Evidence map›Paper›PMID 35377940›Full record

SynthesisDiabetes care2022

Urinary Proteomics Identifies Cathepsin D as a Biomarker of Rapid eGFR Decline in Type 1 Diabetes.

Christine P Limonte, Erkka Valo, Viktor Drel, Loki Natarajan, Manjula Darshi, Carol Forsblom, Clark M Henderson, Andrew N Hoofnagle, Wenjun Ju, Matthias Kretzler and 22 more

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Diabetes care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.6field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 34 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
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  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Hallmarks of the metabolic secretome.Trends in endocrinology and metabolism: TEM · 2024
    Review
  15. Article
  16. Pathomechanisms of Diabetic Kidney Disease.Journal of clinical medicine · 2023
    Review
  17. [Non-Classical Clinical Types and Pathological Changes of Diabetic Kidney Disease: A Review].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
    Review
  18. Article
  19. Article
  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

32 authors at 13 institutions in 4 countries.

Christine P LimonteDivision of Nephrology, Department of Medicine, University of Washington, Seattle, WA.ORCID 0000-0002-9162-7428
Erkka ValoFolkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
Viktor DrelDivision of Nephrology, The University of Texas Health Science Center at San Antonio, San Antonio, TX.
Loki NatarajanDivision of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health and Moores Cancer Center at UC San Diego Health, La Jolla, CA.ORCID 0000-0001-5719-828X
Manjula DarshiDivision of Nephrology, The University of Texas Health Science Center at San Antonio, San Antonio, TX.
Carol ForsblomFolkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
Clark M HendersonDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA.
Andrew N HoofnagleKidney Research Institute, University of Washington, Seattle, WA.
Wenjun JuDivision of Nephrology, University of Michigan, Ann Arbor, MI.ORCID 0000-0002-9136-8454
Matthias KretzlerDivision of Nephrology, University of Michigan, Ann Arbor, MI.
Daniel MontemayorDivision of Nephrology, The University of Texas Health Science Center at San Antonio, San Antonio, TX.
Viji NairDivision of Nephrology, University of Michigan, Ann Arbor, MI.
Robert G NelsonChronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ.
John F O'TooleDepartment of Nephrology and Hypertension, Cleveland Clinic, Cleveland, OH.
Robert D TotoDepartment of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX.
Sylvia E RosasJoslin Diabetes Center, Boston, MA.
John RuzinskiDivision of Nephrology, Department of Medicine, University of Washington, Seattle, WA.
Niina SandholmFolkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.ORCID 0000-0003-4322-6942
Insa M SchmidtSection of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA.
Tomas VaisarDivision of Metabolism, Endocrinology, and Nutrition, UW Medicine Diabetes Institute, University of Washington, Seattle, WA.
Sushrut S WaikarSection of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA.
Jing ZhangDivision of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health and Moores Cancer Center at UC San Diego Health, La Jolla, CA.
Peter RossingSteno Diabetes Center Copenhagen, Gentofte, Denmark.ORCID 0000-0002-1531-4294
Tarunveer S AhluwaliaSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Per-Henrik GroopFolkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.ORCID 0000-0003-4055-6954
Subramaniam PennathurDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.ORCID 0000-0003-3628-6883
Janet K Snell-BergeonBarbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO.ORCID 0000-0002-9337-3740
Tina CostacouUniversity of Pittsburgh, Pittsburgh, PA.ORCID 0000-0001-9303-3810
Trevor J OrchardUniversity of Pittsburgh, Pittsburgh, PA.
Kumar SharmaDivision of Nephrology, The University of Texas Health Science Center at San Antonio, San Antonio, TX.
Ian H de BoerDivision of Nephrology, Department of Medicine, University of Washington, Seattle, WA.
Kidney Precision Medicine Project
University of Washington · USThe University of Texas Health Science Center at San Antonio · USUniversity of Helsinki · FIUniversity of Michigan · USBoston University · USUC San Diego Health System · USUniversity of Copenhagen · DKUniversity of Pittsburgh · USCleveland Clinic · USJoslin Diabetes Center · USNational Institute of Diabetes and Digestive and Kidney Diseases · USThe University of Texas Southwestern Medical Center · USUniversity of Colorado Anschutz Medical Campus · US

Funding

Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Sakeneh Zraika · 1986 to 2026
$41.4M
PILOT STUDY--CLINICAL NUTRITION RESEARCHP30DK035816 · NIDDK · UNIVERSITY OF WASHINGTON · PI GREGORY J MORTON · 1986 to 2026
$30.4M
Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAVID P OLSON · 2013 to 2026
$24.3M
ConProject-002U2CDK114886 · NIDDK · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN, IYENGAR, SRINIVAS RAVI V · 2017 to 2021
$21.0M
University of Michigan O'Brien Kidney Translational Core CenterP30DK081943 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PENNATHUR, SUBRAMANIAM · 2008 to 2022
$12.9M
Epidemiology, Pathophysiology and Treatment of Diabetic NephropathyZIADK069062 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI NELSON, ROBERT G · 2009 to 2023
$10.1M
Epidemiology of Diabetes Complications (EDC) Phase II: renewalR37DK034818 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ORCHARD, TREVOR J. · 2009 to 2018
$6.5M
Nutrition, Obesity and Atherosclerosis Training ProgramT32HL007028 · NHLBI · UNIVERSITY OF WASHINGTON · PI Karin E Bornfeldt · 1985 to 2026
$6.4M
EPIDEMIOLOGY OF DIABETIC COMPLICATIONS--PHASE IIR01DK034818 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COSTACOU, TINA · 1986 to 2019
$5.6M
RESEARCH TRAINING IN RENAL DISEASET32DK007467 · NIDDK · UNIVERSITY OF WASHINGTON · PI BANSAL, NISHA, KESTENBAUM, BRYAN R · 1986 to 2023
$5.1M
Randomized trial of vitamin D and omega-3 fatty acids for diabetic kidney diseaseR01DK088762 · NIDDK · UNIVERSITY OF WASHINGTON · PI DE BOER, IAN H · 2010 to 2019
$4.7M
Complications and Comorbidities of Type 1 DiabetesR01HL113029 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI SNELL-BERGEON, JANET KATHLEEN · 2013 to 2016
$2.9M
NHLBI NIH HHS R01 HL079611NHLBI NIH HHS R01 HL113029NHLBI NIH HHS T32 HL007028NIDCR NIH HHS R01 DE026480NIDDK NIH HHS P30 DK017047NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30 DK035816NIDDK NIH HHS P30 DK081943NIDDK NIH HHS R01 DK034818NIDDK NIH HHS R01 DK088762NIDDK NIH HHS R01 DK110541NIDDK NIH HHS R01 DK116731NIDDK NIH HHS R37 DK034818NIDDK NIH HHS RC1 DK086958NIDDK NIH HHS T32 DK007467NIDDK NIH HHS U2C DK114886NIDDK NIH HHS UH3 DK114861NIDDK NIH HHS UH3 DK114866NIDDK NIH HHS UH3 DK114870NIDDK NIH HHS UH3 DK114907NIDDK NIH HHS UH3 DK114908NIDDK NIH HHS UH3 DK114915NIDDK NIH HHS UH3 DK114920NIDDK NIH HHS UH3 DK114923NIDDK NIH HHS UH3 DK114926NIDDK NIH HHS UH3 DK114933NIDDK NIH HHS UH3 DK114937
6 · The paper itself

Abstract

objectiveUnderstanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D). RESEARCH DESIGN AND

methodsWe performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures.

resultsThe cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA.

conclusionsUrine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

Indexed as

Diabetes Mellitus, Type 1Diabetic NephropathiesAlbuminuriaAnimalsBiomarkersCase-Control StudiesCathepsin DCohort StudiesDisease ProgressionGlomerular Filtration RateHumansMiceProteomicsBiomarkersCathepsin D

Identifiers

PMID35377940
PMCPMC9210873
OpenAlexW4225743887

What OpenQuestion holds

Textmetadata
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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.