Evidence map›Paper›PMID 40799161›Full record

ArticleMovement disorders : official journal of the Movement Disorder Society2025

Plasma Metabolomics Profiles in Prodromal and Clinical Parkinson's Disease.

Mario H Flores-Torres, Xiaojing Peng, Sarah Jeanfavre, Clary Clish, Ying Wang, Marjorie L McCullough, Brian Healy, Michael A Schwarzschild, Kjetil Bjornevik, Alberto Ascherio

Abstract read
In one paragraph

Article in Movement disorders : official journal of the Movement Disorder Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

10 authors.

Mario H Flores-TorresDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-9791-3196
Xiaojing PengDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-0441-6268
Sarah JeanfavreMetabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA.
Clary ClishMetabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA.
Ying WangDepartment of Population Science, American Cancer Society, Atlanta, Georgia, USA.
Marjorie L McCulloughDepartment of Population Science, American Cancer Society, Atlanta, Georgia, USA.
Brian HealyBrigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Michael A SchwarzschildDepartment of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-6019-8280
Kjetil BjornevikDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-2892-6986
Alberto AscherioDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0585-3294

Funding

Long Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3M
Cancer Epidemiology Cohort in Male Health ProfessionalsU01CA167552 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Lorelei Mucci, Walter C. Willett · 2017 to 2026
$17.0M
Metabolomics and risk of Parkinson's DiseaseR01NS089619 · NINDS · HARVARD SCHOOL OF PUBLIC HEALTH · PI ASCHERIO, ALBERTO · 2015 to 2019
$3.3M
NCI NIH HHS U01 CA167552NCI NIH HHS UM1 CA186107NIH HHS R01 NS089619-01A1NINDS NIH HHS R01 NS089619
6 · The paper itself

Abstract

backgroundThe long prodromal phase of Parkinson's disease (PD) and the link the disease has with metabolic factors suggest that metabolomics could help identify affected individuals at early stages.

objectiveThe goal was to examine whether plasma metabolomic profiles could identify individuals in the prodromal and clinical phase of PD.

methodsWe quantified and compared the plasma metabolomic profiles of 922 individuals with PD who provided blood samples at a median of 11 years before (n = 809) or 2 years after (n = 113) disease diagnosis to that of matched controls, all selected from three established cohort studies (Nurses' Health Study, Health Professionals Follow-up Study, and Cancer Prevention Study II). We used conditional logistic regression models and machine learning techniques to identify metabolites predicting prodromal and clinically manifest PD.

resultsSeveral metabolites, especially amino acids, acyl-carnitines, and other lipids were nominally associated with PD since the years leading to disease diagnosis. Metabolites proposed as biomarkers of foods or care products tended to be associated with a higher PD risk closer to disease diagnosis. Metabolites reflecting higher intake of coffee, smoking, and acetaminophen tended to be associated with a lower PD risk over the course of the disease. Metabolomic profiles in prodromal samples were unable to accurately predict future clinical PD.

conclusionsMetabolic pathways related to the metabolism of amino acids and lipids may be involved in PD progression. Metabolomic differences may also result from behavioral changes and medical management, emphasizing the need to consider prodromal and clinical data in future studies. © 2025 International Parkinson and Movement Disorder Society.

Indexed as

MetabolomeMetabolomicsParkinson DiseaseProdromal SymptomsAgedBiomarkersCohort StudiesFemaleHumansMaleMiddle AgedBiomarkersmetabolomicsParkinson's diseaseprodromalprospective

Identifiers

PMID40799161
PMCPMC12380052

What OpenQuestion holds

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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.