Evidence map›Paper›PMID 34400650›Full record

ArticleNPJ Parkinson's disease2021

Prognostic biomarkers of Parkinson's disease in the Spanish EPIC cohort: a multiplatform metabolomics approach.

Carolina Gonzalez-Riano, Jorge Saiz, Coral Barbas, Alberto Bergareche, José Mª Huerta, Eva Ardanaz, Marcela Konjevod, Elisabet Mondragon, M E Erro, M Dolores Chirlaque and 3 more

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 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.0field-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

32 citing papers in PubMed, 50 citations in OpenAlex.

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  18. Multiplatform untargeted metabolomics.Magnetic resonance in chemistry : MRC · 2023
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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

13 authors at 7 institutions in 2 countries.

Carolina Gonzalez-RianoCentro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid, Spain.ORCID http://orcid.org/0000-0001-7026-8684
Jorge SaizCentro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid, Spain.
Coral BarbasCentro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid, Spain. cbarbas@ceu.es.ORCID http://orcid.org/0000-0003-4722-491X
Alberto BergarecheNeurodegenerative Disorders Area, Biodonostia Health Research Institute, San Sebastián, Spain. JESUSALBERTO.BERGARECHEYARZA@osakidetza.eus.ORCID http://orcid.org/0000-0002-6055-1061
José Mª HuertaInstituto Murciano de Investigación Biosanitaria (IMIB), Murcia, Spain.
Eva ArdanazCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Marcela KonjevodDivision of Molecular Medicine, Rudjer Boskovic Institute, Zagreb, Croatia.
Elisabet MondragonNeurodegenerative Disorders Area, Biodonostia Health Research Institute, San Sebastián, Spain.
M E ErroDepartment of Neurology, Complejo Hospitalario de Navarra, IdiSNA (Navarra Institute for Health Research), Pamplona, Spain.
M Dolores ChirlaqueInstituto Murciano de Investigación Biosanitaria (IMIB), Murcia, Spain.
Eunate AbilleiraPublic Health Laboratory in Gipuzkoa, Biodonostia Health Research Institute, San Sebastián, Spain.ORCID http://orcid.org/0000-0001-9530-9374
Fernando Goñi-IrigoyenCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Pilar AmianoCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Biogipuzkoa Health Research Institute · ESUniversidad San Pablo CEU · ESInstituto Murciano de Investigación Biosanitaria · ESBiomedical Research Networking Center on Neurodegenerative Diseases · ESComplejo Hospitalario de Navarra · ESInstituto de Salud Pública de Navarra · ESRuđer Bošković Institute · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of knowledge about the onset and progression of Parkinson's disease (PD) hampers its early diagnosis and treatment. Metabolomics might shed light on the PD imprint seeking a broader view of the biochemical remodeling induced by this disease in an early and pre-symptomatic stage and unveiling potential biomarkers. To achieve this goal, we took advantage of the great potential of the European Prospective Study on Nutrition and Cancer (EPIC) cohort to apply metabolomics searching for early diagnostic PD markers. This cohort consisted of healthy volunteers that were followed for around 15 years until June 2011 to ascertain incident PD. For this untargeted metabolomics-based study, baseline preclinical plasma samples of 39 randomly selected individuals that developed PD (Pre-PD group) and the corresponding control group were analyzed using a multiplatform approach. Data were statistically analyzed and exposed alterations in 33 metabolites levels, including significantly lower levels of free fatty acids (FFAs) in the preclinical samples from PD subjects. These results were then validated by adopting a targeted HPLC-QqQ-MS approach. After integrating all the metabolites affected, our finding revealed alterations in FFAs metabolism, mitochondrial dysfunction, oxidative stress, and gut-brain axis dysregulation long before the development of PD hallmarks. Although the biological purpose of these events is still unknown, the remodeled metabolic pathways highlighted in this work might be considered worthy prognostic biomarkers of early prodromal PD. The findings revealed by this work are of inestimable value since this is the first study conducted with samples collected many years before the disease development.

Identifiers

PMID34400650
PMCPMC8368017
OpenAlexW3195879556

What OpenQuestion holds

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LicenceCC BY
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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.