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Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease.

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Overview

Authors: Chiara Camastra1,2, Aldo Quattrone1, Andrea Quattrone1,3
ORCID iDs: Chiara Camastra
  1. Neuroscience Research Center, Magna Graecia University, Catanzaro 88100, Italy
  2. Brain Health Imaging Centre, Centre for Addiction and Mental Health, University of Toronto, M5T1R8 Toronto, Canada
  3. Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, 88100 Catanzaro, Italy
Journal: Brain communications, volume 8, issue 4, article fcag316
Dates: received 13 October 2025; accepted 25 July 2026; published online 18 August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag316 · PMID 42643997 · PMCID PMC13504651 · OpenAlex W7203675443
Open access: gold, a free copy (OpenAlex)
Status: empty repository
Categories: structural MRI / diffusion (modality), human (organism), other condition (population), Parkinson's (population), depression (population), sleep disorders (population), clinical / translational (subfield)
Methods: Statistics, Preprocessing, Connectivity, fMRI & imaging
Keywords: Parkinson’s disease, rapid eye movement sleep behaviour disorder, depression, anxiety, coordinate-based network mapping
Topic: Parkinson's Disease Mechanisms and Treatments (Neurology, Medicine), according to OpenAlex
Citations: not cited yet (Europe PMC); 52 references in the paper
Research resources: RRID:SCR_006431

Abstract

Non-motor symptoms, including rapid eye movement sleep behaviour disorder (RBD), depression and anxiety, are common and often co-occurring in patients with Parkinson’s disease. This study aimed to investigate their potential shared neurobiological substrates by integrating structural, functional and neurochemical imaging data. We analysed data from 638 Parkinson’s disease patients from the Parkinson’s Progression Markers Initiative (PPMI), with available 3T T1-weighted MRI scans. RBD, depression and anxiety severity were assessed using validated clinical scales (RBD Screening Questionnaire Score, Geriatric Depression Scale and State-Trait Anxiety Inventory). Voxel-based morphometry (VBM) multivariate regression analyses were performed to identify grey matter (GM) volume loss associated with each clinical symptom. All analyses were rigorously controlled for a comprehensive set of potential confounders, including age, sex, education, disease duration, motor severity and cognitive dysfunction, thereby minimizing confounding effects related to other aspects of the disease. Coordinate-based network mapping was then applied using a large normative resting-state functional connectome (N = 1000), to characterize symptom-specific functional networks based on brain areas functionally connected to the VBM-derived clusters. Finally, spatial correlations between these networks and normative neurotransmitter density maps from PET data were assessed. VBM analyses revealed distinct patterns of GM atrophy across the three symptoms (pFWE<0.05), overlapping in the left middle temporal and right middle frontal gyri. The coordinate-based functional network mapping approach demonstrated that the GM atrophy pattern associated with each symptom (pFWE < 10−6) converged onto brain networks involving several cortical regions and overlapping across symptoms, and with the greatest spatial affinity, among canonical large-scale networks, with the Dorsal and Ventral Attention networks. All three symptom-related networks showed significant alignment with the noradrenaline transporters (NAT) spatial distribution (pFDR < 0.05). Overall, this study proposes a novel conceptual and methodological framework integrating well-established and validated techniques to identify the neuroanatomical bases of specific diseases or symptoms, potentially of interest for future research. Our neuroimaging findings in the large PPMI cohort of early Parkinson’s disease patients demonstrate that the brain networks associated with RBD, depression and anxiety non-motor symptoms were largely overlapping, involved the attention networks and were spatially aligned with the noradrenergic system, suggesting that these symptoms may have shared neurobiological substrates.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

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chiaracamastra/Coordinate-based-network-mapping

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: a027be97a3cefb9d8e4d20bbd3ab90aaaf923c90, 3 December 2025
Size: 2 files, 0 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
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The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

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Data

Datasets cited

Data availability

The data supporting the findings of this study are openly available in the Image and Data Archive at https://ida.loni.usc.edu/login.jsp?project=PPMI.

All custom scripts used for data analysis in this study are available on GitHub at the following repository: https://github.com/chiaracamastra/Coordinate-based-network-mapping. Additional analyses were performed using established MATLAB-based toolboxes (SPM12, CAT12, Lead Connectome Mapper, JuSpace), freely available and downloadable from their respective repositories and installed within the MATLAB environment.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 2, 28 September 2026

  • Funding: added Bristol-Myers Squibb; Biogen; Celgene; Allergan; Avid Radiopharmaceuticals

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 49 references, 1 RRID.

Cite

This paper

Camastra, C., Quattrone, A., & Quattrone, A. (2026). Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease. Brain communications, 8(4), fcag316. https://doi.org/10.1093/braincomms/fcag316

BibTeX

@article{camastra2026structural,
author = {Camastra, Chiara and Quattrone, Aldo and Quattrone, Andrea},
title = {{Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease}},
journal = {Brain communications},
year = {2026},
month = aug,
volume = {8},
number = {4},
pages = {fcag316},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag316},
url = {https://doi.org/10.1093/braincomms/fcag316},
pmid = {42643997},
pmcid = {PMC13504651}
}

RIS

TY - JOUR
AU - Camastra, Chiara
AU - Quattrone, Aldo
AU - Quattrone, Andrea
TI - Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/08/18
VL - 8
IS - 4
SP - fcag316
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag316
UR - https://doi.org/10.1093/braincomms/fcag316
LA - en
ER -

CSL-JSON

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