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. Author manuscript; available in PMC: 2022 Aug 1.
Published in final edited form as: Brain Behav Immun. 2021 May 27;96:135–142. doi: 10.1016/j.bbi.2021.05.023

Impact of ibuprofen and peroxisome proliferator-activated receptor gamma on emotion-related neural activation: A randomized, placebo-controlled trial

Kelly T Cosgrove a,b, Rayus Kuplicki a, Jonathan Savitz a, Kaiping Burrows a, W Kyle Simmons c, Sahib S Khalsa a,d, T Kent Teague e, Robin L Aupperle a,d,*, Martin P Paulus a,d,*
PMCID: PMC8319138  NIHMSID: NIHMS1709726  PMID: 34052365

Abstract

Nonsteroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen have shown initial promise in producing antidepressant effects. This is perhaps due to these drugs being peroxisome proliferator-activated receptor gamma (PPARγ) agonists, in addition to their inhibition of cyclooxygenase enzymes. Some, albeit mixed, evidence suggests that PPARγ agonists have antidepressant effects in humans and animals. This double-blind, placebo-controlled, pharmacologic functional magnetic resonance imaging (ph-fMRI) study aimed to elucidate the impact of ibuprofen on emotion-related neural activity and determine whether observed effects were due to changes in PPARγ gene expression. Twenty healthy volunteers completed an emotional face matching task during three fMRI sessions, conducted one week apart. Placebo, 200 mg, or 600 mg ibuprofen was administered 1 h prior to each scan in a pseudo-randomized order. Peripheral blood mononuclear cells were collected at each session to isolate RNA for PPARγ gene expression. At the doses used, ibuprofen did not significantly change PPARγ gene expression. Ibuprofen dose was associated with decreased blood oxygen level-dependent (BOLD) activation in the dorsolateral prefrontal cortex and fusiform gyrus during emotional face processing (faces-shapes). Additionally, PPARγ gene expression was associated with increased BOLD activation in the insula and transverse and superior temporal gyri (faces-shapes). No interaction effects between ibuprofen dose and PPARγ gene expression on BOLD activation were observed. Thus, results suggest that ibuprofen and PPARγ may have independent effects on emotional neurocircuitry. Future studies are needed to further delineate the roles of ibuprofen and PPARγ in exerting antidepressant effects in healthy as well as clinical populations.

Keywords: ibuprofen, NSAIDs, PPAR gamma, fMRI, depression, emotional faces

1.0. INTRODUCTION

Over-the-counter use of nonsteroidal anti-inflammatory drugs (NSAIDs) is highly prevalent in the United States. Point prevalence rates of NSAIDs use are estimated at 25% for aspirin, 9% for ibuprofen, and 2% for naproxen (Delaney et al., 2011). The large-scale use of NSAIDs is most likely due to their effectiveness with mild to moderate pain and quick onset, as well as their relatively benign safety profile for most populations (Mallen et al., 2011; Rainsford, 2013). In addition to these benefits, recent research suggests that NSAIDs may also have positive effects on mental health.

A plethora of research has demonstrated that pain and emotion processes involve related neural circuitry (see Lumley et al., 2011 for a review). Moreover, antidepressants (i.e., tricyclics and selective serotonin reuptake inhibitors [SSRIs]) are often used in the treatment of chronic pain (Mico et al., 2006). There has also been research indicating that NSAIDs may have beneficial effects on emotional function, with initial evidence coming from animal models of depression. Specifically, ibuprofen has been shown to decrease total immobility time during forced swim and tail suspension tests in Bacillus Calmette-Guerin induced depressive-like behavior in mice, with effects that were comparable to fluoxetine (Saleh et al., 2014). Ibuprofen has also been associated with reduced anxiety-linked behaviors in an aluminum chloride mouse model of neurotoxicity (Jamil et al., 2016), depressive-like behaviors in tumor-bearing mice (Norden et al., 2015), and mice with rotenone-induced Parkinson’s disease (Zaminelli et al., 2014). Thus, in theory, NSAIDs such as ibuprofen may be beneficial for treating depression.

Results concerning the impact of NSAIDs on mental health in human observational studies have been mixed (Andrade, 2014; Köhler-Forsberg et al., 2019; Lehrer & Rheinstein, 2019; Wittenberg et al., 2019). However, studies examining ibuprofen have revealed initial promise for antidepressant effects. A population-based epidemiological study provided evidence that ibuprofen use is associated with reduced likelihood of hospital contact due to psychiatric issues (Köhler et al., 2015). Further, a pooled analysis by Iyengar et al. (2013) demonstrated that ibuprofen use in patients with osteoarthritis was associated with reductions in self-reported depression symptoms in placebo-controlled, randomized trials. It remains unknown, however, how ibuprofen may confer such antidepressant benefits.

Understanding how NSAIDs may impact emotion-related neural activation could help to clarify the potential mental health benefits and associated mechanisms of these drugs. Nonetheless, neuroimaging studies of NSAIDs have primarily focused on pain processing. Findings from neuroimaging studies of ibuprofen have been mixed, with some studies suggesting associated changes in pain-related task activation (Delli Pizzi et al., 2010) and others suggesting no relationship with task activation or functional connectivity (Wanigasekera et al., 2016). Therefore, while the studies are limited, there is some initial evidence that ibuprofen may influence neural responses in specific pain-related brain areas. Yet, to our knowledge, no studies have been conducted to investigate ibuprofen’s impact on emotional neural activation.

Previous research indicates that ibuprofen is rapidly transported across the blood-brain barrier (Parepally et al., 2006). Ibuprofen is known to inhibit inflammation by down-regulating the gene expression of cyclooxygenase (COX) enzymes (both COX-1 and COX-2). COX serves as a catalyst for the synthesis of proinflammatory lipids such as prostaglandin. Thus, through inhibiting COX, ibuprofen prevents inflammation resulting from prostaglandin activity (Rainsford, 2013; Villapol, 2018). However, it is also recognized that ibuprofen impacts many COX-independent pathways (Matos & Jordan, 2015). An additional mechanism that could have a broader effect on central nervous system function involves peroxisome proliferator-activated receptors (PPAR). PPAR are a group of proteins that serve as ligand-dependent transcription factors (Houseknecht et al., 2002), binding to DNA and regulating the expression of genes related to lipid and glucose metabolism, inflammatory processes, and cellular differentiation (Kapadia et al., 2008).

PPAR gamma (PPARγ) has specifically been found to have anti-inflammatory effects and be potentially protective in animal models of neurological, cardiovascular, and psychiatric disease (reviewed in Feinstein, 2003; Garcia-Bueno et al., 2010). Induced stress leads to increased PPARγ expression in the cortex, which in turn exerts anti-inflammatory effects. PPARγ ligands also improve glucose uptake, increase adenosine triphosphate (ATP) production, and decrease N-methyl-D-aspartate (NMDA) transmission after stress induction (Garcia-Bueno et al., 2005; Garcia-Bueno et al., 2007; Garcia-Bueno et al., 2010). Further, PPARγ agonists pioglitazone and rosiglitazone have been associated with an anti-depressant profile in animal models (i.e., leading to decreased immobility time, increased climbing, and reduced plasma corticosterone levels; Eissa Ahmed et al., 2009; Sadaghiani et al., 2011). Additionally, the antidepressant-like effect of atorvastatin in mice during the forced swim test is mediated, at least in part, by PPARγ receptors (Shahsavarian et al., 2014). Several human studies have also been conducted to examine the effect of PPARγ agonists on mood (Kashani et al., 2013). Pioglitazone used alone or in combination with psychiatric medication (e.g., citalopram, lithium), has been associated with decreases in depression symptoms for patients with major depressive disorder or bipolar I disorder (Colle et al., 2017; Kemp et al., 2012; Kemp et al., 2014; Sepanjnia et al., 2012; Zeinoddini et al., 2015). Because of this, PPARγ agonists appear to have high therapeutic potential for the treatment of depression.

Ibuprofen has been found to serve as a PPARγ agonist and act in an equivalent manner to PPARγ ligands (Lehmann et al., 1997). Preliminary studies have indicated that PPARγ plays a role in the relationship between ibuprofen and its neuroprotective effects. Specifically, the activation of PPARγ inhibits Ras homolog family member A (RhoA) and results in neurite growth promotion (Mandrekar-Colucci et al., 2013; Dill et al., 2010) and neural tissue preservation (Fu et al., 2007; Roloff et al., 2015). Thus, if ibuprofen confers a beneficial effect on mental health, PPARγ may have an indirect effect on this relationship. However, the impacts of ibuprofen and PPARγ on emotion-related neural circuitry have not been previously examined.

We conducted a randomized, double-blind, ph-fMRI study to examine the impact of ibuprofen (200 and 600 mg) versus placebo on emotion-related neural activity in psychiatrically healthy participants. In addition, we assessed the potential role of PPARγ in contributing to these neural responses. We utilized an emotional faces paradigm known to reliably elicit activation of visual and affect-processing circuitry at the group level, specifically in the amygdala and fusiform gyrus (McDermott et al., 2020; Sauder et al., 2013). This and similar emotional processing paradigms have been used in previous studies to demonstrate that traditional and novel antidepressants or anxiolytic medications (i.e., SSRIs, benzodiazepines, pregabalin) decrease activation within the amygdala, insula, and anterior cingulate cortex, as well as other limbic and prefrontal regions, including hippocampus and prefrontal cortex for healthy controls and/or depressed populations (Arce et al., 2008; Aupperle et al., 2012; Delaveau et al., 2011; Godlewska et al., 2012; Murphy et al., 2009; Rawlings et al., 2010; Sheline et al., 2001). These effects have often been observed when examining activation throughout the task (i.e., general emotion processing) rather than during specific emotional conditions (Paulus, Feinstein, Castillo, Simmons, & Stein, 2005; Windischberger et al., 2010). Given the potential antidepressant benefits of ibuprofen and PPARγ, we hypothesized that blood oxygen level-dependent (BOLD) activation in the amygdala, insula, dorsal ACC (dACC), dorsolateral PFC (dIPFC), and fusiform gyrus during emotional face processing would be attenuated by ibuprofen in a dose-dependent manner. We also hypothesized that greater ibuprofen dose would increase PPARγ, as indexed by gene expression in peripheral blood mononuclear cells (PBMCs), and that the effects of ibuprofen on BOLD activation would be greater for individuals with increased PPARγ.

2.0. METHODS

2.1. Participants and Study Design

Twenty-two healthy volunteers enrolled in the study. Two participants withdrew prior to study completion, which resulted in a final sample of 20 volunteers (n=10 female; mean age=32 years, SD=7; mean body mass index [kg/m2]=27, SD=6; 95% identified as Caucasian; 10% identified as Hispanic). The sample size used in the present study was based off of those used in prior ph-fMRI crossover studies (e.g., Aupperle et al., 2012 and Windischberger et al., 2010; see Supplemental Materials for a post-hoc power analysis). The study was conducted at the Laureate Institute for Brain Research in Tulsa, OK between July 2015 and October 2015. The study included one screening visit and three scanning sessions. All participants provided written informed consent and received financial compensation for their time. The study protocol was conducted in accordance with the Declaration of Helsinki and was approved by the Western Institutional Review Board. No adverse events were reported during the study. The study design is registered on clinicaltrials.gov (Study of Ibuprofen Effects on Brain Function; Identifier: NCT02507219), and one previous manuscript on the study has been published (Le et al., 2018). The CONSORT Flow Diagram for the present study can be found in the Supplemental Materials (Supplemental Figure 1). General exclusion criteria for the present study were assessed at the screening visit and included satisfying MRI exclusion criteria (e.g., ferrous metal implants and claustrophobia) or history of a mental health disorder currently or within the past six months as assessed by the Mini International Neuropsychiatric Interview (Sheehan et al., 1997). Participants who tested positive on a urine illicit drug screen were excluded. Additional exclusion criteria were significant cardiac or neurological disorders, psychotropic medication use within the last year, regular use of NSAIDs (i.e., on more than 15 of the last 30 days), and current pregnancy (screened for using a urine human chorionic gonadotropin [HCG] test). For a full description of the exclusion criteria, see the Supplemental Materials.

At each scanning session, participants were orally administered either placebo, 200 mg of ibuprofen, or 600 mg of ibuprofen. In the general population, ibuprofen is largely used to treat the acute effects of pain, and the standard over-the-counter dose for ibuprofen is 400 mg (Legg et al., 2014). Thus, the current study used an acute dosing paradigm to examine the impact of doses slightly above and below this standard amount. The placebo was a sugar capsule produced in the same manner as the ibuprofen capsules and was therefore visually identical to the active drugs. All capsules were made by a local pharmacy in Tulsa, OK. Notably, participants were prohibited from using NSAIDs for five days prior to each scanning session. Prior to the initial scanning session, the assignment of placebo or drug for each session was determined in a pseudo-randomized order (i.e., participants were randomly assigned to either ABC, ACB, BAC, BCA, CAB, or CBA in which A = placebo, B = 200 mg ibuprofen, and C = 600 mg ibuprofen). Drugs were administered in a double-blind fashion, such that researchers were blind to the medication codes until after data processing and neuroimaging analysis had been completed. There was an average of one week between each scanning session. For females, these visits were scheduled to avoid menstruation. Each session began at either 8 am or 10 am, and the start time was kept constant within participants. Indeed, all aspects of the study were tightly time-locked to dosing. Functional scans began approximately 1 h after dosing, as this is when ibuprofen is maximally active (Wagner, Albert, Szpunar, & Lockwood, 1984). Venous blood was collected in BD Vacutainer Cell Preparation Tube 5 h after drug administration. PBMCs were separated and aliquoted within 2 h of blood collection and stored in liquid nitrogen until analysis. All aliquots were analyzed using the same equipment between November 2015 and January 2016. See Supplemental Table 1 for the full scanning session timeline.

2.2. Measures

2.2.1. Self-Report

Four self-report measures of interest were used to assess the impact of ibuprofen dose on participants’ pain severity and mood. The Wong-Baker Faces Pain Rating Scale (Wong & Baker, 1988), which assesses current pain severity on a scale from 0 to 10 using a series of cartoon faces, was administered before and after each scan. Results from the Pain Rating Scale were converted to difference scores (i.e., post-minus pre-scan) prior to analyses. Computer adaptive forms of the Patient-Reported Outcomes Measurement Information System (PROMIS) scales were used to measure participant depression, anxiety, and anger after each scan (Pilkonis et al., 2011). PROMIS scales provide results in a T-score metric.

2.2.2. Emotional Faces Task

During each scan session, participants performed a block design version of an emotional face matching task adapted from Hariri et al. (2002). The emotional faces (i.e., happy, fearful, and angry) used for the task were derived from Matsumoto and Ekman’s Japanese and Caucasian Facial Expressions of Emotion (JACFEE; Matsumoto & Ekman, 1988, 1989). The task was conducted during one 8-min, 32-s fMRI run and consisted of 12 blocks: three blocks of shape trials as well as three blocks of happy, fearful, and angry face trials. Trials were presented in a pseudorandom order that was kept constant between participants. During each 30-s block, there were six 5-s trials. Each “face trial” consisted of a target face (on the top of the screen) and two probe faces (on the bottom of the screen). Participants were instructed to identify the probe with the same emotional expression as the target by pressing the corresponding left or right button on an MR-compatible response box. During “shape trials,” participants were instructed to match a target shape to one of two differently oriented probe shapes. See Supplemental Figure 2 for examples of the face and shape trials used in the task.

2.3. PPARγ gene expression

Total RNA was isolated from participants’ previously frozen PBMCs as described in Savitz et al. (2013). In brief, quick thawed PBMCs were put over Qiashredder columns (Qiagen, Valencia, CA) followed by use of the Qiagen MicroRNeasy kit. RNA quality and quantity were assessed on the Bioanalyzer 2100 (Agilent, Santa Clara, CA) and Nanodrop (Thermo Fisher Scientific, Waltham, WA) at the Integrative Immunology Center (IIC), School of Community Medicine, The University of Oklahoma - Tulsa, Tulsa, OK. mRNA was reverse transcribed utilizing the Sensiscript Reverse Transcription kit (Qiagen). All PCRs were performed on the ViiA 7 Real-Time PCR System (Thermo Fisher Scientific) with Taqman Gene Expression Assays (PPARγ and 18S) and Taqman Fast Advanced Master Mix (Thermo Fisher Scientific). Delta Ct values were converted to relative abundance of PPARγ to 18S ([1/2^Delta Ct]*18S=PPARγ). Relative abundance of CD14 was also calculated to estimate the number of monocytes ([1/2^Delta Ct]*18S=CD14). Notably, the values calculated for PPARγ and CD14 were highly correlated (r=0.93, p<0.001).

2.4. MRI

Imaging was performed using a Discovery MR750 3 Tesla MRI scanner (GE Healthcare, Milwaukee, Wisconsin) with an 8-channel receive-only head coil. Functional scans were acquired using gradient-recalled echo-planar imaging sequences with sensitivity encoding (SENSE; acceleration factor: R=2 in the phase encoding direction; matrix size: 128x128, FOV/slice/gap=240/2.9/0 mm, in-plane resolution: 1.875x1.875 mm2, axial plane: 39 slices, TR/TE=2000/27 ms, flip angle: 78°, sampling bandwidth: 250 kHz, 256 volumes). Structural MRI scans employed a T1-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) imaging sequence with SENSE (acceleration factor: R=2, scan time=5 min 40 s; matrix size: 256×256, FOV/slice=240/0.9 mm, in-plane resolution: 0.938×0.938 mm2, TR/TE=5/2.012 ms, inversion and delayed times: TI/TD=725/1400 ms, flip angle: 8°, sampling bandwidth: 31.25 kHz, 186 axial slices per volume).

Imaging data were preprocessed using Analysis of Functional Neuroimages (AFNI) software package (Cox, 1996). All functional images were aligned to the high-resolution anatomical images and resampled to a voxel size of 8 μL or 2x2x2 mm (from the original 1.875x1.875x2.9 mm). Data were spatially blurred with a 4 mm full width at half maximum (FWHM) spatial filter and normalized to Talairach space (via AFNI’s @auto_tlrc program). Four out of 60 scans were excluded from analyses. One participant was excluded entirely (i.e., all three of the subject’s scans were not used for imaging analyses) due to excessive head motion (i.e., average ENORM motion>0.15 mm). Additionally, one scan was excluded from imaging analyses because the subject had below detectable levels of PPARγ on that day. Thus, the scans used for analyses included data from 19 administrations of placebo, 18 administrations of 200 mg ibuprofen, and 19 administrations of 600 mg ibuprofen.

Preprocessed time-series data for each individual were analyzed using a gamma-variate multiple regression model, based on a BOLD hemodynamic response function with a 4-6 s peak lasting the duration of the block. Regressors of interest included four orthogonal regressors used to quantify the neural activation associated with matching of 1) happy faces, 2) fearful faces, 3) angry faces, and 4) shapes. Ten regressors of non-interest were entered into the linear regression model: six motion-related regressors (for roll, pitch, yaw, x-, y-, and z-translations), and the first four polynomial terms to account for slow drift. Individual TRs exceeding a motion threshold of 0.3 or an outlier threshold of 0.1 were excluded. Percent signal change was calculated by dividing the regressor of interest by the zeroth order polynomial regressor. For the present analyses, percent signal change was calculated for the contrast of emotional faces minus shapes (i.e., happy – shapes, fearful – shapes, and angry – shapes).

2.5. Statistical Analyses

Group-level analyses were conducted in R statistical package (version 3.6.1; R Core Team, 2013). Session was treated as a factor, and ibuprofen dose was treated as a continuous variable with values of 0, 200, and 600, which were mean centered. This approach assumes any drug or interaction effect is characterized by a linear dose-response. PPARγ values were also mean centered prior to analyses. Two PPARγ values were greater than two standard deviations above the mean and were therefore identified as outliers. To account for this, robust linear mixed effects models (LMEs) using the ‘rlmer’ function (robustlmm version 2.3; Koller, 2016) were utilized for all analyses. Degrees of freedom were estimated using Satterthwaite’s approach (Satterthwaite, 1941) with analogous non-robust models (using the ‘Imer’ function).

2.5.1. Behavioral and Physiological Analyses

We used robust LMEs to test for 1) an effect of ibuprofen administration on PPARγ levels [PPARγ ~ dose + session with a random effect for subject] and 2) effects of ibuprofen and PPARγ on the four self-report measures [score ~ PPARγ * dose + session with a random effect for subject]. Bonferroni correction was used to account for the number of LMEs conducted (0.05/5), resulting in a p threshold of 0.01 for a family wise error rate of α=0.05.

2.5.2. fMRI Analyses

To analyze the imaging data, a robust LME was conducted, and the model was percent signal change ~ session + task condition + PPARγ * dose, with random effects for subject and dose nested within subject. A main effect of task condition (i.e., happy – shapes, fearful – shapes, and angry – shapes), rather than condition interaction effects, was used given hypotheses concerning potential effects on general emotion processing. Analyses were conducted voxel-wise with family wise error rate correction performed across the whole brain and for specific a priori regions of interest (ROIs) using small volume correction. A whole-brain mask was created by including all voxels in which at least 80% of participants had echo-planar imaging data. ROIs included the amygdala, insula, dACC, fusiform gyrus, and dlPFC based on previous literature implicating them in emotional processing (Fusar-Poli et al., 2009; Hariri et al., 2002; Kanwisher et al., 1997; Posamentier & Abdi, 2003) and responding to antidepressant medications (Arce et al., 2008; Aupperle et al., 2012; Delaveau et al., 2011; Godlewska et al., 2012; Murphy et al., 2009; Rawlings et al., 2010; Sheline et al., 2001). Masks of these regions were defined by combining 36 subregions of the Brainnetome atlas (atlas.brainnetome.org; Fan et al., 2016). For more information on the masks, please see the Supplemental Materials.

Because recent evidence demonstrates that traditional methods of implementing fMRI cluster size multiple comparison corrections fail to account for spatial autocorrelations and do not adequately control false-positive inferences (Eklund et al., 2016), we utilized the AFNI program 3dClustsim with the spatial autocorrelation function (acf) option to calculate cluster size thresholds. Smoothness of the residuals after fitting the group model was calculated using 3dFWHMx within each ROI separately. The smoothness estimated in each ROI was then used to compute whole-brain and small-volume corrected thresholds. For whole-brain analyses, a voxel-wise probability of p<0.001 and α=0.05 was used to determine a cluster size threshold of 315 μL (39 voxels). For small-volume corrections, a voxel-wise probability of p<0.005 and α=0.05 was used to determine cluster size thresholds of amygdala=39 μL (5 voxels), insula=128 μL (16 voxels), fusiform gyrus=138 μL (17 voxels), dACC=161 μL (20 voxels), and dlPFC=218 μL (27 voxels).

3.0. RESULTS

3.1. Physiological and Behavioral

Descriptive statistics of PPARγ gene expression and the self-report measures can be found in Supplemental Table 2. A robust LME did not reveal any significant effects of ibuprofen dose (p=0.73) or session (ps>0.07) on PPARγ gene expression. PPARγ levels at each ibuprofen dose are depicted in Figure 1. PPARγ had a significant effect on Pain Rating Scale difference scores, such that greater PPARγ was associated with increased self-reported pain from pre- to post-scan (p=0.003). Ibuprofen dose was not significantly related to Pain Rating Scale scores (p=0.84). Neither PPARγ nor dose had a significant effect on PROMIS depression, anxiety, or anger scores (ps≥0.14). Further, no significant PPAR*dose interaction effects were observed beyond an effect on PROMIS anger that was trending towards significance (p=0.02). Significant and trending effects of session on PROMIS anxiety and anger were observed (ps≤0.03) and demonstrated that participant reports of anxiety and anger were highest at the first session. Supplemental Table 3 contains all of the results from the physiological and behavioral robust LMEs.

Figure 1.

Figure 1.

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Log2-transformed relative abundance of peroxisome proliferator-activated receptor gamma (PPARγ) gene expression at each dose of ibuprofen (i.e., placebo, 200 mg, and 600 mg). Dose did not have a statistically significant effect on PPARγ gene expression. Relative abundance of PPARγ gene expression was gathered via RNA isolation from peripheral blood mononuclear cells (PBMCs) and was calculated from the Delta Ct of PPARγ relative to 18S ([1/2^Delta Ct]*18S=PPARγ).

3.2. fMRI

3.2.1. Dose Main Effects

Within ROIs, ibuprofen dose was negatively associated with percent signal change in two clusters in the left dlPFC and two bilateral clusters in the fusiform gyri, indicating that participants given greater doses exhibited significantly less hemodynamic activity in these regions when viewing emotional faces (p<0.005; see Table 1 and Figure 2a). No results were found at the whole-brain level.

Table 1.

Effects of ibuprofen dose and peroxisome proliferator-activated receptor gamma (PPARγ) gene expression on blood oxygen level-dependent (BOLD) activation during the emotional faces task.

Region R/L Volume (μL) x y z peak t
Dose Main Effect
 1. dlPFC L 264 −23 39 26 −4.32
 2. dlPFC L 232 −35 3 36 −5.27
 3. Fusiform gyrus R 152 35 −63 −16 −3.99
 4. Fusiform gyrus L 136 −29 −73 −12 −4.74
PPARγ Main Effect
 1. Insula, Transverse temporal gyrus, Superior temporal gyrus R 528 45 −27 12 7.98
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Note. R = Right hemisphere. L = Left hemisphere. dlPFC = Dorsolateral prefrontal cortex. PPARγ = Log2-transformed relative abundance of peroxisome proliferator-activated receptor gamma to 18S. Coordinates represent the area of peak activation and are reported in Talairach space.

Figure 2.

Figure 2.

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Brain regions showing a significant main effect of A) ibuprofen dose [placebo, 200 mg, and 600mg] and B) peroxisome proliferator-activated receptor gamma [PPARγ] gene expression on blood oxygen level-dependent [BOLD] activation during emotional face processing. Identifying numbers correspond with those listed in Table 1. Coordinates are in Talairach space. Scatterplots are included for visualization purposes only. Both dose and PPARγ were mean centered prior to analysis and plotting. dlPFC = dorsolateral prefrontal cortex. PSC = percent signal change.

3.2.2. PPARγ Main Effects

PPARγ gene expression was positively associated with percent signal change in a cluster encompassing regions of the insula and transverse and superior temporal gyri at the whole-brain level during emotional face processing (p<0.001; see Table 1 and Figure 2b). Within ROIs, a significant cluster was found in the right insula, but this was encompassed by the larger, whole-brain cluster.

3.2.3. Dose by PPARγ Interaction Effects

No significant PPARγ*dose interaction effects on percent signal change during the emotional faces task were observed.

4.0. DISCUSSION

To our knowledge, this is the first ph-fMRI study to assess the impact of ibuprofen and PPARγ on emotion-related neural activity using a rigorous, double-blind, placebo-controlled, randomized, crossover design. Such an investigation of the neurobiological impact of ibuprofen is important given previous, though mixed, evidence that ibuprofen and other NSAIDs may produce antidepressant effects. Using an emotional faces task, the present study aimed to determine whether greater doses of ibuprofen would relate to decreased BOLD activation in regions implicated in both emotion processing and response to antidepressant medications in healthy participants. Further, because ibuprofen acts as a PPARγ agonist, this study explored whether ibuprofen dose interacted with PPARγ gene expression to impact BOLD activation in the ROIs. Results provided partial support for the hypotheses, as main effects for ibuprofen dose and PPARγ gene expression were observed in the imaging analyses, but interaction effects were not. Therefore, it appears that ibuprofen and PPARγ may each play a distinct role in modulating neural responses to emotional stimuli.

In regards to the drug effects, findings indicate that higher doses of ibuprofen attenuate emotion-related neural activity in the left dlPFC and bilateral fusiform gyri. The dlPFC is broadly involved in attention regulation and cognitive control, which involves attending to and regulating responses to emotional stimuli (Golkar et al., 2012). The fusiform gyrus contains the fusiform face area (FFA) and is involved in the perception of faces and emotional expressions (Kawasaki et al., 2012). Prior studies indicate that A) emotion-related BOLD activity in these regions may be impacted by depression (Stuhrmann et al., 2011) as well as antidepressant medications (Aupperle et al., 2012; Delaveau et al., 2011) and B) ibuprofen may lead to activation changes in these regions during pain processing (Kawasaki et al., 2012). While the attenuation of activation in the fusiform gyrus is consistent with what would be expected for decreasing neural resources towards the processing of emotional faces, the directionality of findings within the dlPFC is somewhat counterintuitive. Meta-analyses suggest that SSRIs often increase dlPFC activation, which may relate to increased executive control during emotional processing (Outhred et al., 2013). Other studies suggest dlPFC activation may reflect increased cognitive demands across various task domains (Kompus et al., 2009). Thus, current results suggest competing hypotheses. Decreased dlPFC activation with increased dose of ibuprofen may relate to reduced executive control abilities or to a reduced need for regulation due to decreased reactivity to emotional faces. To extend and clarify these conclusions, future studies are needed to replicate our findings in healthy samples and to explore the effects on ibuprofen on emotion-related neural activity for individuals with depression symptomatology or major depressive disorder.

At the doses used (i.e., 200 and 600 mg), there was no overall measurable effect of ibuprofen on PPARγ gene expression across participants. Ibuprofen did not affect self-reported depression, anxiety, or anger, nor was there a significant interaction effect between ibuprofen and PPARγ on emotion-related neural activation. The lack of overall effect of ibuprofen on PPARγ may be due to different time courses of ibuprofen pharmaco-kinetics and PPARγ gene expression. Alternatively, it is possible that the effect of ibuprofen on PPARγ gene expression in blood may be different from that of brain. Moreover, our assays may not be sufficiently sensitive to measure intra-individual changes above and beyond daily fluctuations. Finally, it is possible that a single, acute dose of ibuprofen is not sufficient to robustly alter PPARγ gene expression. Participants in the current study were administered each dose one time (i.e., 1 h prior to each scan) rather than receiving several administrations of the dose (e.g., over the course of six weeks; Sepanjnia et al., 2012). Future research involving longitudinal administration or increased doses of ibuprofen and participants with clinically significant depressive symptoms is warranted to further delineate the relationship between ibuprofen, PPARγ, and mental health.

Despite the lack of a main effect of ibuprofen on PPARγ gene expression, PPARγ was positively associated with BOLD activation in a cluster containing the insula and transverse and superior temporal gyri during emotional face processing. More specifically, the effect was observed in the posterior/mid-insula, which is a principal region in the primary interoceptive cortex and is involved in monitoring one’s internal bodily state (Berntson & Khalsa, 2021; Simmons et al., 2013), including pain processing (Craig, 2003). While speculative, participants with greater PPARγ gene expression may have been engaging in more interoception and self-monitoring when processing emotional faces. This increase in interoception may also underlie the positive association observed between PPARγ gene expression and changes in self-reported pain, albeit the effect size of this relationship was small. Although not explored here, the downstream anti-inflammatory effects of PPARγ may play a role in its association with insula activity. Indeed, prior research has demonstrated altered BOLD activation in the insula to be associated with low-grade systemic inflammation in individuals with major depressive disorder (Byrne et al., 2016; Simmons et al., 2020) and with acute inflammatory stimulation in healthy controls (Eisenberger, Inagaki, Mashal, & Irwin, 2010; Hannestad et al., 2012; Harrison et al., 2009). Thus, the links between PPARγ gene expression, inflammation, and insula activity need to be explored further in future studies. Overall, the present results highlight the potential for PPARγ to impact insular function during emotional processing may be important to consider in regards to potential clinical relevance for pain and depression.

4.1. Limitations

The present study did not have sufficient statistical power to assess sex differences. To address this, future studies should aim to include larger samples. Further, the current sample consisted of psychiatrically healthy individuals, which is similar to previous work delineating mechanisms for antidepressants (Aupperle et al., 2012; Murphy et al., 2009; Rawlings et al., 2010) and useful for developing a reference for the general processes involved in the assessed relationships. However, results may differ for individuals with mood disorders (Kemp et al., 2012; Kemp et al., 2014; Sepanjnia et al., 2012; Zeinoddini et al., 2015). To assess for these differences, future studies may wish to compare the neurobiological effects of ibuprofen and PPARγ for participants with major depressive disorder and healthy controls. Additionally, ibuprofen may impact mental health through other pathways (e.g., metabolites in the COX-prostaglandin pathway), which were not examined herein and present areas for further research. In the present study, relative abundance of PPARγ (in comparison to 18s) was highly correlated with relative abundance of CD14, suggesting that PPARγ gene expression values may be confounded by the number of monocytes in participants’ blood samples. While the methods used for estimating PPARγ gene expression are consistent with prior work (Hatami et al., 2016), this may indicate that our results may not be specific to PPARγ. Additionally, the study was designed to gather MRI data while ibuprofen was maximally active, meaning that blood samples had to be collected after the scanning protocol was complete (i.e., approximately 5 h after drug administration). This timing may be responsible for the lack of significant effects of ibuprofen dose on PPARγ gene expression and is a limitation future studies should aim to address. Lastly, this study did not directly manipulate PPARγ gene expression. Because PPARγ was found to have independent effects on emotion-related neural activity, future studies should explore the behavioral and neural effects of targeting PPARγ gene expression more directly (e.g., using agonists such as pioglitazone).

4.2. Conclusions

In sum, our results suggest that ibuprofen may impact activation in brain regions involved in emotional processing (e.g., dlPFC, fusiform gyri) while PPARγ may independently impact activation in brain regions involved in interoceptive processing (e.g., insula) for healthy controls. Future studies are needed to build upon the present study and clarify the functional impact of these findings for mental health.

Supplementary Material

1

  • Ibuprofen acts as a PPARγ agonist and thus may confer antidepressant effects

  • We examined the impact of ibuprofen and PPARγ on emotion-related neural activity

  • At the doses used, ibuprofen did not significantly change PPARγ gene expression

  • Ibuprofen dose negatively related to activation in the dlPFC and fusiform gyrus

  • PPARγ gene expression positively related to activation in the insula

Funding:

The study was funded by the William K. Warren Foundation.

Financial interests:

KTC receives funding from the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (F31HD103340). RLA receives funding from the National Institute of Mental Health (K23MH108707; R01MH123691). RLA, RK, and TKT receive funding from the National Institute of General Medical Sciences (P20GM121312). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

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Declarations

Previous presentations: Some findings described herein were presented at the annual conference of the Society of Biological Psychiatry, Chicago, IL, May 16-18, 2019.

Availability of data: Unthresholded statistical maps are available on NeuroVault (https://neurovault.org/collections/ZVYJUGPD/).

All other authors have no financial interests to disclose.

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