Mapping dopaminergic projections in the human brain with resting-state fMRI
Abstract
The striatum receives dense dopaminergic projections making it a key region of the dopaminergic system. Its dysfunction has been implicated in various conditions including Parkinson's disease (PD) and substance use disorder. However, the investigation of dopamine-specific functioning in humans is problematic as current MRI approaches are unable to differentiate between dopaminergic and other projections. Here, we demonstrate that 'connectopic mapping' -a novel approach for characterizing fine-grained, overlapping modes of functional connectivity- can be used to map dopaminergic projections in striatum. We applied connectopic mapping to resting-state functional MRI data of the Human Connectome Project (population cohort; N=839) and selected the second-order striatal connectivity mode for further analyses. We first validated its specificity to dopaminergic projections by demonstrating a high spatial correlation (r=0.884) with dopamine transporter availability -a marker of dopaminergic projections- derived from DaT SPECT scans of 209 healthy controls. Next, we obtained the subject-specific second-order modes from 20 controls, and 39 PD patients scanned under placebo and under dopamine replacement therapy (L-DOPA), and show that our proposed dopaminergic marker tracks PD diagnosis, symptom severity and sensitivity to L-DOPA. Finally, across 30 daily alcohol users and 38 daily smokers, we establish strong associations with self-reported alcohol and nicotine use. Our findings provide evidence that the second-order mode of functional connectivity in striatum maps onto dopaminergic projections, tracks inter-individual differences in PD symptom severity and L-DOPA sensitivity, and exhibits strong associations with levels of nicotine and alcohol use, thereby offering a new biomarker for dopamine-related (dys)function in the human brain.
Data availability
We made use of publicly available data from the Human Connectome Project (HCP) dataset, from publicly available data from the Parkinson Progression Marker Initiative (PPMI) dataset, and from a local PD dataset that was part of a clinical trial.See https://www.humanconnectome.org/study/hcp-young-adult/document/1200-subjects-data-release for access to the HCP data. The subject identifiers from the HCP dataset used in our first analysis can be found in Appendix 2 - Table 4. Please note that the subject identifiers from the subset of HCP subjects included in the nicotine-use and alcohol-use analyses cannot be provided, since the access to information about substance use is restricted. For more information about applying to get access to the HCP restricted data and for the HCP restricted data use terms see: https://www.humanconnectome.org/study/hcp-young-adult/document/wu-minn-hcp-consortium-restricted-data-use-terms.For access to the PPMI dataset, see https://www.ppmi-info.org/access-data-specimens/download-data. The subject identifiers from the PPMI dataset used in our analyses can be found in Appendix 2 - Tables 5 and 6.All derived and anonymized individual data from our local PD dataset are available at the Donders Repository: https://data.donders.ru.nl/.The code used for the connectopic mapping procedure in all three datasets is available at the following Github repository: https://github.com/koenhaak/congrads.In addition, for supplementary analyses, we further used PET scans available in the JuSpace Toolbox: https://github.com/ juryxy/JuSpace.
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The WU-Minn human connectome project: an overview.Human Connectome Project, see Appendix 2 - Table 4.
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The parkinson progression marker initiative (PPMI)Parkinson Progression Marker Initiative, see Appendix 2 - Tables 5 and 6.
Article and author information
Author details
Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Vidi Grant No. 864-12-004)
- Christian F Beckmann
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Vici Grant No. 17854)
- Christian F Beckmann
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Vidi Grant No. 016.156.415)
- Andre F Marquand
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Veni Grant No. 016.171.068)
- Koen V Haak
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Veni Grant No. 91617077)
- Rick Helmich
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO-CAS Grant No. 012-200-013)
- Christian F Beckmann
ZonMw (Rubicon Grant No. 452172019)
- Marianne Oldehinkel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All participants from whom data was used in this manuscript, provided written informed consent (and consent to publish) according to the declaration of Helsinki. For the HCP dataset ethical approval was given by the Washington University Institutional Review Board (IRB), for the PPMI dataset ethical approval was obtained locally at each of the participating sites, and for our local PD dataset ethical approval was obtained from the local ethical committee (Commissie Mensgebonden Onderzoek MO Arnhem Nijmegen, CMO 2014/014).
Reviewing Editor
- Shella Keilholz, Emory University and Georgia Institute of Technology, United States
Version history
- Preprint posted: March 26, 2021 (view preprint)
- Received: July 1, 2021
- Accepted: January 26, 2022
- Accepted Manuscript published: February 3, 2022 (version 1)
- Version of Record published: February 14, 2022 (version 2)
Copyright
© 2022, Oldehinkel et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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