Evidence map›Paper›PMID 33303834›Full record

ArticleScientific reports2020

Urinary metabolic phenotyping for Alzheimer's disease.

Natalja Kurbatova, Manik Garg, Luke Whiley, Elena Chekmeneva, Beatriz Jiménez, María Gómez-Romero, Jake Pearce, Torben Kimhofer, Ellie D'Hondt, Hilkka Soininen and 17 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. 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
2.6field-weighted citation impact, top 9% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Deep learning analysis of urine-derived stem cell mitochondrial morphology as a non-invasive Alzheimer's disease biomarker.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Article
  5. A seven-year longitudinal study of the Alzheimer's disease blood metabolome.medRxiv : the preprint server for health sciences · 2025
    Article
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  18. Orphanet journal of rare diseases · 2021
    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

27 authors at 17 institutions in 10 countries.

Natalja KurbatovaEuropean Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. natalja@ebi.ac.uk.
Manik GargEuropean Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
Luke WhileyDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Elena ChekmenevaDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Beatriz JiménezDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
María Gómez-RomeroDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Jake PearceDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Torben KimhoferDivision of Systems Medicine, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Ellie D'HondtIMEC, Leuven, Belgium.
Hilkka SoininenDepartment of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
Iwona KłoszewskaMedical University of Lodz, Lodz, Poland.
Patrizia MecocciInstitute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy.
Magda Tsolaki3rd Department of Neurology, Aristotle University, Thessaloniki, Greece.
Bruno VellasINSERM U 558, University of Toulouse, Toulouse, France.
Dag AarslandKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Alejo Nevado-HolgadoDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
Benjamine LiuDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
Stuart SnowdenKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Petroula ProitsiKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Nicholas J AshtonKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Abdul HyeKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Cristina Legido-QuigleyKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Matthew R LewisDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Jeremy K NicholsonDepartment of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.
Elaine HolmesUK Dementia Research Institute, Hammersmith Hospital, Imperial College London, London, W12 0NN, UK.
Alvis BrazmaEuropean Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
Simon LovestoneDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
Imperial College London · GBKing's College London · GBMurdoch University · AUSteno Diabetes Center · DKWellcome Trust · GBAristotle University of Thessaloniki · GRCentre for Mental Health · GBEuropean Bioinformatics Institute · GBIMEC · BEJanssen (United Kingdom) · GBKuopio University Hospital · FIMedical University of Lodz · PLUK Dementia Research Institute · GBUniversité de Toulouse · FRUniversity of Oxford · GBUniversity of Perugia · ITWarneford Hospital · GB

Funding

Department of HealthMedical Research Council MC_PC_12025
6 · The paper itself

Abstract

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer's Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer's Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer's Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer's Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer's pathology in previous studies.

Indexed as

PhenotypeAgedAged, 80 and overAlzheimer DiseaseBiomarkersCognitive DysfunctionFemaleHumansMaleMetabolomicsQuantitative Trait LociBiomarkers

Identifiers

PMID33303834
PMCPMC7730184
OpenAlexW3111765626

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.