Evidence map›Paper›PMID 27410520›Full record

ReviewAmerican journal of nephrology2016

Metabolomics in Diabetic Kidney Disease: Unraveling the Biochemistry of a Silent Killer.

Manjula Darshi, Benjamin Van Espen, Kumar Sharma

Open access · bronzeAbstract readReview
In one paragraph

Review in American journal of nephrology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
4.0field-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

55 citing papers in PubMed, 94 citations in OpenAlex.

  1. Review
  2. Review
  3. New Insights into the Role of Mitochondrial Dysfunction in Diabetic Kidney Disease in the Omics Era.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
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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 at 1 institution in 1 country.

Manjula DarshiInstitute of Metabolomic Medicine, University of California San Diego, La Jolla, Calif., USA.
Benjamin Van Espen
Kumar Sharma
University of California San Diego · US

Funding

Novel Paradigms in Diabetic ComplicationsDP3DK094352 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHARMA, KUMAR · 2011 to 2011
$6.0M
NIDDK NIH HHS DP3 DK094352
6 · The paper itself

Abstract

The development of new therapies for chronic diseases, such as diabetic kidney disease (DKD), will continue to be hampered by lack of sufficient biomarkers that will provide insights and will be responsive to treatment interventions. The recent application of metabolomic technologies, such as nuclear magnetic resonance and mass spectroscopy, has allowed large-scale analysis of small molecules to be interrogated in a targeted or untargeted manner. Recent advances from both human and animal studies that have arisen from metabolomic analysis have recognized that mitochondrial function and fatty acid oxidation play key roles in the development and progression of DKD. Although many challenges in the technology for clinical chronic kidney disease (CKD) are yet to be validated, there will very likely be ongoing major contributions of metabolomics to develop new biochemical understanding for diabetic and CKD. The clinical application of metabolomics and accompanying bioinformatic tools will likely be a cornerstone of personalized medicine triumphs for CKD.

Indexed as

Amino AcidsAnimalsBiomarkersCitric Acid CycleDiabetic NephropathiesFatty AcidsHumansLipid MetabolismMass SpectrometryMetabolomicsMitochondriaNuclear Magnetic Resonance, BiomolecularPrecision MedicineRenal Insufficiency, ChronicSignal TransductionUreaAmino AcidsBiomarkersFatty AcidsUrea

Identifiers

PMID27410520
PMCPMC6581452
OpenAlexW2466928446

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.