Background & Objective
Pain is a common non-motor symptom in Parkinson’s disease. As dopaminergic dysfunction is suggested to affect intrinsic nociceptive processing, this study was designed to characterize laser-induced pain processing in early-stage Parkinson’s disease patients in the dopaminergic OFF state, using a multimodal experimental approach at behavioral, autonomic, imaging levels.
13 right-handed early-stage Parkinson’s disease patients without cognitive or sensory impairment were investigated OFF medication, along with 13 age-matched healthy control subjects. Measurements included warmth perception thresholds, heat pain thresholds, and central pain processing with event-related functional magnetic resonance imaging (erfMRI) during laser-induced pain stimulation at lower (E = 440 mJ) and higher (E = 640 mJ) target energies. Additionally, electrodermal activity was characterized during delivery of 60 randomized pain stimuli ranging from 440 mJ to 640 mJ, along with evaluation of subjective pain ratings on a visual analogue scale.
No significant differences in warmth perception thresholds, heat pain thresholds, electrodermal activity and subjective pain ratings were found between Parkinson’s disease patients and controls, and erfMRI revealed a generally comparable activation pattern induced by laser-pain stimuli in brain areas belonging to the central pain matrix. However, relatively reduced deactivation was found in Parkinson’s disease patients in posterior regions of the default mode network, notably the precuneus and the posterior cingulate cortex.
Our data during pain processing extend previous findings suggesting default mode network dysfunction in Parkinson’s disease. On the other hand, they argue against a genuine pain-specific processing abnormality in early-stage Parkinson’s disease. Future studies are now required using similar multimodal experimental designs to examine pain processing in more advanced stages of Parkinson’s disease.
Citation: Petschow C, Scheef L, Paus S, Zimmermann N, Schild HH, Klockgether T, et al. (2016) Central Pain Processing in Early-Stage Parkinson's Disease: A Laser Pain fMRI Study. PLoS ONE 11(10): e0164607. https://doi.org/10.1371/journal.pone.0164607
Editor: Oscar Arias-Carrion, Hospital General Dr. Manuel Gea Gonzalez, MEXICO
Received: May 4, 2016; Accepted: September 28, 2016; Published: October 24, 2016
Copyright: © 2016 Petschow et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Ethical permission for public sharing of the anonymized fMRI and behavioral data was not part of our existing ethical permission of the study. Data are available upon request. Data can be obtained by a request to Professor H. Boecker (email@example.com).
Funding: C. Petschow received research support from the BONFOR SciMed-Promotionsstipendium of the university of Bonn. L. Scheef has no relevant financial relationships with commercial interest to disclosure. S. Paus is an employer of the University Clinic of Bonn. He has received research grants from Ipsen Pharma and Merz Pharmaceuticals. He is a member of the Advisory Boards of Allergan, Ipsen Pharma and Merz Pharmaceuticals. He has received lecturer fees from Allergan, Ipsen Pharma and Merz Pharmaceuticals. N. Zimmermann has no relevant financial relationships with commercial interest to disclosure. H. Schild has received funding from the Deutsche Forschungsgemeinschaft and the Bundesministerium für Bildung und Forschung (BMBF). T. Klockgether receives/has received research support from the Deutsche Forschungsgemeinschaft (DFG), the Bundesministerium für Bildung und Forschung (BMBF), the Robert Bosch Foundation and the European Union (EU). He serves on the editorial board of The Cerebellum. He has received a consulting fee from ICON Clinical Research. H. Boecker receives/has received research support from the Deutsche Forschungsgemeinschaft (DFG) and the Bundesministerium für Bildung und Forschung (BMBF). He has received a lecturer fee from the National Paralympic Committee Germany and royalties from Springer, NY.
Competing interests: C. Petschow received research support from the BONFOR SciMed-Promotionsstipendium of the university of Bonn. L. Scheef has no relevant financial relationships with commercial interest to disclosure. S. Paus is an employer of the University Clinic of Bonn. He has received research grants from Ipsen Pharma and Merz Pharmaceuticals. He is a member of the Advisory Boards of Allergan, Ipsen Pharma and Merz Pharmaceuticals. He has received lecturer fees from Allergan, Ipsen Pharma and Merz Pharmaceuticals. N. Zimmermann has no relevant financial relationships with commercial interest to disclosure. H. Schild has received funding from the Deutsche Forschungsgemeinschaft and the Bundesministerium für Bildung und Forschung (BMBF). T. Klockgether receives/has received research support from the Deutsche Forschungsgemeinschaft (DFG), the Bundesministerium für Bildung und Forschung (BMBF), the Robert Bosch Foundation and the European Union (EU). He serves on the editorial board of The Cerebellum. He has received a consulting fee from ICON Clinical Research. H. Boecker receives/has received research support from the Deutsche Forschungsgemeinschaft (DFG) and the Bundesministerium fu?r Bildung und Forschung (BMBF). He has received a lecturer fee from the National Paralympic Committee Germany and royalties from Springer, NY. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Parkinson’s disease (PD) is a neurodegenerative disorder causing progressive deterioration of motor function . So-called ‘non-motor symptoms’ [2–6] are nowadays increasingly recognized as integral components of PD, including cognitive , mood , autonomic , and sleep [10,11] disturbances. Although pain symptoms are less widely appreciated as non-motor manifestations of PD, already the original description of ‘the shaking palsy’ by James Parkinson identified pain as part of the clinical symptomatology, often occurring as one of the first signs at disease onset . Pain in PD is under recognized and undertreated , affecting roughly 40–60% of PD patients [5,6,13–19], and is linked to depression, decreased quality of life , female gender, age, disease duration and severity . According to Ford , pain in PD can be differentiated into: (i) musculoskeletal pain, (ii) radicular, or neuropathic pain, (iii) dystonia-related pain, (iv) akathitic discomfort, and (v) primary, or central parkinsonian pain. A study involving 176 home-living PD patients  found elevated pain levels on the ‘Bodily Pain Scale’, with musculoskeletal pain making up 70%, followed by dystonic pain (40%), radicular-neuropathic pain (20%), and central neuropathic pain (10%).
The concept of ‘primary parkinsonian pain’ independent of PD motor symptoms was initially outlined by Souques in 1921 describing bizarre stabbing and burning sensations . It is understood as a primary dysfunction of central pain pathways and is attributed to central dopamine loss, as it occurs frequently in untreated patients or during “OFF” periods, and is modifiable by dopamine substitution . Schestatsky et al. provided a neurophysiological characterization in nine PD patients with primary central pain, as compared to 9 PD patients without pain, and 9 healthy control subjects . PD patients with primary central pain had lower heat pain and laser pinprick thresholds, higher laser-evoked pain amplitudes, and less habituation of the laser-induced sudomotor skin responses than PD patients without pain and control subjects . Abnormalities in pain processing were attenuated after L-Dopa substitution , implicating ‘primary parkinsonian pain’ to be a direct consequence of the hypodopaminergic state in PD. Likewise, pain in PD can be provoked by dopamine agonist withdrawal .
The neuronal mechanisms mediating pain processing in PD are as yet not well understood. Functional neuroimaging has been relevant for delineating central mechanisms underlying motor [25–28] and cognitive [29–31] disturbances in PD. More recent imaging research has also focused on non-motor sensory aspects [32,33] of the pathophysiological spectrum (for review see: ). Central pain processing in PD has, however, exclusively been addressed by one previous positron emission tomography (PET) H215O activation study. Brefel-Courbon et al. compared pain thresholds before and after administration of levodopa in nine PD patients and nine controls, along with cerebral activity during experimental nociceptive stimulation . In the OFF, pain thresholds were significantly lower than in the control cohort, but levodopa medication raised these thresholds significantly. The OFF was associated with relatively increased pain-evoked activation of the insula, prefrontal cortex and anterior cingulate cortex, which was attenuated by L-dopa treatment. These examinations in a rather small cohort provided interesting first indications that L-dopa administration modulates pain responses and pain thresholds in PD . A major limitation, however, is the very liberal level of significance (p < 0.01, uncorrected), questioning the general validity and reproducibility of the reported findings. Also, the authors did not test for the presence of Parkinson-associated neuropathies , which may affect the propagation of standardized nociceptive stimuli into the parkinsonian brain, hence, introducing variance of peripheral, rather than central origin.
Here, we intended to resolve the above mentioned ambiguities, (i) by excluding patients with polyneuropathy, (ii) by using event-related functional magnetic resonance imaging (fMRI) with its intrinsically higher spatial resolution compared to PET, (iii) by applying conservative statistical thresholds, (iv) by combining imaging with standardized heat pain threshold measurements, psychophysiological pain intensity ratings, and skin-conductance measurements. We focused exclusively on OFF state examinations, as we primarily conceived to trace potential abnormalities of central pain processing in PD patients, using a multilevel experimental approach.
In a telephone call subjects were informed about study objective as well as procedure and were interviewed about exclusion criteria which were psychotropic substance abuse, medication affecting pain perception, psychiatric disorders, diabetes mellitus, and evidence of peripheral neuropathy. At a first visit interested subjects were informed about the study procedure again. After subjects gave a first written informed consent for pretests they underwent an electroneurographic polyneuropathy screening.
We screened a total of N = 83 persons (N = 43 PD; N = 40 healthy controls) for potential enrollment into the study and had to rule out four cases with preexisting claustrophobia, seven cases with severe psychiatric disorders, two cases with tinnitus, six cases with missing interest in finally participating in the study, and two cases with metallic implants. Of these, another 10 PD patients and 9 healthy controls had to be excluded because of peripheral neuropathy evidenced in the electrophysiological workup. 6 PD patients and 7 healthy controls withdrew participation during different recruitment stages.
After screening, 15 healthy controls (HC) and 15 patients with the clinical diagnosis of idiopathic PD according to the diagnostic criteria of the UK-Parkinson’s Diseases Society Brain-Bank  could be enrolled. All subjects gave a second written informed consent to the study examinations. One PD patient and one healthy control had to be excluded after enrollment in the MRI study due to claustrophobia (2). Incidental MRI findings were found in one further PD and one further HC, resulting in a total sample with complete and analyzable data of 13 HC (four female, nine male, mean age 54.46 ± 9.60 years) and 13 PD (four female, nine male, mean age 48.62 ± 5.85 years; for clinical details see Table 1). All subjects were right-handed . At a second visit subjects took part in the following study procedure (Fig 1). Patients were studied after > 12 hours overnight treatment withdrawal.
Subject recruitment included a first telephone interview and was followed by a first visit for an electroneurographic polyneuropathy screening. At a second visit enrolled subjects underwent the experimental pain study, consisting of psychological questionnaires, clinical tests, quantitative sensory testing, event related fMRI, and behavioral pain testings.
The study was approved by the local Ethics Committee of the University Hospital of Bonn, Germany (reference number 115/11). All participants gave written informed consent and were recruited between November 2012 and October 2014.
Psychological questionnaires and clinical tests
Psychological and clinical tests included Beck Depression Inventory (BDI-II) , Mini International Neuropsychiatric Interview (MINI) , Mini-Mental State Examination (MMSE) , German vocabulary test (Wortschatztest, WST)  and State-Trait Anxiety Inventory (STAI) . PD patients were clinically examined using the Unified Parkinson’s Disease Rating Scale (UPDRS)  and the Hoehn & Yahr Scale  in the OFF state. Disease specific cognitive deficits were evaluated using the Parkinson Neuropsychometric Dementia Assessment (PANDA) .
Group differences of normally distributed values (age, STAI-state, WST) were compared by two-sample t-tests, whereas group differences of values that were not normally distributed (distribution skewed, Shapiro-Wilk-Test: p < 0.01) were tested nonparametrically by the Mann-Whitney U test (BDI, EHI, MMSE). Statistical analysis was performed with SPSS Statistics 22 (IBM, USA) and values are presented as mean ± standard deviation. Statistical significance was considered at a threshold of p < 0.05.
Pain and sensory threshold recordings
Individual warmth perception thresholds (WPT) and heat pain thresholds (HPT) were examined with the Medoc TSA-II (Medoc, Ramat. Yishai, Israel) thermal pain stimulation device (“ascending methods of limits” option; starting temperature 32°C, rise time 0.5°C/s). Warmth sensation was induced by a 9 cm2 Peltier thermode, centered on right volar forearm. For WPT, subjects signaled the first-time warmth sensation by a button press. For HPT, subjects signaled the first-time pain sensation. Subjects were familiarized with the procedure performing three test trials, the five following main trials were averaged to determine the individual WPT and HPT [47,48].
According to published implementations of laser heat pain stimulation in fMRI [49–51], a “Low Pain” laser stimulus with lower energy (LPS, E = 440 mJ) and a “High Pain” laser stimulus with higher energy (HPS, E = 640 mJ) were applied to right foot dorsum by a Thulium(Tm)-YAG-Laser (THEMIS, StarMedTec GmbH, Starnberg, Germany). After each stimulus, the application unit was moved about 1 cm within a 3 x 3 cm surface. First, 3 LPS and 3 HPS were applied outside the scanner to familiarize subjects with the pain stimulation. The perceived pain intensity of each test stimulus was evaluated on a 10 cm visual analogue scale (VAS, 0 cm “no pain”, 10 cm “most severe imaginable pain”). VAS values of the 3 LPS and 3 HPS were averaged as a measure of individually perceived pain intensity during application of test stimuli. During fMRI, subjects received 40 LPS in a first session, followed by 30 HPS in a second session. This approach was chosen to minimize uncertainty and associated expectation effects for upcoming painful stimuli. The interstimulus interval was randomized between 10 s to 20 s (mean LPS session 15.59 s, mean HPS session 15.43 s). Stimulus evaluation was not implemented in the fMRI paradigm to minimize cognitive influences on the imaging data.
FMRI acquisition, preprocessing, and analysis
MRI was performed on a 3T scanner (Ingenia, Philips, Best, The Netherlands) equipped with an 8-channel SENSE head coil. T2*-weighted echo planar imaging (EPI) sequences were acquired (repetition time (TR) = 2595 ms, echo time (TE) = 35 ms, flip angle = 90°, field of view (FOV) = 230 x 230 x 147mm3, voxel size = 3.6 x 3.6 x 3.6 mm3, 41 axial slices in interleaved ascending mode). Scan duration was 11 min 7 s (LPS session) and 8 min 5 s (HPS session), resulting in 250 LPS and 180 HPS volumes per subject. This difference arose from piloting data which indicated lower skin conductance response (SCR) detection rates for LP compared to HP stimulation. In this data, an SCR could be measured in 80% of the applied LPS and in 100% of the applied HPS. Accordingly, LP stimuli number was adapted (40 low pain stimuli vs. 30 high pain stimuli). A high-resolution T1-weighted 3D-MPRAGE sequence (TI = 1300 ms, TR = 7.7 ms, TE = 3.9 ms, flip angle = 15°; FOV = 256 × 256 × 180 mm3, isotropic voxel resolution = 1 × 1 × 1 mm3, 180 slices, duration: 4 min 39 s) was acquired for anatomical reference and spatial normalization. The overall scanning duration including additional sequences (resting brain: 11 min 7 s, 3D-T2: 6 min 3 s, FLAIR: 5 min 31 s, and DTI: 8 min 38 s) was 55 min 10 s.
Preprocessing and analysis were performed with SPM8 (Wellcome Department of Imaging Neuroscience, London, UK) including slice-timing correction, realignment to the first volume, spatial normalization and smoothing (8 x 8 x 8 mm3). Exclusion criteria for imaging data were translational movements above the half-voxel resolution. However, no imaging data had to be excluded for movement artifacts. The first level design matrix consisted of the pain stimulation onsets convolved with the canonical hrf as implemented in SPM8 and six motion regressor derived from the realignment as nuisance factors. Both sessions (session 1: LPS, session 2: HPS) were in one model as separate sessions. The two contrast images contained the statistical effects of pain against baseline (LPS and HPS) and were used for further analysis at second level. Per group main pain effects of LPS and HPS were analyzed by use of a one-sample t-test. Between-group analysis was performed with a two-sample t-test for LPS and HPS condition separately. Statistical significance was considered for voxels exceeding a threshold of p < 0.05 (corrected for family wise errors at cluster level). Significant activations were localized using SPM Anatomy Toolbox Version 2.0  and MRIcron (Version 6.6.2013, Chris Rorden, www.mricro.com).
Subjects were instructed to evaluate 60 laser-pain stimuli on a VAS. In total, 10 x 6 randomized laser heat pain stimuli with an energy of 440 mJ (LPS), 480 mJ, 520 mJ, 560 mJ, 600 mJ and 640 mJ (HPS) were applied to the right foot dorsum with an varying interstimulus interval (ISI) between 10 s to 20 s (mean ISI 16.1 s). During the ISI an evaluation of the pain stimuli followed using a VAS. VAS values were averaged for each of the six different pain stimuli. Group differences between the not normally distributed values of VAS (distribution skewed, Shapiro-Wilk-Test: p < 0.001) were investigated nonparametrically by the Mann-Whitney U test. Intra-group differences of VAS values were tested with the Friedman test plus post hoc testing. Linear correlations between target energy and VAS values were investigated by Spearman’s correlation coefficient.
During the behavioral assessment, we simultaneously acquired the SCR . Ag/AgCl electrodes (BIOPAC Systems, Inc.) were attached to the palmar index and the middle finger of the left hand. Data was acquired with the data acquisition unit MP150 (BIOPAC Systems, Inc.). Electrodermal Activity (EDA) was recorded in DC mode (gain 5 μmho/V, low pass filter 1 Hz, sampling rate 100 Hz) and processed with AcqKnowledge Version 4.1 (BIOPAC Systems, Inc.) using the “Event-related EDA Analysis” option (high-pass filter of 0.05 Hz). SCR amplitudes were defined as the difference between maximum and baseline responses within a time window of 1–4 s after stimulus onset and rise times of 1–3 s . Data was transformed logarithmically. SCR magnitudes were estimated for each of the six pain stimuli and standardized by z-transformation.
Group differences concerning standardized SCR magnitudes were compared by two-sample t-tests. Intra-group differences of SCR-magnitudes were tested by a one-way analysis of variance (ANOVA) with repeated measures and Bonferroni corrected post hoc tests. Linear correlations between target energy and SCR magnitude were investigated by Pearson’s correlation coefficient.
One PD patient and one control subject were excluded from EDA analysis due to artificial EDA data.
Clinical and neuropsychological characterization
None of the participants showed results indicating psychiatric diseases (MINI). MMSE results of both groups showed no cognitive deficits (score ≥ 27 points) or significant group differences regarding cognitive capacity (PD: 29.38 ± 0.96 points; HC: 29.77 ± 0.44 points; U = 68.50, p = 0.418).
Significant group differences were observed for BDI-II, STAI-state and WST. PD had significantly higher scores in BDI (PD: 5.62 ± 3.45 points, range 0–11 points; HC: 1.46 ± 1.85 points, range 0–6 points; U = 143.5, p = 0.002), STAI-state (PD: 35.85 ± 8.09 points; HC: 26.85 ± 4.36 points, t(24) = 3.53, p = 0.002), and significantly lower scores in WST (PD: 103.15 ± 11.10 points; HC: 112.46 ± 11.04 points; t(24) = -2.14, p = 0.042).
The PANDA test yielded consistent results, both for cognition and mood (Table 1). Although one PD patient showed a score of 14 points at the threshold level (PANDA cognition part), the subject was not excluded due to a normal MMSE score. To consider possible effects of increased situational anxiety and different mood states, we performed additional fMRI models with BDI and STAI-state scores as covariates at the second level.
Warmth perception and thermal heat pain threshold
Temperatures of WPT and HPT did not differ significantly between PD and HC (WPTPD: 33.83 ± 1.02°C vs. WPTHC: 34.01 ± 1.65°C, t(24) = -0.33, p = 0.741; HPTPD: 44.71 ± 1.91°C vs. HPTHC: 45.97 ± 1.40°C, t(24) = -1.93, p = 0.066).
Evaluation of laser stimuli with different target energies
The evaluation of the pain stimuli with six different target energies (each applied 10 times) didn’t result in significant group differences of VAS values (Table 2). In both groups, post hoc tests showed that HPS was evaluated by significant higher VAS values than LPS (PD: p < 0.001; HC: p < 0.001). Target energy and VAS values were significantly correlated (PD: rs = 0.60, p < 0.001; HC: rs = 0.63, p < 0.001). The correlation between target energy and VAS values was not significantly different between PD and HC (p = 0.795).
Electrodermal measurements did not result in significant group differences of standardized SCR magnitudes (Table 2). The different target energies yielded significantly different standardized SCR magnitudes (Table 2). In both groups, post hoc tests showed that HPS led to significant higher standardized SCR magnitudes than LPS (PD: p < 0.001; HC: p < 0.025). Target energy and standardized SCR magnitudes were significantly correlated (PD: r = 0.77, p < 0.001; HC: r = 0.64, p < 0.001) and showed a linear relationship (PD: r2 = 0.59, y = -5.53 + 0.01x; HC: r2 = 0.41, y = -4.59 + 8.5·10-3x). The correlation between target energy and SCR magnitudes was not significantly different between PD and HC (p = 0.125).
Central pain activation in PD patients (OFF state) and in healthy controls.
For LPS, PD patients showed significant activation (p < 0.05, FWE cluster corrected) in ipsilateral supplementary motor cortex (SMA), bilateral in parietal operculum/secondary somatosensory cortex (S2) (contralateral: OP1-4; ipsilateral: OP4) (LPSPD > baseline), mesial cingulate cortex (MCC), and contralateral insula (Ig1, Ig2) (Fig 2A, Table 3). For LPS, control subjects showed significant activations (p < 0.05, FWE cluster corrected) in parietal operculum/S2 (contralateral: OP1, OP3, OP4; ipsilateral: OP1, OP3), inferior parietal cortex (contralateral: PFcm, PFop; ipsilateral: PFcm, PFop), and in primarily contralateral SMA (LPSHC > baseline) (Fig 2B, Table 4).
Central activation (p < 0.05, FWE cluster corrected) in early-stage PD patients (A, C) and healthy controls (B, D) for the LPS (A, B) and HPS (C, D) condition. For activated regions see also Table 3 and Table 4. HC: healthy controls, HPS: high pain laser stimulus with higher target energy (E = 600 mJ), LPS: low pain laser stimulus with lower target energy (E = 440 mJ), PD: patients with early-stage Parkinson’s disease in OFF state.
For HPS, PD patients showed significant activations (p < 0.05, FWE cluster corrected) in parietal inferior lobule (PFcm, PFm, PFop, PFt), parietal operculum/S2 (OP1-4), SMA, mesial cingulate cortex, and in the insula (contralateral: Ig2, Id; ipsilateral: Ig1, Ig2, Id1) (HPSPD > baseline). Additional bilateral activation was observed in superior parietal lobule/precuneus (5m, 5l, 5Ci), anterior and posterior cingulate cortex (ACC, PCC), and in thalamus (Fig 2C, Table 3). For HPS, control subjects showed significant bilateral activation (p < 0.05, FWE cluster corrected) in parietal operculum/S2 (contralateral: OP1-4; ipsilateral: OP1, OP4), inferior parietal cortex (contralateral: PFcm, PFop, PFt; ipsilateral: PFcm, PFm, PFop, PFt), SMA, and insula (Ig1, Ig2) (Fig 2D, Table 4).
Between group comparison: PD patients (OFF state) vs. healthy controls.
For LPS, the between group comparison of activation in PD patients and healthy controls (contrasts: LPSPD > LPSHC, LPSHC > LPSPD) did not reveal any significant differences. On the contrary, the between group comparison for HPS (contrasts: HPSPD > HPSHC, HPSHC > HPSPD) showed increased activations (p < 0.05, FWE cluster corrected) in precuneus and PCC in PD patients (Fig 3, Table 5). For visualization purposes and to demonstrate the full extent of the activation differences, the statistical threshold was reduced to p < 0.001, uncorrected, showing also a tendency for increased activations in ipsilateral medial frontal gyrus and thalamus bilaterally. Hence, relatively increased activations in PD were localized in regions of the default mode network (DMN), containing medial prefrontal cortex (mPFC), PCC, precuneus, lateral parietal cortex and medial temporal cortex [55,56]. To test whether these effects were driven by BDI or STAI-state values, a regression analysis was performed in the PD group (p < 0.001, uncorrected). This analysis found no indication that the precuneus/PCC activation is driven by the covariates BDI plus STAI-state.
Increased central activation (p < 0.05, FWE cluster corrected) for the high laser pain condition (HPS, target energy E = 600 mJ) in patients with early-staged Parkinson’s disease (PD, OFF state) vs. healthy control subjects (HC) in posterior cingulate cortex (A) and precuneus (B). Trend activation (p < 0.001, uncorrected) in ipsilateral medial frontal gyrus (C) and bilateral thalamus (D).
This is the first study investigating central pain perception in PD using a multimodal experimental approach, notably at behavioral, autonomic, and imaging levels. No significant differences in WPT, HPT, EDA and subjective pain ratings were found between early-stage PD patients and controls, and erfMRI revealed a generally comparable activation pattern in brain areas belonging to the central pain matrix. Relatively reduced deactivation was found in PD in posterior regions of the DMN, notably the precuneus and the posterior cingulate cortex. In the following the results are discussed at the peripheral and central levels.
Peripheral pain perception in PD
When investigating pain discrimination in PD, careful clinical assessments are essential to account for the elevated prevalence of pain [16,57,58], and the association of chronic pain, depression and anxiety disorders in PD [59–63]. Therefore, we enrolled exclusively PD patients without chronic pain or psychiatric diseases, minimizing secondary effects on pain perception. Although our PD patients showed higher BDI scores and state anxiety values, we didn’t observe significant group differences concerning warmth perception thresholds, heat pain thresholds, laser-induced pain perception or electrodermal measurements. Thus, we assume a negligible effect of these parameters on sensory discriminative levels of pain perception.
Compared to HC, our behavioral investigations revealed unaltered warmth and thermal heat pain thresholds, and comparable laser-induced cutaneous pain perception in early-stage PD patients tested in the OFF state. We thus assume comparable peripheral sensory and nociceptive transmission, a claim further strengthened by electrophysiological exclusion of peripheral neuropathy. Thus, while our results support former reports of unaltered warmth perception thresholds in PD , we couldn’t confirm previous work reporting decreased pain thresholds [35,64–67] and, thus, found no support for a modified sensory discriminative pain perception in early-stage PD. Indeed, the literature on altered sensory discriminative pain perception is highly inconsistent [36,68,69]. This might be explained to some extent by patient selection differences (e.g. disease stage, presence of chronic pain, pharmacological treatment, etc.). For instance, associations between decreased pain thresholds and severity of motor symptoms indicate that pain in PD might be triggered by rigidity or bradykinesia . In addition, neuropathological deficits at the level of peripheral nerves could have affected pain perception, as the presence of peripheral sensory dysfunction wasn’t systematically ruled out in all of the mentioned studies. Finally, variable test methods including a wide range of stimulus modalities (e.g. thermic, electric, or laser-induced), stimulus localizations (e.g. upper vs. lower extremities) and stimulus durations (< 1 ms to 90 s) might explain the mentioned inconsistencies in the literature.
Our electrodermal measurements during laser-induced pain also didn’t reveal any significant group differences, suggesting unaltered autonomic response to nociception in early-stage PD patients.
Central pain activation in PD
Laser-induced nociceptive stimulation induced a pain-specific activation pattern encompassing regions of the central pain matrix (CPM) [70–74], including secondary somatosensory cortex (S2), insula, cingulate cortex and thalamus, both in PD patients and healthy controls. Besides group difference found in DMN regions, no significant group differences were observed within regions of the CPM, either in HPS or LPS pain conditions. This suggests a comparable recruitment of areas involved in sensory discriminative or affective nociceptive processing like SII [50,73,75,76] and the insula [70,72,73,77] in early-stage PD patients and controls. This finding is contrary to our study hypothesis, influenced by the hitherto only imaging study examining central pain processing in PD . Brefel-Courbon et al. reported increased activation in PD in regions involved in affective nociceptive processing (i.e. ipsilateral posterior insula, prefrontal cortex, contralateral ACC). Although these PD patients were in a more advanced clinical stage (Hoehn and Yahr stage 2.2 vs.1.27), the validity and reproducibility of these results at a very liberal statistical threshold has to be questioned . Moreover, no systematic screening for peripheral sensory dysfunction was performed , or for neuropsychological factors affecting pain sensation (e.g. depressive symptoms, situational anxiety).
Default mode network in PD
Relative increases of HPS-induced activation were observed in precuneus and PCC in the PD group. The changes reflect decreased deactivation in the PD group, as compared to HC and reinforce former imaging data showing abnormal processing of external stimuli and increased activity (resp. decreased deactivation) of the DMN in PD patients [78,79]. To our knowledge, this is the first study showing DMN dysfunction in PD patients during nociceptive processing. As both covariates did not correlate with the precuneus and PCC activation in the PD cohort, it is rather unlikely that the observed DMN effects are driven by mood or anxiety levels. Alterations of DMN activity and connectivity have also been described in states of altered cognitive processing, both in physiological aging and neurodegenerative diseases [80,81]. DMN dysfunction has been reported also in neuropsychiatric disorders like autism, schizophrenia, Alzheimer’s disease and depression [82,83].
A limiting factor of our study is the small sample size of subjects which is mainly a consequence of adherence to strict exclusion / inclusion criteria, notably using electrophysiological testing to rule out individuals with evidence of peripheral neuropathy which may influence conductance of nociceptive stimuli and affect central pain-related activation patterns. We chose these criteria for the benefit of high-quality data in homogeneous collectives with highly diminished confounding effects on pain perception.
Early-stage PD patients show abnormalities of DMN function during nociceptive processing, extending previous findings in other behavioral domains. Experimental correlates of nociceptive processing, as tested at behavioral, autonomic, imaging levels, revealed no genuine pain-specific processing abnormality in early-stage PD, after exclusion of peripheral neuropathy using electrophysiological screening. Applying similar rigorous methodological approaches, future studies are now required to examine pain processing in more advanced stages of PD.
- Conceptualization: CP LS SP HHS TK HB.
- Data curation: CP LS.
- Formal analysis: CP LS HB.
- Funding acquisition: CP HB.
- Investigation: CP LS SP NZ HB.
- Methodology: CP LS HB.
- Project administration: HB CP.
- Resources: SP NZ HHS TK HB.
- Software: CP LS.
- Supervision: HB LS.
- Validation: CP LS HB.
- Visualization: CP HB.
- Writing – original draft: CP HB.
- Writing – review & editing: LS SP NZ HHS TK HB.
- 1. Rodriguez-Oroz MC, Jahanshahi M, Krack P, Litvan I, Macias R, Bezard E, et al. Initial clinical manifestations of Parkinson’s disease: features and pathophysiological mechanisms. Lancet Neurol. 2009;8: 1128–1139. pmid:19909911
- 2. Lima MM, Martins EF, Delattre AM, Proenca MB, Mori MA, Carabelli B, et al. Motor and non-motor features of Parkinson’s disease—a review of clinical and experimental studies. CNS Neurol Disord Drug Targets. 2012;11: 439–449. pmid:22483309
- 3. Bernal-Pacheco O, Limotai N, Go CL, Fernandez HH. Nonmotor Manifestations in Parkinson Disease. Neurologist. 2012;18: 1–16. pmid:22217609
- 4. Garcia-Ruiz PJ, Chaudhuri KR, Martinez-Martin P. Non-motor symptoms of Parkinson’s disease A review…from the past. J Neurol Sci. 2014;338: 30–33. pmid:24433931
- 5. Simuni T, Sethi K. Nonmotor manifestations of Parkinson’s disease. Ann Neurol. 2009;64: 65–80.
- 6. Martinez-Martin P, Schapira AH V, Stocchi F, Sethi K, Odin P, MacPhee G, et al. Prevalence of nonmotor symptoms in Parkinson’s disease in an international setting; study using nonmotor symptoms questionnaire in 545 patients. Mov Disord. 2007;22: 1623–1629. pmid:17546669
- 7. Goldman JG, Williams-Gray C, Barker RA, Duda JE, Galvin JE. The spectrum of cognitive impairment in Lewy body diseases. Mov Disord. 2014;29: 608–621. pmid:24757110
- 8. Marsh L. Depression and Parkinson’s disease: current knowledge. Curr Neurol Neurosci Rep. 2013;13: 409. pmid:24190780
- 9. Chaudhuri KR. Autonomic dysfunction in movement disorders. Curr Opin Neurol. 2001;14: 505–511. pmid:11470968
- 10. Breen DP, Vuono R, Nawarathna U, Fisher K, Shneerson JM, Reddy AB, et al. Sleep and circadian rhythm regulation in early Parkinson disease. JAMA Neurol. 2014;71: 589–595. pmid:24687146
- 11. Neikrug AB, Avanzino JA, Liu L, Maglione JE, Natarajan L, Corey-Bloom J, et al. Parkinson’s disease and REM sleep behavior disorder result in increased non-motor symptoms. Sleep Med. 2014;15: 959–966. pmid:24938585
- 12. Parkinson J. An essay on the shaking palsy. London: Sherwood, Neely, and Jones; 1817.
- 13. Beiske AG, Loge JH, Rønningen A, Svensson E. Pain in Parkinson’s disease: Prevalence and characteristics. Pain. 2009;141: 173–177. pmid:19100686
- 14. Ford B. Pain in Parkinson’s Disease. Clin Neurosci. 1998;5: 63–72. pmid:10785830
- 15. Giuffrida R, Vingerhoets FJG, Bogousslavsky J, Ghika J. Pain in Parkinson’s disease. Rev Neurol (Paris). 2005;161: 407–418.
- 16. Borsook D. Neurological diseases and pain. Brain. 2012;135: 320–344. pmid:22067541
- 17. Lee MA, Walker RW, Hildreth TJ, Prentice WM. A Survey of Pain in Idiopathic Parkinson’s Disease. J Pain Symptom Manage. 2006;32: 462–469. pmid:17085272
- 18. Nègre-Pagès L, Regragui W, Bouhassira D, Grandjean H, Rascol O. Chronic pain in Parkinson’s disease: The cross-sectional French DoPaMiP survey. Mov Disord. 2008;23: 1361–1369. pmid:18546344
- 19. Defazio G, Berardelli A, Fabbrini G, Martino D, Fincati E, Fiaschi A, et al. Pain as a Nonmotor Symptom of Parkinson Disease: Evidence From a Case-Control Study. Arch Neurol. 2008;65: 1191–1194. pmid:18779422
- 20. Rana AQ, Kabir A, Jesudasan M, Siddiqui I, Khondker S. Pain in Parkinson’s disease: Analysis and literature review. Clin Neurol Neurosurg. 2013;115: 2313–2317. pmid:24075714
- 21. Souques M. Des douleurs dans la paralysie agitante. Rev Neurol (Paris). 1921;37: 629–633.
- 22. Juri C, Rodriguez-Oroz M, Obeso J. The pathophysiological basis of sensory disturbances in Parkinson’s disease. J Neurol Sci. Elsevier B.V.; 2010;289: 60–65. pmid:19758602
- 23. Schestatsky P, Kumru H, Valls-Solé J, Valldeoriola F, Marti MJ, Tolosa E, et al. Neurophysiologic study of central pain in patients with Parkinson disease. Neurology. 2007;69: 2162–2169. pmid:18056580
- 24. Rabinak CA, Nirenberg MJ. Dopamine agonist withdrawal syndrome in Parkinson disease. Arch Neurol. 2010;67: 58–63. pmid:20065130
- 25. Ceballos-Baumann AO. Functional imaging in Parkinson’s disease: activation studies with PET, fMRI and SPECT. J Neurol. 2003;250: i15–i23. pmid:12761630
- 26. Brooks DJ. Functional imaging studies on dopamine and motor control. J Neural Transm. 2001;108: 1283–1298. pmid:11768627
- 27. Fukuda M, Edwards C, Eidelberg D. Functional brain networks in Parkinson’s disease. Parkinsonism Relat Disord. 2001;8: 91–94. pmid:11489673
- 28. Brooks DJ. Motor disturbance and brain functional imaging in Parkinson’s disease. Eur Neurol. 1997;38: 26–32.
- 29. Christopher L, Strafella AP. Neuroimaging of brain changes associated with cognitive impairment in Parkinson’s disease. J Neuropsychol. 2013;7: 225–240. pmid:23551844
- 30. Duncan GW, Firbank MJ, O’Brien JT, Burn DJ. Magnetic resonance imaging: A biomarker for cognitive impairment in Parkinson’s disease? Mov Disord. 2013;28: 425–438. pmid:23450518
- 31. Carbon M, Marié R- M. Functional imaging of cognition in Parkinson’s disease. Curr Opin Neurol. 2003;16: 475–480. pmid:12869806
- 32. Takeda A, Saito N, Baba T, Kikuchi A, Sugeno N, Kobayashi M, et al. Functional imaging studies of hyposmia in Parkinson’s disease. J Neurol Sci. 2010;289: 36–39. pmid:19720385
- 33. Boecker H, Ceballos-Baumann A, Bartenstein P, Weindl A, Siebner HR, Fassbender T, et al. Sensory processing in Parkinson’s and Huntington's disease. Investigations with 3D H2 15O-PET. Brain. 1999;122: 1651–1665. pmid:10468505
- 34. Stoessl AJ. Functional imaging studies of non-motoric manifestations of Parkinson’s Disease. Parkinsonism Relat Disord. 2009;15 Suppl 3: S13–16. pmid:20082973
- 35. Brefel-Courbon C, Payoux P, Thalamas C, Ory F, Quelven I, Chollet F, et al. Effect of levodopa on pain threshold in Parkinson’s disease: a clinical and positron emission tomography study. Mov Disord. 2005;20: 1557–1563. pmid:16078219
- 36. Nolano M, Provitera V, Estraneo A, Selim MM, Caporaso G, Stancanelli A, et al. Sensory deficit in Parkinson’s disease: Evidence of a cutaneous denervation. Brain. 2008;131: 1903–1911. pmid:18515869
- 37. Gibb WR, Lees AJ. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1988;51: 745–752. pmid:2841426
- 38. Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971;9: 97–113. pmid:5146491
- 39. Leentjens AF, Verhey FR, Luijckx GJ, Troost J. The validity of the Beck depression inventory as a screening and diagnostic instrument for depression in patients with Parkinson’s disease. Mov Disord. 2000;15: 1221–1224. pmid:11104209
- 40. Sheehan D V, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59: 22–33.
- 41. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12: 189–198. pmid:1202204
- 42. Schmidt K-H, Metzler P. WST—Wortschatztest. Weinheim: Beltz Test GmbH; 1992.
- 43. Spielberger CD, Gorsuch RL, Lushene R, Vagg PR, Jacobs GA. Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press; 1983.
- 44. Fahn S, Elton RL. UPDRS Development Committee. The Unified Parkinson’s Disease Rating Scale. In: Fahn , Marsden CD, Calne DB, Goldstein M, editors. Recent Developments in Parkinson’s Disease. 2nd ed. Florham Park, NJ: Macmillan Healthcare Information; 1987. pp. 153–163.
- 45. Hoehn MM, Yahr MD. Parkinsonism: onset, progression, and mortality. 1967. Neurology. 1998;50: 318–334. pmid:9484345
- 46. Kalbe E, Calabrese P, Kohn N, Hilker R, Riedel O, Wittchen H- U, et al. Screening for cognitive deficits in Parkinson’s disease with the Parkinson neuropsychometric dementia assessment (PANDA) instrument. Park Relat Disord. 2008;14: 93–101.
- 47. Wagner G, Koschke M, Leuf T, Schlösser R, Bär KJ. Reduced heat pain thresholds after sad-mood induction are associated with changes in thalamic activity. Neuropsychologia. 2009;47: 980–987. pmid:19027763
- 48. Bär KJ, Greiner W, Letsch A, Köbele R, Sauer H. Influence of gender and hemispheric lateralization on heat pain perception in major depression. J Psychiatr Res. 2003;37: 345–353. pmid:12765857
- 49. Bingel U, Gläscher J, Weiller C, Büchel C. Somatotopic representation of nociceptive information in the putamen: An event-related fMRI study. Cereb Cortex. 2004;14: 1340–1345. pmid:15217895
- 50. Bingel U, Lorenz J, Glauche V, Knab R, Gläscher J, Weiller C, et al. Somatotopic organization of human somatosensory cortices for pain: A single trial fMRI study. Neuroimage. 2004;23: 224–232. pmid:15325369
- 51. Helmchen C, Mohr C, Roehl M, Bingel U, Lorenz J, Büchel C. Common neural systems for contact heat and laser pain stimulation reveal higher-level pain processing. Hum Brain Mapp. 2008;29: 1080–1091. pmid:17924552
- 52. Eickhoff SB, Paus T, Caspers S, Grosbras MH, Evans AC, Zilles K, et al. Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. Neuroimage. 2007;36: 511–521. pmid:17499520
- 53. Fowles DC, Christie MJ, Edelberg R, Grings WW, Lykken DT, Venables PH. Committee report. Publication recommendations for electrodermal measurements. Psychophysiology. 1981;18: 232–239. pmid:7291438
- 54. Dawson ME, Schell AM, Filion DL. The electrodermal system. In: Cacioppo JT, Tassinary LG, Berntson GG, editors. Handbook of Psychophysiology. 3rd ed. Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, Sao Paulo: Cambridge University Press; 2007. pp. 159–181.
- 55. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci U S A. 2001;98: 676–682. pmid:11209064
- 56. Raichle ME, Snyder AZ. A default mode of brain function: A brief history of an evolving idea. Neuroimage. 2007;37: 1083–1090. pmid:17719799
- 57. Nègre-Pagès L, Grandjean H, Lapeyre-Mestre M, Montastruc JL, Fourrier A, Lépine JP, et al. Anxious and depressive symptoms in Parkinson’s disease: the French cross-sectionnal DoPaMiP study. Mov Disord. 2010;25: 157–166. pmid:19950403
- 58. Richard IH. Anxiety disorders in Parkinson’s disease. Adv Neurol. 2005;96: 42–55. pmid:16383211
- 59. Ehrt U, Larsen JP, Aarsland D. Pain and its relationship to depression in Parkinson disease. Am J Geriatr Psychiatry. 2009;17: 269–275. pmid:19322934
- 60. Henderson R, Kurlan R, Kersun JM, Como P. Preliminary examination of the comorbidity of anxiety and depression in Parkinson’s disease. J Neuropsychiatry Clin Neurosci. 1992;4: 257–264. pmid:1498578
- 61. Nuti A, Ceravolo R, Piccinni A, Dell’Agnello G, Bellini G, Gambaccini G, et al. Psychiatric comorbidity in a population of Parkinson’s disease patients. Eur J Neurol. 2004;11: 315–320. pmid:15142224
- 62. Rutten S, Ghielen I, Vriend C, Hoogendoorn AW, Berendse HW, Leentjens AFG, et al. Anxiety in Parkinson’s disease: Symptom dimensions and overlap with depression and autonomic failure. Park Relat Disord. 2014;21: 189–193.
- 63. Yamanishi T, Tachibana H, Oguru M, Matsui K, Toda K, Okuda B, et al. Anxiety and depression in patients with Parkinson’s disease. Intern Med. 2013;52: 539–545. pmid:23448761
- 64. Djaldetti R, Shifrin A, Rogowski Z, Sprecher E, Melamed E, Yarnitsky D. Quantitative measurement of pain sensation in patients with Parkinson disease. Neurology. 2004;62: 2171–2175. pmid:15210877
- 65. Gerdelat-Mas A, Simonetta-Moreau M, Thalamas C, Ory-Magne F, Slaoui T, Rascol O, et al. Levodopa raises objective pain threshold in Parkinson’s disease: a RIII reflex study. J Neurol Neurosurg Psychiatry. 2007;78: 1140–1142. pmid:17504881
- 66. Zambito Marsala S, Tinazzi M, Vitaliani R, Recchia S, Fabris F, Marchini C, et al. Spontaneous pain, pain threshold, and pain tolerance in Parkinson’s disease. J Neurol. 2011;258: 627–633. pmid:21082324
- 67. Urakami K, Takahashi K, Matsushima E, Sano K, Nishikawa S, Takao T. The threshold of pain and neurotransmitter’s change on pain in Parkinson's disease. Jpn J Psychiatry Neurol. 1990;44: 589–593. pmid:1705999
- 68. Guieu R, Pouget J, Serratrice G. Nociceptive threshold and Parkinson disease. Rev Neurol (Paris). 1992;148: 641–644.
- 69. Tinazzi M, Del Vesco C, Defazio G, Fincati E, Smania N, Moretto G, et al. Abnormal processing of the nociceptive input in Parkinson’s disease: A study with CO2 laser evoked potentials. Pain. 2008;136: 117–124. pmid:17765400
- 70. Apkarian AV, Bushnell MC, Treede R-D, Zubieta J-K. Human brain mechanisms of pain perception and regulation in health and disease. Eur J Pain. 2005;9: 463–484. pmid:15979027
- 71. Davis KD. The neural circuitry of pain as explored with functional MRI. Neurol Res. 2000;22: 313–317. pmid:10769826
- 72. Duerden EG, Albanese MC. Localization of pain-related brain activation: A meta-analysis of neuroimaging data. Hum Brain Mapp. 2013;34: 109–149. pmid:22131304
- 73. Peyron R, Laurent B, García-Larrea L. Functional imaging of brain responses to pain. A review and meta-analysis (2000). Neurophysiol Clin. 2000;30: 263–288. pmid:11126640
- 74. Tracey I, Mantyh PW. The cerebral signature for pain perception and its modulation. Neuron. 2007;55: 377–391. pmid:17678852
- 75. Baumgärtner U, Iannetti GD, Zambreanu L, Stoeter P, Treede R-D, Tracey I. Multiple somatotopic representations of heat and mechanical pain in the operculo-insular cortex: a high-resolution fMRI study. J Neurophysiol. 2010;104: 2863–2872. pmid:20739597
- 76. Del Gratta C, Della Penna S, Ferretti A, Franciotti R, Pizzella V, Tartaro A, et al. Topographic organization of the human primary and secondary somatosensory cortices: comparison of fMRI and MEG findings. Neuroimage. 2002;17: 1373–1383. pmid:12414277
- 77. Greenspan JD, Lee RR, Lenz FA. Pain sensitivity alterations as a function of lesion location in the parasylvian cortex. Pain. 1999;81: 273–282. pmid:10431714
- 78. Delaveau P, Salgado-Pineda P, Fossati P, Witjas T, Azulay JP, Blin O. Dopaminergic modulation of the default mode network in Parkinson’s disease. Eur Neuropsychopharmacol. 2010;20: 784–792. pmid:20674286
- 79. van Eimeren T, Monchi O, Ballanger B, Strafella AP. Dysfunction of the default mode network in Parkinson disease: a functional magnetic resonance imaging study. Arch Neurol. 2009;66: 877–883. pmid:19597090
- 80. Agosta F, Pievani M, Geroldi C, Copetti M, Frisoni GB, Filippi M. Resting state fMRI in Alzheimer’s disease: Beyond the default mode network. Neurobiol Aging. 2012;33: 1564–1578. pmid:21813210
- 81. Sambataro F, Murty VP, Callicott JH, Tan HY, Das S, Weinberger DR, et al. Age-related alterations in default mode network: Impact on working memory performance. Neurobiol Aging. 2010;31: 839–852. pmid:18674847
- 82. Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJS. Default-mode brain dysfunction in mental disorders: A systematic review. Neurosci Biobehav Rev. 2009;33: 279–296. pmid:18824195
- 83. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008;1124: 1–38. pmid:18400922