Evidence map›Paper›PMID 32442208›Full record

Trial reportPloS one2020

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease.

Shosha E I Dekker, Aswin Verhoeven, Darius Soonawala, Dorien J M Peters, Johan W de Fijter, Oleg A Mayboroda, DIPAK Consortium

Abstract readClinical TrialMulticenter StudyValidation Study
In one paragraph

Trial report in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Biomarkers of Kidney Disease Progression in ADPKD.Kidney international reports · 2024
    Review
  5. Article
  6. Review
  7. Article
  8. Review
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  12. Article
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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

7 authors.

Shosha E I DekkerDepartment of Nephrology, Leiden University Medical Center, Leiden, the Netherlands.ORCID 0000-0002-6066-8614
Aswin VerhoevenCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands.
Darius SoonawalaDepartment of Nephrology, Leiden University Medical Center, Leiden, the Netherlands.
Dorien J M PetersDepartment of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
Johan W de FijterDepartment of Nephrology, Leiden University Medical Center, Leiden, the Netherlands.
Oleg A MayborodaCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands.
DIPAK Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe variable course of autosomal dominant polycystic kidney disease (ADPKD), and the advent of renoprotective treatment require early risk stratification. We applied urinary metabolomics to explore differences associated with estimated glomerular filtration rate (eGFR; CKD-EPI equation) and future eGFR decline.

methodsTargeted, quantitative metabolic profiling (1H NMR-spectroscopy) was performed on baseline spot urine samples obtained from 501 patients with ADPKD. The discovery cohort consisted of 338 patients (56% female, median values for age 46 [IQR 38 to 52] years, eGFR 62 [IQR 45 to 85] ml/min/1.73m2, follow-up time 2.5 [range 1 to 3] years, and annual eGFR slope -3.3 [IQR -5.3 to -1.3] ml/min/1.73m2/year). An independent cohort (n = 163) was used for validation. Multivariate modelling and linear regression were used to analyze the associations between urinary metabolites and eGFR, and eGFR decline over time.

resultsTwenty-nine known urinary metabolites were quantified from the spectra using a semi-automatic quantification routine. The model optimization routine resulted in four metabolites that most strongly associated with actual eGFR in the discovery cohort (F = 128.9, P = 7×10-54, R2 = 0.724). A model using the ratio of two other metabolites, urinary alanine/citrate, showed the best association with future annual change in eGFR (F = 51.07, P = 7.26×10-12, R2 = 0.150). This association remained significant after adjustment for clinical risk markers including height-adjusted total kidney volume (htTKV). Results were confirmed in the validation cohort.

conclusionsQuantitative NMR profiling identified urinary metabolic markers that associated with actual eGFR and future rate of eGFR decline. The urinary alanine/citrate ratio showed additional value beyond conventional risk markers.

Indexed as

Glomerular Filtration RateModels, BiologicalAdultBiomarkersFemaleHumansKidneyMaleMiddle AgedPolycystic Kidney, Autosomal DominantBiomarkers

Identifiers

PMID32442208
PMCPMC7244119

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Registered trials

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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.