Autonomic dysfunction in Parkinson disease (PD) develops throughout all stages of the disease, including before diagnosis.1–3 Notably, autonomic dysfunction has recently been highlighted as a strong predictor of poor prognosis in PD.4 Thus, identifying the neuroanatomical correlates of autonomic dysfunction is vital to further understand the disease and develop therapeutics for patients with PD. Recent neuroimaging studies have revealed complex mechanisms, including disrupted functional connectivity within the lateral premotor-parietal5 and thalamo-striatal-hypothalamic circuits,6 and white matter disintegration in the cingulum,7 fronto-subcortical, and posterior cortical regions,8 which may be related to autonomic dysfunction in patients with PD. However, little is known regarding the association between early autonomic dysfunction and dopaminergic neuronal degeneration or PD-related metabolic changes.
Dopamine transporter (DAT) images contain valuable diagnostic information for differentiating neurodegenerative diseases caused by presynaptic dopaminergic degeneration.9 Furthermore, early-phase 18F-fluorinated N-3 -fluoropropyl-2-beta-carboxymethoxy-3-beta-(4-iodophenyl) nortropane (18F-FP-CIT) PET images (ie, images that are acquired within the first 10 minutes after injection) seem to provide additional information on regional cerebral perfusion, which resembles 18F-FDG uptake images.10,11 In the present study, we hypothesized that dysautonomia in patients with PD is closely coupled with nigrostriatal dopaminergic degeneration and PD-related cortical or subcortical metabolic changes. Hence, we analyzed DAT availability and regional cerebral perfusion in patients with de novo PD in relation to the early presence of autonomic dysfunction using quantitative analyses of dual-phase 18F-FP-CIT PET data and comprehensive autonomic function tests.
We consecutively enrolled 120 patients with de novo PD who visited the Movement Disorders Outpatient Clinic of Severance Hospital, Yonsei University Health System, from March 2015 to April 2018. Parkinson disease was diagnosed according to the clinical diagnostic criteria of the United Kingdom PD Society Brain Bank.12 All patients showed decreased DAT availability in the posterior putamen on 18F-FP-CIT PET scans. Each patient underwent comprehensive autonomic function tests as a baseline evaluation; 3 patients failed to complete the comprehensive assessment of autonomic function due to arrhythmia and were excluded from the study. Parkinsonian motor symptoms were assessed using the Unified PD Rating Scale Part III (UPDRS-III). Olfactory function was measured using the Cross-Cultural Smell Identification Test (CCSIT), and depression was evaluated using the Beck Depression Inventory (BDI). The presence of rapid eye movement behavior disorder (RBD) was determined using an RBD screening questionnaire with a cutoff score of 5/6.13 The Korean version of the Mini-Mental State Examination (K-MMSE) was used to assess general cognition.14 This study was approved by the Institutional Review Board of Yonsei University Severance Hospital. The requirement for informed consent in patients with PD was waived because of the retrospective nature of the study and the use of anonymized patient data.
In addition, 37 healthy controls voluntarily underwent 18F-FP-CIT PET scans and were included as the control group when comparing the regional uptake of early-phase 18F-FP-CIT PET images. These healthy controls were from our prospective cohort study in subjects with normal cognition, which was also approved by our Institutional Review Board. Written informed consent was obtained from all healthy controls to use their neuroimaging and clinical data for other secondary studies.
Autonomic Function Test
Comprehensive autonomic function tests were used to evaluate the sudomotor, cardiovagal, and adrenergic functions of patients with PD.15,16 Sudomotor function was assessed with the Quantitative Sudomotor Axon Reflex Test. Cardiovagal function was assessed using the heart rate response to deep breathing and the Valsalva ratio. Adrenergic function was assessed based on beat-to-beat blood pressure and heart rate response during phases II and IV of the Valsalva maneuver, in addition to the presence of orthostatic hypotension in a head-up tilt test. The Composite Autonomic Severity Score (CASS), which consists of 3 subscores (CASS sudomotor, 0–3; CASS cardiovagal, 0–3; CASS adrenergic, 0–4) and is a validated scoring system for laboratory quantification of autonomic deficits,15 was calculated using the results of the aforementioned autonomic function tests, as described previously.15,17 Patients with a CASS of 3 or lower had either mild or no evidence of autonomic failure (PD without definite autonomic dysfunction, PD-AUT−; n = 73), whereas those with a CASS of 4 to 10 had moderate to severe autonomic failure (PD with autonomic dysfunction, PD-AUT+; n = 44).15
Acquisition of the 18F-FP-CIT PET Images (Early- and Late-Phase Images)
18F-FP-CIT PET was performed using a Discovery 600 (GE Healthcare, Milwaukee, WI) PET/CT scanner. The brain CT images were acquired for attenuation correction with a 0.8-second rotation time, 60 mA, 120 kVp, 3.75 mm section thickness, 0.625 mm collimation, and 9.375 mm table feed per rotation. Approximately 5 mCi (185 MBq) of 18F-FP-CIT were injected immediately after the start of the PET acquisition, and early-phase FP-CIT PET data were acquired for 10 minutes. Ninety minutes after the injection, the late-phase FP-CIT PET images were acquired for 15 minutes. All FP-CIT PET images were reconstructed using the ordered subset expectation maximization algorithm with 4 iterations and 32 subsets.
Quantitative Analyses of 18F-FP-CIT PET (Early- and Late-Phase Images)
Image processing was performed using MATLAB (The MathWorks, Inc, Natick, MA) software for statistical parametric mapping (SPM8). The early-phase 18F-FP-CIT images were spatially normalized to the Dementia-Specific FDG-PET template, which was created by images acquired from 50 neurological patients and 50 age-matched controls.18,19 The spatially normalized early-phase 18F-FP-CIT images underwent intensity scaling and global intensity normalization to standardize the magnitudes of all voxel values. Statistical parametric mapping analysis was performed to assess the group differences in regional uptake in the early-phase 18F-FP-CIT PET images between the PD group and healthy control group (n = 37), while adjusting for age, sex, and/or disease duration of PD. The results for the differences between the groups in regional uptake were considered significant at an uncorrected P value of less than 0.001.
All reconstructed late-phase 18F-FP-CIT images were normalized to the late-phase 18F-FP-CIT template, which was made using the late-phase 18F-FP-CIT PET images and T1-weighted MRI scans of 40 healthy controls. All healthy controls from which the late-phase 18F-FP-CIT template was derived had no previous history of neurologic or psychiatric illness. They showed normal cognitive function on a detailed neuropsychological test, and exhibited normal findings on neurologic examination, structural MRI, and 18F-FP-CIT PET. Twelve volumes of interest (VOIs) were drawn on the late-phase 18F-FP-CIT template, as described previously.20 In brief, along the anterior-posterior commissure line on the transverse plane, the striatum was divided into dorsal and ventral portions. The ventral portion was further divided into 2 subregions: ventral striatum and ventral putamen. Then, the dorsal portion was split into 4 anterior and posterior subregions by the coronal anterior commissure plane: the anterior caudate, posterior caudate, anterior putamen, and posterior putamen. DAT availability in each VOI was estimated using the specific/nonspecific binding ratio as a surrogate, which was defined as follows: (SUVmean of the striatal subregion VOIs − SUVmean of the occipital VOI)/SUVmean of the occipital VOI.
Cortical Thickness Analyses
The high-resolution T1-weighted MRI data were acquired using the same protocol as described in our previous work.21 The high-resolution T1-weighted MRI data were processed to extract cortical surfaces and cortical thickness using the Freesurfer pipeline 6.0 (https://surfer.nmr.mgh.harvard.edu).22 The T1-weighted MRI data processing pipeline included nonbrain tissue removal,23 Talairach transformation, tissue segmentation, intensity normalization,24 tessellation of the gray matter (GM)/white matter (WM) boundary, automated topology correction,25,26 and surface deformation following intensity gradients to optimally place the GM/WM and GM/cerebrospinal fluid (CSF) boundaries.27 Cortical thickness was calculated as the closest distance from the GM/WM boundary to the GM/CSF boundary at each vertex on the tessellated surface.28 We visually validated the quality of segmentation and cortical surface model before extracting cortical thickness. There were no obvious errors for all subjects. To perform surface-based analysis across subjects, surface-based registration to the Freesurfer spherical atlas29 and surface-based smoothing were performed using 10 mm full-width at half maximum. The statistical analysis of cortical thickness was performed at a vertexwise level using an analysis of covariance with age, sex, education, and disease duration as covariates for comparisons between the PD groups. The results for the differences between the groups in cortical thickness were considered significant at a clusterwise corrected P value less than 0.05.30
To compare the baseline demographic characteristics, autonomic dysfunction, and striatal DAT availability between the PD groups, Student t tests and Pearson χ2 tests were used for continuous and categorical variables, respectively. The Pearson correlation coefficient was calculated to assess the association between DAT availability and autonomic dysfunction severity, as assessed according to the CASS. Bonferroni correction was used for multiple comparison corrections. Statistical analyses were performed using the SPSS (version 23.0; IBM Corp, Armonk, NY), and results with a 2-tailed P value of less than 0.05 were considered statistically significant.
Baseline Clinical Characteristics and Autonomic Function Test
The baseline clinical characteristics and results of the comprehensive autonomic function tests are summarized in Table 1. Patients in the PD-AUT+ group were older and exhibited more severe parkinsonian motor signs than those in the PD-AUT− group (P = 0.008 and P = 0.034, respectively). The PD-AUT+ group also had lower CCSIT scores (P = 0.015), lower K-MMSE scores (P = 0.022), and a higher frequency of RBD (P < 0.001). No significant differences were observed in sex, PD duration, years of education, BDI scores, or vascular risk factors between the groups. The PD-AUT+ group exhibited greater autonomic deficits than the PD-AUT− group based on laboratory assessment. Similarly, the autonomic abnormalities determined according to the CASS were also more severe in the PD-AUT+ group (total CASS, 5.39 ± 1.43) than in the PD-AUT− group (1.64 ± 1.09, P < 0.001).
Striatal DAT Availability of the PD-AUT+ and PD-AUT− Groups (Late-Phase Analyses)
Compared with the PD-AUT− group, the PD-AUT+ group exhibited greater decreases in DAT availability in the whole striatum as well as in all subregions of the striatum (Table 2, Fig. 1). In correlation analysis, the total CASS was significantly associated with DAT availability in the whole striatum (γ = −0.374, P = 0.001) and all striatal subregions (Table 3). In analysis of individual autonomic components, the subscores of the adrenergic component were also correlated with DAT availability in all striatal subregions. The subscores of the cardiovagal component were negatively correlated with DAT availability in the caudate and ventral striatum (P < 0.05), and a trend toward a negative correlation with DAT availability in the putamen was also observed. However, no significant correlations were observed between the subscores of the sudomotor component and striatal DAT availability (Table 3).
Regional Cerebral Perfusion Patterns of the PD-AUT+ and PD-AUT− Groups (Early-Phase Analyses)
Compared with the healthy control group, the PD-AUT− group exhibited increased regional uptake in the cerebellum and superior frontal areas (Fig. 2A) and decreased regional uptake in the cerebellar and temporo-parieto-occipital cortices, midbrain, and putamen (Fig. 2B), whereas the PD-AUT+ group exhibited increased regional uptake in pontocerebellar, superior frontal, and primary motor areas (Fig. 2C), and decreased regional uptake in the temporo-parieto-occipital areas and putamen (Fig. 2D). In a direct comparison, the PD-AUT+ group exhibited decreased regional uptake in the parieto-occipital areas (Fig. 2E) and increased regional uptake in the pallido-thalamic, pontocerebellar, inferior frontal, and primary motor areas (Fig. 2F) compared with the PD-AUT− group.
Cortical Thickness Analyses
There were no regions of different cortical thickness between the PD-AUT+ and PD-AUT− groups (clusterwise corrected P value less than 0.05; data not shown).
In this study, we investigated the association between autonomic dysfunction and striatal dopamine depletion or cerebral perfusion changes in patients with de novo PD. The major findings were as follows. First, the PD-AUT+ group was older and had higher UPDRS-III scores, lower CCSIT scores, and a higher frequency of RBD than the PD-AUT− group. Second, the PD-AUT+ group exhibited greater decreases in DAT availability in all striatal subregions. Third, striatal DAT availability was negatively correlated with both the total CASS and the adrenergic subscores. Cardiovagal subscores also tended to correlate with striatal DAT availability, whereas sudomotor subscores did not. Finally, the PD-AUT+ group exhibited more prominent PD-related perfusion alterations relative to the PD-AUT− group on early-phase 18F-FP-CIT PET images. These findings suggest that autonomic dysfunction is closely linked to a greater nigrostriatal dopamine depletion and PD-related alterations of cerebral perfusion in patients with de novo PD.
In the present study, we found that more severe striatal dopamine depletion was observed throughout the sensorimotor striatum as well as the associative and limbic striatum rather than in a region-specific pattern in the PD-AUT+ group. In addition, the group with autonomic dysfunction had an older age of onset, a higher frequency of RBD, lower CCSIT scores, and lower K-MMSE scores, thus reflecting a higher nonmotor burden. Ample evidence has suggested an association between dysautonomia and various motor and nonmotor features in PD,31–35 and the presence of these features together (eg, autonomic dysfunction as well as cognitive impairment, psychotic symptoms, depression, daytime sleepiness, and axial symptoms36) reflects more advanced disease. Moreover, early dysautonomia has been suggested as a poor prognostic factor regarding rapid motor decline32,37 and the future development of dementia in PD.38 The results of our study support the findings of previous neuroimaging studies, suggesting that the presence of dysautonomia in de novo PD may reflect severe nigral pathology and functional or structural alterations in cerebral white matter and cortices.6,8,39 Accordingly, the pathological conditions underlying autonomic dysfunction may synergistically and more extensively modulate the neurodegenerative process,40 resulting in the progression of additional nonmotor manifestations.
In our study, we also found that the severity of striatal dopamine depletion was significantly correlated with the severity of cardiovagal and adrenergic dysfunction. Because cardiovagal and adrenergic functions reflect both the central and peripheral autonomic systems,16,41 whereas sudomotor function assessed using the Quantitative Sudomotor Axon Reflex Test reflects only the peripheral autonomic system,42 our finding suggests that the severity of striatal dopamine depletion is associated with degeneration in the central autonomic nervous system in early PD patients. A recent cross-sectional study showed that the degree of dysautonomia was correlated with the Hoehn-Yahr stage and UPDRS-III score in patients with PD, suggesting a relationship between dysautonomia and the severity of parkinsonian motor symptoms.31 In that study, cardiovascular function was correlated according to the progression of motor function, whereas sudomotor function did not predict the advanced stage or severe motor symptoms. Another study found that nigral degeneration was unrelated to cardiac sympathetic denervation.43 Collectively, these findings indicate that even though dysfunction in the central and peripheral autonomic systems is observed in early PD patients, only central dysautonomia would be closely coupled with the degree of nigral pathology and disease severity.
Some evidence has suggested that the early phase of 18F-FP-CIT PET may reflect regional cerebral perfusion, which is well-coupled to cerebral metabolism, especially in dopamine-poor brain regions,10,11,44 and thus can provide complementary 18F-FDG PET-like information.11 Therefore, the functional abnormalities or metabolic network changes associated with the neurodegenerative process of PD, involving cortico-striato-pallido-thalamo-cortical loops and related pathways,45 can be assessed using early-phase 18F-FP-CIT PET data. Several functional imaging studies have reported a specific abnormal spatial covariance pattern in PD,46 namely, the PD-related pattern (PDRP), which is characterized by increased pallidothalamic and pontocerebellar metabolic activity associated with reductions in parieto-occipital regions.47 In this study, the PD-AUT+ group exhibited early-phase 18F-FP-CIT uptake of more prominent PDRP compared with the PD-AUT− group without any difference in cortical thickness between the groups. Generally, the PDRP expression has been known to correlate with the cross-sectional disease severity and UPDRS motor scores,47–50 as well as the longitudinal disease progression measured by striatal DAT availability and parkinsonian motor ratings.48 In this regard, our findings imply that the presence of dysautonomia would be closely linked to a greater pathological burden in PD, which may be a functional and neuroanatomical basis for the poor prognosis of PD patients with autonomic dysfunction.
This study had some limitations. First, due to the lack of a standard measurement to assess the severity of autonomic dysfunction in patients with PD, the CASS may not be the most appropriate assessment tool. In addition, the CASS mainly represents cardiovascular function and does not include urinary and gastrointestinal function, which are crucial features of dysautonomia in PD patients. Second, further validation is needed to use the early-phase images of 18F-FP-CIT PET as an imaging modality providing complementary 18F-FDG-like information.11 Lastly, this study was cross-sectional, thereby, limiting conclusions regarding the value of dysautonomia as a predictor of prognosis related to disease severity.
In conclusion, the results of this study showed that autonomic dysfunction is closely associated with DAT availability and altered metabolic activity, while providing evidence for a direct relationship between dysautonomia and pathological burden in patients with PD.
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