Evidence map›Paper›PMID 38033715›Full record

ReviewGlomerular diseases

Combing Genome-Wide Association Studies and Single-Cell Analysis to Elucidate the Mechanisms of Kidney Disease: Proceedings of the Henry Shavelle Professorship.

Jonathan Levinsohn, Shen Li, Eunji Ha, Katalin Susztak

Abstract readReview
In one paragraph

Review in Glomerular diseases. 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

4 authors.

Jonathan LevinsohnDivision of Nephrology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Shen LiDivision of Nephrology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Eunji HaDivision of Nephrology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Katalin SusztakDivision of Nephrology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.

Funding

Role of the Notch Pathway in Kidney InjuryR01DK076077 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI KATALIN SUSZTAK · 2007 to 2026
$8.0M
Epigenetics of Chronic Kidney DiseaseR01DK087635 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI KATALIN SUSZTAK · 2009 to 2026
$7.0M
APOL1 associated kidney diseaseR01DK105821 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI SUSZTAK, KATALIN · 2016 to 2024
$4.6M
Training CoreTL1DK143326 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI Wei Tong · 2024 to 2026
$2.5M
The role of cytosolic nucleotide sensors in inflammatory fibrosisR01DK132630 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI SUSZTAK, KATALIN · 2022 to 2025
$2.0M
NIDDK NIH HHS R01 DK076077NIDDK NIH HHS R01 DK087635NIDDK NIH HHS R01 DK105821NIDDK NIH HHS R01 DK132630NIDDK NIH HHS TL1 DK143326
6 · The paper itself

Abstract

Background: Kidney diseases pose a significant global health burden; there is an urgent need to deepen our understanding of their underlying mechanisms. Summary: This review focuses on new innovative approaches that merge genome-wide association studies (GWAS) and single-cell omics (including transcriptomics) in kidney disease research. We begin by detailing how GWAS has identified numerous genetic risk factors, offering valuable insight into disease susceptibility. Then, we explore the application of scRNA-seq, highlighting its ability to unravel how genetic variants influence cellular phenotypes. Through a synthesis of recent studies, we illuminate the synergy between these two powerful methodologies, demonstrating their potential in elucidating the complex etiology of kidney diseases. Moreover, we discuss how this integrative approach could pave the way for precise diagnostics and personalized treatments. Key Message: This review underscores the transformative potential of combining GWAS and scRNA-seq in the journey toward a deeper understanding of kidney diseases.

Indexed as

Genome-wide association analysisKidney diseaseQuantitative trait lociSingle-cell analysis

Identifiers

PMID38033715
PMCPMC10686632

What OpenQuestion holds

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LicenceCC BY-NC
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.