Evidence map›Paper›PMID 35125393›Full record

ReviewCurrent opinion in nephrology and hypertension2022

Spatial transcriptomics and the kidney.

Ricardo Melo Ferreira, Debora L Gisch, Michael T Eadon

Abstract readReview
In one paragraph

Review in Current opinion in nephrology and hypertension, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. T-Cell Remodeling in Renal Fibrosis: From Acute Injury to Chronic Kidney Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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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.

Ricardo Melo FerreiraDepartment of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Debora L Gisch
Michael T Eadon

Funding

PROBE DELIVERY COREP30DK079312 · NIDDK · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI DAGHER, PIERRE C · 2007 to 2021
$17.1M
Nephron Sub-segmental Omics and Quantitative 3D Imaging of Human Kidney.UH3DK114923 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI ASHKAR, TAREK MAURICE, DAGHER, PIERRE C · 2019 to 2021
$2.2M
Acute inhibition of renal gene expression to prevent nephrotoxicity.K08DK107864 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI EADON, MICHAEL THOMAS · 2016 to 2020
$772k
NIDDK NIH HHS K08 DK107864NIDDK NIH HHS P30 DK079312NIDDK NIH HHS UH3 DK114923
6 · The paper itself

Abstract

purpose of reviewThe application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed. RECENT

findingsSpatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets. SUMMARY: Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.

Indexed as

Gene Expression ProfilingTranscriptomeHumansKidneyRNA, MessengerSingle-Cell AnalysisRNA, Messenger

Identifiers

PMID35125393
PMCPMC9035033

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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.