Evidence map›Paper›PMID 29644335›Full record

ReviewNPJ Parkinson's disease2018

Neuromelanin detection by magnetic resonance imaging (MRI) and its promise as a biomarker for Parkinson's disease.

David Sulzer, Clifford Cassidy, Guillermo Horga, Un Jung Kang, Stanley Fahn, Luigi Casella, Gianni Pezzoli, Jason Langley, Xiaoping P Hu, Fabio A Zucca and 2 more

Registry-linked trialOpen access · goldAbstract readReview
In one paragraph

Review in NPJ Parkinson's disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05487885 (Anhedonia, Development, and Emotions), which is not on this map. Cited by 147 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
147citing papers in PubMed, 2 pooled it
17.5field-weighted citation impact, top 1% 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.

NCT05487885 phase4completednot on this mapstarted 2022, after this paper: background citation

Anhedonia, Development, and Emotions: Phenotyping and Therapeutics (ADEPT) Study

TypeinterventionalSponsorErika ForbesRan2022 to 2025Enrolled123ConditionsDepression, AnhedoniaArmsContinuous theta burst stimulation (cTBS), Positive Affect Training, Ketamine Injectable Solution
3 · Its place in the literature

Who cites it

147 citing papers in PubMed, 2 syntheses or guidelines pooled it, 268 citations in OpenAlex.

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  20. Neuromelanin-induced cellular stress and neurotoxicity in the pathogenesis of Parkinson's disease.Apoptosis : an international journal on programmed cell death · 2025
    Review

87 more citing papers are in PubMed but not listed here.

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

12 authors at 8 institutions in 3 countries.

David Sulzer1Department of Psychiatry, Columbia University Medical Center , New York State Psychiatric Institute, New York, NY USA.
Clifford Cassidy4The Royal's Institute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON Canada.
Guillermo Horga1Department of Psychiatry, Columbia University Medical Center , New York State Psychiatric Institute, New York, NY USA.
Un Jung Kang2Department of Neurology, Columbia University Medical Center, New York, NY USA.
Stanley Fahn2Department of Neurology, Columbia University Medical Center, New York, NY USA.
Luigi Casella5Department of Chemistry, University of Pavia, Pavia, Italy.
Gianni PezzoliParkinson Institute, ASST "Gaetano Pini-CTO", Milan, Italy.
Jason Langley7Center for Advanced NeuroImaging, University of California Riverside, Riverside, CA USA.
Xiaoping P Hu8Department of Bioengineering, University of California Riverside, Riverside, CA USA.
Fabio A Zucca9Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy.
Ioannis U IsaiasDepartment of Neurology, University Hospital and Julius-Maximillian-University, Wuerzburg, Germany.
Luigi Zecca9Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy.
Columbia University Irving Medical Center · USNew York State Psychiatric InstituteUniversity of California, Riverside · USInstitute of Biomedical Technologies · ITIstituto Ortopedico Gaetano Pini · ITNational Research Council · ITUniversity of Ottawa · CAUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diagnosis of Parkinson's disease (PD) occurs after pathogenesis is advanced and many substantia nigra (SN) dopamine neurons have already died. Now that therapies to block this neuronal loss are under development, it is imperative that the disease be diagnosed at earlier stages and that the response to therapies is monitored. Recent studies suggest this can be accomplished by magnetic resonance imaging (MRI) detection of neuromelanin (NM), the characteristic pigment of SN dopaminergic, and locus coeruleus (LC) noradrenergic neurons. NM is an autophagic product synthesized via oxidation of catecholamines and subsequent reactions, and in the SN and LC it increases linearly during normal aging. In PD, however, the pigment is lost when SN and LC neurons die. As shown nearly 25 years ago by Zecca and colleagues, NM's avid binding of iron provides a paramagnetic source to enable electron and nuclear magnetic resonance detection, and thus a means for safe and noninvasive measure in living human brain. Recent technical improvements now provide a means for MRI to differentiate between PD patients and age-matched healthy controls, and should be able to identify changes in SN NM with age in individuals. We discuss how MRI detects NM and how this approach might be improved. We suggest that MRI of NM can be used to confirm PD diagnosis and monitor disease progression. We recommend that for subjects at risk for PD, and perhaps generally for older people, that MRI sequences performed at regular intervals can provide a pre-clinical means to detect presymptomatic PD.

Identifiers

PMID29644335
PMCPMC5893576
OpenAlexW2797850641

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.