Inflammatory biomarkers in addictive disorders

biomolecules Review Inflammatory Biomarkers in Addictive Disorders Alvaro Morcuende 1, Francisco Navarrete 1,2 , Elena Nieto 1, Jorge Manzanares 1,2 and Teresa Femenía1,2,*   Citation: Morcuende, A.; Navarrete, F.; Nieto, E.; Manzanares, J.; Femenía, T. Inflammatory Biomarkers in Addictive Disorders. Biomolecules 2021,11, 1824. https://doi.org/ 10.3390/biom11121824 Academic Editor: Livio Luongo Received: 23 October 2021 Accepted: 30 November 2021 Published: 3 December 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda. de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain; [email protected] (A.M.); fnavarr[email protected] (F.N.); [email protected] (E.N.); [email protected] (J.M.) 2Red Temática de Investigación Cooperativa en Salud (RETICS), Red de Trastornos Adictivos, Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain *Correspondence: [email protected]; Tel.: +34-965-919-553 Abstract: Substance use disorders are a group of diseases that are associated with social, professional, and family impairment and that represent a high socio-economic impact on the health systems of countries around the world. These disorders present a very complex diagnosis and treatment regimen due to the lack of suitable biomarkers supporting the correct diagnosis and classification and the difficulty of selecting effective therapies. Over the last few years, several studies have pointed out that these addictive disorders are associated with systemic and central nervous system inflammation, which could play a relevant role in the onset and progression of these diseases. Therefore, identifying different immune system components as biomarkers of such addictive disorders could be a crucial step to promote appropriate diagnosis and treatment. Thus, this work aims to provide an overview of the immune system alterations that may be biomarkers of various addictive disorders. Keywords: inflammation; addiction; cannabinoid; alcohol; opioid; biomarker; diagnostic 1. Introduction Inflammation is a physiological process that helps to repair tissue damage and resolve infections. However, abnormal responses or chronic inflammation can be pathological. There is an increase of proinflammatory cytokines and C-reactive protein (CRP) during inflammation, an acute-phase protein of hepatic origin that is released to the plasma in response to inflammation. These inflammatory mediators are associated with several psychiatric disorders [ 1 , 2 ] and have been shown to contribute to the development of neuroinflammation [ 3 ]. Neuroinflammatory processes are widely implicated in many psychiatric diseases, including major depression, anxiety disorders, schizophrenia, or substance use disorder (SUD) [ 4 – 6 ]. Peripheral inflammatory states can contribute to neuroinflammation through several alterations in various organs and tissues. Among the most notable alterations is the disruption of the blood–brain barrier, which facilitates the infiltration of inflammatory mediators into the central nervous system and alterations in the intestinal permeability that are associated with changes in the composition of the gut microbiota. Consequently, an increase in microbiota products and derivatives [ 7 ] may play a relevant role in activating the innate immune system, triggering a systemic inflammatory reaction followed by an adaptive immune response [8]. One of the main routes of starting the innate immune system is through the nuclear factor kappa-light-chain-enhancer of the activated B cell (NF-kB) signaling pathway. This pathway promotes the release of proinflammatory cytokines such as Interleukin-1 beta (IL-1 β ) and tumor necrosis factor-alpha (TNFα ), influencing the neurobiological processes that occur during the development of addiction [ 9 ]. Cytokines are small proteins that have a specific effect on the interactions and communications between cells. Some of them, such as IL-6 or IL-10 and INF-y, may carry mixed actions with proor anti-inflammatory actions depending on the specific situation [ 10 , 11 ]. In turn, proinflammatory cytokines can cross the Blood Brain Barrier (BBB) to enter the brain and to trigger neuroinflammation Biomolecules 2021,11, 1824. https://doi.org/10.3390/biom11121824 https://www.mdpi.com/journal/biomolecules Biomolecules 2021,11, 1824 2 of 34 in addition to prompting BBB disruption. CRP also contributes to the leakage of the BBB [ 3 ] and has been positioned as a potential biomarker of neuroinflammation in major psychiatric disorders [12,13]. In addition to inflammatory cytokines, different elements are released into the extracellular space when damage takes place and are recognized by the innate immune system components. These elements are called “Damage associated Molecular Patterns” (DAMPS) and are recognized by specific receptors, which are known as Pattern Recognition Receptors (PRR), which are composed of several families of receptors. Within the PRRs, Toll-Like Receptors (TLRs) or NOD-Like Receptors (NLRs) can be highlighted. These receptors recognize DAMPS and Pathogen-Associated Molecular Patterns (PAMPS) or products that are associated with oxidative stress, such as reactive oxygen species (ROS). Once these PRRs are activated, a signaling cascade is initiated that releases inflammatory mediators through pathways such as the NF-kB [14–16]. Recently, several studies have focused on determining the association between inflammation and SUD, which has given rise to many findings in this regard. However, it is still unclear how the immune system and inflammatory mediators may be associated with the vulnerability for the development of SUD, its progression, and whether immunotherapy may be an appropriate approach to tackle these disorders. In addition, the existence of disease-associated microglia (DAM) and disease-associated astrocytes (DAA) has been recently identified. Recent studies show how microglia and astrocytes acquire different phenotypes in neuroinflammatory and degenerative diseases and aging [ 17 – 20 ]. As a result of a complex process, their phenotype can be protective or associated with the disease. Immune cells that do not release high proinflammatory cytokines when exposed to a trigger such as a lipopolysaccharide (LPS) cannot just be considered more anti-inflammatory. Therefore, prolonged neuroinflammation could result in a dystrophic phenotype and a non-responsive state by the microglia and astrocytes, resulting in different responses in the release of proinflammatory cytokines. In the case of substance use disorders (SUD), studies related to DAM and DAA and the specific phenotypes associated with the development and the stage of the disease are still very limited. It has been shown how different cell types can synthesize proinflammatory cytokines, both neuronal and glial, and how they can substantially affect brain physiology, such as IL-6 or IL-1 β in Long Term Potentiation (LTP), memory, and synaptic plasticity [ 21 , 22 ]. These neuroadaptive changes also occur in SUD, where alterations in the innate immune system associated with areas of the mesolimbic system and processes involved in addictive behaviors have been seen [ 9 , 23 , 24 ]. On the other hand, among TLRs, of which 13 have been described in mice and only 10 have been described in humans [ 16 ], the most studied receptor was TLR4. This receptor is involved in behavioral deficits that result due to alcohol consumption [ 25 ], alterations in synaptic plasticity, and opioid drug reinforcement [ 26 ]. However, the growing interest in the innate immune system highlights the involvement of other receptors, such as TLR3, TLR7, and NPRL3, in the case of substance disorders that are related to alcohol [ 27 – 29 ]. Furthermore, these mechanisms are postulated to be the potential therapeutic targets for substance use disorders [24]. The diagnosis and prognosis of SUD are limited by the lack of specific biomarkers, with clinical diagnosis largely being based on addiction scales and questionnaires as the primary classification tool. This is a significant disadvantage compared to other diseases, as patients with very heterogeneous clinical features are classified under the umbrella of a single diagnosis. Therefore, to improve the therapeutic process, identifying more specific and sensitive markers, particularly biomarkers that have good reproducibility, a good signal-to-noise ratio, and, very importantly, reflect the dynamism and clinical progression of the disease, are needed [ 30 ]. The purpose of this review is to evaluate the role of the immune system in substance use disorders and focuses on substances that act as nervous system depressants to assess its potential use as a biomarker and to guide future research. Biomolecules 2021,11, 1824 3 of 34 2. Methods The literature review searched for scientific information in the Medline database (PubMed) and employed Medical Subject Headings (MeSH). A total of three search boxes were employed according to the total number of drugs included in the review. The terms “cannabinoid,” “alcohol,” and “opioid” were combined with the term “inflammatory markers” by the Boolean operator “AND”. All of the authors critically analyzed the results of each search to decide the selection of the references according to the adequacy of its content with the subject matter of the study. No PubMed filters were applied to maximize the selection of all of the available and appropriate information. All original articles, systematic reviews, or meta-analyses identifying relevant inflammatory biomarkers in cannabinoid, alcohol, or opioid addiction were accepted. Those articles not related to the topic of interest, not written in English, or to which access was not possible were discarded. 3. Cannabinoids Cannabis, such as hashish or marijuana, is the most commonly used illicit drug worldwide. Available data suggest that the prevalence and incidence of its consumption continue to rise in the next few years, thus representing a serious public health problem [ 31 ]. Approximately 24% of patients initiating treatment for substance abuse have a cannabis use disorder (CUD) diagnosis [ 32 ]. According to the last World Drug Report [ 33 ], two hundred million people used marijuana (cannabis) in 2019. Importantly, this report also alerts about the worrying reduction in the risk perception that is associated with cannabis use among adolescents and the 4-fold increase in cannabis herb potency (the content of Delta9-Tetrahydrocannabinol (THC)). An evaluation of the global disease burden indicates that CUD encompassing intoxication, withdrawal syndrome, and dependence criteria accounted for 2 million disability-adjusted life years (DALYs) globally in 2010 [34]. 3.1. Endocannabinoid-Mediated Regulation of the Immune System The involvement of the endocannabinoid system in the regulation of the immune system was first described when a peripheral receptor for cannabinoids (cannabinoid 2 receptor (CB2r)) was identified and characterized in the macrophages found in the marginal zone of the spleen [ 35 ]. Human cannabinoid receptors and their gene transcripts were also identified in the blood samples from regular human volunteers who reported no prior use of marijuana [ 36 ]. Several reports using endocannabinoids, natural cannabinoids, and synthetic cannabinoids revealed a significant role of these compounds on inflammation and immunomodulation [ 37 – 39 ]. Several reports have accounted for the anti-inflammatory properties of THC and other cannabinoids through multiple immunerelated mechanisms, such as the suppression of TNFα and other cytokines such as IL-6, IFNγ , and IL-12 [ 40 – 42 ]. Thus, accumulated evidence points to the fact that cannabis extracts could modulate immune function, an essential factor that should be considered both from the recreational and therapeutic point of view associated with the use of cannabis and its derivatives. The following sections compile the studies that have evaluated the changes that occur in different immune system targets after cannabis use, which could be useful as potential biomarkers (Table 1). Biomolecules 2021,11, 1824 4 of 34 Table 1. Main findings from animal and clinical studies evaluating changes of inflammatory biomarkers after exposure to cannabinoids. Target Experimental Design Sample Major Finding Species Method References IL-1β Sub-chronic THC administration Peritoneal macrophages stimulated with LPS ↓IL-1βjust after 10-day THC treatment during adolescence or adulthood BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Peritoneal macrophages stimulated with LPS ↑IL-1βin adult animals as a long-term effect after 10-day THC treatment during adolescence BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Chronic cannabis use Saliva No significant changes in marijuana users Human ELISA [45] Serum ↑IL-1βin patients diagnosed with Cannabis use disorder Human ELISA [46] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] IL-1αChronic cannabis use Serum No significant changes in marijuana users Human ELISA [48] IL-2 Acute THC administration Splenocytes ↓IL-2 after an acute or sub-chronic (7 days) THC exposure Swiss mice ELISA [49] Sub-chronic THC administration Chronic THC administration No significant changes after chronic (14 days) THC treatment Chronic cannabis use Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] Blood ↓IL-2 in marijuana users Human ELISA [50] Biomolecules 2021,11, 1824 5 of 34 Table 1. Cont. Target Experimental Design Sample Major Finding Species Method References IL-6 Chronic cannabis use Alveolar macrophages stimulated with LPS ↓IL-6 in marijuana users Human ELISA [51] Bronchial epithelial cells ↑IL-6 in marijuana users Human ELISA [52] Serum ↓IL-6 in marijuana users Human ELISA [53] Plasma ↓IL-6 in marijuana users Human ELISA [54] Serum ↓IL-6 in marijuana users Human ELISA [55] Saliva ↑IL-6 in marijuana users Human ELISA [45] Serum ↑IL-6 in patients diagnosed with cannabis use disorder Human ELISA [46] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] Serum No significant changes in marijuana users Human ELISA [56] IL-8 Chronic cannabis use Bronchial lavage samples No significant changes in marijuana users Human ELISA [57] ↑IL-8 in marijuana and tobacco users Bronchial epithelial cells No significant changes in marijuana users Human ELISA [52] Serum ↑IL-8 in patients diagnosed with cannabis use disorder Human ELISA [46] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] Biomolecules 2021,11, 1824 6 of 34 Table 1. Cont. Target Experimental Design Sample Major Finding Species Method References IL-10 Chronic cannabis use Bronchial epithelial cells No significant changes in marijuana users Human ELISA [52] Plasma No significant changes in marijuana users Human ELISA [54] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] Sub-chronic THC administration Peritoneal macrophages stimulated with LPS ↑IL-10 after 10-day THC treatment during adolescence or adulthood BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Peritoneal macrophages stimulated with LPS ↓IL-10 in adult animals as a long-term effect after 10-day THC treatment during adolescence BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Prefrontal cortex ↓IL-10 in adult animals as a long-term effect after 11-day THC treatment during adolescence Sprague Dawley rats ELISA [58] IL-12 Chronic cannabis use Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] TNF-αChronic cannabis use Alveolar macrophages stimulated with LPS ↓TNF-αin marijuana users Human ELISA [51] Bronchial epithelial cells No significant changes (1–10 or 21–40 years of cannabis use) Human ELISA [52] ↑TNF-α(11–20 years of cannabis use) Plasma ↓TNF-αin marijuana users Human ELISA [54] Serum ↓TNF-αin marijuana users Human ELISA [48] Biomolecules 2021,11, 1824 7 of 34 Table 1. Cont. Target Experimental Design Sample Major Finding Species Method References Saliva No significant changes in marijuana users Human ELISA [45] Serum ↑TNF-αin patients diagnosed with cannabis use disorder Human ELISA [46] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] Sub-chronic THC administration Peritoneal macrophages stimulated with LPS ↓ TNFα just after 10-day THC treatment during adolescence or adulthood BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Peritoneal macrophages stimulated with LPS ↑TNF-αin adult animals as a long-term effect after 10-day THC treatment during adolescence BALB/Cj mice ELISA Real-time PCR [43] Brain (Hypothalamus and hippocampus) [44] Prefrontal cortex ↑TNF-αin adult animals as a long-term effect after 11-day THC treatment during adolescence Sprague Dawley rats ELISA [58] TGFβChronic cannabis use Alveolar macrophages stimulated with LPS No significant changes in marijuana users Human ELISA [51] Blood No significant changes in marijuana users Human ELISA [50] ↑TGFβin marijuana and MDMA users Biomolecules 2021,11, 1824 8 of 34 Table 1. Cont. Target Experimental Design Sample Major Finding Species Method References IFN-γ Subchronic THC administration Splenocytes ↓IFN-γafter subchronic (7 days) THC treatment Swiss mice ELISA [49] Chronic THC administration ↓IFN-γafter chronic (14 days) THC treatment Chronic cannabis use Serum No significant changes in patients diagnosed with cannabis use disorder Human ELISA [46] Serum No significant changes in long-term marijuana users Human Multiplex immunoassay [47] TLR Chronic cannabis use Bronchial epithelial cells ↑TLR2, TLR5, TLR6, TLR9 in marijuana users Human ELISA [52] CCL11 Plasma ↑CCL11 in current cannabis users Human ELISA [59] COX-2 Sub-chronic THC administration Prefrontal cortex ↑COX-2 in adult animals as a long-term effect after 11-day THC treatment during adolescence Sprague Dawley rats ELISA [58] CRP Acute cannabis use Serum No significant changes in marijuana users after recent consumption (after adjusting for covariables) Human Nephelometrybased high throughput assay [60] Serum No significant changes in marijuana users after recent consumption (after adjusting for covariables) Human Highly sensitive CRP assay [61] Serum/Plasma No significant changes in marijuana users after recent consumption (after adjusting for covariables) Human Cardiac C-reactive Protein (Latex) Sensitive immunoturbidimetric assay [62] Biomolecules 2021,11, 1824 9 of 34 Table 1. Cont. Target Experimental Design Sample Major Finding Species Method References Chronic cannabis use Plasma No significant changes in marijuana users Human Turbidimetric assay [54] Serum ↑prevalence of <0.5 mg/dl CRP levels in marijuana users Human Latexenhanced nephelometry [63] ↓CRP in past marijuana users No significant changes in current marijuana users Serum ↓CRP in current marijuana users Human Latexenhanced nephelometry [64] No significant changes in past marijuana users Serum No significant changes in marijuana users Human Immunoturbidimetric assay [65] Plasma No significant changes in marijuana users Human Highly sensitive CRP assay [66] Whole-blood spots ↑CRP in marijuana users Human Biotinstreptavidin based immunofluorometric system [67] Serum ↑CRP in long-term marijuana users (associated with ↑ TSPO) Human Highsensitivity enzyme-linked immunosorbent assay [47] Serum ↑CRP in marijuana users (associated with ↑ CVD) Human ELISA [68] Serum ↑CRP in marijuana users (associated with ↑ CVD) Human ELISA [56] “↑” refers to an increase and “↓” to a decrease in the target of interest. 3.2. Consequences of Cannabis Use on Inflammatory Biomarkers In recent years, an increasing number of animal and clinical studies have evaluated how the immune system is modified in response to exposure to cannabis or to specific cannabinoid compounds. These investigations facilitated changes in different inflammatory biomarkers, mainly cytokines and acute-phase proteins, which may provide valuable information about the immediate or long-term consequences of prolonged cannabis use on the immune system. Biomolecules 2021,11, 1824 16 of 34 Table 3. Cont. Target Experimental Design Sample Major Finding Species Method References Microglial activation ↑microglial activation in the cortex Immunohistochemistry [29] mRNA Caspase-1 ↑expression in cortex Real-time PCR NLRP3 ↑protein levels Western Blot Leukocyte ↑numbers of leukocyte Flow Cytometry IL-1 β, IL-18, IFN-γ, IL-33 ↑level in the whole brain ELISA mRNA CXCL2 (MIP2-α), CX3CL1 (Fractalkine) ↑mRNA levels Real-time PCR mRNA CCL4 (MIP-1β)↓mRNA levels TNFα, MCP1, and IL-1β↑in cerebellum ELISA [98] miR-155 ↑in cerebellum Real-time PCR mRNA IL-1β, IL-6, MCP-1 ↑whole brain expression mRNA levels [101] MCP-1 Brain Tissue (Postmortem) ↑Level in VTA, SN, Hippocampus, and Amygdala Human ELISA [100] Iba-1+, Glut5 ↑microglial, iba-1+ and glut5+ cells, in cingulated cortex Immunohistochemistry Glut5 ↑microglial, Glut5 positive cells, in midbrain and VTA mRNA TLR7 ↑expression in hippocampus Real-time PCR [28] TLR7, HMGB1, CD11b ↑in hippocampus Western Blot miR181b-3p Liver ↓miRNA level in liver C57BL/6J RNA NextGeneration Sequencing [97] oral sugar test Urine ↑gut permeability before the development of alcoholic liver disease SpragueDawley rats Gas chromatography [96] Biomolecules 2021,11, 1824 17 of 34 Table 3. Cont. Target Experimental Design Sample Major Finding Species Method References TSPO activity Neuroimaging ↑Binding with F-DPA-714 during and 7 months after exposure Non-human primates PET [104] ↑Binding with (11C)PBR28 Wistar rats [103] ↓Binding with (11C)PBR28 in alcoholic patients admitted in rehabilitation Human [103] [105] [106] “↑” refers to an increase and “↓” to a decrease in the target of interest. These changes were also found up to one month after the cessation of alcohol consumption [ 111 ]. Consistently with previous findings, advanced glycation end products (AGE) remain elevated one month after the termination of consumption [ 112 ], and decreases in Clara Cell secretory protein (CC16) [ 111 ], a protein with anti-inflammatory properties that has been postulated as a biomarker in several lung diseases, have also been observed [ 113 ]. Therefore, improving inflammatory parameters may provide a basis for detecting relapses in patients undergoing alcohol withdrawal in the short and medium term. However, it is necessary to investigate the potential of inflammatory biomarkers during a more prolonged detoxification period and to predict the patients who are the most susceptible to delirium tremens due to alcohol withdrawal, a condition that could compromise their lives (Table 4). 4.4. Alcoholic Liver Disease One of the most visible consequences of the chronic, long-term consumption of large amounts of alcohol is the progression to liver disease (ALD). The disease progresses from the initial stages with fatty liver disease, which is reversible in many cases, to liver inflammation, and finally to loss of function due to liver fibrosis or cirrhosis. Alterations in the levels of TNFα and HSP70 [ 114 ] were found in HSP70 from the early stages of AML. It is a well-known DAMP that is associated with low-grade inflammation. This low-grade inflammation can be measured by the High-sensitivity C-reactive protein (hsCRP), which has a lower threshold than conventional CRP. Furthermore, the hsCRP values correlate positively with the markers of hepatic dysfunction [115]. Additionally, in an animal model of binge and escalating alcohol exposure, levels of IL-6, IL-1 β , and TNFα together with IL-10 were increased [ 116 ]. At the same time, IL-10 decreased after 12 weeks, indicating an imbalance in the level of proinflammatory and anti-inflammatory cytokines that concurred with the appearance of liver fibrosis. A study with patients positively correlated the soluble suppression values of tumorigenesis-2 (sST2) with IL-6, IL-1 β , the severity of the Child–Pugh scale, and the Maddrey test score used to discriminate the severity of alcoholic hepatitis. Interestingly, this study did not show an elevation in IL-33 levels [ 117 ]; IL-33 is the ligand of ST2. It should be noted that the measurement of sST2 is postulated to be a prognostic biomarker in heart failure [118]. Biomolecules 2021,11, 1824 18 of 34 Table 4. Alcohol Use Disorder: Withdrawal. Target Experimental Design Sample Major Finding Species Method References IL-6, IL-8, IL-10 Withdrawal Serum ↓levels after a few days of abstinence in patients with an alcohol withdrawal syndrome Human ELISA [82] Advanced glycation end products (AGE) ↑In patients with at least one month of abstinence compared to control. Spectrophotometric [112] IL-1RA, Il-8, Il-6 ↑ Alcoholic patients without liver disease one month of detoxification, compared with control. ELISA [111] Clara cell secretory protein (CC16) ↓ Alcoholic patients without liver disease one month of detoxification CCL18 Subcutaneous Adipocyte tissue ↑after one week of withdrawal in ALD patients Real-time PCR [108] “↑” refers to an increase and “↓” to a decrease in the target of interest. As for the progression of fibrosis and the already established and other types of biomarkers that could assess prognosis, an increase of YKL40, a molecule that is involved in the maturation of the monocytes to macrophages that are linked to inflammation and fibrosis development, was also found [ 119 ]. In addition, in terms of survival rates, a decrease in Treg lymphocytes and an increase in Th17 lymphocytes were observed in nonsurviving patients after admission for alcoholic liver disease. In the same study, an increase in IL-17a, IL-1 β , and IL-6 was found, with increased IL-6 being a diagnostic and prognostic biomarker to fatal ALD [ 120 ]. Accordingly, patients with an IL-6 level ≥38.66 pg/mL [121] at hospital admission had significantly elevated mortality than those with low levels. Additionally, IFNγ with antifibrotic effects decreased in patients with higher long-term mortality in AAH [122]. Furthermore, in the liver of a mouse animal model of ALD, there was an increase of pattern recognition receptors for gene expression, such as TLR1, TLR2, TLR4, TLR6, TLR7, TLR8, and TLR9 [ 123 ]. An increase of the microglia in the subventricular zone (SVZ) and the superior frontal gyrus (SFG) and increased levels of IL-6 in the percental gyrus (PCG) [ 124 ] were found in post mortem samples of alcoholic patients with cirrhosis and hepatic encephalopathy. On the other hand, some studies suggested that the severity of acute alcoholic hepatitis can be assessed with the sCD163 protein [ 125 ], a protein that is associated with the activation of macrophages and the titer of antibodies against Porphyromonas gingivalis 33,277 and w38 [126], suggesting an increase in endotoxemia. Therefore, in liver disease, due to prolonged and heavy alcohol consumption, potential biomarkers that assess and reflect the dynamism and progression of the disease based on inflammatory markers have been observed and may be able to establish the basis for future research (Table 5). Biomolecules 2021,11, 1824 19 of 34 Table 5. Table: Alcoholic Liver Disease. Target Experimental Design Sample Major Finding Species Method References sST2 Alcoholic Liver Disease (ALD) Plasma It was positively correlated with Maddrey discriminant function (MDF), Child–Pugh scale, IL-6 Il1B, and ALD severity. Human ELISA [117] High-sensitivity C-reactive protein (hsCRP) It was correlated with the liver dysfunction marker and hepatic venous pressure. On the contrary, it had a negative correlation with survivability. [115] YKL40 ↑hit the severity of fibrosis and hepatic inflammation [119] IL-1β, IL-6, and TNF-α Serum Binge and escalating alcohol exposure ↑ serum levels. Wistar rats [116] IL-10 Binge and escalating alcohol exposure ↑at the end of 4 and 8 weeks but ↓after that and was significantly decreased at 12 and 16 weeks. HSP70, TNFα Depending on the severity of the Alcoholic Fatty Liver Disease Human [114] IL-17A, IL-1beta, IL-6 ↑IL-6 highest diagnostic and prognostic biomarker to the fatal ALD course [120] Th17/Treg Whole Blood ↑Th17 and ↓Treg frequencies were observed in non-survivors Flow Cytometry mRNA expression of Toll-Like Receptors Liver Upregulated TLR1, 2, 4, 6, 7, 8, and 9 (TLR10, TLR11 Not tested) C57Bl6/J Real-time PCR [123] Microglia Brain Tissue (Postmortem) ↑in the subventricular zone (SVZ) in an alcoholic with cirrhosis and hepatic encephalopathy Human Immunohistochemistry [124] IL-6 ↑in superior frontal gyrus (SFG), the precentral gyrus (PCG) in an alcoholic with cirrhosis and hepatic encephalopathy ELISA Acute Alcoholic Hepatitis sCD163 Plasma Positive correlation with severity and mortality of Acute Alcoholic Hepatitis (AAH) Human ELISA [125] IgM, IgA, IgG against p. gingivalis 33277 and w83 Progression and severity of Acute Alcoholic Hepatitis (AAH) [126] Biomolecules 2021,11, 1824 20 of 34 Table 5. Cont. Target Experimental Design Sample Major Finding Species Method References IFN-γ Serum Negative association with low levels of IFNγ at admission and long-term mortality in patients with Acute Alcoholic Hepatitis (AAH) [122] Il-6 Patients with IL-6 ≥ 38.66 pg/mL had significantly decreased mean survival than those with lower levels in Acute Alcoholic Hepatitis. [121] CD163 Liver ↑ in patients with Acute Alcoholic Hepatitis (AAH) [125] “↑” refers to an increase and “↓” to a decrease in the target of interest. 5. Opioid Use Disorder Opioid use disorder is a social warming epidemic that affects more than 16 million people and causes more than 120,000 deaths per year worldwide [ 127 ]. Diagnosis is based on the American Psychiatric Association’s DSM-5. It includes, among others, an intense craving for opioids, continued opioid use despite associated social, physical, or psychological problems, the presence of tolerance, and the presence of withdrawal. Heroin represents the classical situation opioid of abuse, but other opioids derived from medical use include morphine, codeine, fentanyl, and synthetic opioids such as tramadol and oxycodone [127]. Opioids can interfere with the immune system by participating in immune cell function and by modulating the innate and acquired immune responses [ 128 ]. One of the significant concerns related to chronic opioid use is the development of immunosuppression, thereby increasing the risk of chronic disease and infection [ 128 ]. Indeed, recent data suggest that the effect on immune function is much more complicated. Opioids act as biological response modifiers, and their actions are highly contextual, plastic, adaptable, and influenced by other processes or pathophysiological conditions. In particular, emerging growing evidence points to neuroinflammation as being crucial for addictive process [ 129 ]. To clarify the role of inflammation on opioid addiction and the potential use of inflammatory biomarkers in this disorder, we mainly focused on reports investigating the effects of opioids in chronic exposure and the context of addiction. We discarded reports that were related to the inflammation-modulatory roles of opioids in pain or analgesia and other conditions. 5.1. Acute Opioid Administration Acute opioid administration is related to several immune alterations. However, its relationship to the future development of addiction and the time-course modifications that occur with prolonged administration have been sparsely investigated. Interestingly, in this context, an essential role for anti-inflammatory cytokine IL-10 has been described. Morphine administration-activated glia in the rat nucleus accumbens (NAc) is concomitant with an increase in CRP, IFNγ , CXCL9, CCL11, CCL12, CCL25, CCL17, CCL4, CCR4, and IL-10 expression and a decrease in CX3CL1 (fraktaline) [ 130 ]. The neonatal handling and pharmacological inhibition of glia in adulthood that is induced by ibudilast significantly increased the baseline expression of the anti-inflammatory cytokine IL-10 in the NAc. This action attenuated morphine-induced glial activation and cytokine/chemokine expression and prevented future morphine addiction in adulthood after morphine exposure. This idea supports the fact that IL-10 may be precisely related to this mechanism and that it could Biomolecules 2021,11, 1824 21 of 34 therefore be used as a potential marker in animal studies or in post mortem brains. In line with this, it was found that IL-10 mRNA expression within the NAcc negatively correlated with increased risk of the drug-induced reinstatement of Conditioned Place Preferences (CPP), suggesting a protective role for this specific cytokine against morphine-induced glial reactivity and the drug-induced reinstatement of morphine CPP. Moreover, the authors did not find peripheral immune activation, as levels of peripheral IL-1 β were not affected, whereas IL-10 significantly increased in the periphery. However, in contrast to CNS, handled rats showed decreased peripheral IL-10 levels [ 130 ]. Similarly, acute morphine administration did not change the serum levels of IL-1 β and IL-6, which was not the case after 6 days of morphine administration [ 131 ]. In contrast to chronic administration, acute morphine administration also increased IL-1 β levels in several brain regions, including in the striatum and hippocampus, and TNF α was also shown to be increased in the cortex [ 132 ]. Interestingly, chronic pain is accompanied by a proinflammatory profile. Several results point out that these patients have an increased risk of developing opioid addiction [ 133 ]. Notably, basal differences in immune mediators that are related to the concomitant pathology and individuals may play an essential role in the development of addiction, which should be considered. Overall, these data suggest that acute opioid administration has different immunomodulatory effects in the periphery and CNS, influencing future addictive behavior. However, there is still a lack of information regarding how acute opioid use and its interaction with the immune system relates to the development of addictive behavior (Table 6). Table 6. Opioid use disorder: Acute Opioid Administration. Target Experimental Design Sample Major Finding Specie Method References IL-1β, IL-10 Acute Opioid Administration Serum ↑IL-10 Sprague Dawley rats ELISA [130] CRP, IFN-γ, CXCL9, CCL11, CCL12, CCL25, CCL17, CCL4, CCR4, CX3CL1, IL-10 Brain Tissue ↑CRP, IFN-γ, CXCL9, CCL11, CCL12, CCL25, CCL17, CCL4, CCR4, IL-10 ↓CX3CL1 Increased levels of IL-10 in Nacc are correlated with reduced risk of opioiddependence Real-time PCR CCL5, IL-1β, TNFα ↑IL-1βin cortex, hippocampus, and striatum ↑TNFα Sprague Dawley rats ELISA [132] IL-6, IL-1βSerum No change Sprague Dawley rats ELISA [131] “↑” refers to an increase and “↓” to a decrease in the target of interest. 5.2. Chronic Opioid Administration The chronic use of opioids produces dependence, tolerance, and addiction that are mediated by immune dysregulation (Table 7). Chronic opioid administration up-regulates peripheral IL-6, IL-1 β , TNF α , CRP [ 131 , 134 , 135 ]. Moreover, opioid exposure in the prenatal period can impact the peripheral inflammatory profile after birth, as shown by increased serum levels of IL-1 β , IL-6, TNF α , and CXCL1, with IL-1 β continuing to be increased for over a month. Moreover, isolated peripheral blood mononuclear cells (PBMC) increased basal TNF α release as well as increased LPS-induced TNF α and IL-1B release, showing Biomolecules 2021,11, 1824 22 of 34 that prenatal opioid exposure can reprogram the immune system to sustained peripheral activation and reactivity [136]. Table 7. Opioid Use Disorder: Chronic Opioid Exposure. Target Experimental Design Sample Major Finding Species Method References IL-6, IL-1β Chronic opioid exposure Serum ↑IL-6, IL-1βafter 6 days of morphine administration. Sprague Dawley rats ELISA [131] IL-6, IL-1β Brain Tissue ↑IL-6, IL-1βmRNA in NAcc and mPFC, after 6 days of morphine administration. Real-time PCR IL-6, IL-1β ↑IL-6, IL-1βlevel in NAcc and mPFC, after 6 days of morphine administration. ELISA IL6, TNFα, NF-kB, iNOS ↑NF-kB, iNOS, TNFα, IL-6, after 8 weeks of tramadol administration. Albino rats Real-time PCR, WB [134] IL6, TNFα Serum ↑IL-6, TNFα, after 8 weeks of tramadol administration. Real-time PCR CRP, TNF-α, IL-17A ↑IL-6, TNFα, after 14 days of 50 mg/kg treatment of tramadol or tapentadol. ↓IL-17A only at 50mg/kg of tapentadol Wistar rats ELISA [135] IL-1β, TNF, IL-6, CXCL1 ↑IL-1β, IL-6, TNFα, CXCL1 in a model of perinatal methadone exposure Sprague Dawley rats Multiplex Electrochemiluminescent Immunoassay (MECI) [136] IL-1β, TNF, IL-6 Peripheral blood mononuclear cells ↑Basal TNFα↑TNFα, IL-1βafter LPS stimulation, in a model of perinatal methadone exposure. MECI IL-1β, CXCL1, TNF, IL-6 Brain Tissue ↑TLR4, MyD88, IL-1 β, CXCL1 in the cortex, in a model of perinatal methadone exposure. Real-time PCR, MECI IL6, TNFα, TLR2, CD11b ↑IL-6, TNFα, TLR2, CD11b in NAcc after 3 days of morphine administration. C57BL/6 mice Real-time PCR [137] TLR4 ↑TLR4 mRNA in NAcc, after prolonged remifentanil self-administration. Sprague Dawley rats Real-time PCR [138] CCL5, IL-1β, TNFα ↑CCL5 in cortex and striatum ↓IL-1βin the cortex, after scaling morphine administration for 5 days. Sprague Dawley rats ELISA [132] CXCL12 ↑CXCL12 in VTA, after 6 days of morphine administration. Sprague Dawley rats Real-time PCR, WB [139] Biomolecules 2021,11, 1824 23 of 34 Table 7. Cont. Target Experimental Design Sample Major Finding Species Method References Adaptive immunity markers Serum ↑Total B cells ↑IgG3, IgG4, IgM ↑sCD40l, TNFα, TGFα, IL-8, endotoxin. In active heroin injection drug users. Human Flow cytometry, ELISA, LAL [140] CRP, C3 and C4, IgM, IgA, antioxidant capacity (TAC) ↑CRP, C3, C4, IgA, TAC in chronic opium smokers. ELISA, FRAP [141] TNFαPlasma ↑TNFαin OUD patients. ELISA [142] Immunological parameters Serum ↑white blood cell, neutrophil count, and neutrophil percentage were ↓lymphocyte percentage, and basophils count ↑inflammatory indexes. In OUD patients. N.D. [141] PBL proliferation, IL-2, IL-4, IL-6, IL-10, IFNγ Whole blood ↑Peripheral Blood Leukocytes (PBL) proliferation ↑Basal IL-6 ↑IL-10 release after stimulation. In heroin addicts. ELISA [143] IL-1β, IL-15, CD15, CD68, IL-8, IL-10, TNFα, IL-6, COX-2, HSP-70, IRP-150 Brain Tissue (Postmortem) ↑IL-15, CD68, TNF-a, IL-6; COX-2, HSP-70, ORP-150, in heroin-related deaths. Immunohistochemistry, WB [144] TNFα, IL-8 Plasma ↑TNFα, IL-8 in heroin-dependent patients. TNFα, IL-8 were correlated to years using heroin ELISA [145] Dysregulated gene expression Brain Tissue (Postmortem) OUD patients exhibit an enhanced expression of transcripts related to neuroinflammation. Top activated upstream regulators were identified to be TNFα, IL-1β, NFkB in DLPFC and IL-1βin NAcc. RNA Next-Generation sequencing [146] ↑Gene module firebrick3 (associated with immune responses) in opioid abuse group. [147] IL4 and PECAM1 are identified as critical genes for opioid addiction. [148] “↑” refers to an increase and “↓” to a decrease in the target of interest. Several studies demonstrated that microglial activation occurs in the context of opioid addiction in the central nervous system [ 149 , 150 ], and recent evidence suggests that activated glia, including astrocytes and microglia, play an essential role in opioid addiction. For example, it has been shown that astrocytes are involved in the dependence that is induced by repeated morphine treatment [ 151 ] and microglia in the NAc in the acquisition and maintenance of dependence, although it is not involved in the expression of morphine-induced reward in the CPP [ 152 ]. Consistently, glial inhibitors decrease opioid addiction and physical dependence [ 130 , 152 , 153 ]. Transcriptomics and metabolomics analysis related chronic opioid exposure with the upregulation of inflammatory pathways in the brain [ 154 , 155 ], further demonstrating the involvement of inflammation in opioid addiction. The release of proinflammatory cytokines in the CNS was associated with addictive behavior. In particular, in the NAc, a significant upregulation of IL-6, TNF α , and IL1 β [ 131 , 137 ] and IL-6 and IL-1 β in mPFC [ 131 ] were found. Moreover, TLR2 and TLR4 Biomolecules 2021,11, 1824 24 of 34 expression were shown to have increased after chronic opioid administration in the NAc in rodents [ 137 , 138 ], whereas NF-kB, TNF α , and IL-6 are up-regulated in whole-brain homogenate after chronic tramadol exposure [134]. Accordingly, other studies found that chronic morphine administration induces the expression of the chemokine CCL5 in the cortex and striatum [ 132 ] and CXCL12 in VTA, which has been related to the acquisition and maintenance of morphine-induced conditioned place preference (CPP) [ 139 ]. However, some contradictory results have also reported that chronic morphine administration did not increase the mRNA TNF α and IL-1 β levels in the cortex, striatum, and hippocampus, whereas IL-1 β was downregulated in the cortex [ 132 ]. Additionally, an essential role of IL-10 has been further demonstrated by Lacagnina et al. This author showed that the intracranial administration of IL-10 into the NAc reduces remifentanil self-administration by suppressing proinflammatory cytokine and chemokine gene expression [138]. Human studies also revealed several immunological alterations in the context of Opioid Use Disorder (OUD). Opioid addicts have increased plasma levels of sCD40L, TNFα , TGFα , IL-8, and CRP, and complement factors C3 and C4 [ 140 – 142 , 145 ]. Interestingly, increased levels of TNF α and IL-8 were positively correlated with years of using heroin [145]. On the other hand, total antioxidant capacity (TAC) was positively and significantly correlated to nitric oxide production in opium smokers, again suggesting a regulatory response that can occur in opium addicts to control the inflammation [ 141 ]. Additional reports have described increased inflammation in opioid addicts, together with increased white blood cell count, neutrophil count, and neutrophil percentage, while the lymphocyte percentage and basophil count were significantly lower [ 156 ]. Heroin abusers show adaptive immunity alterations, as seen by chronic B cell activation and increased total B cells [ 140 ]. Moreover, peripheral blood leukocytes (PBL) in heroin addicts showed the enhanced spontaneous production of IL-6, whereas the stimulation of PBL with con-A increased IL-10 release and proliferative activity compared to controls [143] Identifying the inflammatory biomarkers of opioid addiction in the human brain is less advanced, but recent reports highlight the importance of immune response dysregulation. For example, a profound inflammatory profile is found in the heroin-related human post mortem brain, as shown by the increased expression of IL-15, CD68, TNFα , IL-6, COX-2, and HSP-70, especially in the brainstem [ 144 ]. Consistently, a recent report revealed that in post mortem samples from the midbrain of opioid-induced death patients, the most dysregulated gene module was firebrick3, which was highly enriched in inflammatory and immunomodulatory genes [ 147 ]. Additionally, a large transcriptomic study in the post mortem brains of OUD patients further revealed the importance of neuroinflammation in this disorder. They focused on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc). They found that the top-activated upstream regulators in DLPFC were TNF, IL1 β , and NFκ B in the DLPFC, whereas IL1 β was one of the top-activated upstream regulators in NAc. Moreover, this study revealed the direct links between neuroinflammation, risky behavior, and OUD, suggesting that neuroinflammatory pathways may ultimately drive drug-seeking behavior in OUD [ 146 ]. In addition, a recent report identified IL4 and PECAM1 as potential biomarkers for opioid use disorder [148]. 5.3. Opioid Withdrawal Data obtained from rodents suggest an increase in inflammatory mediators in the brain during the withdrawal period that are associated with the severity of withdrawal behavior. For example, a recent report measured gene expression in astrocytes, microglia, and neurons in the central amygdala (CeA) of control, morphine-dependent, and withdrawal rats. They found inflammatory genes, such as CXCR1, TLR2, TNF, and TNFRSF1A, to be up-regulated in the morphine group. However, chronic morphine exposure did not substantially influence the transcriptional state, but morphine withdrawal did. In particular, a significant upregulation of neuroinflammatory genes, notably TNF, occurred in the withdrawal condition in all three cell types, with astrocytes showing the most profound Biomolecules 2021,11, 1824 25 of 34 shift [ 157 ]. Another study found an up-regulation of inflammatory cytokines and microglia proliferation in withdrawal conditions compared to in morphine-dependent conditions. In particular, withdrawal increases IL-1 β in the hippocampus and striatum and TNFα in the striatum, reducing CCL5 in the frontal cortex. In contrast with morphine-dependent conditions, no changes were observed [132]. Interestingly, increased hippocampal levels of IL-1 β and TNF α were linked to the severity of withdrawal behavior. These changes were also associated with the cortisol levels related to stress and anxiety during withdrawal [ 158 ]. Furthermore, another study consistently found that elevated hippocampal IL-1 β expression was associated with the severity withdrawal behavior [ 159 ]. Moreover, morphine withdrawal induces TNF α release and neuronal TNF-receptor 1 activation, which were involved in behavioral modifications during withdrawal [ 160 ]. Additionally, the treatment with venlafaxine inhibited withdrawal behavior and inhibited the up-regulation of TNFα , IL-1 β , and IL-6 that had been induced by withdrawal. Interestingly, venlafaxine failed to affect the brain with the increased concentrations of IL-10, suggesting that withdrawal is dependent on proinflammatory cytokines [ 161 ]. The involvement of neuroinflammation arises because the glial inhibitor ibudilast inhibits withdrawal behavior [162]. In patients, data from withdrawal periods were collected in the context of methadonemaintenance therapy (MMT), where several studies have shown the association with changes in the inflammatory profile. Opioid addicts under MMT significantly increased plasma IL-1 β , IL-6, and IL-8 compared to healthy subjects. Interestingly, TNF α was not increased, but both TNF α and IL-6 levels were significantly correlated with the dairy methadone dosage administered and IL-1 β with the duration of methadone maintenance treatment [ 163 ]. Several studies have shown that MMT significantly reduces the plasma levels of TNFα , CRP, IL-6, and TGFβ 1 [ 142 , 164 ]. Additionally, MMT significantly increased cognitive abilities in opioid addicts that were associated with changes in various inflammatory markers. For instance, TNFα levels negatively correlate with the visual memory index and IL-6 levels negatively correlate with the verbal memory index [ 164 ]. Another study consistently found that CRP and TGFβ 1 decreased during MMT, although in this case, IL-1β, TNFα, and IL-6 did not change. Interestingly, the authors found a significantly positive correlation between plasma IL-6 levels and MMT outcomes, including the severity of heroin addiction and patient adherence to MMT [ 165 ]. Another study used dextromethorphan (D.M.) as co-adjuvant therapy for MMT and found that TNF α , IL-8, and opioid dependence significantly decreased after 12 weeks of MMT-DM but not in the MMT-Placebo patients. Moreover, methadone required dose increases in the MMT-Placebo groups and dose decreases in the MMT-DM group, suggesting that patients become tolerant to methadone when it is used alone. The persistence of those cytokines may be associated with the maintained dependence and development of tolerance [ 145 ]. Accordingly, a subsequent study of the effects of D.M. found a higher reduction in TNF α but not in IL-8, IL-6, and CRP in the MMT-DM group compared to the MMT-Placebo group. Moreover, dextromethorphan decreased the rate of treatment withdrawal [ 166 ]. Additionally, the MMT patients with comorbid pain showed elevated IFNγ and higher rates of continued opioid abuse [ 167 ]. Opioid addicts under MMT also maintained enhanced IL-6 release by the Peripheral Blood Leukocytes. In contrast, the increased production of IL-2, IFNγ, and IL-10 after stimulation was normalized by MMT [143]. These data suggest that several immunological alterations accompany opioid addiction and that neuroinflammation plays a crucial role in opioid dependence and relapse. 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