progression. This approach has not only identified key cellular players in renal pathophysiology but also revealed the spatial organization of cells within the kidney, which is crucial for understanding their functional specialization. This paper highlights the transformative impact of these techniques on renal research that have paved the way for targeted therapeutic interventions and personalized medicine in the management of kidney disease.

Indexed as

Gene Expression ProfilingKidney DiseasesRNA-SeqSequence Analysis, RNASingle-Cell AnalysisTranscriptomeAnimalsHumansKidneySingle-Cell Gene Expression AnalysisCellular heterogeneityKidney diseasePathologyRenal physiologySingle-cell sequencingSpatial transcriptomics

Identifiers

PMID40200175
PMCPMC12288332

What OpenQuestion holds

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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 OpenQuestion graph.