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Dopamine has no direct causal role in the formation of treatment expectations and placebo analgesia in humans [1]

['Angelika Kunkel', 'Department Of Neurology', 'Center For Translational Neuro-', 'Behavioral Sciences', 'C-Tnbs', 'University Medicine Essen', 'University Duisburg-Essen', 'Essen', 'Livia Asan', 'Isabel Krüger']

Date: 2024-10

Abstract Dopamine-based reward and learning mechanisms have been suggested to contribute to placebo effects. However, the exact role of dopaminergic neurotransmission in their generation and maintenance is still unclear. This study aimed to shed light on the causal role of dopamine in establishing positive treatment expectations, as well as on the magnitude and duration of their effect on pain. To this end, we used an established placebo analgesia paradigm in combination with 2 opposing pharmacological modulations of dopaminergic tone, i.e., the dopamine antagonist sulpiride and the dopamine precursor L-dopa which were both applied in an experimental, double-blind, randomized, placebo-controlled trial with a between-subject design in N = 168 healthy volunteers. The study medication successfully altered dopaminergic tone during the conditioning procedure. Contrary to our hypotheses, the medication did not modulate the formation of positive treatment expectation and placebo analgesia tested 1 day later. Placebo analgesia was no longer detectable on day 8 after conditioning. Using a combined frequentist and Bayesian approach, our data provide strong evidence against a direct dopaminergic influence on the generation and maintenance of placebo effects. Further exploration of the neurochemical mechanisms underlying placebo analgesia remains paramount in the quest to exploit these effects for optimal treatment outcomes. Trial registration: ClinicalTrials.gov German Clinical Trials Register, ID: DRKS00029366, https://drks.de/search/en/trial/DRKS00029366.

Citation: Kunkel A, Asan L, Krüger I, Erfurt C, Ruhnau L, Caliskan EB, et al. (2024) Dopamine has no direct causal role in the formation of treatment expectations and placebo analgesia in humans. PLoS Biol 22(9): e3002772. https://doi.org/10.1371/journal.pbio.3002772 Academic Editor: Ben Seymour, University of Cambridge, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND Received: November 3, 2021; Accepted: July 29, 2024; Published: September 24, 2024



Note: As this is a Preregistered Research Article, the study design and methods were peer-reviewed before data collection. The time to acceptance includes the experimental time taken to perform the study. Learn more about Preregistered Research Articles. Copyright: © 2024 Kunkel 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: Data and code to reproduce all results are publicly shared on the Open Science Framework (OSF) (https://osf.io/f49dt/). R code and input data to perform frequentist statistics are shared, as well as the JASP file for Bayesian analyses. The complete dataset is additionally provided in Brain Imaging Data Structure (BIDS) format. The in-principle-accepted Stage 1 manuscript of this Preregistered Research Article was deposited as public registration in OSF (https://osf.io/py8b3). Funding: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, https://www.dfg.de/; Project-ID 422744262 - TRR 289, to UB; and Project ID-FU 356/12 - UMEA, to LA) and the Medical Faculty Essen and Stiftung Universitätsmedizin Essen (Project ELAN, https://www.uni-due.de/med/elan/, to IK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Abbreviations: (rm)ANOVA, (repeated measures) analysis of variance; BAS, Behavioral Activation System; BF, Bayes factor; BFI-10, 10-item-Big-Five-Inventory; BFincl, inclusion Bayes factor; BIDS, Brain Imaging Data Structure; BIS, Behavioral Inhibition System; BL, time point baseline; CTR, control; DA, dopamine; DOPA, group L-dopa; ECG, electrocardiogram; EEG, electroencephalography; EFFECT score, subscore of the GEEE for rating positive treatment effects; EXPECT score, subscore of the GEEE for rating positive treatment expectation; fMRI, functional magnetic resonance imaging; FPQ-III, Fear of Pain Questionnaire; GASE, Generic Assessment of Side Effects in Clinical Trials; GEEE, Generic rating scale for previous treatment experiences, treatment expectations, and treatment effects; HPT, heat pain threshold; INA, group inactive pill; ITI, inter-trial interval; mm, millimeter; NAc, nucleus accumbens; PA, placebo analgesia; PANAS, Positive and Negative Affect Schedule; PCS, Pain Catastrophizing Scale; PET, positron emission tomography; PLC, placebo; preCOND, time point just before conditioning; preT1, time point just before test session 1 (day 2); preT2, time point just before test session 2 (day 8); PSS-10, Perceived Stress Scale; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; SEM, standard error of the mean; SSAS, Somatosensory Amplification Scale; STADI State, State-Trait-Anxiety-Depression-Inventory State; SUL, group sulpiride; VAS, visual analogue scale; μm, micrometer

Introduction Placebo effects are an individual’s psychophysiological response to contextual information and associated expectations to treatments that are physically and pharmacologically inert. The strength of placebo effects varies considerably among and within individuals depending on contextual factors, prior experiences of treatment benefit, and expectations regarding the treatment [1,2]. The effects and mechanisms of expectation have been best characterized in the field of experimental pain and placebo analgesia (PA), i.e., the pain relief following the administration of an inert treatment and/or the expectation that a potent analgesic substance is being administered [3,4]. Experimentally, this expectation is typically generated by combining verbal suggestions and learning processes by surreptitiously lowering pain stimulus intensities during a conditioning phase. The brain systems and neurochemical pathways underlying PA have been studied extensively over the past 2 decades. Converging evidence from functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and positron emission tomography (PET) studies indicates that PA is associated with changes in nociceptive processing, including alterations at the level of the spinal cord [5], thalamus, and cortical brain areas related to nociception and pain [6–8]. However, the effect sizes of this influence on brain areas implicated in nociception are considerably smaller than their underlying behavioral effects [9]. This points towards processes other than inhibition of bottom-up nociceptive signaling and most likely involves changes in affective and evaluative mechanisms [10,11]. In line with this view, PA has been linked to both the top-down activation of descending pain modulatory pathways but also intracortical mechanisms, driven by limbic and paralimbic regions. At the neurochemical level, the endogenous opioid system has been shown to play a critical role in PA, as indicated by behavioral and fMRI studies using the opioid antagonist naloxone and PET studies using in vivo receptor binding approaches with opioidergic ligands (for review, see [7]). However, neither the engagement of descending pain modulatory pathways nor the involvement of opioids can so far fully explain PA. Instead, there is growing evidence for a role of non-opioidergic neurotransmitter systems in PA [12–14]. In particular, dopamine-based reward mechanisms appear to contribute to placebo responses [13,15–18]. A pioneering study using PET imaging found that dopamine (DA) signaling in the nucleus accumbens (NAc) increased during the anticipation of analgesia following the administration of a placebo treatment. The signal strength was proportional to the individuals’ PA response. Interestingly, PA also correlated positively with NAc activation during anticipation of monetary reward in the same individuals. Further, interindividual differences in PA have been linked to dopamine-related personality traits and gray matter density in the ventral striatum [19]. These and related findings suggest a key role for the mesolimbic reward system in PA. First efforts to elucidate the significance of dopaminergic signaling to analgesia have targeted dopaminergic neurotransmission pharmacologically during the test phase of PA paradigms. We demonstrated that blocking D2/D3 receptor activity with the antagonist haloperidol specifically reduced placebo-related activity in the striatum but did not affect the magnitude of PA at the behavioral level [14]. Similarly, in a study with patients suffering from neuropathic pain, PA was influenced neither by haloperidol nor the DA precursor L-dopa [20]. While the findings of both studies render a direct analgesic role of dopamine unlikely, they suggest an involvement of the dopaminergic system in other processes inherently linked to PA, such as the acquisition of positive treatment expectation induced by positive prior treatment experiences, or the inherent reward associated with experiencing pain relief. In this view, DA may affect PA through a modulatory influence during the learning phase of PA. We previously tested if increasing dopaminergic tone using L-dopa during the conditioning of PA could boost PA in the later test phase [10]. Although the study hints at an enhancing effect of L-dopa on the acquisition of conditioned PA, particularly in women, this finding was difficult to interpret as our experimental manipulation failed to induce robust PA independent of the dopaminergic manipulation. Strikingly, recent evidence from clinical populations suggests that the intake of L-dopa together with the non-steroidal anti-inflammatory drug naproxen can serve to prevent the transition from acute to chronic back pain [21]. The mechanistic basis of this effect could be rooted in the same principle of enhancing the reward system during the experience of analgesia, which we propose for conditioned PA. Taken together, despite clear evidence for the involvement of mesolimbic DA signaling in PA, its exact functional role and contribution to the development of positive treatment expectation and PA is still poorly understood. Deciphering the neuropharmacological foundations of PA could be of direct clinical relevance, as it enables the development of active DA-enhancing interventions to boost placebo components in pain treatments or to reduce placebo effects via DA inhibition in clinical randomized controlled trials, where they hamper the assay sensitivity to detect novel therapeutic targets. To investigate the general contribution of DA in the acquisition of positive treatment expectation and its subsequent effect on pain in a proof-of-concept manner, we employed an established experimental paradigm of conditioned PA in combination with 2 pharmacological manipulations of dopaminergic signaling in the brain using a randomized, placebo-controlled, double-blind design. We allocated N = 168 healthy participants to either receive a single dose of the D2 receptor antagonist sulpiride, the DA precursor L-dopa, or an inactive control prior to the conditioning phase of the PA paradigm. Expectation of analgesia and its effect on experimental heat pain was assessed in the conditioning session and in 2 test sessions on days 2 and 8. For statistical analyses, we applied classic frequentist statistics as well as Bayesian analyses. This hybrid approach allowed us to present well-known frequentist, p-value–based metrics to compare the results with those of previous studies and meta-analyses, and to additionally quantify the evidence using the framework of Bayesian inference, which is increasingly embraced as a method of reporting evidence in the field of neuroscience. Particularly, we implemented Bayesian parameter effect analyses to complement frequentist results for parameter significance and effect size. Further, Bayesian hypothesis testing enabled us to rate the strength of evidence in favor of or against our proposed hypotheses on a continuous scale by using the Bayes factor (BF), which allowed us to discriminate evidence of absence from absence of evidence. Combining both frequentist and Bayesian approaches is recommended as a pragmatic and powerful way to report and communicate scientific evidence [22]. In this study, we focused on 3 hypotheses (1 main and 2 exploratory hypotheses): Main hypothesis (1): Pharmacologic manipulation of DA signaling during the experience of pain relief associated with the placebo treatment in the conditioning session modulates the magnitude of PA. To address this main hypothesis, we checked for interaction effects between medication (L-dopa versus sulpiride versus inactive pill) and our experimental condition (placebo cream versus control cream) in test session 1 (day 2). Exploratory hypothesis (2): (a) PA persists up to day 8, as indicated by a significant main effect of our experimental condition (placebo cream versus control cream) on day 8. (b) Pharmacological manipulation of DA signaling during conditioning affects the persistence of PA on day 8. In this analysis, we tested the longevity of the PA in our experiment and probe putative long-term effects of the pharmacological dopaminergic modulation applied during conditioning. Exploratory hypothesis (3): DA-manipulation during conditioning alters the establishment of treatment expectation. We propose that treatment expectation is formed in a DA-dependent way during the experience of a positive treatment effect (conditioning session). We thus hypothesize that the (anti)dopaminergic medication influences the acquisition of treatment expectation during the conditioning session as measured by the change in expectation ratings before conditioning and before the test session of PA (see Fig 1B). PPT PowerPoint slide

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TIFF original image Download: Fig 1. (A) Upper panel. The experiment takes place on 3 days with the conditioning on day 1, test session 1 on day 2, and test session 2 on day 8. Participants are treated with 2 identical creams with the PLC introduced as “analgesic cream” and the CTR as inactive sensory control cream. The location of the control (gray area) and placebo (blue area) site on the left volar forearm is pseudo-randomized. Painful heat stimulus intensity levels are individualized to correspond to target ratings of 40, 60, and 80 on a 101-point VAS with endpoints marked not painful and unbearably painful. Lower panel. Trial timing. Each trial consists of 5 phases: ITI with the flanker task, anticipation phase, pain stimulus, short pause, and pain intensity rating. The ITI has a random duration of 15–25 s. The anticipation phase begins when the white crosshair turns red, indicating that a painful stimulation is about to follow. After a variable delay time, the painful heat stimulus (duration 20 s) is administered, and 3–7 s after the end of the heat stimulation participants provide pain intensity ratings using a VAS. (B) Experimental schedule. Double-blind and random allocation of participants to one of the 3 medication groups: sulpiride (SUL), L-dopa (DOPA), or inactive control (INA). Differential pharmacokinetic profiles require a staggered pill intake at 2 different time points where the SUL group takes an active pill (sulpiride 400 mg) at time point one, and the DOPA group takes an active pill (levodopa/carbidopa 100/25 mg) at time point 2. For the INA group, pills at both time points are inactive. Treatment expectation at 4 different time points (EXPECT), and efficiency ratings of the placebo manipulation (EFFECT) are measured at three time points via the GEEE. CTR, control; ITI, inter-trial interval; PLC, placebo; VAS, visual analogue scale. https://doi.org/10.1371/journal.pbio.3002772.g001

Discussion This study experimentally investigated the effect of a pharmacological manipulation targeting dopaminergic signaling on the formation of positive treatment expectations during the experience of pain relief in response to a placebo treatment. With a final sample of n = 154 participants, our study provides strong evidence against an influence of our dopamine manipulation on treatment expectations (induced by instructed and conditioned pain relief in combination with a sham treatment) and PA. Here, we critically evaluate the validity of our experimental approach, summarize the conclusions drawn from our results, and discuss implications for our understanding of the role of dopamine in placebo analgesia. Although we did not confirm the expected effects of dopamine in our experiment, and the a priori hypotheses were rejected, our data contribute to a more nuanced understanding of the neurobiology underpinning placebo analgesia which aids the characterization of the intricate interplay between cognition, neurochemistry, and treatment outcome. Critically, a series of manipulation checks and control analyses confirmed the validity of our experimental approach to test the predefined hypotheses. We found no direct analgesic effects of the study medication on heat pain sensitivity or pain ratings during conditioning, confirming previous experimental studies using pro- or antidopaminergic drugs [41,49]. A decrease in pain ratings in the placebo compared to the control condition was confirmed across all 3 medication groups, with no significant between-group differences. Notably, we successfully induced placebo analgesia during the first test session, even though testing took place 1 day after conditioning. Most previous studies have performed conditioning for PA and subsequent testing on the same day, which explains the relatively modest placebo effect observed in our paradigm compared to the literature (medium effect size of η p 2 = 0.05 in our experiment corresponding to a Cohen’s d of 0.46), whereas a Cohen’s d of 0.95 is described in the literature for conditioned PA tested on the same day [50]. Furthermore, we can assume that dopaminergic transmission was successfully altered in the SUL and DOPA group, as previous research has demonstrated reward-related behavioral and neuroimaging effects in dopamine-dependent behavior using the same agent and dosages [12,51]. Importantly, our predefined surrogate parameters for successful manipulation of dopaminergic transmission exhibited high values for serum L-dopa in the DOPA group and elevated prolactin in the SUL group, respectively. Our data could therefore not support a link between dopaminergic neurotransmission and placebo analgesia, contrary to what has been proposed previously based on a smaller correlational study [13]. Bayesian analyses confirmed that our data provide strong evidence for the absence of an effect of the pharmacological dopamine manipulation. Hence, considering the present evidence, the conceptual framework for the role of dopamine in placebo analgesia and positive treatment expectations needs to be re-evaluated and critically discussed. Dopaminergic neural activity is known to be associated with encoding prediction errors in reward learning [52]. When an unexpected reward is received, dopamine neurons increase their firing rate. Importantly, this increase in dopaminergic firing occurs not only when a reward is received, but also during the perception of a conditioned stimulus that has been associated with the impending reward through learning [53]. Applying this principle to the context of pain, the experience of pain relief can be considered a rewarding outcome. The administration of a treatment, such as an analgesic cream, could act as an external stimulus that becomes associated with pain relief through conditioning. This notion is supported by evidence demonstrating the effectiveness of conditioning in eliciting PA in experimental settings [52]. Moreover, the integration of conditioning with verbal suggestion and/or observational learning appears to enhance PA, suggesting that conditioning serves, at least in part, as an independent pathway for the establishment of PA [54]. Despite the conceptual similarities between reward learning and conditioned PA, our experiment did not reveal any effects of the dopaminergic manipulation during the learning experience on positive treatment expectations and PA. There are several potential reasons why dopamine may not have influenced PA in this case. The clear association between the placebo cream and pain relief, communicated through verbal suggestions, already creates an expectation of pain relief in the participants. In such a scenario, where participants expect pain relief with the placebo, and only experience confirmations of their expectations given the 100% contingency between the stimulus (placebo) and the outcome (reduced pain) during conditioning, it is conceivable that no relevant prediction error can form, and dopaminergic firing, which typically modulates learning through the detection of prediction errors, may not play a significant role. In addition, the 15 trials per block during conditioning may have created a ceiling effect, resulting in a high certainty of the learnt association between placebo and pain relief in all groups, leaving limited room for dopamine to exert its influence. Furthermore, previous research has shown that dopamine receptor blockade with sulpiride does not affect the learning rate in a reinforcement learning task compared to a control group. Both groups learned to choose a rewarded option at the same rate. Instead, the drug was found to lower the incentive value of the reward, with sulpiride recipients being slower to choose the reward than the controls [12]. Similarly, the dopaminergic mechanisms for PA in our study may be more pertinent to the attribution of incentive value of reward, rather than for forming predictive associations between a stimulus and a rewarding outcome. Another dopamine-dependent psychological component of reward is the “wanting” aspect, which refers to the motivation to obtain the reward [47]. Dopamine mediates the incentive salience of a reward, thereby promoting choices and behaviors that lead to obtaining the reward. Although we ensured that the applied heat stimuli were perceived as moderately painful in both test sessions, it is plausible that the participants did not develop sufficient motivation, or desire for pain relief. Additionally, the block design of the treatment conditions may have reduced the ability to desire pain relief during the placebo block, as participants were aware that successive stimuli would only occur on the “treated” site. In situations where there is high certainty of effective treatment, the level of desire may be minimal to begin with. In contrast, the experimental design used by Scott and colleagues [13,18] involved a more invasive paradigm in which hypertonic saline was infused into the masseter muscle, producing a persistent, tonic pain, and participants are instructed to expect a decrease in this tonic pain when the placebo was administered. This difference in design may have led to a greater overall desire for pain relief compared to the classic experimental heat pain placebo paradigm used in the current study. Furthermore, the paradigm used in this study did not involve an active role on the part of the participant. Both control and placebo creams were passively administered by the experimenter, and the participants were passively guided through the experiment with no active engagement with the pain stimulation or the treatment. A relationship between active behavior and the extent of pain relief as a reward has been demonstrated in previous studies [55,56]. Individuals reported more pain relief when they “earned” it as a result of their choices in a wheel-of-fortune game than when they just passively watched the game before being informed of the subsequent pain decrease [55]. It was the participants’ agency that led to the outcome of pain relief. A more recent study showed that L-dopa supplementation markedly increased this modulatory effect of agency, with pain relief being more pronounced in the “active” than the “passive” condition [57]. This finding suggests a dopaminergic modulation of the influence of agency on pain perception. We know from experimental data that choice of preferred treatment can enhance placebo effects [58]. Similarly, the beneficial effects of an analgesic might be modulated by the degree of agency during its administration. Indeed, clinical trials have confirmed that postoperative pain can be alleviated more efficiently when patients use patient-controlled devices than when they receive the same dose passively [59]. However, the dopaminergic modulation of the effect of agency has not yet been tested directly in clinical pain conditions. A general modulatory effect of dopaminergic drugs on the efficacy of pain treatment has yielded conflicting results in patients. One study reported no effect of L-dopa or haloperidol on pain intensity in neuropathic pain conditions during open and hidden local application of lidocaine, which was administered by the study personnel [20]. Another study suggested that the intake of L-dopa together with the analgesic naltrexone for several weeks could decrease pain levels in female patients with subacute low back pain and may have even prevented the development of chronic back pain [21]. It could be speculated that the involvement of the “agency” aspect explains these discrepant results, with the active, prolonged use of naltrexone over weeks potentially accentuating the dopaminergic influence, and no significant dopaminergic modulation under the single passive application of lidocaine, similar to the findings of our study. However, the findings by Reckziegel and colleagues may also reflect a more general change in dopaminergic transmission in chronic pain patients which may lead to very different results with L-dopa augmentation [60,61].

Conclusions The evidence presented here argues against a direct causal role for dopamine during the experience of a treatment effect in the establishment of positive treatment expectations and placebo analgesia in healthy volunteers. Rather, in line with previous literature, we suggest a more nuanced role of dopamine. Certain dopamine-dependent dimensions of reward processing, including active agency and motivational aspects, may interact with pain experience and contribute to placebo analgesia. Future efforts to advance the understanding of dopaminergic mechanisms for modulating treatment response in pain must consider the undoubtedly complex involvement of dopaminergic neurotransmission in pain and its modulation.

Acknowledgments We gratefully acknowledge Sarah Hoppen and Detlef Pucher for their assistance in medication delivery. We thank Julian Kleine-Borgmann for designing Fig 1, Katarina Forkmann for technical support, and Matthias Zunhammer for his support during study planning.

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