Evidence map›Paper›PMID 35477557›Full record

ArticleJournal of the American Society of Nephrology : JASN2022

Molecular Characterization of Membranous Nephropathy.

Rachel Sealfon, Laura Mariani, Carmen Avila-Casado, Viji Nair, Rajasree Menon, Julien Funk, Aaron Wong, Gabriel Lerner, Norifumi Hayashi, Olga Troyanskaya and 2 more

Abstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  11. De novo membranous nephropathy in a pig-to-baboon kidney xenograft: A new xenograft glomerulopathy.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2024
    Article
  12. Article
  13. Article
  14. Molecular Characterization of Membranous Nephropathy:Journal of the American Society of Nephrology : JASN · 2022
    Article
  15. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Rachel SealfonCenter for Computational Biology, Flatiron Institute, New York, New York.
Laura MarianiDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Carmen Avila-CasadoToronto General Hospital Research Institute, Toronto, Ontario, Canada.
Viji NairDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Rajasree MenonDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0001-6280-9639
Julien FunkCenter for Computational Biology, Flatiron Institute, New York, New York.
Aaron WongCenter for Computational Biology, Flatiron Institute, New York, New York.
Gabriel LernerDepartment of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, Massachusetts.
Norifumi HayashiDepartment of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, Massachusetts.
Olga TroyanskayaCenter for Computational Biology, Flatiron Institute, New York, New York.
Matthias KretzlerDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0003-4064-0582
Laurence H BeckDepartment of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, Massachusetts.ORCID 0000-0003-1482-4089

Funding

The Impact of COVID-19 on People Living with Rare Diseases and Their FamiliesU2CTR002818 · NCATS · CINCINNATI CHILDRENS HOSP MED CTR · PI Michal Kouril · 2019 to 2026
$51.2M
Central Hub for Kidney Precision MedicineU24DK114886 · NIDDK · UNIVERSITY OF WASHINGTON · PI Jonathan Himmelfarb, Matthias Kretzler · 2022 to 2026
$21.1M
ConProject-002U2CDK114886 · NIDDK · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN, IYENGAR, SRINIVAS RAVI V · 2017 to 2021
$21.0M
Training Program in Clinical & Translationa Research in Human Glomerular DiseaseU54DK083912 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KRETZLER, MATTHIAS · 2009 to 2023
$20.3M
University of Michigan O'Brien Kidney Translational Core CenterP30DK081943 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BROSIUS, FRANK C · 2008 to 2022
$12.9M
CureGNU24DK100845 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CRYSTAL A. GADEGBEKU, Laura H Mariani · 2019 to 2026
$12.1M
RESEARCH TRAINING IN NEPHROLOGYT32DK007053 · NIDDK · BOSTON UNIVERSITY MEDICAL CAMPUS · PI RIFKIN, IAN R · 1986 to 2019
$3.9M
Boston Chronic Kidney Disease Research Biopsy CenterU01DK133092 · NIDDK · BOSTON MEDICAL CENTER · PI Sylvia E Rosas, Sushrut S. Waikar · 2022 to 2026
$3.5M
Safety and Efficacy of Human Clinical Trials Using Kidney-on-a-Chip Microphysiological SystemsUH3TR003288 · NCATS · UNIVERSITY OF WASHINGTON · PI FREEDMAN, BENJAMIN SOLOMON, HIMMELFARB, JONATHAN · 2022 to 2024
$2.3M
PREcision Medicine through IntErrogation of Rna in the kidnEy (PREMIERE)UH3DK114907 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HACOHEN, NIR, HODGIN, JEFFREY BENTON · 2019 to 2021
$1.8M
Cleveland Precision Medicine Chronic Kidney Disease CohortUH3DK114908 · NIDDK · CLEVELAND CLINIC LERNER COM-CWRU · PI O'TOOLE, JOHN F., POGGIO, EMILIO DANIEL · 2019 to 2021
$900k
Integrative Molecular Epidemiology Approach to Identify Nephrotic Syndrome SubgroupsK08DK115891 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARIANI, LAURA H · 2018 to 2021
$678k
NCATS NIH HHS U2C TR002818NCATS NIH HHS UH3 TR003288NIDDK NIH HHS K08 DK115891NIDDK NIH HHS P30 DK081943NIDDK NIH HHS T32 DK007053NIDDK NIH HHS U01 DK133092NIDDK NIH HHS U24 DK100845NIDDK NIH HHS U24 DK114886NIDDK NIH HHS U2C DK114886NIDDK NIH HHS U54 DK083912NIDDK NIH HHS UH3 DK114907NIDDK NIH HHS UH3 DK114908
6 · The paper itself

Abstract

backgroundMolecular characterization of nephropathies may facilitate pathophysiologic insight, development of targeted therapeutics, and transcriptome-based disease classification. Although membranous nephropathy (MN) is a common cause of adult-onset nephrotic syndrome, the molecular pathways of kidney damage in MN require further definition.

methodsWe applied a machine-learning framework to predict diagnosis on the basis of gene expression from the microdissected kidney tissue of participants in the Nephrotic Syndrome Study Network (NEPTUNE) cohort. We sought to identify differentially expressed genes between participants with MN versus those of other glomerulonephropathies across the NEPTUNE and European Renal cDNA Bank (ERCB) cohorts, to find MN-specific gene modules in a kidney-specific functional network, and to identify cell-type specificity of MN-specific genes using single-cell sequencing data from reference nephrectomy tissue.

resultsGlomerular gene expression alone accurately separated participants with MN from those with other nephrotic syndrome etiologies. The top predictive classifier genes from NEPTUNE participants were also differentially expressed in the ERCB participants with MN. We identified a signature of 158 genes that are significantly differentially expressed in MN across both cohorts, finding 120 of these in a validation cohort. This signature is enriched in targets of transcription factor NF-κB. Clustering these MN-specific genes in a kidney-specific functional network uncovered modules with functional enrichments, including in ion transport, cell projection morphogenesis, regulation of adhesion, and wounding response. Expression data from reference nephrectomy tissue indicated 43% of these genes are most highly expressed by podocytes.

conclusionsThese results suggest that, relative to other glomerulonephropathies, MN has a distinctive molecular signature that includes upregulation of many podocyte-expressed genes, provides a molecular snapshot of MN, and facilitates insight into MN's underlying pathophysiology.

Indexed as

Glomerulonephritis, MembranousKidney DiseasesNephrotic SyndromePodocytesAdultHumansKidneyKidney Glomerulusmachine learningmembranous nephropathypodocytescRNA-seqsingle-cell sequencingtranscriptional profiling

Identifiers

PMID35477557
PMCPMC9161788

What OpenQuestion holds

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Registered trials

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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.