Evidence map›Paper›PMID 22424432›Full record

ReviewTranslational research : the journal of laboratory and clinical medicine2012

Genomic biomarkers for chronic kidney disease.

Wenjun Ju, Shahaan Smith, Matthias Kretzler

Abstract readReview
In one paragraph

Review in Translational research : the journal of laboratory and clinical medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction.International journal of molecular sciences · 2021
    Review
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. The nephrologist of tomorrow: towards a kidney-omic future.Pediatric nephrology (Berlin, Germany) · 2017
    Review
  15. Article
  16. Genetics and primary care: where are we headed?Journal of translational medicine · 2014
    Article
  17. Article
  18. Review
  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

3 authors.

Wenjun JuDivision of Nephrology, Department of Internal Medicine, University of Michigan, 1150 W. Medical Center Drive, Ann Arbor, MI 48109-0680, USA. wenjunj@med.umich.edu
Shahaan Smith
Matthias Kretzler

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
Integrated Systems Biology Approach to Diabetic Microvascular ComplicationsR24DK082841 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABCOUWER, STEVEN F, BROSIUS, FRANK C · 2008 to 2020
$13.1M
University of Michigan O'Brien Kidney Translational Core CenterP30DK081943 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PENNATHUR, SUBRAMANIAM · 2008 to 2022
$12.9M
Molecular Progression Predictors in the Chronic Renal Insufficiency CohortR01DK079912 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KRETZLER, MATTHIAS · 2008 to 2012
$2.8M
NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30 DK081943NIDDK NIH HHS R01 DK079912NIDDK NIH HHS R24 DK082841
6 · The paper itself

Abstract

Chronic kidney disease (CKD) remains a major challenge in nephrology and for public health care, affecting 14% to 15% of the adult US population and consuming significant health care resources. In the next 20 years, the number of patients with end stage renal disease is projected to increase by 50%. Ideal biomarkers that allow early identification of CKD patients at high risk of progression are urgently needed for early and targeted treatment to improve patient care. Recent success of integrating molecular approaches for personalized management of neoplastic diseases, including diagnosis, staging, prognosis, treatment selection, and monitoring, has strongly encouraged kidney researchers to pursue molecular definitions of patients with kidney disease. Challenges for molecular marker identification in CKD are a high degree of cellular heterogeneity of the kidney and the paucity of human tissue availability for molecular studies. Despite these limitations, potential molecular biomarker candidates have been uncovered at multiple levels along the genome--phenome continuum. Here we will review the identification and validation of potential genomic biomarker candidates of CKD and CKD progression in clinical studies. The challenges in predicting CKD progression, as well as the promises and opportunities resulting from a molecular definition of CKD will be discussed.

Indexed as

BiomarkersGenomicsHumansRenal Insufficiency, ChronicRisk FactorsBiomarkers

Identifiers

PMID22424432
PMCPMC3329158

What OpenQuestion holds

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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.