Evidence map›Paper›PMID 29709239›Full record

ArticleKidney international2018

Cytosine methylation predicts renal function decline in American Indians.

Chengxiang Qiu, Robert L Hanson, Gudeta Fufaa, Sayuko Kobes, Caroline Gluck, Jing Huang, Yong Chen, Dominic Raj, Robert G Nelson, William C Knowler and 1 more

Abstract read
In one paragraph

Article in Kidney international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Metabolic memory: mechanisms and diseases.Signal transduction and targeted therapy · 2024
    Review
  18. Article
  19. Article
  20. Molecular pathways that drive diabetic kidney disease.The Journal of clinical investigation · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Chengxiang QiuRenal, Electrolyte, and Hypertension Division, Department of Medicine, Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Robert L HansonPhoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA. Electronic address: rhanson@phx.niddk.nih.gov.
Gudeta FufaaPhoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA.
Sayuko KobesPhoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA.
Caroline GluckRenal, Electrolyte, and Hypertension Division, Department of Medicine, Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Jing HuangDepartment of Biostatistics, Epidemiology and Informatics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Yong ChenDepartment of Biostatistics, Epidemiology and Informatics, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Dominic RajDivision of Renal Diseases and Hypertension, The George Washington School of Medicine, Washington, DC, USA.
Robert G NelsonPhoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA.
William C KnowlerPhoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA.
Katalin SusztakRenal, Electrolyte, and Hypertension Division, Department of Medicine, Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
National Institute of Diabetes and Digestive and Kidney Diseases · USUniversity of Pennsylvania · USGeorge Washington University · US

Funding

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
Role of the Notch Pathway in Kidney InjuryR01DK076077 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI KATALIN SUSZTAK · 2007 to 2026
$8.0M
Genetic Epidemiology of Diabetic NephropathyZIADK069094 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI HANSON, ROBERT · 2009 to 2025
$7.7M
Epigenetics of Chronic Kidney DiseaseR01DK087635 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI KATALIN SUSZTAK · 2009 to 2026
$7.0M
Dynamic learning for post-vaccine event prediction using temporal information in VAERSR01AI130460 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHEN, YONG, TAO, CUI · 2017 to 2021
$3.4M
Epigenetic drivers and biomarkers of diabetic kidney diseaseDP3DK108220 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI SUSZTAK, KATALIN · 2015 to 2015
$2.4M
Intramural NIH HHS ZIA DK069094NIAID NIH HHS R01 AI130460NIDDK NIH HHS DP3 DK108220NIDDK NIH HHS R01 DK076077NIDDK NIH HHS R01 DK087635
6 · The paper itself

Abstract

Diabetic nephropathy accounts for most of the excess mortality in individuals with diabetes, but the molecular mechanisms by which nephropathy develops are largely unknown. Here we tested cytosine methylation levels at 397,063 genomic CpG sites for association with decline in the estimated glomerular filtration rate (eGFR) over a six year period in 181 diabetic Pima Indians. Methylation levels at 77 sites showed significant association with eGFR decline after correction for multiple comparisons. A model including methylation level at two probes (cg25799291 and cg22253401) improved prediction of eGFR decline in addition to baseline eGFR and the albumin to creatinine ratio with the percent of variance explained significantly improving from 23.1% to 42.2%. Cg22253401 was also significantly associated with eGFR decline in a case-control study derived from the Chronic Renal Insufficiency Cohort. Probes at which methylation significantly associated with eGFR decline were localized to gene regulatory regions and enriched for genes with metabolic functions and apoptosis. Three of the 77 probes that were associated with eGFR decline in blood samples showed directionally consistent and significant association with fibrosis in microdissected human kidney tissue, after correction for multiple comparisons. Thus, cytosine methylation levels may provide biomarkers of disease progression in diabetic nephropathy and epigenetic variations contribute to the development of diabetic kidney disease.

Indexed as

CytosineDNA MethylationEpigenesis, GeneticAdultAgedAlbuminuriaApoptosisCase-Control StudiesCell CycleCpG IslandsDiabetic NephropathiesDisease ProgressionEnergy MetabolismFemaleFibrosisGenetic Predisposition to DiseaseCytosinediabetic nephropathygene expression

Identifiers

PMID29709239
PMCPMC5973533
OpenAlexW2802437353

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.