Evidence map›Paper›PMID 29237716›Full record

ArticleJournal of lipid research2018

Shared and distinct lipid-lipid interactions in plasma and affected tissues in a diabetic mouse model.

Kelli M Sas, Jiahe Lin, Thekkelnaycke M Rajendiran, Tanu Soni, Viji Nair, Lucy M Hinder, Hosagrahar V Jagadish, Thomas W Gardner, Steven F Abcouwer, Frank C Brosius and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of lipid research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

34 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
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  7. Dietary interventions improve diabetic kidney disease, but not peripheral neuropathy, in a db/db mouse model of type 2 diabetes.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2023
    Article
  8. Impact of renal tubularFrontiers in molecular biosciences · 2023
    Article
  9. Article
  10. Review
  11. Review
  12. Serum lipidomic determinants of human diabetic neuropathy in type 2 diabetes.Annals of clinical and translational neurology · 2022
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
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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

14 authors at 2 institutions in 1 country.

Kelli M SasDivision of Nephrology, Departments of Internal Medicine, University of Michigan, Ann Arbor, MI 48109.
Jiahe LinDepartments of Statistics, University of Michigan, Ann Arbor, MI 48109.
Thekkelnaycke M RajendiranDepartments of Pathology, University of Michigan, Ann Arbor, MI 48109.
Tanu SoniMichigan Regional Comprehensive Metabolomics Resource Core Ann Arbor, MI 48105.
Viji NairDivision of Nephrology, Departments of Internal Medicine, University of Michigan, Ann Arbor, MI 48109.
Lucy M HinderDepartments of Neurology, University of Michigan, Ann Arbor, MI 48109.
Hosagrahar V JagadishDepartments of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109.
Thomas W GardnerDepartments of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI 48109.
Steven F AbcouwerDepartments of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI 48109.
Frank C BrosiusDivision of Nephrology, Departments of Internal Medicine, University of Michigan, Ann Arbor, MI 48109.
Eva L FeldmanDepartments of Neurology, University of Michigan, Ann Arbor, MI 48109.
Matthias KretzlerDivision of Nephrology, Departments of Internal Medicine, University of Michigan, Ann Arbor, MI 48109.
George MichailidisDepartment of Statistics and Computer and Information Sciences, University of Florida, Gainesville, FL 32611.
Subramaniam PennathurDivision of Nephrology, Departments of Internal Medicine, University of Michigan, Ann Arbor, MI 48109 spennath@umich.edu.
University of Michigan–Ann Arbor · USUniversity of Florida · US

Funding

Michigan Institute for Clinical and Health Research (MCHR)UL1TR000433 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MASHOUR, GEORGE ALEXANDER · 2012 to 2016
$49.9M
Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
Pilot and Feasibility (P and F) ProgramP30DK089503 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Kanakadurga Singer · 2010 to 2026
$20.3M
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 BROSIUS, FRANK C · 2008 to 2022
$12.9M
Statistics and Bioinformatics Core - WangU24DK097153 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURANT, CHARLES F · 2012 to 2017
$10.1M
Tissue-Specific Metabolic Reprogramming in Diabetic ComplicationsDP3DK094292 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BROSIUS, FRANK C, BURANT, CHARLES F · 2011 to 2011
$5.5M
Regulation of Retinal Cell Death in DiabetesR01EY020582 · NEI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABCOUWER, STEVEN F, GARDNER, THOMAS W. · 2010 to 2018
$4.0M
NCATS NIH HHS UL1 TR000433NEI NIH HHS R01 EY020582NIDDK NIH HHS DP3 DK094292NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30 DK081943NIDDK NIH HHS P30 DK089503NIDDK NIH HHS R24 DK082841NIDDK NIH HHS U24 DK097153
6 · The paper itself

Abstract

Lipids are ubiquitous metabolites with diverse functions; abnormalities in lipid metabolism appear to be related to complications from multiple diseases, including type 2 diabetes. Through technological advances, the entire lipidome has been characterized and researchers now need computational approaches to better understand lipid network perturbations in different diseases. Using a mouse model of type 2 diabetes with microvascular complications, we examined lipid levels in plasma and in renal, neural, and retinal tissues to identify shared and distinct lipid abnormalities. We used correlation analysis to construct interaction networks in each tissue, to associate changes in lipids with changes in enzymes of lipid metabolism, and to identify overlap of coregulated lipid subclasses between plasma and each tissue to define subclasses of plasma lipids to use as surrogates of tissue lipid metabolism. Lipid metabolism alterations were mostly tissue specific in the kidney, nerve, and retina; no lipid changes correlated between the plasma and all three tissue types. However, alterations in diacylglycerol and in lipids containing arachidonic acid, an inflammatory mediator, were shared among the tissue types, and the highly saturated cholesterol esters were similarly coregulated between plasma and each tissue type in the diabetic mouse. Our results identified several patterns of altered lipid metabolism that may help to identify pathogenic alterations in different tissues and could be used as biomarkers in future research into diabetic microvascular tissue damage.

Indexed as

Disease Models, AnimalLipid MetabolismAnimalsDiabetes Mellitus, ExperimentalLipidsMaleMiceLipidsdiabeteseyekidneymass spectrometrynervesystems biology

Identifiers

PMID29237716
PMCPMC5794414
OpenAlexW2772219889

What Socratic holds

Textmetadata
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 Socratic graph.