The Role of Pro-Inflammatory and Regulatory Signaling by IL-33 in the Brain and Liver: A Focused Systematic Review of Mouse and Human Data and Risk of Bias Assessment of the Literature

Abstract

Interleukin (IL)-33 is a member of the IL-1 family of proteins that have multiple roles in organ-specific inflammation. Many studies suggest diagnostic and therapeutic implications of this cytokine. Many studies have reported pro-inflammatory roles for IL-33 in innate immune responses involving the heart and lung. Recent studies also describe pro-inflammatory and regulatory roles for IL-33 in the pathogenesis of brain and liver disorders in addition to regulatory roles for this cytokine in the heart and lung. In this focused systematic review, we will review the literature regarding pro-inflammatory and regulatory effects of IL-33 in the brain and liver. We will also assess the potential risk of bias in the published literature in order to uncover gaps in the knowledge that will be useful for the scientific community. We utilized guidelines set by preferred reporting items for systemic reviews and meta-analyses. The electronic database was PubMed. Eligibility criteria included organ-specific inflammation in mice and humans, organ-specific inflammation in the central nervous and hepatic systems, and IL-33. Outcomes were pro-inflammatory or regulatory effects of IL-33. Risk of bias in individual studies and across studies was addressed by adapting the Cochrane Rob 2.0 tool. We discovered that a source of bias across the studies was a lack of randomization in human studies. Additionally, because the majority of studies were performed in mice, this could be perceived as a potential risk of bias. Regarding the central nervous system, roles for IL-33 in the development and maturation of neuronal circuits were reported; however, exact mechanisms by which this occurred were not elucidated. IL-33 was produced by astrocytes and endothelial cells while IL-33 receptors were expressed by microglia and astrocytes, demonstrating that these cells are first responders for IL-33; however, in the CNS, IL-33 seems to induce Th1 cytokines such as IL-1β and TNF-α chemokines such as RANTES, MCP-1, MIP-1α, and IP-10, as well as nitric oxide. In the liver, similar risks of bias were determined because of the lack of randomized controlled trials in humans and because the majority of studies were performed in mice. Interestingly, the strain of mouse utilized in the study seemed to affect the role of IL-33 in liver inflammation. Lastly, similar to the brain, IL-33 appeared to have ST2-independent regulatory functions in the liver. Our results reveal plausible gaps in what is known regarding IL-33 in the pathogenesis of brain and liver disorders. We highlight key studies in the lung and heart as examples of advancements that likely occurred because of countless basic and translational studies in this area. More research is needed in these areas in order to assess the diagnostic or therapeutic potential of IL-33 in these disorders.

Keywords: IL-33; brain; central nervous system; down-regulation; hepatitis; inflammation; liver; up-regulation.

Figure 1

IL-33 mechanism of activation. The ST2L/IL-1RAcP receptor complex is found on the cell membrane of Th2 cells, ILC2s, and FoxP3+ Tregs. Upon binding to IL-33, this receptor complex undergoes a conformational change to allow for activation of the inflammatory response. A cascade of events unfolds, in which MyD88, IRAK-1, IRAK-4, and TRAF-6 become activated. Subsequently, NF-kB, JNK, and ERK/MAPK pathways are activated to produce a pro-inflammatory response. TIR: Toll interleukin receptor; MyD88: Myeloid differentiation primary response protein; IRAK: Interleukin receptor-associated kinase; TRAF: TNF-receptor-associated factor 6; NF-κB: Nuclear factor kappa light chain enhancer; JNK; c-Jun N-terminal kinases; ERK: Extracellular signal-regulated kinase.

Figure 2

Effects of IL-33, as pro-inflammatory and regulatory, on the central nervous system, liver, cardiovascular system, and pulmonary system. Following activation of the IL-33 pathway, and subsequent activation of NF-κB, JNK, and ERK/MAPK pathways, a pro-inflammatory response is initiated. This pro-inflammatory response results in the release of cytokines, including IL-3, IL-4, and IL-5. These cytokines act on target cells within the central nervous, hepatic, cardiovascular, and pulmonary systems. Within the central nervous system, activated oligodendrocytes, astrocytes, microglia, and neurons induce pro-inflammatory or regulatory effects. In the liver, activated macrophages and hepatic sinusoidal endothelial cells (HSECs) induce pro-inflammatory effects, while FoxP3+ Tregs induce regulatory effects. In the heart, cardiac endothelial cells induce pro-inflammatory or regulatory effects. In the pulmonary system, pulmonary endothelial cells and M2 macrophages induce pro-inflammatory and regulatory effects.

Figure 3

PRISMA Study Selection Flow Diagram. The PRISMA Flow Diagram demonstrates each phase of the search strategy in which articles were evaluated. During each phase, articles were excluded based on our defined criteria. The last phase of exclusion resulted in a final collection of articles, which were then divided into a pro-inflammatory or regulatory. These articles were then further broken down by population, including humans, mice, and both. * The majority of full-text articles were excluded because they were review articles published prior to December 31 2017, IL-33 was not a main focus of the article, or the article was not available in English.

Figure 4

Risk of bias across studies focusing on the brain, in both mice and humans. This figure displays the relative percentages of intention-to-treat data of assessed risk of bias in the brain in human and mouse studies. The overall bias was determined using five categories: Selection of the reported result, measurement of the reported outcome, missing outcome data, deviations from intended interventions, and randomization process. Risk was determined as “low risk,” “some concerns,” or “high risk,” based on the Cochrane RoB 2.0 tool algorithm. The data for this figure included 14 articles.

Figure 5

Risk of bias across studies focusing on the liver, in both mice and humans. This figure displays the relative percentages of intention-to-treat data of assessed risk of bias in the liver in human and mouse studies. The overall bias was determined using five categories: Selection of the reported result, measurement of the reported outcome, missing outcome data, deviations from intended interventions, and randomization process. Risk was determined as “low risk,” “some concerns,” or “high risk,” based on the Cochrane RoB 2.0 tool algorithm. The data for this figure included nine articles.

Figure 6

Risk of bias across all mouse studies, including brain, liver, cardiovascular, and pulmonary. This figure displays the relative percentages of intention-to-treat data of assessed risk of bias in all mouse studies. The overall bias was determined using five categories: Selection of the reported result, measurement of the reported outcome, missing outcome data, deviations from intended interventions, and randomization process. Risk was determined as “low risk,” “some concerns,” or “high risk,” based on the Cochrane RoB 2.0 tool algorithm. The data for this figure included 24 articles.

Figure 7

Risk of bias across all human studies, including brain, liver, cardiovascular, and pulmonary. This figure displays the relative percentages of intention-to-treat data of assessed risk of bias across human studies. The overall bias was determined using five categories: Selection of the reported result, measurement of the reported outcome, missing outcome data, deviations from intended interventions, and randomization process. Risk was determined as “low risk,” “some concerns,” or “high risk,” based on the Cochrane RoB 2.0 tool algorithm. The data for all human studies included 26 articles.