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van der Horn HJ, Vakhtin AA, Julio K, Nitschke S, Shaff N, Dodd AB, Erhardt E, Phillips JP, Pirio Richardson S, Deligtisch A, Stewart M, Suarez Cedeno G, Meles SK, Mayer AR, Ryman SG. Parkinson's disease cerebrovascular reactivity pattern: A feasibility study. J Cereb Blood Flow Metab 2024:271678X241241895. [PMID: 38578669 DOI: 10.1177/0271678x241241895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
A mounting body of research points to cerebrovascular dysfunction as a fundamental element in the pathophysiology of Parkinson's disease (PD). In the current feasibility study, blood-oxygen-level-dependent (BOLD) MRI was used to measure cerebrovascular reactivity (CVR) in response to hypercapnia in 26 PD patients and 16 healthy controls (HC), and aimed to find a multivariate pattern specific to PD. Whole-brain maps of CVR amplitude (i.e., magnitude of response to CO2) and latency (i.e., time to reach maximum amplitude) were computed, which were further analyzed using scaled sub-profile model principal component analysis (SSM-PCA) with leave-one-out cross-validation. A meaningful pattern based on CVR latency was identified, which was named the PD CVR pattern (PD-CVRP). This pattern was characterized by relatively increased latency in basal ganglia, sensorimotor cortex, supplementary motor area, thalamus and visual cortex, as well as decreased latency in the cerebral white matter, relative to HC. There were no significant associations with clinical measures, though sample size may have limited our ability to detect significant associations. In summary, the PD-CVRP highlights the importance of cerebrovascular dysfunction in PD, and may be a potential biomarker for future clinical research and practice.
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Affiliation(s)
- Harm Jan van der Horn
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Andrei A Vakhtin
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Kayla Julio
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Stephanie Nitschke
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Nicholas Shaff
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Andrew B Dodd
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Erik Erhardt
- Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, USA
| | - John P Phillips
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Sarah Pirio Richardson
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, NM, USA
- New Mexico VA Health Care System, Albuquerque, NM, USA
| | - Amanda Deligtisch
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, NM, USA
| | - Melanie Stewart
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, NM, USA
| | - Gerson Suarez Cedeno
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, NM, USA
| | - Sanne K Meles
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Andrew R Mayer
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
| | - Sephira G Ryman
- Department of Translational Neuroscience, The Mind Research Network, Albuquerque, NM, USA
- Nene and Jamie Koch Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico, Albuquerque, NM, USA
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Ananth MR, Gardus JD, Huang C, Palekar N, Slifstein M, Zaborszky L, Parsey RV, Talmage DA, DeLorenzo C, Role LW. Loss of cholinergic input to the entorhinal cortex is an early indicator of cognitive impairment in natural aging of humans and mice. Res Sq 2024:rs.3.rs-3851086. [PMID: 38260541 PMCID: PMC10802688 DOI: 10.21203/rs.3.rs-3851086/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
In a series of translational experiments using fully quantitative positron emission tomography (PET) imaging with a new tracer specific for the vesicular acetylcholine transporter ([18F]VAT) in vivo in humans, and genetically targeted cholinergic markers in mice, we evaluated whether changes to the cholinergic system were an early feature of age-related cognitive decline. We found that deficits in cholinergic innervation of the entorhinal cortex (EC) and decline in performance on behavioral tasks engaging the EC are, strikingly, early features of the aging process. In human studies, we recruited older adult volunteers that were physically healthy and without prior clinical diagnosis of cognitive impairment. Using [18F]VAT PET imaging, we demonstrate that there is measurable loss of cholinergic inputs to the EC that can serve as an early signature of decline in EC cognitive performance. These deficits are specific to the cholinergic circuit between the medial septum and vertical limb of the diagonal band (MS/vDB; CH1/2) to the EC. Using diffusion imaging, we further demonstrate impaired structural connectivity in the tracts between the MS/vDB and EC in older adults with mild cognitive impairment. Experiments in mouse, designed to parallel and extend upon the human studies, used high resolution imaging to evaluate cholinergic terminal density and immediate early gene (IEG) activity of EC neurons in healthy aging mice and in mice with genetic susceptibility to accelerated accumulation amyloid beta plaques and hyperphosphorylated mouse tau. Across species and aging conditions, we find that the integrity of cholinergic projections to the EC directly correlates with the extent of EC activation and with performance on EC-related object recognition memory tasks. Silencing EC-projecting cholinergic neurons in young, healthy mice during the object-location memory task impairs object recognition performance, mimicking aging. Taken together we identify a role for acetylcholine in normal EC function and establish loss of cholinergic input to the EC as an early, conserved feature of age-related cognitive decline in both humans and rodents.
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Kanel P, Carli G, Vangel R, Roytman S, Bohnen NI. Challenges and innovations in brain PET analysis of neurodegenerative disorders: a mini-review on partial volume effects, small brain region studies, and reference region selection. Front Neurosci 2023; 17:1293847. [PMID: 38099203 PMCID: PMC10720329 DOI: 10.3389/fnins.2023.1293847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 11/13/2023] [Indexed: 12/17/2023] Open
Abstract
Positron Emission Tomography (PET) brain imaging is increasingly utilized in clinical and research settings due to its unique ability to study biological processes and subtle changes in living subjects. However, PET imaging is not without its limitations. Currently, bias introduced by partial volume effect (PVE) and poor signal-to-noise ratios of some radiotracers can hamper accurate quantification. Technological advancements like ultra-high-resolution scanners and improvements in radiochemistry are on the horizon to address these challenges. This will enable the study of smaller brain regions and may require more sophisticated methods (e.g., data-driven approaches like unsupervised clustering) for reference region selection and to improve quantification accuracy. This review delves into some of these critical aspects of PET molecular imaging and offers suggested strategies for improvement. This will be illustrated by showing examples for dopaminergic and cholinergic nerve terminal ligands.
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Affiliation(s)
- Prabesh Kanel
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
- Morris K. Udall Center of Excellence for Parkinson’s Disease Research, University of Michigan, Ann Arbor, MI, United States
- Parkinson’s Foundation Research Center of Excellence, University of Michigan, Ann Arbor, MI, United States
| | - Giulia Carli
- Morris K. Udall Center of Excellence for Parkinson’s Disease Research, University of Michigan, Ann Arbor, MI, United States
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States
| | - Robert Vangel
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - Stiven Roytman
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - Nicolaas I. Bohnen
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
- Morris K. Udall Center of Excellence for Parkinson’s Disease Research, University of Michigan, Ann Arbor, MI, United States
- Parkinson’s Foundation Research Center of Excellence, University of Michigan, Ann Arbor, MI, United States
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States
- Neurology Service and GRECC, Veterans Administration Ann Arbor Healthcare System, Ann Arbor, MI, United States
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