Evidence map›Paper›PMID 42698345›Full record

ArticleMovement disorders : official journal of the Movement Disorder Society2026

Longitudinal Iron Changes in the Substantia Nigra of Early-Stage Parkinson's Disease.

Guangwei Du, Christopher Sica, Sol de Jesus, Lan Kong, Richard B Mailman, Xuemei Huang

Abstract read
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In one paragraph

Article in Movement disorders : official journal of the Movement Disorder Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Guangwei DuDepartment of Neurology, Penn State College of Medicine, Hershey, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-8267-0301
Christopher SicaDepartment of Radiology, Rush University, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0002-9714-921X
Sol de JesusDepartment of Neurology, Penn State College of Medicine, Hershey, Pennsylvania, USA.ORCID https://orcid.org/0000-0003-3186-7857
Lan KongSchool of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-6098-9445
Richard B MailmanDepartment of Pharmacology, University of Virginia, Charlottesville, Virginia, USA.ORCID https://orcid.org/0000-0003-1353-2738
Xuemei HuangDepartment of Neurology, University of Virginia, Charlottesville, Virginia, USA.ORCID https://orcid.org/0000-0003-3583-5502

Funding

Michael J. Fox Foundation for Parkinson's Research 18078NIH HHS RR033184NIH HHS TR000127NIH HHS TR002014NINDS NIH HHS NS060722NINDS NIH HHS NS082151Pennsylvania Department of Health
6 · The paper itself

Abstract

backgroundProgression of substantia nigra pars compacta (SNc) iron content in early-stage Parkinson's patients (PD) is poorly understood.

objectiveTo determine if nigral iron measured by quantitative susceptibility mapping (QSM) with zero-referencing    can track disease progression in early-stage PD.

methodsThirty-four early-stage PD patients and 35 matched controls were recruited. Iron content in the SNc and related regions were obtained using QSM with zero-referencing at both baseline and 1-year follow-up, along with clinical metrics.

resultsOf seven clinic metrics and five regional iron measures, only Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part II (MDS-UPDRS-II) (P = 0.046) and SNc iron (P = 0.0025 for cerebrospinal fluid zero-referencing; P = 0.014 for whole-brain zero-referencing) showed significant changes in PD subjects in the 1-year epoch. The changes in SNc iron were also correlated with changes in MDS-UPDRS-II (P = 0.004).

conclusionNigral iron content measured by zero-referencing QSM can be used to track disease progression in early-stage PD over the 1-year epoch. © 2026 International Parkinson and Movement Disorder Society.

Indexed as

brain ironlongitudinalParkinson's diseasesubstantia nigrasusceptibility MRI

Identifiers

PMID42698345

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.