Evidence map›Paper›PMID 34650080›Full record

ArticleNPJ Parkinson's disease2021

A six-metabolite panel as potential blood-based biomarkers for Parkinson's disease.

Stephan Klatt, James D Doecke, Anne Roberts, Berin A Boughton, Colin L Masters, Malcolm Horne, Blaine R Roberts

Open access · goldAbstract read
In one paragraph

Article in NPJ Parkinson's disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Stephan KlattThe Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia.ORCID http://orcid.org/0000-0003-0064-3367
James D DoeckeCooperative Research Centre for Mental Health, Parkville, VIC, 3052, Australia.ORCID http://orcid.org/0000-0003-2863-0293
Anne RobertsDepartment of Biochemistry, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Berin A BoughtonSchool of Biosciences, The University of Melbourne, Parkville, VIC, 3052, Australia.ORCID http://orcid.org/0000-0001-6342-9814
Colin L MastersThe Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia.
Malcolm HorneThe Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia.ORCID http://orcid.org/0000-0001-9427-2100
Blaine R RobertsDepartment of Biochemistry, Emory University School of Medicine, Atlanta, GA, 30322, USA. blaine.roberts@emory.edu.ORCID http://orcid.org/0000-0001-5466-0053
The University of Melbourne · AUEmory University · USCommonwealth Scientific and Industrial Research Organisation · AU

Funding

Department of Health | National Health and Medical Research Council (NHMRC) APP1138673Department of Health | National Health and Medical Research Council (NHMRC) APP1164692
6 · The paper itself

Abstract

Characterisation and diagnosis of idiopathic Parkinson's disease (iPD) is a current challenge that hampers both clinical assessment and clinical trial development with the potential inclusion of non-PD cases. Here, we used a targeted mass spectrometry approach to quantify 38 metabolites extracted from the serum of 231 individuals. This cohort is currently one of the largest metabolomic studies including iPD patients, drug-naïve iPD, healthy controls and patients with Alzheimer's disease as a disease-specific control group. We identified six metabolites (3-hydroxykynurenine, aspartate, beta-alanine, homoserine, ornithine (Orn) and tyrosine) that are significantly altered between iPD patients and control participants. A multivariate model to predict iPD from controls had an area under the curve (AUC) of 0.905, with an accuracy of 86.2%. This panel of metabolites may serve as a potential prognostic or diagnostic assay for clinical trial prescreening, or for aiding in diagnosing pathological disease in the clinic.

Identifiers

PMID34650080
PMCPMC8516864
OpenAlexW3205954881

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.