Skip to main content
VA Author Manuscripts logoLink to VA Author Manuscripts
. Author manuscript; available in PMC: 2020 Apr 1.
Published in final edited form as: Pharmacol Biochem Behav. 2019 Jan 26;179:34–42. doi: 10.1016/j.pbb.2019.01.007

Neuroinflammation in addiction: A review of neuroimaging studies and potential immunotherapies

Milky Kohno a,b,e, Jeanne Link f, Laura E Dennis a,e, Holly McCready a,e, Marilyn Huckans b,d,e, William F Hoffman a,b,c,d,e, Jennifer M Loftis a,b,e,*
PMCID: PMC6637953  NIHMSID: NIHMS1040636  PMID: 30695700

Abstract

Addiction is a worldwide public health problem and this article reviews scientific advances in identifying the role of neuroinflammation in the genesis, maintenance, and treatment of substance use disorders. With an emphasis on neuroimaging techniques, this review examines human studies of addiction using positron emission tomography to identify binding of translocator protein (TSPO), which is upregulated in reactive glial cells and activated microglia during pathological states. High TSPO levels have been shown in methamphetamine use but exhibits variable patterns in cocaine use. Alcohol and nicotine use, however, are associated with lower TSPO levels. We discuss how mechanistic differences at the neurotransmitter and circuit level in the neural effects of these agents and subsequent immune response may explain these observations. Finally, we review the potential of anti-inflammatory drugs, including ibudilast, minocycline, and pioglitazone, to ameliorate the behavioral and cognitive consequences of addiction.

Keywords: Cytokine, Inflammation, Microglia, Positron emission tomography, Resting-state functional connectivity, Substance use disorder

1. Introduction

Neuroinflammation has been attributed to the pathogenesis of a number of central nervous system (CNS) diseases (Block and Hong, 2005; Chen et al., 2016; Tansey et al., 2007), and although classically defined as the accumulation of mobile innate and/or adaptive immune cells in the tissue, there is diversity in what is considered to be inflammation in the brain, including gliosis, microglia activation, and the release of cytokines, chemokines, and pro-inflammatory factors (see “Neuroinflammation in psychiatric disorders: an introductory primer” in this Special Issue for additional background information). Broadly, neuroinflammation is thought to contribute to the neural adaptations following chronic exposure to drugs of abuse (Lacagnina et al., 2017; Liu et al., 2016; Pocock and Kettenmann, 2007), as many drugs render the brain more vulnerable to inflammation and resultant neuropathology. There is considerable interest in the mechanism by which drug use interacts with inflammatory processes, contributing to brain dysfunction, impairing cognitive control, and consequently promoting drug-use behavior. Preclinical studies show that drug exposure increases the release of pro-inflammatory cytokines, and glial cells (microglia and astrocytes) with chemokine and cytokine receptors respond quickly to CNS injury (Pocock and Kettenmann, 2007). Drug-induced dysregulation of neuroimmune signaling may compromise neuronal function, exacerbate neurodegeneration, and increase neurotoxicity, which may contribute to drug-related behavior through the activation of microglia and other glia-mediated synaptic remodeling (Lacagnina et al., 2017; Liu et al., 2016; Pocock and Kettenmann, 2007). Although the neural circuits relevant to substance use disorders may be impaired before inflammation or drug use, drug-induced inflammation may further compromise brain function in individuals with substance use disorders. It is, therefore, important to examine the combination of insults and interactive effects of substance use and neuroinflammation as new therapeutic strategies are considered.

The neuroimmune response to drugs of abuse is characterized, in part, by proliferation and morphological and functional changes of microglia and astrocytes (Ransohoff and Brown, 2012). Microglia are distributed throughout the brain with greatest concentrations found in substantia nigra, basal ganglia, and hippocampus (Lawson et al., 1990). Microglia respond directly to drug-induced CNS injury and are activated by stimulation of chemokine and cytokine receptors or by peripheral signals, potentially resulting from drug-induced damage to the blood brain barrier (Lacagnina et al., 2017; Loftis and Huckans, 2013). Activation of microglia results in a number of downstream processes including cell migration to the site of injury and phagocytosis (Hanisch, 2002; Otten et al., 2000), the production of pro-inflammatory factors, such as interleukin (IL)-1β, IL-6, and tumor necrosis factor-α (TNF-α), and the generation of reactive oxygen and nitrogen species that cause neuronal damage (Beardsley and Hauser, 2014). Astrocytes play a critical role in the uptake of synaptically-released glutamate (Cui et al., 2014), are affected by the activity level of dopamine (DA) neurons (Imaizumi et al., 2008), and can shape DA neuron activity and plasticity (Jucaite et al., 2012). Like microglia, astrocytes produce and secrete pro-inflammatory cytokines in response to tissue injury or other insults (Ransohoff and Brown, 2012), including exposure to substances of abuse (Lawson et al., 1990). Thus, excess neurotransmitters (e.g., DA and glutamate) released by drug use may bind to receptors expressed on glial cells and further amplify inflammatory signaling via additional release of cytokines and chemokines, potentially contributing to positive feedback that promotes inflammation.

A number of animal studies have established a link between neuroinflammation and drug exposure (Lacagnina et al., 2017; Loftis and Huckans, 2013), and it is important that work in humans expand on preclinical work to extend the clinical relevance and address the greater complexity of human drug use. The following review will, therefore, focus on findings from human neuroimaging studies of addiction, with an emphasis on positron emission tomography (PET). Although astrocytes are the most abundant type of glial cell in the brain and are affected by substances of abuse (Bull et al., 2015; Cao et al., 2016), there are no techniques to directly quantify astrocyte activation in humans in vivo. Currently, in vivo quantification of glial activation is only available to examine ligand binding of the 18-kDa translocator protein (TSPO), a protein formerly known as the peripheral benzodiazepine receptor and primarily located on the outer membrane of mitochondria. Within the CNS, a variety of cells are capable of expressing TSPO; however, the pattern of expression appears to differ between normal and injured CNS (Cosenza-Nashat et al., 2009). Second generation radiotracers such as [18F]FEDAA1106, [11C]PBR28, [11C]DPA-713, and [18F]DPA-714 now provide better specific binding ratios (Imaizumi et al., 2008) and higher test-retest, intra-individual reproducibility (Jucaite et al., 2012) compared with first generation [11C](R)-PK11195. A number of clinical studies show changes in TSPO binding with [11C] PBR28 (Hannestad, 2012), and more studies have begun investigating TSPO levels in addictions, specifically alcohol, nicotine, methamphetamine, and cocaine use disorders. As clinical and preclinical studies have demonstrated a link between immunological cells in blood and activated microglia (Kanegawa et al., 2016), this review will highlight the work conducted using PET as an index for neuroinflammation and also examine relevant work with magnetic resonance imaging linking brain function to peripheral markers of inflammation in substance use disorders. The review includes the limitations of PET imaging as an index of neuroinflammation and concludes with a brief summary of therapeutic strategies that may help target and treat the combination of insults and interactive effects of substance abuse and neuroinflammation.

2. Methamphetamine

Methamphetamine exposure impairs mitochondrial energetic metabolism, which enhances susceptibility to oxidative stress, proapoptosis, and neuroinflammation (Shin et al., 2018), including release of inflammatory cytokines and microglial activation (Banerjee et al., 2010; Clark et al., 2013; Goncalves et al., 2008; LaVoie et al., 2004; Loftis et al., 2011; Loftis and Janowsky, 2014; Mahajan et al., 2008; Silverstein et al., 2011; Wisor et al., 2011). Methamphetamine-induced DA and glutamate release also contribute to neuroinflammation. Excess DA autoxidizes to form toxic quinones, and quinone cycling results in oxidative stress, mitochondrial dysfunction, and damage to presynaptic membranes due to the production of superoxide radicals and hydrogen peroxide (Shah et al., 2012). Monoamine oxidase also oxidizes DA to form reactive oxygen species leading to cell damage and death through an increase in hydrogen peroxide, which interacts with metal ions to form toxic hydroxyl radicals (Ransohoff and Brown, 2012). In addition, excess prefrontal glutamate release by methamphetamine activates metabotropic glutamate receptors subtype 5 (mGluR5), which promotes the release of nuclear transcription factors (e.g., nuclear factor kappa light chain enhancer of activated B cells (NF-κB)) through intracellular signaling pathways (AKT/P13K) (Shah et al., 2012). Translocation of the transcription factors to the nucleus promotes the expression of proinflammatory cytokines (Ojaniemi et al., 2003; Shah et al., 2012).

Neuroimaging studies provide further evidence for methamphetamine-induced neuroinflammation. Magnetic resonance spectroscopy studies to assess metabolic alterations linked to immune cell activity show reductions in the ratio of creatine plus phosphocreatine (Cr + PCr)/choline-containing compound (Cho) and in the concentration of N-acetylaspartate (NAA) in individuals with a history of methamphetamine use (Ernst et al., 2000; Sekine et al., 2002). These markers are also correlated with years of methamphetamine use and severity of psychiatric symptoms (Ernst et al., 2000; Sekine et al., 2002), suggesting that neurotoxicity increases as a function of methamphetamine exposure. Individuals with a history of methamphetamine use (average duration of use: 6.8 years) also exhibit greater microglial activation indexed by [11C](R)-PK11195 PET in midbrain, striatum, orbitofrontal and insular cortex (Sekine et al., 2008), and lower levels of microglial activation are associated with greater duration of abstinence (average duration of abstinence: 1.8 years). This study, however, used the time activity curve of healthy controls as an input function, and the effect of differing plasma curves between methamphetamine and controls could lead to inaccurate assessment of regional TSPO binding using compartmental models (see Limitations section).

A recent study shows that increased peripheral IL-6 levels in individuals with a history of methamphetamine use are positively correlated with greater resting-state functional connectivity between the nucleus accumbens, amygdala, and hippocampus but inversely correlated with connectivity between the dorsolateral prefrontal cortex and striatum (Kohno et al., 2018). This is consistent with reports that methamphetamine use is associated with stronger functional connectivity within DA terminal regions, including striatum and limbic structures (Dean et al., 2014; Kohno et al., 2014; Kohno et al., 2016). As peripheral markers of immune activation are associated with impaired cognition (Loftis et al., 2011) and with abnormalities in prefrontal and striatal function (Felger et al., 2016), neuroinflammation may promote mesocorticolimbic and cognitive deficits commonly seen in methamphetamine use disorder. To the extent that DA plays a role in reward processing and executive function, it is possible that neuroinflammation promotes addiction-related brain and behavioral deficits (Dean et al., 2012; London et al., 2015) through altered activity of the mesocorticolimbic DA system. Consistent with this notion, activation of DA D1 and D2 receptors on microglia promotes migration (Farber et al., 2005), and microglial activation precedes the methamphetamine-induced degeneration of DA terminals in the striatum (Thomas et al., 2004; LaVoie et al., 2004). Moreover, individuals with methamphetamine use disorder consistently show low DA D2 receptor availability, which, in turn, is negatively related to mesolimbic functional connectivity (Kohno et al., 2016). These studies provide compelling evidence that methamphetamine exposure leads to activation of neuroinflammatory pathways in regions where individuals with a history of methamphetamine use consistently show deficits in gray matter volume and brain function (London et al., 2015).

Results from postmortem studies suggest that methamphetamine use enhances oxidative stress. One study assessed 4-hydroxynonenal and malondialdehyde (produced from lipid peroxidation), as markers of oxidative stress in postmortem brain of adults with and without prior methamphetamine exposure. For 4-hydroxynonenal, 50% of those in the methamphetamine group had levels above the upper limits of the control group range, and a dose-response analysis showed that the high-dose methamphetamine group had higher concentrations of 4-hydroxynonenal and malondialdehyde in striatum, cerebral cortex, and cerebellar cortex (Fitzmaurice et al., 2006). Postmortem results of methamphetamine-induced gliosis, however, are conflicting. Two studies examining gliosis assessed with histopathological analysis did not detect methamphetamine-induced gliosis (Moszczynska et al., 2004; Wilson et al., 1996), whereas another study using quantitative analysis of microglia and astrocyte markers found a marked increase of microglial markers in striatum in individuals with a history of methamphetamine use compared to controls (Kitamura et al., 2010). Differences among studies could be attributed to factors including age, genetic heterogeneity, sex, comorbidities, amount and duration of drug exposure, cause of death, and postmortem interval (Gomez-Nicola and Boche, 2015), as well as the qualitative and quantitative analysis methods. Interestingly, a postmortem study of individuals with a history of cocaine use found a marked increase (108%) in the number of activated microglia cells in the midbrain (Little et al., 2009). In the following section, similarities and differences in other markers of immune system signaling between cocaine and methamphetamine use are discussed.

3. Cocaine

Cocaine also increases dopaminergic and glutamatergic signaling; subsequent DA and glutamate stimulation of immune cells likely facilitates an inflammatory response like that induced by methamphetamine. Chronic cocaine use is associated with an increase in IL-6 (Ersche et al., 2014; Fox et al., 2012; Levandowski et al., 2016; Moreira et al., 2016) and also with a reduction in circulating levels of the anti-inflammatory/immunoregulatory factor, IL-10, and an increase in the ratio of pro-inflammatory to anti-inflammatory markers (Moreira et al., 2016). Acute cocaine exposure, however, seems to have an opposite effect and reduces levels of IL-6 (Halpern et al., 2003; Irwin et al., 2007). Whether a reduction in IL-6 is an anti-inflammatory response to acute cocaine use or a pro-inflammatory response is unclear, as regenerative or inflammatory processes of IL-6 are dependent on trans-signaling or classic signaling, respectively (Scheller et al., 2011). Variability between the response to acute exposure or chronic use may explain mixed results in pro- and anti-inflammatory responses and may contribute to differences seen in levels of TSPO.

Postmortem tissue of individuals with a history of cocaine use show a significant increase in activated microglia compared to controls (Little et al., 2009), while there are no significant quantifiable differences in TSPO levels indexed with [11C]PBR28 PET between individuals with prior cocaine use and controls (Narendran et al., 2014). Like IL-6, activation of microglia may also depend on patterns of use, as participants in the PET study were approximately two weeks abstinent from cocaine, while post mortem tissue were collected from individuals with recent use.

Although it is expected that cocaine and methamphetamine would affect microglia in similar ways, differences between cocaine and methamphetamine on DA kinetics have been shown in both human and animals studies, which can manifest in differences in neuroinflammation. In animals, the levels of DA are higher after administration of methamphetamine than after cocaine. Higher levels of intrasynaptic DA and slower clearance of methamphetamine compared to cocaine contributes to the longer behavioral effects, oxidative stress, and damage to the dopaminergic system (Koob, 1998). Amphetamines and methamphetamine have longer half-lives compared to that of cocaine, where the duration of action for cocaine is approximately 1–3 h, while the half-life of amphetamines and methamphetamine are approximately 8–13 h (Harris et al., 2003; Jufer et al., 2000). In non-human primates, [11C]cocaine and [11C]d-methamphetamine show differences in brain distribution, kinetics, and clearance rates. Not only does [11C]d-methamphetamine peak more slowly than [11C]cocaine, but it also clears more slowly than cocaine, and its distribution extends beyond the striatum to cortical brain regions (Fowler et al., 2007). Similarly, in humans, cocaine is concentrated only in the striatum and its uptake and clearance are faster than that of methamphetamine (Fowler et al., 2008).

While differences in DA kinetics and signaling are factors that may explain differences in patterns of microglial activation in methamphetamine and cocaine use disorder, methodological variability among the studies needs to be noted. Differences in radioligand and analysis methods could contribute to mixed results along with the heterogeneity of genotypes conferring binding affinity. Another important factor is glutamate neurotransmission and both cocaine and methamphetamine use are associated with an increase in glutamate release and down regulation of glutamate transporters (Kalivas, 2007). Inflammatory cytokines similarly increase glucose metabolism (Haroon et al., 2014) and extrasynaptic levels of glutamate by decreasing glutamate transporters (Tilleux and Hermans, 2007) and increasing astrocytic glutamate release (Ida et al., 2008). As excess of glutamate promotes the transcription of inflammatory cytokines and activates microglia (Ojaniemi et al., 2003; Shah et al., 2012), more work is necessary to examine the effects of these stimulants on glutamate signaling and the effects on the neural immune response. In addition, future studies controlling for the heterogeneity in recent exposure to stimulant drugs when investigating activated microglia and markers of inflammation are needed.

4. Alcohol

Alcohol exposure is associated with neurotoxicity, activation of microglia, and release of cytokines and inflammatory mediators; these phenomena are now being recognized as contributing factors to alcohol use disorder pathology (Henriques et al., 2018; Mayfield et al., 2013; Pascual et al., 2017; Vetreno et al., 2014). Much of the work showing elevated pro-inflammatory but reduced anti-inflammatory signaling come from preclinical studies of alcohol administration (Henriques et al., 2018).

Three human PET studies, using [11C]PBR28, show lower TSPO levels in individuals with alcohol dependence (Hillmer et al., 2017; Kalk et al., 2017; Kim et al., 2018) and an inverse relationship between TSPO binding and number of drinks per day and alcohol dependence severity (Hillmer et al., 2017). In contrast, a PET study in non-human primates, using [18F]DPA-714, shows a significant increase in TSPO binding during ethanol exposure, which remains elevated for 7–12 months (Saba et al., 2017). Using PET with [11C]PBR28, a study in rats found no differences in TSPO binding between alcohol dependent and non-dependent rats (Kim et al., 2018). Although one human study recruited well-matched controls in age, sex, and cigarette use (Hillmer et al., 2017), it is possible that other drug use history (e.g., marijuana) and environmental factors could contribute to differences between human and animal studies of alcohol-induced activation of microglia. Alternatively, endogenous TSPO ligands such as cholesterol could be a factor in PBR28 binding as genotypes that affect PBR28 binding also affect the cholesterol-binding domain of TSPO (Kim et al., 2018). Another possible explanation is that chronic alcohol use may attenuate the activation of microglia through gamma-aminobutyric acid (GABA)-mediated inhibition of cytokines. Activation of microglia increases the expression of GABA receptors, and GABAB receptor agonists reduce IL-6-mediated activation of microglia (Kuhn et al., 2004; Pocock and Kettenmann, 2007). The neuromodulatory effects of chronic alcohol use on GABA release may also induce anti-inflammatory processes, as acute alcohol exposure can increase IL-10 which results in pre- and post-synaptic regulation of GABA transmission (Suryanarayanan et al., 2016).

Chronic and binge models of alcohol exposure provide evidence for alcohol-induced neurotoxicity, which is mediated by innate immunomodulatory responses, such as activation of glial cells, cytokine production, and the neuronal Toll-like receptor 4 (TLR4) response (Crews et al., 2017). Repeated alcohol-mediated neurotoxic insults may compromise the innate immune response or result in complex compensatory and neuroadaptive processes that limit neuroinflammation. Individual differences such as age and sex, however, are important factors in the neuroimmune response (Pascual et al., 2017; Wilhelm et al., 2017), and more studies are needed to better identify the mechanisms by which alcohol use affects immune signaling.

5. Nicotine

Cigarette smoke is associated with both immunosuppressive and immunostimulatory components (Sopori, 2002; Sopori and Kozak, 1998). It is, however, difficult to dissociate the effects of nicotine from those of constituents in tobacco. Cigarette smoking promotes activation of epithelial and immune cells that release pro-inflammatory factors and promote the recruitment of neutrophils, macrophages, T cells, and dendritic cells (Savage et al., 1991; Sopori, 2002; Sopori and Kozak, 1998). Nicotine, in contrast, is thought to be a significant contributor to the inhibition of the antibody response and the immunosuppressive effects of chronic smoking (Geng et al., 1995; Geng et al., 1996). Animal studies show that smoking can increase reactive oxygen species and decrease levels of antioxidants (Savage et al., 1991; Sopori, 2002; Sopori and Kozak, 1998). Increases in inflammatory markers associated with cigarette smoking are also shown to be dose-dependent and related to smoking intensity and time since smoking cessation (Sopori, 2002).

Whether from nicotine or cigarette smoke, neuroimaging studies provide evidence for neuroadaptations in individuals who smoke cigarettes. Smokers, compared to non-smokers, show gray-matter abnormalities throughout the brain (Franklin et al., 2014; Morales et al., 2014; Morales et al., 2012), differences in functional connectivity in prefrontal executive control regions (Fedota and Stein, 2015; Lerman et al., 2014), and an upregulation of nicotinic acetylcholine receptors (Brody et al., 2013; Sabbagh et al., 2002). A recent PET study using [11C]DAA-1106 found less TSPO binding in smokers compared to non-smokers (Brody et al., 2017). As activation of nicotinic acetylcholine receptors result in immunosupressive properties (Guan et al., 2015; Kalra et al., 2004; Wang et al., 2003), the results may highlight an antiinflammatory effect of cigarette smoking. Evidence points to nicotinic acetylcholine alpha 7 receptor subunits in mediating nicotine-induced suppression of neuroinflammation (Wang et al., 2003) through the inhibition of microglial activation and subsequent pro-inflammatory cytokine release (Guan et al., 2015). As individuals who smoke have lower levels of TSPO, which are inversely correlated with the number of cigarettes smoked per day (Brody et al., 2017), the data are in line with the literature suggesting neuroprotective properties of nicotine and the idea that the anti-inflammatory responses of nicotine may be responsible for the decreased incidence in neurological diseases seen in individuals who smoke cigarettes (Birtwistle and Hall, 1996; James and Nordberg, 1995; Newhouse et al., 1997).

6. Cannabinoids

Despite considerable interest in the neural effects of cannabis (also known as marijuana), there have been no published PET studies of microglial activation in individuals who use cannabis. There are several reports, however, on the neuroprotective properties of cannabinoids, components of the cannabis plant. Acute exposure to cannabinoids [e.g., delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabinol (CBN)] can lower cellular immune responses, inhibit production of inflammatory cytokines and chemokines, reduce excitotoxicity, and decrease neuronal cell damage (Jean-Gilles et al., 2010; McCoy, 2016; Schwaeble and Constantinescu, 2010; Tanasescu and Constantinescu, 2010). Repeated exposure to cannabinoids also has immunomodulatory effects. One study found that individuals with HIV who use cannabis have lower levels of peripheral blood CD16+ monocytes, an index of immune activation, than individuals with HIV who do not use cannabis (Rizzo et al., 2018). Cannabinoid receptor agonists reduce beta-amyloid-induced activation of microglia in Alzheimer’s disease models and reduce the onset and severity of autoimmune characteristics of multiple sclerosis in animal models, along with reductions of inflammation (Pacher and Kunos, 2013; Zhang et al., 2009; Martín-Moreno et al., 2012). Resting microglia lack cannabinoid 2 (CB2) receptors; however, there is a significant increase in CB2 receptor expression on microglia on diseased tissues or in culture (Stella, 2009), suggesting that the anti-inflammatory effects of cannabinoids may be mediated by CB2 receptors. The effect of cannabinoids in lowering excitotoxicity and inhibiting the release of pro-inflammatory mediators has important implications in pathological inflammatory conditions, especially substance addiction where co-use is common.

While most evidence supports an anti-inflammatory effect of cannabis, there are reports consistent with pro-inflammatory effects. Individuals with cannabis use disorder show increases in plasma pro-inflammatory cytokines (IL-1β, IL-6, IL-8, and TNF-α) compared to individuals with no history of cannabis use (Bayazit et al., 2017). Neuroinflammatory responses to cannabis may depend on age at initiation of use. Adult female Sprague-Dawley rats treated with THC in adolescence (postnatal days 35–45) exhibit a persistent neuroinflammatory state within the prefrontal cortex, including up-regulation of CB2 receptors on microglia cells, increased expression of TNF-α and other pro-inflammatory factors, and a reduction in IL-10 levels. Interestingly, this neuroinflammatory phenotype is attenuated by the antiinflammatory drug, ibudilast when administered during THC treatment (Zamberletti et al., 2015).

The effect of cannabis on inflammatory mediators has important implications in pathological inflammatory conditions, especially addiction, where co-use is common. As evidence supports both pro- and anti-inflammatory responses to cannabis, it is critical for future studies to disentangle the independent effect of cannabis and the interactive effect with other drugs of abuse on immune signaling.

7. Implications for treatment

Methamphetamine, cocaine and, under some circumstances, alcohol evoke a neuro-inflammatory response. Thus, interventions aimed at reducing inflammation may serve as a useful adjunct to behavioral treatments for substance use disorders. Several potential anti-inflammatory pharmacotherapies that have been or are currently being tested in human clinical trials are summarized in Table 1.

Table 1.

Clinical trials of potential anti-inflammatory treatments for substance use disorder.

Clinical trial Study design SUDa Participants Dose/duration Outcome measures
Ibudilast
NCT03341078
 Not yet
 recruiting
Phase II: Double-blind, randomized, placebo controlled, parallel assignment MA Use disorder N = 65 20 mg bid (2 wks)
50 mg bid (4 wks)
Neuroinflammation (PET); Monetary Incentive Delay Task and functional connectivity (fMRI); Cognitive function, Craving and MA use
NCT02025998
 Completed
Phase I: Double-blind, randomized, placebo controlled, cross-over Alcohol Dependence/abuse N= 24 50 mg bid (1 wk) Alcohol effects; Alcohol urge; Cue & stress-induced craving; Differential emotion
NCT03489850
 Not yet
 recruiting
Phase II: Double-blind, randomized, placebo controlled, parallel assignment Alcohol In treatment/seeking N= 50 20 mg (2 d) 50 mg bid (12 d) Alcohol-related negative reinforcement; Cue-reactivity (fMRI); Withdrawal-related dysphoria
NCT01860807
 Not yet
 recruiting
Phase II: Double-blind, randomized, placebo controlled, cross-over MA Treatment seeking N = 140 50 mg bid (12 wks) MA use; Treatment retention
NCT01860807
 Completed
Phase I: Double-blind, randomized, placebo controlled, crossover MA Dependence N = 11 20 mg (1 wk) 50 mg bid (1 wk) Safety and tolerability with MA; Craving and drug effects; Discounting tasks
Minocycline
NCT03244592
 Not yet
 recruiting
Phase I & II: Double-blind, randomized, placebo controlled, parallel assignment Alcohol Dependence/abuse N= 32 200 mg (4 wks) Neuroinflammation (PET); Cue-induced craving; Alcohol use; Cognitive function
NCT02541500 Phase III: Open label, single group assignment Opioid Stimulant Dependence N = 40 200 mg (4 mos) Stimulant use; Treatment retention; HIV-risk (sex and drug behaviors); Neuropsychological function
NCT02359006
 Completed
Double-blind, randomized, placebo controlled, crossover Opioid Current methadone maintenance N = 55 200 mg (15 d) Pain sensitivity; Withdrawal symptoms; Cognitive Performance
NCT02187211
 Recruiting
Phase I: Double-blind, randomized, placebo controlled, cross-over Alcohol Heavy social drinkers N= 60 200 or 400 mg (10 d) Effects of alcohol
Pioglitazone
NCT01395784
 Completed
Phase II: Non-randomized Opioid Prescription abuse N= 32 15 then 45 mg(9 wks) Subjective drug effects (VAS) Analgesic Response (Cold pressor test)
NCT01517165
 Completed
Phase I: Randomized, Parallel Assignment Opioid In treatment with buprenorphine N = 24 mg not specified (13 wks) Abstinence without severe withdrawal; Proportions of negative urine toxicology and need for adjuct medication
NCT01395797
 Completed
Phase I & II: Randomized, Parallel Assignment Opioid Nicotine Dependence to heroin or nicotine N = 82 0, 15 mg or 45 mg (2 wks) Persistence of responding (Drug Break Point) Subjective drug effects (VAS)
NCT01631630
 Completed
Phase II: Randomized, Parallel Assignment Alcohol Use disorder N = 16 45 mg (2 wks) Alcohol urge; Anxiety, Depression scales; Craving
NCT02774343
 Completed
Phase I & II: Randomized, Parallel Assignment Cocaine Cocaine dependent N= 30 30 then 45 mg (12 wks) White-matter Integrity (DTI); Obsessive Compulsive Drug Use Scale; Cue reactivity; cocaine use and craving
NCT03060772
 Recruiting
Phase II: Randomized, Parallel Assignment Alcohol Use disorder N = 36 30 mg (4 wks) Phagocytic Index; NADPH oxidase; Alveolar macrophage oxidative stress; GSH/GSSG; Cys/CySS redox potential
a

Studies of opioid use disorder are included in the table, although the role of neuroinflammation in opioid addiction was not a focus of this review. Recent, comprehensive reviews on glia and opioids are available (Bachtell et al., 2017; Kadhim et al., 2018). Abbreviations: DTI, diffusion tension imaging; MA, methamphetamine; SUD, substance use disorder; VAS, visual analogue scale.

Ibudilast (3-isobutyryl-2-isopropylpyrazolo-[1,5-a]pyridine), an anti-inflammatory non-selective phosphodiesterase inhibitor, has neuroprotective and immunomodulatory properties and has shown therapeutic benefit for neuroinflammatory conditions (Burnouf and Pruniaux, 2002), including addictions (Ray et al., 2014). The compound suppresses the production of nitric oxide, reactive oxygen species, IL-1β, IL-6, and TNF-α and enhances the production of anti-inflammatory markers, including nerve growth factor, glia-derived neurotrophic factor, and neurotrophin-4 in activated microglia (Mizuno et al., 2004; Suzumura et al., 1999). Similarly, ibudilast attenuates alcohol drinking in animal models (Bell et al., 2015) and humans (Ray et al., 2017) and reduces methamphetamine-induced locomotor activity and stress-induced methamphetamine reinstatement (Beardsley et al., 2010). In a recent human study, ibudilast reduced methamphetamine use and craving for methamphetamine (Worley et al., 2016).

Minocycline (7-dimethylamino-6-dimethyl-6-deoxytetracycline) is a second-generation antibiotic that is a semi-synthetic tetracycline analogue and is approved by the US Food and Drug Administration (FDA) for the treatment of some sexually transmitted diseases, rheumatoid arthritis, and acne (Garrido-Mesa et al., 2013). Similar to ibudilast, minocycline shows potential as a neuroprotective and anti-inflammatory agent, independent of its antibiotic properties (Garrido-Mesa et al., 2013). Minocycline inhibits microglial p38 mitogen-activated protein kinase and pro-inflammatory cytokine production, but it has no known phosphodiesterase activity (Garrido-Mesa et al., 2013). In animal models, minocycline extinguishes morphine- and methamphetamine-induced conditioned place preference and blocks drug-induced reinstatement (Arezoomandan and Haghparast, 2016; Attarzadeh-Yazdi et al., 2014; Fujita et al., 2012). Furthermore, minocycline reduces methamphetamine self-administration (Snider et al., 2013) and methamphetamine-induced release of DA (Fujita et al., 2012; Hashimoto et al., 2013; Zhang et al., 2006), suggesting that minocycline can attenuate the reward effects of methamphetamine and reduce relapse. Minocycline also holds promise in attenuating the effects of cocaine and alcohol, where minocycline treatment prevents the development of cocaine sensitization (Chen et al., 2009) and reduces ethanol intake in male and female mice using a free choice voluntary drinking model (Agrawal et al., 2011). In humans, minocycline reduces the subjective effects of amphetamine in healthy controls (Sofuoglu et al., 2011) and attenuates cigarette craving in individuals with nicotine dependence (Sofuoglu et al., 2009).

Peroxisome proliferator-activated receptor (PPAR) agonists are also under investigation as pharmacotherapeutic strategies for substance use disorders. PPARs function as transcription factors that regulate the expression of genes that are involved in lipid and glucose metabolism and inflammation (Daynes and Jones, 2002). There are two subtypes of PPARs that have been studied in substance use, PPAR-α and PPAR-γ (Le Foll et al., 2013). PPAR-γ activation has anti-inflammatory effects that involve inhibiting the expression of cytokines (IL-1β, IL-6, and TNF-α), the production of inducible nitric oxide, and the expression of matrix metalloproteinase 9 and macrophage scavenger receptor 1 on monocytes, macrophages, and epithelial cells (Daynes and Jones, 2002; Delerive et al., 2001; Kielian and Drew, 2003; Willson et al., 2000). As PPAR-γ are highly expressed in brain regions associated with the development and maintenance of addictive behaviors, such as the nucleus accumbens, dorsal striatum, ventral tegmental area, and hippocampus, many studies have examined how PPAR-γ agonists affect drug-seeking behavior.

Repeated administration of methamphetamine in mice is associated with an increase in PPAR-γ activity and protein levels in the nucleus accumbens (Maeda et al., 2007). Pioglitazone and ciglitazone, PPAR-γ agonists (thiazolidinediones), both reduce behavioral sensitization to methamphetamine during the withdrawal period (Maeda et al., 2007). In human cocaine use disorder, a 12-week treatment of pioglitazone reduced craving for cocaine and increased white-matter integrity in the corpus callosum and thalamic radiation (Schmitz et al., 2017). Similarly, a three-week treatment of pioglitazone reduced cigarette craving in heavy smokers; however, pioglitazone was not effective in reducing the reinforcing effects of cigarettes or in reducing smoking-cue reactivity (Jones et al., 2017). There are currently no published reports on the effect of PPAR-γ agonists in humans with alcohol use disorder; however, one study has shown a link between PPAR genotypes (single nucleotide polymorphisms in PPAR-α and PPAR-γ) with alcohol withdrawal and alcohol dependence (Blednov et al., 2015). In preclinical studies, PPAR-γ agonist treatment is effective in reducing alcohol use, where activation of PPAR-γ with pioglitazone and rosiglitazone selectively reduce alcohol drinking in rats—an effect blocked by pretreatment with GW9662, a selective PPAR-γ antagonist (Stopponi et al., 2013; Stopponi et al., 2011). Preclinical data suggest that pioglitazone and other PPAR-γ agonists are promising candidates in attenuating drug-seeking behavior and craving, but more research in humans with substance use disorders is required to evaluate the effects of PPAR agonists in individuals with substance use disorders.

PET measures of glial activation could be used to clarify whether the mechanism by which these pharmacotherapies affect addictive behaviors is mediated by their anti-inflammatory effects. To our knowledge, however, there are no published studies that examine the effect of these agents on microglial activation in addiction. Reports of any animal or human PET studies of anti-inflammatory drugs are sparse. Minocycline decreases binding of [11C](R)-PK11195 in zymosan-treated female rats (Converse et al., 2011), but PET has not been used to test either ibudilast or thiazolidinediones effects on microglial activation. Clearly, there is a critical need for clinical trials that leverage PET neuroimaging to measure the effect of anti-inflammatory agents on microglial activation in addiction.

7.1. Limitations

Although the improvements of second generation radiotracers have promoted more studies to investigate TSPO binding as an index for activated microglia in a number of psychiatric disorders, the method is not without limitations. TSPO is upregulated on activated microglia and greater TSPO binding is thought to represent a biomarker of neuroinflammation. Studies have shown that [11C]PBR28 provides accurate estimates of TSPO densities and high levels of specific binding; such that, > 95% of brain uptake represented specific binding to TSPO in rhesus monkeys (Imaizumi et al., 2008). This fraction, however, is lower in humans and genotype dependent (Owen et al., 2014), which may account for mixed results across species. The multicellular expression of TSPO, however, would suggest that TSPO binding with PET imaging may not solely reflect the activation of microglial cells and may represent a broader inflammatory process (Lavisse et al., 2012). In addition, TSPO immunoreactivity is present in various CNS cell types, including microglia, astrocytes, and vascular endothelial cells (Notter et al., 2018). The partial volume effect from endothelial cells can be accounted for by including an additional blood to endothelial compartment in the standard two-tissue compartmental model, which results in stronger correlations between binding and mRNA TSPO expression than the standard two-compartment model (Rizzo et al., 2014). A recent paper examining TSPO binding in schizophrenia suggests that TSPO binding may reflect an anti-inflammatory response that limits acute inflammation, whereas a downregulation may represent a chronic low-grade inflammatory state (Notter et al., 2018). In light of the findings from the alcohol and nicotine studies, this notion would be consistent with the animal literature that drugs of abuse contribute to neuroinflammation. Although contrary to the increase in TSPO binding in individuals with a history methamphetamine use (Sekine et al., 2008), the increase in TSPO binding in methamphetamine use disorder has not been re-examined with second generation radiotracers. In addition, this study used the time-activity curve of healthy controls as a reference-tissue input function rather than using an arterial input function, which makes the assumption that groups are similar in uptake and specific binding. Future studies of methamphetamine use disorder and second generation TSPO tracers that use an arterial input function or if applicable, a cerebellar reference region, as recently used in Alzheimer’s disease (Lyoo et al., 2015), are needed. Although PET imaging allows for an in vivo quantitative assessment of TSPO in humans, the use of in vivo imaging techniques depends upon careful validation with preclinical studies, well-controlled postmortem evaluations, and other measurements to assess rigor, specificity, and sensitivity. Further, altered TSPO binding is not equivalent to altered microglia activation exclusively; complementary measures of inflammation are recommended (Notter et al., 2018).

8. Conclusions

Pathological neural activity induced by drugs of abuse contribute to an immune response, however the interactions and interplay between drug-induced neurotransmitter release and multiple receptor subtypes on microglia remains unclear. As excess glutamate promotes the transcription of inflammatory cytokines and activates microglia (Ojaniemi et al., 2003; Shah et al., 2012), drugs promoting glutamatergic neurotransmission may enhance excitotoxicity and further induce neuroinflammatory processes. Neuroprotective effects of some drugs suggest neural adaptive mechanisms to limit neuroinflammation through up-regulation of receptors and the inhibition of microglia activation. Neuroimmune responses through IL-6 and TNF-α inhibition is associated with activation of nicotinic acetylcholine or GABA receptors. This is consistent with human PET investigations of neuroinflammation, where alcohol and nicotine use disorders are associated with lower levels of TSPO than controls, with opposite effects for methamphetamine use disorder.

It is important to consider the effects of polydrug use and the possible amplification or attenuation of the neurotoxic cascade. Nicotine and marijuana use are ubiquitous in substance use disorders and both drugs need to be controlled for in future studies. This is especially true with the mixed results seen in studies of stimulant use. Although the differential effects of methamphetamine and cocaine on TSPO binding are unexpected and could be attributed to differences in DA kinetics and toxicity, radiotracer affinities, methodological analysis techniques or genotype imbalances, carefully controlled studies of polysubstance use are warranted. Studies of addiction have not well-characterized or controlled for marijuana use or other polydrug use in the context of neuroinflammation, and establishing this link would help better clarify the long term impact of drugs of abuse on the immune response.

8.1. Future directions and treatments to reduce inflammation

Use of anti-inflammatory drugs is a promising avenue for the treatment of substance use disorders (Table 1); however, it is yet to be determined whether ibudilast, minocycline, or pioglitazone attenuate human drug use behavior through a reduction in neuroinflammation. Non-pharmacologic forms of treatment may also attenuate drug-induced neurotoxicity, and one study shows that 12 weeks of aerobic exercise significantly reduces serum methane dicarboxylic aldehyde (oxidative stress marker), and improves cognitive processing speed in individuals with a history of methamphetamine dependence (Zhang et al., 2018). Another study in adults with methamphetamine dependence shows an increase in DA D2 receptor availability after an eight-week exercise program (Robertson et al., 2016). Whether these effects are independent of reversing drug-induced toxicity, these data suggest that exercise can contribute to healing drug-induced neural deficits. More work using neuroimaging is necessary to understand the mechanism by which anti-inflammatory drugs or aerobic exercise can affect and improve neural immune signaling pathways, thereby ameliorating drug-induced adaptations and adverse behavioral consequences of drug abuse.

Acknowledgments

Funding

This work was supported in part by NIAAA R21AA020039 (WFH), Department of Veterans Affairs Clinical Sciences Research and Development Career Development Program IK2CX001790 (MK), Merit Review Program CSRD (VA) I0CX001558 (WFH), Department of Veterans Affairs Biomedical Laboratory Research and Development Merit Review Program award 1I01BX002061 (JML), DOJ 2010-DD-BX-0517 (WFH), NIDA P50DA018165 (WFH, JML, MH), the Oregon Clinical and Translational Research Institute (OCTRI) grant number: 1 UL1 RR024140 01 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. MK was also supported by NIDA T32 DA007262, NIAAA T32 AA007468, Collins Medical Trust, and the Medical Research Foundation.

Abbreviations:

DA

dopamine

GABA

gamma-aminobutyric acid

IL

interleukin

PET

positron emission tomography

PPAR

peroxisome proliferator-activated receptors

TNF

tumor necrosis factor

TSPO

translocator protein

Footnotes

Publisher's Disclaimer: Disclaimer

The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.

References

  1. Agrawal RG, Hewetson A, George CM, Syapin PJ, Bergeson SE, 2011. Minocycline reduces ethanol drinking. Brain Behav. Immun 25 (Suppl. 1), S165–S169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arezoomandan R, Haghparast A, 2016. Administration of the glial cell modulator, minocycline, in the nucleus accumbens attenuated the maintenance and reinstatement of morphine-seeking behavior. Can. J. Physiol. Pharmacol 94, 257–264. [DOI] [PubMed] [Google Scholar]
  3. Attarzadeh-Yazdi G, Arezoomandan R, Haghparast A, 2014. Minocycline, an antibiotic with inhibitory effect on microglial activation, attenuates the maintenance and reinstatement of methamphetamine-seeking behavior in rat. Prog. NeuroPsychopharmacol. Biol. Psychiatry 53, 142–148. [DOI] [PubMed] [Google Scholar]
  4. Bachtell RK, Jones JD, Heinzerling KG, Beardsley PM, Comer SD, 2017. Glial and neuroinflammatory targets for treating substance use disorders. Drug Alcohol Depend 180, 156–170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Banerjee A, Zhang X, Manda KR, Banks WA, Ercal N, 2010. HIV proteins (gp120 and Tat) and methamphetamine in oxidative stress-induced damage in the brain: potential role of the thiol antioxidant N-acetylcysteine amide. Free Radic. Biol. Med 48, 1388–1398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bayazit H, Selek S, Karababa IF, Cicek E, Aksoy N, 2017. Evaluation of oxidant/ antioxidant status and cytokine levels in patients with cannabis use disorder. Clin. Psychopharmacol. Neurosci 15, 237–242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Beardsley PM, Hauser KF, 2014. Glial modulators as potential treatments of psychostimulant abuse. Adv. Pharmacol 69, 1–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Beardsley PM, Shelton KL, Hendrick E, Johnson KW, 2010. The glial cell modulator and phosphodiesterase inhibitor, AV411 (ibudilast), attenuates prime- and stress-induced methamphetamine relapse. Eur. J. Pharmacol 637, 102–108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bell RL, Lopez MF, Cui C, Egli M, Johnson KW, Franklin KM, Becker HC, 2015. Ibudilast reduces alcohol drinking in multiple animal models of alcohol dependence. Addict. Biol 20, 38–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Birtwistle J, Hall K, 1996. Does nicotine have beneficial effects in the treatment of certain diseases? Br. J. Nurs 5, 1195–1202. [DOI] [PubMed] [Google Scholar]
  11. Blednov YA, Benavidez JM, Black M, Ferguson LB, Schoenhard GL, Goate AM, Edenberg HJ, Wetherill L, Hesselbrock V, Foroud T, Harris RA, 2015. Peroxisome proliferator-activated receptors alpha and gamma are linked with alcohol consumption in mice and withdrawal and dependence in humans. Alcohol. Clin. Exp. Res 39, 136–145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Block ML, Hong JS, 2005. Microglia and inflammation-mediated neurodegeneration: multiple triggers with a common mechanism. Prog. Neurobiol 76, 77–98. [DOI] [PubMed] [Google Scholar]
  13. Brody AL, Mukhin AG, La Charite J, Ta K, Farahi J, Sugar CA, Mamoun MS, Vellios E, Archie M, Kozman M, Phuong J, Arlorio F, Mandelkern MA, 2013. Up-regulation of nicotinic acetylcholine receptors in menthol cigarette smokers. Int. J. Neuropsychopharmacol 16, 957–966. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Brody AL, Hubert R, Enoki R, Garcia LY, Mamoun MS, Okita K, London ED, Nurmi EL, Seaman LC, Mandelkern MA, 2017. Effect of cigarette smoking on a marker for neuroinflammation: a [(11)C]DAA1106 positron emission tomography study. Neuropsychopharmacology 42, 1630–1639. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Bull C, Syed WA, Minter SC, Bowers MS, 2015. Differential response of glial fibrillary acidic protein-positive astrocytes in the rat prefrontal cortex following ethanol self-administration. Alcohol. Clin. Exp. Res 39, 650–658. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Burnouf C, Pruniaux MP, 2002. Recent advances in PDE4 inhibitors as immunoregulators and anti-inflammatory drugs. Curr. Pharm. Des 8, 1255–1296. [DOI] [PubMed] [Google Scholar]
  17. Cao L, Fu M, Kumar S, Kumar A, 2016. Methamphetamine potentiates HIV-1 gp120-mediated autophagy via Beclin-1 and Atg5/7 as a pro-survival response in astrocytes. Cell Death Dis 7, e2425. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Chen H, Uz T, Manev H, 2009. Minocycline affects cocaine sensitization in mice. Neurosci. Lett 452, 258–261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Chen WW, Zhang X, Huang WJ, 2016. Role of neuroinflammation in neurodegenerative diseases (review). Mol. Med. Rep 13, 3391–3396. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Clark KH, Wiley CA, Bradberry CW, 2013. Psychostimulant abuse and neuroinflammation: emerging evidence of their interconnection. Neurotox. Res 23, 174–188. [DOI] [PubMed] [Google Scholar]
  21. Converse AK, Larsen EC, Engle JW, Barnhart TE, Nickles RJ, Duncan ID, 2011. 11C-(R)-PK11195 PET imaging of microglial activation and response to minocycline in zymosan-treated rats. J. Nucl. Med 52, 257–262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Cosenza-Nashat M, Zhao ML, Suh HS, Morgan J, Natividad R, Morgello S, Lee SC, 2009. Expression of the translocator protein of 18 kDa by microglia, macrophages and astrocytesbased on immunohistochemical localization in abnormal human brain. Neuropathol. Appl. Neurobiol 35, 306–328. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Crews FT, Walter TJ, Coleman LG Jr., Vetreno RP, 2017. Toll-like receptor signaling and stages of addiction. Psychopharmacology 234, 1483–1498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Cui C, Shurtleff D, Harris RA, 2014. Neuroimmune mechanisms of alcohol and drug addiction. Int. Rev. Neurobiol 118, 1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Daynes RA, Jones DC, 2002. Emerging roles of PPARs in inflammation and immunity. Nat. Rev. Immunol 2, 748–759. [DOI] [PubMed] [Google Scholar]
  26. Dean AC, Groman SM, Morales AM, London ED, 2012. An evaluation of the evidence that methamphetamine abuse causes cognitive decline in humans. Neuropsychopharmacology 38, 259–274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Dean AC, Kohno M, Hellemann G, London ED, 2014. Childhood maltreatment and amygdala connectivity in methamphetamine dependence: a pilot study. Brain Behav 4, 867–876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Delerive P, Fruchart JC, Staels B, 2001. Peroxisome proliferator-activated receptors in inflammation control. J. Endocrinol 169, 453–459. [DOI] [PubMed] [Google Scholar]
  29. Ernst T, Chang L, Leonido-Yee M, Speck O, 2000. Evidence for long-term neurotoxicity associated with methamphetamine abuse: a 1H MRS study. Neurology 54, 1344–1349. [DOI] [PubMed] [Google Scholar]
  30. Ersche KD, Hagan CC, Smith DG, Abbott S, Jones PS, Apergis-Schoute AM, Doffinger R, 2014. Aberrant disgust responses and immune reactivity in cocainedependent men. Biol. Psychiatry 75, 140–147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Farber K, Pannasch U, Kettenmann H, 2005. Dopamine and noradrenaline control distinct functions in rodent microglial cells. Mol. Cell. Neurosci 29, 128–138. [DOI] [PubMed] [Google Scholar]
  32. Fedota JR, Stein EA, 2015. Resting-state functional connectivity and nicotine addiction: prospects for biomarker development. Ann. N. Y. Acad. Sci 1349, 64–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Felger JC, Li Z, Haroon E, Woolwine BJ, Jung MY, Hu X, Miller AH, 2016. Inflammation is associated with decreased functional connectivity within corticostriatal reward circuitry in depression. Mol. Psychiatry 21, 1358–1365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Fitzmaurice PS, Tong J, Yazdanpanah M, Liu PP, Kalasinsky KS, Kish SJ, 2006. Levels of 4-hydroxynonenal and malondialdehyde are increased in brain of human chronic users of methamphetamine. J. Pharmacol. Exp. Ther 319, 703–709. [DOI] [PubMed] [Google Scholar]
  35. Fowler JS, Kroll C, Ferrieri R, Alexoff D, Logan J, Dewey SL, Schiffer W, Schlyer D, Carter P, King P, Shea C, Xu Y, Muench L, Benveniste H, Vaska P, Volkow ND, 2007. PET studies of d-methamphetamine pharmacokinetics in primates: comparison with l-methamphetamine and (−)-cocaine. J. Nucl. Med 48, 1724–1732. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Fowler JS, Volkow ND, Logan J, Alexoff D, Telang F, Wang GJ, Wong C, Ma Y, Kriplani A, Pradhan K, Schlyer D, Jayne M, Hubbard B, Carter P, Warner D, King P, Shea C, Xu Y, Muench L, Apelskog K, 2008. Fast uptake and long-lasting binding of methamphetamine in the human brain: comparison with cocaine. NeuroImage 43, 756–763. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Fox HC, D’Sa C, Kimmerling A, Siedlarz KM, Tuit KL, Stowe R, Sinha R, 2012. Immune system inflammation in cocaine dependent individuals: implications for medications development. Hum. Psychopharmacol 27, 156–166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Franklin TR, Wetherill RR, Jagannathan K, Johnson B, Mumma J, Hager N, Rao H, Childress AR, 2014. The effects of chronic cigarette smoking on gray matter volume: influence of sex. PLoS One 9, e104102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Fujita Y, Kunitachi S, Iyo M, Hashimoto K, 2012. The antibiotic minocycline prevents methamphetamine-induced rewarding effects in mice. Pharmacol. Biochem. Behav 101, 303–306. [DOI] [PubMed] [Google Scholar]
  40. Garrido-Mesa N, Zarzuelo A, Galvez J, 2013. Minocycline: far beyond an antibiotic. Br. J. Pharmacol 169, 337–352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Geng Y, Savage SM, Johnson LJ, Seagrave J, Sopori ML, 1995. Effects of nicotine on the immune response. I. Chronic exposure to nicotine impairs antigen receptor-mediated signal transduction in lymphocytes. Toxicol. Appl. Pharmacol 135, 268–278. [DOI] [PubMed] [Google Scholar]
  42. Geng Y, Savage SM, Razani-Boroujerdi S, Sopori ML, 1996. Effects of nicotine on the immune response. II. Chronic nicotine treatment induces T cell anergy. J. Immunol 156, 2384–2390. [PubMed] [Google Scholar]
  43. Gomez-Nicola D, Boche D, 2015. Post-mortem analysis of neuroinflammatory changes in human Alzheimer’s disease. Alzheimers Res. Ther 7, 42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Goncalves J, Martins T, Ferreira R, Milhazes N, Borges F, Ribeiro CF, Malva JO, Macedo TR, Silva AP, 2008. Methamphetamine-induced early increase of IL-6 and TNF-alpha mRNA expression in the mouse brain. Ann. N. Y. Acad. Sci 1139, 103–111. [DOI] [PubMed] [Google Scholar]
  45. Guan YZ, Jin XD, Guan LX, Yan HC, Wang P, Gong Z, Li SJ, Cao X, Xing YL, Gao TM, 2015. Nicotine inhibits microglial proliferation and is neuroprotective in global ischemia rats. Mol. Neurobiol 51, 1480–1488. [DOI] [PubMed] [Google Scholar]
  46. Halpern JH, Sholar MB, Glowacki J, Mello NK, Mendelson JH, Siegel AJ, 2003. Diminished interleukin-6 response to proinflammatory challenge in men and women after intravenous cocaine administration. J. Clin. Endocrinol. Metab 88, 1188–1193. [DOI] [PubMed] [Google Scholar]
  47. Hanisch UK, 2002. Microglia as a source and target of cytokines. Glia 40, 140–155. [DOI] [PubMed] [Google Scholar]
  48. Hannestad J, 2012. The application of PET imaging in psychoneuroimmunology research. Methods Mol. Biol 934, 325–353. [DOI] [PubMed] [Google Scholar]
  49. Haroon E, Woolwine BJ, Chen X, Pace TW, Parekh S, Spivey JR, Hu XP, Miller AH, 2014. IFN-alpha-induced cortical and subcortical glutamate changes assessed by magnetic resonance spectroscopy. Neuropsychopharmacology 39, 1777–1785. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Harris DS, Boxenbaum H, Everhart ET, Sequeira G, Mendelson JE, Jones RT, 2003. The bioavailability of intranasal and smoked methamphetamine. Clin. Pharmacol. Ther 74, 475–486. [DOI] [PubMed] [Google Scholar]
  51. Hashimoto K, Ishima T, Fujita Y, Zhang L, 2013. Antibiotic drug minocycline: a potential therapeutic drug for methamphetamine-related disorders. Nihon Arukoru Yakubutsu Igakkai Zasshi 48, 118–125. [PubMed] [Google Scholar]
  52. Henriques JF, Portugal CC, Canedo T, Relvas JB, Summavielle T, Socodato R, 2018. Microglia and alcohol meet at the crossroads: microglia as critical modulators of alcohol neurotoxicity. Toxicol. Lett 283, 21–31. [DOI] [PubMed] [Google Scholar]
  53. Hillmer AT, Sandiego CM, Hannestad J, Angarita GA, Kumar A, McGovern EM, Huang Y, O’Connor KC, Carson RE, O’Malley SS, Cosgrove KP, 2017. In vivo imaging of translocator protein, a marker of activated microglia, in alcohol dependence. Mol. Psychiatry 22, 1759–1766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Ida T, Hara M, Nakamura Y, Kozaki S, Tsunoda S, Ihara H, 2008. Cytokine-induced enhancement of calcium-dependent glutamate release from astrocytes mediated by nitric oxide. Neurosci. Lett 432, 232–236. [DOI] [PubMed] [Google Scholar]
  55. Imaizumi M, Briard E, Zoghbi SS, Gourley JP, Hong J, Fujimura Y, Pike VW, Innis RB, Fujita M, 2008. Brain and whole-body imaging in nonhuman primates of [11C]PBR28, a promising PET radioligand for peripheral benzodiazepine receptors. NeuroImage 39, 1289–1298. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Irwin MR, Olmos L, Wang M, Valladares EM, Motivala SJ, Fong T, Newton T, Butch A, Olmstead R, Cole SW, 2007. Cocaine dependence and acute cocaine induce decreases of monocyte proinflammatory cytokine expression across the diurnal period: autonomic mechanisms. J. Pharmacol. Exp. Ther 320, 507–515. [DOI] [PubMed] [Google Scholar]
  57. James JR, Nordberg A, 1995. Genetic and environmental aspects of the role of nicotinic receptors in neurodegenerative disorders: emphasis on Alzheimer’s disease and Parkinson’s disease. Behav. Genet 25, 149–159. [DOI] [PubMed] [Google Scholar]
  58. Jean-Gilles L, Gran B, Constantinescu CS, 2010. Interaction between cytokines, cannabinoids and the nervous system. Immunobiology 215, 606–610. [DOI] [PubMed] [Google Scholar]
  59. Jones JD, Comer SD, Metz VE, Manubay JM, Mogali S, Ciccocioppo R, Martinez S, Mumtaz M, Bisaga A, 2017. Pioglitazone, a PPARgamma agonist, reduces nicotine craving in humans, with marginal effects on abuse potential. Pharmacol. Biochem. Behav 163, 90–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Jucaite A, Cselenyi Z, Arvidsson A, Ahlberg G, Julin P, Varnas K, Stenkrona P, Andersson J, Halldin C, Farde L, 2012. Kinetic analysis and test-retest variability of the radioligand [11C](R)-PK11195 binding to TSPO in the human brain - a PET study in control subjects. EJNMMI Res 2, 15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Jufer RA, Wstadik A, Walsh SL, Levine BS, Cone EJ, 2000. Elimination of cocaine and metabolites in plasma, saliva, and urine following repeated oral administration to human volunteers. J. Anal. Toxicol 24, 467–477. [DOI] [PubMed] [Google Scholar]
  62. Kadhim S, McDonald J, Lambert DG, 2018. Opioids, gliosis and central immunomodulation. J. Anesth 32, 756–767. [DOI] [PubMed] [Google Scholar]
  63. Kalivas PW, 2007. Cocaine and amphetamine-like psychostimulants: neurocircuitry and glutamate neuroplasticity. Dialogues Clin. Neurosci 9, 389–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Kalk NJ, Guo Q, Owen D, Cherian R, Erritzoe D, Gilmour A, Ribeiro AS, McGonigle J, Waldman A, Matthews P, Cavanagh J, McInnes I, Dar K, Gunn R, Rabiner EA, Lingford-Hughes AR, 2017. Decreased hippocampal translocator protein (18 kDa) expression in alcohol dependence: a [(11)C]PBR28 PET study. Transl. Psychiatry 7, e996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Kalra R, Singh SP, Pena-Philippides JC, Langley RJ, Razani-Boroujerdi S, Sopori ML, 2004. Immunosuppressive and anti-inflammatory effects of nicotine administered by patch in an animal model. Clin. Diagn. Lab. Immunol 11, 563–568. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Kanegawa N, Collste K, Forsberg A, Schain M, Arakawa R, Jucaite A, Lekander M, Olgart Hoglund C, Kosek E, Lampa J, Halldin C, Farde L, Varrone A, Cervenka S, 2016. In vivo evidence of a functional association between immune cells in blood and brain in healthy human subjects. Brain Behav. Immun 54, 149–157. [DOI] [PubMed] [Google Scholar]
  67. Kielian T, Drew PD, 2003. Effects of peroxisome proliferator-activated receptor-gamma agonists on central nervous system inflammation. J. Neurosci. Res 71, 315–325. [DOI] [PubMed] [Google Scholar]
  68. Kim SW, Wiers CE, Tyler R, Shokri-Kojori E, Jang YJ, Zehra A, Freeman C, Ramirez V, Lindgren E, Miller G, Cabrera EA, Stodden T, Guo M, Demiral SB, Diazgranados N, Park L, Liow JS, Pike V, Morse C, Vendruscolo LF, Innis RB, Koob GF, Tomasi D, Wang GJ, Volkow ND, 2018. Influence of alcoholism and cholesterol on TSPO binding in brain: PET [(11)C]PBR28 studies in humans and rodents. Neuropsychopharmacology 43, 1832–1839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Kitamura O, Takeichi T, Wang EL, Tokunaga I, Ishigami A, Kubo S, 2010. Microglial and astrocytic changes in the striatum of methamphetamine abusers. Leg. Med. (Tokyo) 12, 57–62. [DOI] [PubMed] [Google Scholar]
  70. Kohno M, Morales AM, Ghahremani DG, Hellemann G, London ED, 2014. Risky decision making, prefrontal cortex, and mesocorticolimbic functional connectivity in methamphetamine dependence. JAMA Psychiat 71, 812–820. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Kohno M, Okita K, Morales AM, Robertson CL, Dean AC, Ghahremani DG, Sabb FW, Rawson RA, Mandelkern MA, Bilder RM, London ED, 2016. Midbrain functional connectivity and ventral striatal dopamine D2-type receptors: link to impulsivity in methamphetamine users. Mol. Psychiatry 21, 1554–1560. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Kohno M, Loftis JM, Huckans M, Dennis LE, McCready H, Hoffman WF, 2018. The relationship between interleukin-6 and functional connectivity in methamphetamine users. Neurosci. Lett 677, 49–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Koob GF, 1998. Circuits, drugs, and drug addiction. Adv. Pharmacol 42, 978–982. [DOI] [PubMed] [Google Scholar]
  74. Kuhn SA, van Landeghem FK, Zacharias R, Farber K, Rappert A, Pavlovic S, Hoffmann A, Nolte C, Kettenmann H, 2004. Microglia express GABA(B) receptors to modulate interleukin release. Mol. Cell. Neurosci 25, 312–322. [DOI] [PubMed] [Google Scholar]
  75. Lacagnina MJ, Rivera PD, Bilbo SD, 2017. Glial and neuroimmune mechanisms as critical modulators of drug use and abuse. Neuropsychopharmacology 42, 156–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Lavisse S, Guillermier M, Herard AS, Petit F, Delahaye M, Van Camp N, Ben Haim L, Lebon V, Remy P, Dolle F, Delzescaux T, Bonvento G, Hantraye P, Escartin C, 2012. Reactive astrocytes overexpress TSPO and are detected by TSPO positron emission tomography imaging. J. Neurosci 32, 10809–10818. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. LaVoie MJ, Card JP, Hastings TG, 2004. Microglial activation precedes dopamine terminal pathology in methamphetamine-induced neurotoxicity. Exp. Neurol 187, 47–57. [DOI] [PubMed] [Google Scholar]
  78. Lawson LJ, Perry VH, Dri P, Gordon S, 1990. Heterogeneity in the distribution and morphology of microglia in the normal adult mouse brain. Neuroscience 39, 151–170. [DOI] [PubMed] [Google Scholar]
  79. Le Foll B, Di Ciano P, Panlilio LV, Goldberg SR, Ciccocioppo R, 2013. Peroxisome proliferator-activated receptor (PPAR) agonists as promising new medications for drug addiction: preclinical evidence. Curr. Drug Targets 14, 768–776. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Lerman C, Gu H, Loughead J, Ruparel K, Yang Y, Stein EA, 2014. Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function. JAMA Psychiat 71, 523–530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Levandowski ML, Hess AR, Grassi-Oliveira R, de Almeida RM, 2016. Plasma interleukin-6 and executive function in crack cocaine-dependent women. Neurosci. Lett 628, 85–90. [DOI] [PubMed] [Google Scholar]
  82. Little KY, Ramssen E, Welchko R, Volberg V, Roland CJ, Cassin B, 2009. Decreased brain dopamine cell numbers in human cocaine users. Psychiatry Res 168, 173–180. [DOI] [PubMed] [Google Scholar]
  83. Liu H, Leak RK, Hu X, 2016. Neurotransmitter receptors on microglia. Stroke Vasc. Neurol 1, 52–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Loftis JM, Huckans M, 2013. Substance use disorders: psychoneuroimmunological mechanisms and new targets for therapy. Pharmacol. Ther 139, 289–300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Loftis JM, Janowsky A, 2014. Neuroimmune basis of methamphetamine toxicity. Int. Rev. Neurobiol 118, 165–197. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Loftis JM, Choi D, Hoffman W, Huckans MS, 2011. Methamphetamine causes persistent immune dysregulation: a cross-species, translational report. Neurotox. Res 20, 59–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. London ED, Kohno M, Morales AM, Ballard ME, 2015. Chronic methamphetamine abuse and corticostriatal deficits revealed by neuroimaging. Brain Res 1628, 174–185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Lyoo CH, Ikawa M, Liow JS, Zoghbi SS, Morse CL, Pike VW, Fujita M, Innis RB, Kreisl WC, 2015. Cerebellum can serve as a pseudo-reference region in Alzheimer disease to detect neuroinflammation measured with PET radioligand binding to translocator protein. J. Nucl. Med 56, 701–706. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Maeda T, Kiguchi N, Fukazawa Y, Yamamoto A, Ozaki M, Kishioka S, 2007. Peroxisome proliferator-activated receptor gamma activation relieves expression of behavioral sensitization to methamphetamine in mice. Neuropsychopharmacology 32, 1133–1140. [DOI] [PubMed] [Google Scholar]
  90. Mahajan SD, Aalinkeel R, Sykes DE, Reynolds JL, Bindukumar B, Adal A, Qi M, Toh J, Xu G, Prasad PN, Schwartz SA, 2008. Methamphetamine alters blood brain barrier permeability via the modulation of tight junction expression: implication for HIV-1 neuropathogenesis in the context of drug abuse. Brain Res 1203, 133–148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Martín-Moreno AM, Brera B, Spuch C, Carro E, García-García L, Delgado M, Pozo MA, Innamorato NG, Cuadrado A, de Ceballos ML, 2012. Prolonged oral cannabinoid administration prevents neuroinflammation, lowers β-amyloid levels and improves cognitive performance in Tg APP 2576 mice. J. Neuroinflammation 9, 8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Mayfield J, Ferguson L, Harris RA, 2013. Neuroimmune signaling: a key component of alcohol abuse. Curr. Opin. Neurobiol 23, 513–520. [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. McCoy KL, 2016. Interaction between cannabinoid system and toll-like receptors controls inflammation. Mediat. Inflamm 2016, 5831315. [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Mizuno T, Kurotani T, Komatsu Y, Kawanokuchi J, Kato H, Mitsuma N, Suzumura A, 2004. Neuroprotective role of phosphodiesterase inhibitor ibudilast on neuronal cell death induced by activated microglia. Neuropharmacology 46, 404–411. [DOI] [PubMed] [Google Scholar]
  95. Morales AM, Lee B, Hellemann G, O’Neill J, London ED, 2012. Gray-matter volume in methamphetamine dependence: cigarette smoking and changes with abstinence from methamphetamine. Drug Alcohol Depend 125, 230–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Morales AM, Ghahremani D, Kohno M, Hellemann GS, London ED, 2014. Cigarette exposure, dependence, and craving are related to insula thickness in young adult smokers. Neuropsychopharmacology 39, 1816–1822. [DOI] [PMC free article] [PubMed] [Google Scholar]
  97. Moreira FP, Medeiros JR, Lhullier AC, Souza LD, Jansen K, Portela LV, Lara DR, da Silva RA, Wiener CD, Oses JP, 2016. Cocaine abuse and effects in the serum levels of cytokines IL-6 and IL-10. Drug Alcohol Depend 158, 181–185. [DOI] [PubMed] [Google Scholar]
  98. Moszczynska A, Fitzmaurice P, Ang L, Kalasinsky KS, Schmunk GA, Peretti FJ, Aiken SS, Wickham DJ, Kish SJ, 2004. Why is parkinsonism not a feature of human methamphetamine users? Brain 127, 363–370. [DOI] [PubMed] [Google Scholar]
  99. Narendran R, Lopresti BJ, Mason NS, Deuitch L, Paris J, Himes ML, Kodavali CV, Nimgaonkar VL, 2014. Cocaine abuse in humans is not associated with increased microglial activation: an 18-kDa translocator protein positron emission tomography imaging study with [11C]PBR28. J. Neurosci 34, 9945–9950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  100. Newhouse PA, Potter A, Levin ED, 1997. Nicotinic system involvement in Alzheimer’s and Parkinson’s diseases. Implications for therapeutics. Drugs Aging 11, 206–228. [DOI] [PubMed] [Google Scholar]
  101. Notter T, Coughlin JM, Gschwind T, Weber-Stadlbauer U, Wang Y, Kassiou M, Vernon AC, Benke D, Pomper MG, Sawa A, Meyer U, 2018. Translational evaluation of translocator protein as a marker of neuroinflammation in schizophrenia. Mol. Psychiatry 23, 323–334. [DOI] [PubMed] [Google Scholar]
  102. Ojaniemi M, Glumoff V, Harju K, Liljeroos M, Vuori K, Hallman M, 2003. Phosphatidylinositol 3-kinase is involved in Toll-like receptor 4-mediated cytokine expression in mouse macrophages. Eur. J. Immunol 33, 597–605. [DOI] [PubMed] [Google Scholar]
  103. Otten U, Marz P, Heese K, Hock C, Kunz D, Rose-John S, 2000. Cytokines and neurotrophins interact in normal and diseased states. Ann. N. Y. Acad. Sci 917, 322–330. [DOI] [PubMed] [Google Scholar]
  104. Owen DR, Guo Q, Kalk NJ, Colasanti A, Kalogiannopoulou D, Dimber R, Lewis YL, Libri V, Barletta J, Ramada-Magalhaes J, Kamalakaran A, Nutt DJ, Passchier J, Matthews PM, Gunn RN, Rabiner EA, 2014. Determination of [(11)C]PBR28 binding potential in vivo: a first human TSPO blocking study. J. Cereb. Blood Flow Metab 34 (6), 989–994. [DOI] [PMC free article] [PubMed] [Google Scholar]
  105. Pacher P, Kunos G, 2013. Modulating the endocannabinoid system in human health and disease–successes and failures. FEBS J 280, 1918–1943. [DOI] [PMC free article] [PubMed] [Google Scholar]
  106. Pascual M, Montesinos J, Marcos M, Torres JL, Costa-Alba P, Garcia-Garcia F, Laso FJ, Guerri C, 2017. Gender differences in the inflammatory cytokine and chemokine profiles induced by binge ethanol drinking in adolescence. Addict. Biol 22, 1829–1841. [DOI] [PubMed] [Google Scholar]
  107. Pocock JM, Kettenmann H, 2007. Neurotransmitter receptors on microglia. Trends Neurosci 30, 527–535. [DOI] [PubMed] [Google Scholar]
  108. Ransohoff RM, Brown MA, 2012. Innate immunity in the central nervous system. J. Clin. Invest 122, 1164–1171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Ray LA, Roche DJ, Heinzerling K, Shoptaw S, 2014. Opportunities for the development of neuroimmune therapies in addiction. Int. Rev. Neurobiol 118, 381–401. [DOI] [PubMed] [Google Scholar]
  110. Ray LA, Bujarski S, Shoptaw S, Roche DJ, Heinzerling K, Miotto K, 2017. Development of the neuroimmune modulator ibudilast for the treatment of alcoholism: a randomized, placebo-controlled, human laboratory trial. Neuropsychopharmacology 42, 1776–1788. [DOI] [PMC free article] [PubMed] [Google Scholar]
  111. Rizzo G, Veronese M, Tonietto M, Zanotti-Fregonara P, Turkheimer FE, Bertoldo A, 2014. Kinetic modeling without accounting for the vascular component impairs the quantification of [(11)C]PBR28 brain PET data. J. Cereb. Blood Flow Metab 34, 1060–1069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  112. Rizzo MD, Crawford RB, Henriquez JE, Aldhamen YA, Gulick P, Amalfitano A, Kaminski NE, 2018. HIV-infected cannabis users have lower circulating CD16+ monocytes and IFN-gamma-inducible protein 10 levels compared with nonusing HIV patients. AIDS 32, 419–429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  113. Robertson CL, Ishibashi K, Chudzynski J, Mooney LJ, Rawson RA, Dolezal BA, Cooper CB, Brown AK, Mandelkern MA, London ED, 2016. Effect of exercise training on striatal dopamine D2/D3 receptors in methamphetamine users during behavioral treatment. Neuropsychopharmacology 41, 1629–1636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  114. Saba W, Goutal S, Auvity S, Kuhnast B, Coulon C, Kouyoumdjian V, Buvat I, Leroy C, Tournier N, 2017. Imaging the neuroimmune response to alcohol exposure in adolescent baboons: a TSPO PET study using (18) F-DPA-714. Addict. Biol 10.1111/adb.12548 [Epub ahead of print]. [DOI] [PubMed]
  115. Sabbagh MN, Lukas RJ, Sparks DL, Reid RT, 2002. The nicotinic acetylcholine receptor, smoking, and Alzheimer’s disease. J. Alzheimers Dis 4, 317–325. [DOI] [PubMed] [Google Scholar]
  116. Savage SM, Donaldson LA, Cherian S, Chilukuri R, White VA, Sopori ML, 1991. Effects of cigarette smoke on the immune response. II. Chronic exposure to cigarette smoke inhibits surface immunoglobulin-mediated responses in B cells. Toxicol. Appl. Pharmacol 111, 523–529. [DOI] [PubMed] [Google Scholar]
  117. Scheller J, Chalaris A, Schmidt-Arras D, Rose-John S, 2011. The pro- and anti-inflammatory properties of the cytokine interleukin-6. Biochim. Biophys. Acta 1813, 878–888. [DOI] [PubMed] [Google Scholar]
  118. Schmitz JM, Green CE, Hasan KM, Vincent J, Suchting R, Weaver MF, Moeller FG, Narayana PA, Cunningham KA, Dineley KT, Lane SD, 2017. PPAR-gamma agonist pioglitazone modifies craving intensity and brain white matter integrity in patients with primary cocaine use disorder: a double-blind randomized controlled pilot trial. Addiction 112, 1861–1868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  119. Schwaeble W, Constantinescu CS, 2010. Relationship between cannabinoids and the immune system. Special Issue 8, 2010 Introduction. Immunobiology 215, 587. [DOI] [PubMed] [Google Scholar]
  120. Sekine Y, Minabe Y, Kawai M, Suzuki K, Iyo M, Isoda H, Sakahara H, Ashby CR Jr., Takei N, Mori N, 2002. Metabolite alterations in basal ganglia associated with methamphetamine-related psychiatric symptoms. A proton MRS study. Neuropsychopharmacology 27, 453–461. [DOI] [PubMed] [Google Scholar]
  121. Sekine Y, Ouchi Y, Sugihara G, Takei N, Yoshikawa E, Nakamura K, Iwata Y, Tsuchiya KJ, Suda S, Suzuki K, Kawai M, Takebayashi K, Yamamoto S, Matsuzaki H, Ueki T, Mori N, Gold MS, Cadet JL, 2008. Methamphetamine causes microglial activation in the brains of human abusers. J. Neurosci 28, 5756–5761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  122. Shah A, Silverstein PS, Singh DP, Kumar A, 2012. Involvement of metabotropic glutamate receptor 5, AKT/PI3K signaling and NF-kappaB pathway in methamphetamine-mediated increase in IL-6 and IL-8 expression in astrocytes. J. Neuroinflammation 9, 52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  123. Shin EJ, Tran HQ, Nguyen PT, Jeong JH, Nah SY, Jang CG, Nabeshima T, Kim HC, 2018. Role of mitochondria in methamphetamine-induced dopaminergic neurotoxicity: involvement in oxidative stress, neuroinflammation, and pro-apoptosis-a review. Neurochem. Res 43, 57–69. [DOI] [PubMed] [Google Scholar]
  124. Silverstein PS, Shah A, Gupte R, Liu X, Piepho RW, Kumar S, Kumar A, 2011. Methamphetamine toxicity and its implications during HIV-1 infection. J. Neuro-Oncol 17, 401–415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  125. Snider SE, Hendrick ES, Beardsley PM, 2013. Glial cell modulators attenuate methamphetamine self-administration in the rat. Eur. J. Pharmacol 701, 124–130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  126. Sofuoglu M, Waters AJ, Mooney M, O’Malley SS, 2009. Minocycline reduced craving for cigarettes but did not affect smoking or intravenous nicotine responses in humans. Pharmacol. Biochem. Behav 92, 135–140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  127. Sofuoglu M, Mooney M, Kosten T, Waters A, Hashimoto K, 2011. Minocycline attenuates subjective rewarding effects of dextroamphetamine in humans. Psychopharmacology 213, 61–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  128. Sopori M, 2002. Effects of cigarette smoke on the immune system. Nat. Rev. Immunol 2, 372–377. [DOI] [PubMed] [Google Scholar]
  129. Sopori ML, Kozak W, 1998. Immunomodulatory effects of cigarette smoke. J. Neuroimmunol 83, 148–156. [DOI] [PubMed] [Google Scholar]
  130. Stella N, 2009. Endocannabinoid signaling in microglial cells. Neuropharmacology 56 (Suppl. 1), 244–253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  131. Stopponi S, Somaini L, Cippitelli A, Cannella N, Braconi S, Kallupi M, Ruggeri B, Heilig M, Demopulos G, Gaitanaris G, Massi M, Ciccocioppo R, 2011. Activation of nuclear PPARgamma receptors by the antidiabetic agent pioglitazone suppresses alcohol drinking and relapse to alcohol seeking. Biol. Psychiatry 69, 642–649. [DOI] [PubMed] [Google Scholar]
  132. Stopponi S, de Guglielmo G, Somaini L, Cippitelli A, Cannella N, Kallupi M, Ubaldi M, Heilig M, Demopulos G, Gaitanaris G, Ciccocioppo R, 2013. Activation of PPARgamma by pioglitazone potentiates the effects of naltrexone on alcohol drinking and relapse in msP rats. Alcohol. Clin. Exp. Res 37, 1351–1360. [DOI] [PubMed] [Google Scholar]
  133. Suryanarayanan A, Carter JM, Landin JD, Morrow AL, Werner DF, Spigelman I, 2016. Role of interleukin-10 (IL-10) in regulation of GABAergic transmission and acute response to ethanol. Neuropharmacology 107, 181–188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  134. Suzumura A, Ito A, Yoshikawa M, Sawada M, 1999. Ibudilast suppresses TNFalpha production by glial cells functioning mainly as type III phosphodiesterase inhibitor in the CNS. Brain Res 837, 203–212. [DOI] [PubMed] [Google Scholar]
  135. Tanasescu R, Constantinescu CS, 2010. Cannabinoids and the immune system: an overview. Immunobiology 215, 588–597. [DOI] [PubMed] [Google Scholar]
  136. Tansey MG, McCoy MK, Frank-Cannon TC, 2007. Neuroinflammatory mechanisms in Parkinson’s disease: potential environmental triggers, pathways, and targets for early therapeutic intervention. Exp. Neurol 208, 1–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  137. Thomas DM, Walker PD, Benjamins JA, Geddes TJ, Kuhn DM, 2004. Methamphetamine neurotoxicity in dopamine nerve endings of the striatum is associated with microglial activation. J. Pharmacol. Exp. Ther 311, 1–7. [DOI] [PubMed] [Google Scholar]
  138. Tilleux S, Hermans E, 2007. Neuroinflammation and regulation of glial glutamate uptake in neurological disorders. J. Neurosci. Res 85, 2059–2070. [DOI] [PubMed] [Google Scholar]
  139. Vetreno RP, Broadwater M, Liu W, Spear LP, Crews FT, 2014. Adolescent, but not adult, binge ethanol exposure leads to persistent global reductions of choline acetyltransferase expressing neurons in brain. PLoS One 9, e113421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  140. Wang H, Yu M, Ochani M, Amella CA, Tanovic M, Susarla S, Li JH, Wang H, Yang H, Ulloa L, Al-Abed Y, Czura CJ, Tracey KJ, 2003. Nicotinic acetylcholine receptor alpha7 subunit is an essential regulator of inflammation. Nature 421, 384–388. [DOI] [PubMed] [Google Scholar]
  141. Wilhelm CJ, Fuller BE, Huckans M, Loftis JM, 2017. Peripheral immune factors are elevated in women with current or recent alcohol dependence and associated with altered mood and memory. Drug Alcohol Depend 176, 71–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  142. Willson TM, Brown PJ, Sternbach DD, Henke BR, 2000. The PPARs: from orphan receptors to drug discovery. J. Med. Chem 43, 527–550. [DOI] [PubMed] [Google Scholar]
  143. Wilson JM, Kalasinsky KS, Levey AI, Bergeron C, Reiber G, Anthony RM, Schmunk GA, Shannak K, Haycock JW, Kish SJ, 1996. Striatal dopamine nerve terminal markers in human, chronic methamphetamine users. Nat. Med 2, 699–703. [DOI] [PubMed] [Google Scholar]
  144. Wisor JP, Schmidt MA, Clegern WC, 2011. Cerebral microglia mediate sleep/wake and neuroinflammatory effects of methamphetamine. Brain Behav. Immun 25, 767–776. [DOI] [PubMed] [Google Scholar]
  145. Worley MJ, Heinzerling KG, Roche DJ, Shoptaw S, 2016. Ibudilast attenuates subjective effects of methamphetamine in a placebo-controlled inpatient study. Drug Alcohol Depend 162, 245–250. [DOI] [PMC free article] [PubMed] [Google Scholar]
  146. Zamberletti E, Gabaglio M, Prini P, Rubino T, Parolaro D, 2015. Cortical neuroinflammation contributes to long-term cognitive dysfunctions following adolescent delta-9-tetrahydrocannabinol treatment in female rats. Eur. Neuropsychopharmacol 25, 2404–2415. [DOI] [PubMed] [Google Scholar]
  147. Zhang L, Kitaichi K, Fujimoto Y, Nakayama H, Shimizu E, Iyo M, Hashimoto K, 2006. Protective effects of minocycline on behavioral changes and neurotoxicity in mice after administration of methamphetamine. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 30, 1381–1393. [DOI] [PubMed] [Google Scholar]
  148. Zhang M, Martin BR, Adler MW, Razdan RJ, Kong W, Ganea D, Tuma RF, 2009. Modulation of cannabinoid receptor activation as a neuroprotective strategy for EAE and stroke. J. NeuroImmune Pharmacol 4, 249–259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  149. Zhang K, Zhang Q, Jiang H, Du J, Zhou C, Yu S, Hashimoto K, Zhao M, 2018. Impact of aerobic exercise on cognitive impairment and oxidative stress markers in methamphetamine-dependent patients. Psychiatry Res 266, 328–333. [DOI] [PubMed] [Google Scholar]

RESOURCES