Evidence map›Paper›PMID 40281349›Full record

ReviewClinical and experimental nephrology2025

Single-cell epigenetics and multiomics analysis in kidney research.

Seishi Aihara, Yoshiharu Muto

Abstract readReview
In one paragraph

Review in Clinical and experimental nephrology, 2025. 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

2 authors.

Seishi AiharaDivision of Nephrology, Department of Internal Medicine, University of Texas Southwestern Medical Center, 5901 Forest Park Rd., Dallas, TX, 75390, USA.
Yoshiharu MutoDivision of Nephrology, Department of Internal Medicine, University of Texas Southwestern Medical Center, 5901 Forest Park Rd., Dallas, TX, 75390, USA. yoshiharu.muto@utsouthwestern.edu.ORCID http://orcid.org/0000-0002-0358-9442

Funding

National Coordinating Center (NCC) for the Polycystic Kidney Disease (PKD) Research and Translation Core CentersU24DK126110 · NIDDK · UNIVERSITY OF MARYLAND BALTIMORE · PI Terry J Watnick · 2020 to 2026
$7.4M
NIDDK NIH HHS U24 DK126110NIDDK NIH HHS U24DK126110
6 · The paper itself

Abstract

The rapid evolution of single-cell sequencing technologies has significantly advanced our knowledge of cellular heterogeneity and the underlying molecular basis in healthy and diseased kidneys. While single-cell transcriptomic analysis excels in characterizing cell states in the heterogeneous population, the complex regulatory mechanisms governing the gene expressions are difficult to decipher using transcriptomic data alone. Single-cell sequencing technology has recently extended to include epigenome and other modalities, allowing single-cell multiomics analysis. Especially, the integrative analysis of epigenome and transcriptome dissects the cell-specific, gene-regulatory mechanisms driving cellular heterogeneity. An increasing number of single-cell multimodal atlases are being generated in nephrology research, offering novel insights into cellular diversity and the underpinning epigenetic regulation. This ongoing paradigm shift in kidney research accelerates the identification of new biomarkers and potential therapeutic targets, promoting clinical translation. In this era of transformative nephrology research, the basic knowledge of single-cell sequencing analysis and multiomics approach is valuable not only for basic science researchers but for all nephrologists. This review overview single-cell analysis, with a focus on emerging epigenomic and multiomics approaches and their application to kidney research.

Indexed as

Epigenesis, GeneticEpigenomicsKidneyKidney DiseasesNephrologySingle-Cell AnalysisAnimalsEpigenomeGene Expression ProfilingHumansMultiomicsTranscriptomeEpigeneticsKidneyMultiomicsSingle-cell analysis

Identifiers

PMID40281349
PMCPMC12441082

What Socratic holds

Textmetadata
LicenceCC BY
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.