Evidence map›Paper›PMID 30323304›Full record

ArticleScientific reports2018

Circulating metabolic biomarkers of renal function in diabetic and non-diabetic populations.

Clara Barrios, Jonas Zierer, Peter Würtz, Toomas Haller, Andres Metspalu, Christian Gieger, Barbara Thorand, Christa Meisinger, Melanie Waldenberger, Olli Raitakari and 10 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

38 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review
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

20 authors at 9 institutions in 7 countries.

Clara BarriosDepartment for Twin Research, King's College London, London, UK.
Jonas ZiererDepartment for Twin Research, King's College London, London, UK. jonas.zierer@kcl.ac.uk.ORCID http://orcid.org/0000-0002-9693-1859
Peter WürtzResearch Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
Toomas HallerEstonian Genome Center, University of Tartu, Tartu, Estonia.
Andres MetspaluEstonian Genome Center, University of Tartu, Tartu, Estonia.
Christian GiegerInstitute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Barbara ThorandInstitute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Christa MeisingerInstitute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Melanie WaldenbergerInstitute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Olli RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
Sol OteroDepartment of Nephrology, Hospital del Mar, Institut Mar d'Investigacions Mediques, Barcelona, Spain.
Eva RodríguezDepartment of Nephrology, Hospital del Mar, Institut Mar d'Investigacions Mediques, Barcelona, Spain.
Juan Pedro-BotetDepartment of Endocrinology and Nutrition, Hospital del Mar, Institut Mar d'Investigacions Mediques, Barcelona, Spain.
Mika KähönenDepartment of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland.
Mika Ala-KorpelaSystems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Gabi KastenmüllerInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Tim D SpectorDepartment for Twin Research, King's College London, London, UK.
Julio PascualDepartment of Nephrology, Hospital del Mar, Institut Mar d'Investigacions Mediques, Barcelona, Spain.
Cristina MenniDepartment for Twin Research, King's College London, London, UK. cristina.menni@kcl.ac.uk.ORCID http://orcid.org/0000-0001-9790-0571
Helmholtz Zentrum München · DEHospital del Mar Research Institute · ESKing's College London · GBUniversity of Tartu · EEBaker Heart and Diabetes Institute · AUTampere University · FITampere University Hospital · FIUniversity of Helsinki · FIUniversity of Turku · FI

Funding

Medical Research Council MC_UU_12013/1Medical Research Council MR/M004422/1Medical Research Council MR/M016560/1Wellcome Trust
6 · The paper itself

Abstract

Using targeted NMR spectroscopy of 227 fasting serum metabolic traits, we searched for novel metabolic signatures of renal function in 926 type 2 diabetics (T2D) and 4838 non-diabetic individuals from four independent cohorts. We furthermore investigated longitudinal changes of metabolic measures and renal function and associations with other T2D microvascular complications. 142 traits correlated with glomerular filtration rate (eGFR) after adjusting for confounders and multiple testing: 59 in diabetics, 109 in non-diabetics with 26 overlapping. The amino acids glycine and phenylalanine and the energy metabolites citrate and glycerol were negatively associated with eGFR in all the cohorts, while alanine, valine and pyruvate depicted opposite association in diabetics (positive) and non-diabetics (negative). Moreover, in all cohorts, the triglyceride content of different lipoprotein subclasses showed a negative association with eGFR, while cholesterol, cholesterol esters (CE), and phospholipids in HDL were associated with better renal function. In contrast, phospholipids and CEs in LDL showed positive associations with eGFR only in T2D, while phospholipid content in HDL was positively associated with eGFR both cross-sectionally and longitudinally only in non-diabetics. In conclusion, we provide a wide list of kidney function-associated metabolic traits and identified novel metabolic differences between diabetic and non-diabetic kidney disease.

Indexed as

AgedAged, 80 and overBiomarkersCase-Control StudiesCohort StudiesCross-Sectional StudiesDiabetes Mellitus, Type 2Diabetic NephropathiesFemaleGlomerular Filtration RateHumansKidneyKidney Function TestsMaleMiddle AgedRenal Insufficiency, ChronicBiomarkers

Identifiers

PMID30323304
PMCPMC6189123
OpenAlexW2897794736

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.