Evidence map›Paper›PMID 32717193›Full record

ArticleKidney international2021

A profile of multiple circulating tumor necrosis factor receptors associated with early progressive kidney decline in Type 1 Diabetes is similar to profiles in autoimmune disorders.

Katsuhito Ihara, Jan Skupien, Bozena Krolewski, Zaipul I Md Dom, Kristina O'Neil, Eiichiro Satake, Hiroki Kobayashi, Narges M Rashidi, Monika A Niewczas, Andrzej S Krolewski

Open access · greenAbstract read
In one paragraph

Article in Kidney international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. 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

10 authors at 3 institutions in 2 countries.

Katsuhito IharaResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Jan SkupienDepartment of Metabolic Diseases, Jagellonian University Medical College, Krakow, Poland.
Bozena KrolewskiResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Zaipul I Md DomResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Kristina O'NeilResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA.
Eiichiro SatakeResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Hiroki KobayashiResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Narges M RashidiOlink Proteomics, Watertown, Massachusetts, USA.
Monika A NiewczasResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Andrzej S KrolewskiResearch Division, Joslin Diabetes Center, Boston, Massachusetts, USA; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. Electronic address: Andrzej.Krolewski@joslin.harvard.edu.
Joslin Diabetes Center · USJagiellonian University · PLOlink (United States) · US

Funding

SPECIAL ASSAY COREP30DK036836 · NIDDK · JOSLIN DIABETES CENTER · PI ROHIT N. KULKARNI · 1986 to 2026
$50.5M
Tumor necrosis factor superfamily of ligands and receptors in progressive renal decline in diabetesR01DK041526 · NIDDK · JOSLIN DIABETES CENTER · PI KROLEWSKI, ANDRZEJ S · 1990 to 2018
$7.8M
Search for biomarkers to measure progression of diabetic nephropathy in Type 1 diabetes; application of proteomics technologiesDP3DK112177 · NIDDK · JOSLIN DIABETES CENTER · PI GALECKI, ANDRZEJ T, KROLEWSKI, ANDRZEJ S · 2016 to 2016
$2.3M
Understanding the role of the Complement Proteome in progressive Diabetic Kidney DiseaseR01DK123459 · NIDDK · JOSLIN DIABETES CENTER · PI NIEWCZAS, MONIKA ANNA · 2020 to 2024
$2.3M
NIDDK NIH HHS DP3 DK112177NIDDK NIH HHS P30 DK036836NIDDK NIH HHS R01 DK041526NIDDK NIH HHS R01 DK123459
6 · The paper itself

Abstract

This study comprehensively evaluated the association between known circulating tumor necrosis factor (TNF) superfamily ligands and receptors and the development of early progressive kidney decline (PKD) leading to end-stage kidney disease (ESKD) in Type 1 diabetes. Participants for the study were from the Macro-Albuminuria Study (198 individuals), and the Micro-Albuminuria Study (148 individuals) of the Joslin Kidney Study. All individuals initially had normal kidney function and were followed for seven-fifteen years to determine the slope of the estimate glomerular filtration rate and to ascertain onset of ESKD. Plasma concentrations of 25 TNF superfamily proteins were measured using proximity extension assay applied in the OLINK proteomics platform. In the both studies risk of early PKD, determined as estimated glomerular filtration rate loss greater than or equal to three ml/min/1.73m

Indexed as

Diabetes Mellitus, Type 1Diabetic NephropathiesAlbuminuriaDisease ProgressionGlomerular Filtration RateHumansKidneyReceptors, Tumor Necrosis FactorRisk FactorsReceptors, Tumor Necrosis Factordiabetic kidney diseaseend-stage kidney diseaseprogressive kidney declineTNF receptorstumor necrosis factor (TNF) superfamilytype 1 diabetes

Identifiers

PMID32717193
PMCPMC7891866
OpenAlexW3043952466

What OpenQuestion holds

Textmetadata
LicenceTDM
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.