Evidence map›Paper›PMID 26449608›Full record

ArticleJournal of the American Society of Nephrology : JASN2016

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis.

Florin L Craciun, Vanesa Bijol, Amrendra K Ajay, Poornima Rao, Ramya K Kumar, John Hutchinson, Oliver Hofmann, Nikita Joshi, James P Luyendyk, Ulrike Kusebauch and 6 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
3.9field-weighted citation impact, top 6% of its field
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

44 citing papers in PubMed, 69 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Role of local complement activation in kidney fibrosis and repair.The Journal of clinical investigation · 2025
    Review
  7. Article
  8. Article
  9. Observational
  10. INSIGHTS INTO ACUTE KIDNEY INJURY AND TRANSITION TO CHRONIC KIDNEY DISEASE BY SINGLE-CELL TECHNOLOGIES.Transactions of the American Clinical and Climatological Association · 2025
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. The NaCellular and molecular life sciences : CMLS · 2021
    Review
  20. Article
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

16 authors at 6 institutions in 2 countries.

Florin L CraciunRenal Division, Department of Medicine and.
Vanesa BijolDepartment of Pathology, Brigham and Women's Hospital, Boston, Massachusetts;
Amrendra K AjayRenal Division, Department of Medicine and.
Poornima RaoRenal Division, Department of Medicine and.
Ramya K KumarRenal Division, Department of Medicine and.
John HutchinsonDepartment of Biostatistics and.
Oliver HofmannDepartment of Biostatistics and.
Nikita JoshiDepartment of Pathology and Diagnostic Investigation, Michigan State University, East Lansing, Michigan;
James P LuyendykDepartment of Pathology and Diagnostic Investigation, Michigan State University, East Lansing, Michigan;
Ulrike KusebauchInstitute for Systems Biology, Seattle, Washington;
Christopher L MossInstitute for Systems Biology, Seattle, Washington;
Anand SrivastavaRenal Division, Department of Medicine and.
Jonathan HimmelfarbKidney Research Institute, University of Washington, Seattle, Washington; and.
Sushrut S WaikarRenal Division, Department of Medicine and.
Robert L MoritzInstitute for Systems Biology, Seattle, Washington;
Vishal S VaidyaRenal Division, Department of Medicine and Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Harvard Program in Therapeutic Sciences, Harvard Medical School, Boston, Massachusetts vvaidya@bwh.harvard.edu.
Metabolism and Renal Physiology · FRInstitute for Systems Biology · USMichigan State University · USBrigham and Women's Hospital · USHarvard University · USUniversity of Washington · US

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
TRAINING PROGRAM IN ACADEMIC NEPHROLOGYT32DK007527 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI BONVENTRE, JOSEPH VINCENT · 1986 to 2021
$8.8M
Using iPSCs to model patient outcomes in nephrotic syndromeUH3TR000504 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2014 to 2016
$6.1M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
Complete Human Peptide- and MRM-AtlasRC2HG005805 · NHGRI · INSTITUTE FOR SYSTEMS BIOLOGY · PI HOOD, LEROY E, MORITZ, ROBERT L · 2009 to 2010
$4.6M
Role of SMOC2 in Kidney FibrosisR01ES017543 · NIEHS · BRIGHAM AND WOMEN'S HOSPITAL · PI VAIDYA, VISHAL S. · 2011 to 2021
$3.9M
Novel anti-fibrotic mechanisms in chemical-induced liver injuryR01ES017537 · NIEHS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI LUYENDYK, JAMES P · 2009 to 2019
$3.6M
Biomarkers of Kidney PathologyR01DK093574 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI WAIKAR, SUSHRUT S. · 2012 to 2015
$2.4M
Novel Human Biomarkers of Kidney FibrosisU01DK104308 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI HUMPHREYS, BENJAMIN D., WAIKAR, SUSHRUT S. · 2014 to 2018
$2.0M
FAIMS-Selected Reaction Monitoring to Quantitative Protein Networks in DiseaseS10RR027584 · NCRR · INSTITUTE FOR SYSTEMS BIOLOGY · PI MORITZ, ROBERT L · 2011 to 2011
$576k
Role of SMOC2 in Kidney FibrosisR56ES017543 · NIEHS · BRIGHAM AND WOMEN'S HOSPITAL · PI VAIDYA, VISHAL S. · 2016 to 2016
$213k
NCATS NIH HHS UH3 TR000504NCRR NIH HHS S10 RR027584NHGRI NIH HHS RC2 HG005805NIDDK NIH HHS R01 DK093574NIDDK NIH HHS T32 DK007527NIDDK NIH HHS U01 DK104308NIEHS NIH HHS R01 ES017537NIEHS NIH HHS R01 ES017543NIEHS NIH HHS R56 ES017543NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221
6 · The paper itself

Abstract

CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acid-induced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten- to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two- to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P<0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD.

Indexed as

Sequence Analysis, RNAAnimalsFibrosisGenetic MarkersHumansKidneyKidney DiseasesMaleMiceMice, Inbred BALB CProtein BiosynthesisGenetic MarkersCKDfibrosistranscriptional profiling

Identifiers

PMID26449608
PMCPMC4884105
OpenAlexW2188139213

What OpenQuestion holds

Textmetadata
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.