Evidence map›Paper›PMID 31183578›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2019

A metabolomic signature of treated and drug-naïve patients with Parkinson's disease: a pilot study.

Jacopo Troisi, Annamaria Landolfi, Carmine Vitale, Katia Longo, Autilia Cozzolino, Massimo Squillante, Maria Cristina Savanelli, Paolo Barone, Marianna Amboni

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In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed, 27 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

9 authors at 2 institutions in 1 country.

Jacopo TroisiDepartment of Medicine, Surgery and Dentistry, "Scuola Medica Salernitana", Neuroscience Section, University of Salerno, Baronissi, SA, Italy. troisi@theoreosrl.com.ORCID 0000-0003-2962-7379
Annamaria LandolfiDepartment of Medicine, Surgery and Dentistry, "Scuola Medica Salernitana", Neuroscience Section, University of Salerno, Baronissi, SA, Italy.
Carmine VitaleDepartment of Motor Science and Wellness, University Parthenope, Naples, Italy.
Katia LongoInstitute of Diagnosis and Care (IDC) Hermitage-Capodimonte, Naples, Italy.
Autilia CozzolinoDepartment of Medicine and Surgery, Center for Neurodegenerative Diseases (CEMAND), Neuroscience Section, University of Salerno, Fisciano, Italy.
Massimo SquillanteDepartment of Medicine and Surgery, Center for Neurodegenerative Diseases (CEMAND), Neuroscience Section, University of Salerno, Fisciano, Italy.
Maria Cristina SavanelliIos & Coleman, Naples, Italy.
Paolo BaroneDepartment of Medicine, Surgery and Dentistry, "Scuola Medica Salernitana", Neuroscience Section, University of Salerno, Baronissi, SA, Italy.
Marianna AmboniInstitute of Diagnosis and Care (IDC) Hermitage-Capodimonte, Naples, Italy.
University of Salerno · ITParthenope University of Naples · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAbout 90% of cases of Parkinson's disease (PD) are idiopathic and attempts to understand pathogenesis typically assume a multifactorial origin. Multifactorial diseases can be studied using metabolomics, since the cellular metabolome reflects the interplay between genes and environment.

objectiveThe aim of our case-control study is to compare metabolomic profiles of whole blood obtained from treated PD patients, de-novo PD patients and controls, and to study the perturbations correlated with disease duration, disease stage and motor impairment.

methodsWe collected blood samples from 16 drug naïve parkinsonian patients, 84 treated parkinsonian patients, and 42 age matched healthy controls. Metabolomic profiles have been obtained using gas chromatography coupled to mass spectrometry. Multivariate statistical analysis has been performed using supervised models; partial least square discriminant analysis and partial least square regression.

resultsThis approach allowed separation between discrete classes and stratification of treated patients according to continuous variables (disease duration, disease stage, motor score). Analysis of single metabolites and their related metabolic pathways revealed unexpected possible perturbations related to PD and underscored existing mechanisms that correlated with disease onset, stage, duration, motor score and pharmacological treatment.

conclusionMetabolomics can be useful in pathogenetic studies and biomarker discovery. The latter needs large-scale validation and comparison with other neurodegenerative conditions.

Indexed as

MetabolomeAgedAged, 80 and overBiomarkersCase-Control StudiesFemaleGas Chromatography-Mass SpectrometryHumansMaleMetabolomicsMiddle AgedParkinson DiseasePilot ProjectsBiomarkersGas chromatography–mass spectrometryMetabolomeParkinson’s disease

Identifiers

PMID31183578
OpenAlexW2952265197

What OpenQuestion holds

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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.