NeuroImmunology

Summary The importance of the gut microbiome in the regulation of non‐infectious diseases has earned unprecedented interest from biomedical researchers. Widespread use of next‐generation sequencing techniques has prepared a foundation for further research by correlating the presence of specific bacterial species with the onset or severity of a disease state, heralding paradigm‐shifting results. This review covers the mechanisms through which a dysbiotic gut microbiota contributes to the pathological symptoms in an autoimmune neurodegenerative disorder, multiple sclerosis (MS). Although the central nervous system (CNS) is protected by the blood–brain barrier (BBB), it is unclear how gut dysbiosis can trigger potential immunological changes in the CNS in the presence of the BBB. This review focuses on the immunoregulatory functionality of microbial metabolites, which can cross the BBB and mediate their effects directly on immune cells within the CNS and/or indirectly through modulating the response of peripheral T cells to stimulate or inhibit pro‐inflammatory chemokines and cytokines, which in turn regulate the autoimmune response in the CNS. Although more research is clearly needed to directly link the changes in gut microbiome with neuroinflammation, focusing research on microbiota that produce beneficial metabolites with the ability to attenuate chronic inflammation systemically as well as in the CNS, can offer novel preventive and therapeutic modalities against a wide array of inflammatory and autoimmune diseases. Introduction Multiple sclerosis (MS) is a neurodegenerative autoimmune disorder in which the host immune system recognizes the myelin sheath surrounding axon terminals to be immunogenic, resulting in breakdown of tolerance. This triggers chronic inflammation within the central nervous system (CNS), lesion formation, demyelination of axons, along with breakdown in the blood–brain barrier (BBB), and gradual paralysis stemming from an inability to perpetuate action potentials over time. Multiple sclerosis has various forms with varying degrees of severity possessing distinct phenotypic characteristics; however, most cases share a common theme of varying symptoms at early stages followed by unrelenting neurodegeneration over time.1 The inflammation in the CNS in patients with MS is mediated primarily by the T helper type 1 (Th1) and Th17 T‐cell subsets producing pro‐inflammatory cytokines, which leads to infiltrating monocytes and macrophages in the CNS following damage to the BBB. These infiltrating mononuclear cells carry out these inadvertent effector functions resulting in neurodegeneration.2 Experimental autoimmune encephalomyelitis (EAE) is a CD4+ T‐cell‐mediated autoimmune disease induced in model organisms (primarily mouse and rat) in the research setting.3, 4 EAE is widely accepted as a reference standard disease model for in vivo laboratory research geared towards studying the physiology and potential treatments of MS. EAE is inducible in mice through administration of antigens from the myelin sheath along with an adjuvant, which leads to induction of inflammatory T helper cells that infiltrate the CNS. These cells typically include Th1 and Th17 subsets that produce cytokines and chemokines, including interleukin‐17 (IL‐17), tumour necrosis factor‐α (TNF‐α), interferon‐γ and CCL5, observed both locally in the CNS as well as systemically in circulation.2, 5-7 Along with the up‐regulation of pro‐inflammatory markers following induction of EAE, there is suppression of functionality of an anti‐inflammatory T‐cell subset known as T regulatory (Treg) cells.8 Treg cells are CD4+ cells characterized primarily by their expression of the transcription factor Foxp3 and production of the inhibitory cytokines such as IL‐10 and transforming growth factor‐β.3 The production of these suppressive cytokines inhibiting T helper cell proliferation and function is the key mechanism by which Treg cells accomplish their effector function of inducing immune tolerance.9 In addition to producing inhibitory cytokines, Treg cells accomplish their functions through cell–cell contact.9 Treg cells have garnered great interest as a potential focal point for MS treatment due to their induction of tolerance displaying protective effects against demyelination.10 The microbiota is a microbial collective composed of commensal organisms and opportunistic pathogens alike that reside along barrier sites of the host organism. The microbial diversity along these barrier sites plays a regulatory role in digestion, immune system activation, protection from development of opportunistic pathogens, and various other physiological processes.11-13 The importance of a tightly regulated microbiota on host physiology has gained a greater appreciation over recent years due largely to novel technologies giving a previously unavailable ability to culture fastidious organisms, rapidly sequence various macromolecules, and characterize microbe–host interactions with greater detail. The commensal relationship between host and microbial community possesses a highly complicated web of modulatory cross‐talk among organisms and has been recognized as an undeniable factor affecting host response in disease states.14 The count of living microbial cells, as well as genes expressed by those cells, possesses a towering presence over the host it resides within. The relative parity between these numbers is disputed due to difficulties in calculating definitive quantities in an ever‐changing microbiota; however, the ratio is believed to be at the very least a 10‐fold difference favouring the microbial flora.15 Gut–brain axis in MS and EAE Interactions between the host microbiota and the gut‐associated lymphoid tissue (GALT) help shape the immune system both locally and systemically throughout the host.16 The GALT has become a focal point in research targeting autoimmune disorders because of Treg activation by bacterial strains inducing immune tolerance within host organisms.17 The gut–brain axis is a term used to describe the interactions between host and microbiota residing within the gut and the lingering effects between these interactions that take effect within the CNS. The biodiversity present within the gastrointestinal tract has a collective metabolome very different from that of the human host that regulates the availability of nutrients for the host.18 The result of bacterial metabolism under dysbiotic conditions can either prevent nutrients from reaching the host through bacterial sequestering or provide an excess of unwanted xenobiotic metabolites with detrimental effects. The study of outward products of bacterial metabolism in the gut–brain axis is relatively new but rapidly expanding. In combination with microbial metabolism, the interactions between bacteria and the immune cells are an important aspect of the gut–brain axis and are often dependent on the products of bacterial metabolism. Interventional therapies focusing on regulation of microbial diversity as well as the metabolic traits of the microbiome have started showing progress in the treatment of MS, including the use of established non‐pathogenic probiotic regimens in the treatment of EAE.19 Although there are numerous reviews on the immune mechanisms that regulate the pathogenesis of EAE and the role of the microbiome in shaping the immune response in the gut, there is a paucity of reviews that help to understand the effects of microbiota in the gut–brain axis. It was therefore the primary objective of the current review to elucidate the complex interactions between the microbial metabolome found in the gut and how it can regulate immune response in the CNS in EAE and MS. Amino acid metabolism Cysteine metabolism Desulfovibrionaceae are strictly anaerobic bacteria that desulfinate the amino acid ‘cysteine’ for downstream purposes as a primary carbon source.20 The presence of Desulfovibrionaceae within the human gut has been shown in healthy colons; however, intestinal dysbiosis resulting from elevated levels of Desulfovibrionaceae has been shown in studies by sequencing the intestinal microbiota in both patients with MS and EAE‐induced mice.21, 22 An overabundance of Desulfovibrionaceae plays a vital role in the host metabolism due to its sequestering of the amino acid cysteine within the gastrointestinal tract. Abnormal availability of the amino acid cysteine can have widespread effects throughout the host body because it is a building block required for host production of sulphur‐containing bioactive compounds, such as glutathione. The rate‐limiting step of glutathione production, which is a tripeptide antioxidant, is the condensation reaction of cysteine with glutamate to form γ‐glutamylcysteine.23 Glutathione levels in particular are garnering focus due to their role as the primary countermeasure against reactive oxygen species (ROS) ‐related damage within the CNS. Currently, clinical studies are being performed to better understand the pathogenic role of underlying glutathione deficiencies in MS patients at different stages of the disease.24 Damage related to ROS in glutathione‐deficient patients has been shown to be reversible by the dietary supplementation of cysteine and glycine.25 Supplementation of sulphur‐containing precursor molecules was also shown to reduce oxidative stress in studies focusing on EAE‐induced mice.7 These studies suggest that the link between the bioavailability of these precursor molecules and the effector function of glutathione to eliminate elevated levels of ROS are directly related in both mice and humans. Elevated levels of reactive oxygen species within the CNS arise from residential microglia, infiltrating macrophages and general mitochondrial activity in combination with faulty countermeasures to rid the tissues of free radicals. The multifaceted role of ROS in MS pathogenesis has been gaining a greater appreciation within the research community in recent years26 due to elevated concentrations of ROS in CNS tissues playing potential roles in the initiation of lesions, recruitment of lymphocytes and the phagocytosis of myelin. High levels of superoxide in the CNS initiate lesions along the BBB due to disruption of the tight cell–cell junctions within cerebral endothelial cells as well as instigating a chemotaxis of monocytes towards the BBB.27 The phagocytosis of myelin results in the loss of action potentials being perpetuated throughout the nervous system (causing the symptoms of paralysis) and is carried out by infiltrating macrophages. This phagocytosis of myelin sheathing has been shown to be dependent on the concentration of ROS present in the surrounding microenvironment.28 In addition to an elevated ROS production, there is an increased expression of genes involved in the detoxification of ROS in an effort to alleviate self‐inflicted damage caused by inflammation targeting the CNS.29 This increased demand for antioxidant molecules locally within the CNS exposes and further exacerbates a potential susceptibility, if substantial levels of antioxidant precursor molecules are not readily available. Collectively, the above studies suggest that pathological symptoms directly caused by accumulation of ROS during an inflammatory response in the CNS can be attributed at least in part to a lack of sulphur‐containing precursor molecules related to either diet or bacterial dysbiosis. Dysbiosis arising from an overabundance of Desulfovibrionaceae within the host gut, provides a linkable mechanism of cysteine sequestering inducing a host deficiency of the sulphur‐containing bioactive antioxidant glutathione. This glutathione deficiency aids in an abundance of ROS, which degrade the BBB, aid in the recruitment of immune cells to the CNS and are required for myelin phagocytosis. Tryptophan metabolism Bacterial metabolism of tryptophan can be linked to the modulation of inflammation through the production of indole‐based compounds.30 The enzyme tryptophanase, unique to bacteria, breaks down the amino acid residues into indole, ammonia and pyruvate for further bacterial use as an energy source or building block.31 The outward indole by‐products of this reaction can come with a variety of side chains attached to the third carbon. Some of the known side‐chain functional groups include, but are not limited to, acetate, aldehyde and propionate.30 These indole‐based by‐products have the capability to bind as well as activate the aryl hydrocarbon receptor (AHR) present in host lymphocytes, similar to plant‐derived indoles.32 The AHR is a cytosolic receptor that upon activation undergoes conformational changes, binds a carrier protein to import it into the nucleus, and carries out an effector function within the nucleus as a transcription factor.33 The ligands for AHR are primarily planar hydrophobic molecules. Each of the mentioned indole by‐products containing unique side chains possesses a unique binding efficiency to the AHR ligand‐binding site. AHR ligands come from both endogenous and exogenous sources. Endogenous molecules produced by the host add a layer of complexity to the biological activity of ligands as environmental products and can either work as agonists activating the receptor, or as antagonists occupying the binding site with low efficacy to defer the basal levels of endogenous ligand activation.34 This contribution of various indole‐based compounds from the microbiome, which then compete with endogenous ligands produced by the host, results in disruption of balance between commensal organisms and host immune tissue. Modulation of AHR activity through ligand binding by environmental pollutants such as 2,3,7,8‐tetrachlorodibenzodioxin to dietary indoles has been shown primarily to lead to induction of Treg cells.35-37 However, some endogenous ligands such as 6‐formylindolo[3,2‐b]carbazole have also been shown to induce Th17 cells.32, 38, 39 The ability of AHR ligands to induce Treg cells versus Th17 cells may depend on their capacity to cause epigenetic changes including microRNA,37 and clearly more research is needed to understand the complexity of the receptor. Studies focusing on AHR activation and inhibition in EAE have resulted in polarized effects of either amelioration or perpetuation of symptoms, through induction of Treg cells and Th17 cells, respectively.40-42 It has become apparent that AHR activation via bacterial derivatives of tryptophan metabolism has a net positive effect on symptomatic outcomes of EAE. It was shown in one study that using a tryptophan‐depleted diet worsened the overall disease state of EAE in mice, whereas tryptophan supplementation resulted in an amelioration of symptoms.41 This alleviation of symptoms within the CNS was found to be mediated in part by repressing the expression of Nos2 and Ccl2 in astrocytes.41 An up‐regulation of Nos2 and Ccl2 expression within astrocytes aggravated EAE symptoms due to a localized pro‐inflammatory phenotype. Ccl2 is a cytokine involved in chemotaxis of memory T cells and monocytes to peripheral tissue sites, helping to initiate local inflammatory responses.43 Nos2, commonly known as nitric oxide synthase, produces the reactive molecule nitric oxide (NO), which contributes to vasodilatation and is used as a ROS in targeted killing.44 There does appear to be promise in the protective nature of tryptophan by‐products against autoimmune inflammation in the CNS through the gut–brain axis. However, this area of research is relatively new and will require much more focus in the coming years to pinpoint the exact roles of these dynamic processes in EAE. Carbohydrate metabolism Short‐chain fatty acid production from dietary fibres The gut microbiota also plays a key role in the production of short chain fatty acids (SCFAs) through the fermentation of carbohydrates that are indigestible to the host organism. These SCFAs direct inflammatory responses throughout the body by modulating the chromatin structure within the nuclei of lymphocytes favouring gene products that result in the proliferation of anti‐inflammatory Foxp3+ Treg cells.45, 46 SCFAs regulate T‐cell populations through the inhibition and activation of histone‐modifying enzymes that either up‐regulate (through acetylation) or down‐regulate (through deacetylation) transcription at proximal promoter regions. Treg induction by SCFA is accomplished through the inhibition of histone deacetylase activity near the Foxp3 promoter region while simultaneously promoting acetylation of histone 3 at the Foxp3 promoter region.47 The actual SCFA binding sites among CD4+ T cells for inhibition of histone deacteylase enzymes are currently disputed and could occur through either intracellular binding affecting the mTOR pathway,48 or through the cell surface G‐protein‐coupled receptors such as GPR41 and GPR43, specific for SCFAs.49 The SCFA ligand binding site on CD4+ T cells is currently debated due to GPR41 and GPR43 double knockouts having seemingly no effect on Treg cell proliferation as well as SCFAs being entirely permeable through the plasma membrane requiring no need for active transport.50 Butyrate production stems from prokaryotic fermentation of acetyl CoA precursors originating from dietary fibre catalysis. A diverse collection of species within the gastrointestinal tract have shown capabilities to ferment acetyl CoA into butyrate within the colon, however there is a primary focus on the Clostridium clusters XIVa and IV and the phylum Bacteroidetes, which both produce large quantities of butyrate.51, 52 Clinical studies focusing on sequencing the microbiome have shown a relative depletion of Bacteroidetes as well as the Clostridium clusters XIVa and IV in human samples from patients with MS when compared with healthy individuals.53 The direct effect of butyrate induction within the colon has been tested through both high‐fibre diet supplementation as well as direct oral butyrate treatments. Observed in both of these routes of butyrate supplementation was an amelioration of clinical symptoms of EAE using in vivo scoring algorithms combined with an increase in the numbers of Foxp3+ CD4+ T cells.45 Propionic acid is another SCFA produced from bacterial fermentation of indigestible fibres that could play a role in the prevention and relief of symptoms in inflammatory disorders. Propionic acid is produced by fermentation within the succinate pathway and modulates histone modifications at the Foxp3 promoter region in a manner similar to butyrate.46, 52 A large portion of the intestinal flora has been linked to the production of propionic acid, including the Gram‐negative phylum Bacteroidetes and the Gram‐positive phylum Firmicutes, which contains the genus Clostridium. Studies have shown that faecal transplants high in propionic acid in combination with propionic‐acid‐producing bacterial species have been beneficial in ameliorating the clinical symptoms of EAE in mice.54 Short‐chain fatty acids are found within the body in staggering concentrations for biologically active compounds, relatively ~150 mm when pooled as a collective within the large intestine of healthy individuals, making changes in compositional and collective abundance more than sufficient to have changes in the phenotypic properties of lymphocytes within the GALT.52 Lipid metabolism Polyunsaturated fatty acids Another mechanism modulating the inflammatory response throughout the host is perpetuated by the metabolism of polyunsaturated fatty acids, namely omega‐6 and omega‐3 fatty acids, from host cells as well as bacterial cells within the gut. These long hydrocarbon chains are directly involved in the regulation of metabolic endotoxaemia, a disorder in which an overabundance of lipopolysaccharide (LPS) ‐producing gut bacteria leads to activation of Toll‐like receptor 4 (TLR4), producing widespread chronic low‐grade inflammation.55 Omega‐3 fatty acids display an anti‐inflammatory phenotype when ingested in higher proportions than omega‐6 fatty acids due to the activation of intestinal alkaline phosphatase, an antimicrobial peptide that targets Gram‐negative organisms while simultaneously promoting the growth of Gram‐positive organisms.56 In addition to reducing Gram‐negative abundance, intestinal alkaline phosphatase exhibits anti‐toxic effects by hydrolysing phosphate groups coupled to Lipid‐A present on degraded LPS, reducing its binding efficiency to the TLR4 100‐fold.56 TLR4 activation leads to cryopyrin inflammasome activation releasing subsequent amounts of pro‐inflammatory cytokines, TNF‐α, IL‐1 and IL‐6 circulating in host organisms.57 This chronic low‐grade systemic inflammation connects the effects of microbial dysbiosis instigated by host diet to perpetual worsening of autoimmune disorders. This potential explanation coincides with the geographic distribution of diets high or low in omega‐3 fatty acids. Regions of the world with diets rich in omega‐3 fatty acids tend to have fewer instances of MS in comparison with those of the world that have a lower ratio of omega‐3 fatty acids to omega‐6 fatty acids,58 adding a potential geographical proof to polyunsaturated fatty acids as a contributing factor. With focus on polyunsaturated fatty acids as a non‐invasive intervention in the treatment of MS, clinical trials have tested the effects of supplementation of unsaturated fatty acids and found that there was a positive trend in the attenuation of symptoms, although it did not produce statistically significant results.59 Saturated long‐chain fatty acids Saturated long‐chain fatty acids, such as lauric acid, have been shown to have antimicrobial properties in high concentrations.60 These lipid molecules have a tendency to primarily target Gram‐positive microbes. They have even been implicated recently as a potential topical therapy for inflammatory skin conditions caused by Gram‐positive organisms such as Propionibacterium acnes.60 Because saturated fatty acids form an increasingly substantial portion of energy‐supplying molecules in westernized diets, there has been growing interest in the role of lauric acid in EAE due to shaping the microbiota with antimicrobial properties as well as shaping the GALT with TLR4 agonist properties similar to that of LPS.61 In vitro experiments supplementing media with saturated long‐chain fatty acids, namely lauric acid, showed an up‐regulation of Th17 cells and Th1 cells alongside a down‐regulation of Treg cells.62 In depth analysis of the transcriptome from these experiments showed an increase in pro‐inflammatory markers (TNF‐α, interferon‐γ and Csf2) as well as a decrease in the anti‐inflammatory marker Foxp3. Interestingly, these differential cytokine levels coincided with an up‐regulation of the AHR, which shows a potential increased susceptibility to both endogenous and microbiota‐produced compounds to compete as antagonists/agonists to drive further T‐cell proliferation towards either an inflammatory or anti‐inflammatory phenotype. To focus on the effects of microbial by‐products, researchers included faecal filtrates from saturated long‐chain fatty acid‐fed mice to cell cultures in Th17 cell polarizing conditions, which resulted in higher proportions of activated Th17 cells than that of control groups when compared with media that were supplemented with the faecal filtrates of mice fed a normal diet.62 Sequencing analysis from these experiments showed decreased abundance of Bacteroidetes families as well as of Prevotellaceae. Both of these bacterial populations have previously been implicated in having protective roles against the progression of EAE symptoms through production of the SCFA butyrate,51, 52 which in turn up‐regulates Treg cell proliferation. Passage through the BBB Passage of compounds from the peripheral blood supply into the CNS through the vascular endothelium composing the BBB is dependent on characteristics such as lipid solubility, tertiary structure, concentration, molecular weight and charge of the compound.63 Generally compounds that can freely pass through the endothelium are low‐molecular‐weight lipid‐soluble molecules with little to no charge. Majority of the bioactive compounds previously covered in this review are either theorized to be BBB permeable due to having all of the key characteristics of BBB‐positive compounds, or have been proven to be BBB permeable through previous experimentation. Cytokines, generally hydrophilic in nature, present in the peripheral blood can modulate immunological functions within the CNS due to transporter‐protein‐mediated passage through the BBB and deposition into the CNS.64-66 The passage of cytokines produced by peripheral lymphatic tissue through the BBB endothelium presents a bridge for BBB‐negative compounds to have lasting effects on the physiology of the CNS through the modulation of peripheral lymphocytes. Intravenously injected indole compounds similar in structure to those produced by bacterial tryptophan metabolism have been shown to be able to freely pass through the BBB when present in the peripheral blood in high enough concentrations.67 While structurally similar to many BBB‐positive compounds, the indole‐based microbial by‐products of tryptophan metabolism have not been characterized as BBB‐negative or ‐positive in vivo. The antioxidant glutathione is known to be BBB‐positive due to well‐defined transport proteins along the BBB that permit the deposition of glutathione in the non‐oxidized state into the CNS.68 LPS has been shown to be minimally invasive through the BBB endothelium of mice in vivo.69 The neuroinflammatory effects of LPS can be accomplished by TLR activation in peripheral tissues inducing secondary effects within the CNS through BBB‐positive mediators such as pro‐inflammatory cytokines. SCFAs are BBB‐positive, used by the CNS, and are integral in the development of proper permeability within the BBB.70, 71 It is currently unknown how much of the protective effects displayed by SCFAs in EAE are the result of direct interaction with the CNS versus interactions in the periphery. Summary and conclusion Multiple sclerosis is a debilitating autoimmune disease and, similar to 80 other autoimmune disorders, has no cure and limited treatment options aimed at reducing the clinical symptoms. Although there is increasing evidence suggesting that gut microbiota may play a critical role in the development or progression of MS, the precise mechanisms through which the gut microbiome can influence immune functions in the CNS despite the presence of BBB is unclear. This review systematically analysed the role of microbial metabolites and how they may regulate the immune functions of the host both within and outside the CNS, thereby providing evidence to support the hypothesis on the gut–brain axis (Fig 1). So far, research on the role of microbiota in MS has been fruitful in developing a better understanding of the pathogenesis of MS, but much more research is clearly needed in this field. Specifically, whether MS results from alterations in the microbiota caused by environmental factors and whether the microbiota influence the severity of the disease through regulation of immunological tolerance, needs additional research. Focusing research on probiotic organisms that produce beneficial metabolites or introducing changes in diet or other environmental factors to induce dysbiosis that is associated with induction of Treg cells or other immunosuppressive cytokines to attenuate chronic inflammation, can offer novel preventive and therapeutic modalities against a wide array of inflammatory and autoimmune diseases. Additionally, identification of specific deleterious microbiota triggering or promoting MS, and approaches to replace them with those that dampen chronic inflammation, can yield microbially based therapies that can help patients with minimally invasive procedures as well as cutting down on the costs of expensive long‐term medications and their associated toxicity. Disclosures The authors declare that there are no conflicts of interest. Funding NIH grants R01ES019313, R01MH094755, R01AI123947, R01AI129788, P01AT003961, P20GM103641, and R01AT006888. References Citing Literature Number of times cited according to CrossRef: 7 Eric M. Brown, Douglas J. Kenny and Ramnik J. Xavier, Gut Microbiota Regulation of T Cells During Inflammation and Autoimmunity, Annual Review of Immunology, 10.1146/annurev-immunol-042718-041841, 37, 1, (599-624), (2019). Crossref Daniel M. Altmann, Establishing the new playbook for interactions among microbiota, bacterial metabolites, adaptive immunity, autoimmune disease and metabolic syndrome, Immunology, 154, 4, (533-534), (2018). Wiley Online Library Daniel M. Altmann, Neuroimmunology and neuroinflammation in autoimmune, neurodegenerative and psychiatric disease, Immunology, 154, 2, (167-168), (2018). Wiley Online Library Antonio Inserra, Claudio Alberto Mastronardi, Geraint Rogers, Julio Licinio and Ma-Li Wong, Neuroimmunomodulation in Major Depressive Disorder: Focus on Caspase 1, Inducible Nitric Oxide Synthase, and Interferon-Gamma, Molecular Neurobiology, 10.1007/s12035-018-1359-3, (2018). Crossref Matthew Lacorcia and Clarissa U. Prazeres da Costa, Maternal Schistosomiasis: Immunomodulatory Effects With Lasting Impact on Allergy and Vaccine Responses, Frontiers in Immunology, 10.3389/fimmu.2018.02960, 9, (2018). Crossref Leila Abdelhamid and Xin Luo, Retinoic Acid, Leaky Gut, and Autoimmune Diseases, Nutrients, 10.3390/nu10081016, 10, 8, (1016), (2018). Crossref Monica J Killen, Susan Giorgi-Coll, Adel Helmy, Peter JA Hutchinson and Keri LH Carpenter, Metabolism and inflammation: implications for traumatic brain injury therapeutics, Expert Review of Neurotherapeutics, 10.1080/14737175.2019.1582332, (1-16), (2019). Crossref

Single-cell analyses of glioblastoma samples reveal multiple cellular states, their
plasticity and the genetic underpinnings of state proportions in a given tumor.

Objective To investigate intrathecal inflammation using cerebrospinal fluid (CSF) cytokines and chemokines in a subgroup of pediatric epilepsy patients with frequent daily seizures. Methods We measured 32 cytokines/chemokines using multiplex immunoassay in CSF collected from pediatric patients with febrile infection‐related epilepsy syndrome (FIRES)/FIRES‐related disorders (FRD; n = 6), febrile status epilepticus (FSE; n = 8), afebrile status epilepticus (ASE; n = 8), and chronic epilepsy with frequent daily seizures (n = 21) and compared the results with noninflammatory neurological disorders (NIND; n = 20) and encephalitis (n = 43). We also performed longitudinal CSF cytokine/chemokine studies in three cases with FIRES/FRD. Results The median age of onset of seizures was 2.4 years (range = 0.08‐12.5). Median CSF timing from the onset of seizures was longer in chronic epilepsy (540 days), whereas FIRES, FSE, and ASE had CSF tested within 1‐2 days of onset of seizures (P < .001). The elevation of cytokines/chemokines was higher in FIRES followed by FSE, when compared to chronic epilepsy and NIND controls. Th1‐associated cytokines/chemokines (TNF‐α, CXCL9, CXCL10, CXCL11), IL‐6, CCL2, CCL19, and CXCL1 (P < .05) were elevated in FIRES, in contrast to the elevation of a broader network of cytokines/chemokines in encephalitis. The cytokines/chemokines (CXCL9, CXCL10, CXCL11, and CCL19) were elevated in FSE when compared to ASE despite the similar median seizure duration and timing of CSF testing in relation to seizures. Chronic epilepsy generally lacked significant elevation of cytokines/chemokines despite frequent daily seizures. The median concentrations of the cytokines/chemokines rapidly declined on serial testing during the course of illness in all three FIRES/FRD cases. Significance We identify significant differences in CSF cytokine/chemokine profile between FIRES/FRD and encephalitis. The prominent elevation of CSF cytokines and chemokines in FIRES/FRD and to a lesser extent FSE highlights that the cytokine/chemokine elevation is significantly associated with the etiology of the underlying process rather than purely reactive. However, it is unclear whether the immune activation contributes to the disease process.

Microglia are essential for the development and function of the adult brain. Microglia arise from erythro-myeloid precursors in the yolk sac and populate the embryonic brain early during development. Unlike monocytes, which are constantly renewed via the differentiation of bone marrow-derived hematopoietic stem cells throughout life, resident microglia in the healthy brain are thought to persist during adulthood via constant self-renewal. Their ontogeny, together with the absence of turnover from the periphery and the singular environment of the central nervous system (CNS), make microglia a unique cell population. Supporting this notion, recent transcriptional studies have revealed that microglia display specific gene expression signatures that are clearly distinct from other brain and peripheral immune cell populations in the healthy and diseased CNS.The unique properties of microglial cells during development, as well as in the adult CNS, such as their role in synaptic stripping or the exceptional capacity to scan the brain parenchyma and rapidly react to its perturbations, have emerged in recent years. In the coming years, understanding (i) how microglia acquire and maintain their unique profiles in order to fulfill distinct tasks in the healthy CNS and (ii) how these are altered in perturbed environments will be essential to develop strategies to diagnose or treat CNS disorders with an immunological component. This Research Topic will provide a comprehensive overvie

STEM CELLS, a peer reviewed journal published monthly, provides a forum for prompt publication of original investigative papers and concise reviews. STEM CELLS is read and written by clinical and basic scientists whose expertise encompasses the rapidly expanding fields of stem and progenitor cell...

Summary Genes encoding antigen‐presenting molecules within the human major histocompatibility complex (MHC) account for the highest component of genetic risk for many neurological diseases, such as multiple sclerosis, neuromyelitis optica, Parkinson's disease, Alzheimer's disease, schizophrenia, myasthenia gravis and amyotrophic lateral sclerosis. Myriad genetic, immunological and environmental factors may contribute to an individual's susceptibility to neurological disease. Here, we review and discuss the decades long research on the influence of genetic variation at the MHC locus and the role of immunogenetic killer cell immunoglobulin‐like receptor (KIR) loci in neurological diseases, including multiple sclerosis, neuromyelitis optica, Parkinson's disease, Alzheimer's disease, schizophrenia, myasthenia gravis and amyotrophic lateral sclerosis. The findings of immunogenetic association studies are consistent with a polygenic model of inheritance in the heterogeneous and multifactorial nature of complex traits in various neurological diseases. Future investigation is highly recommended to evaluate both coding and non‐coding variation in immunogenetic loci using high‐throughput high‐resolution next‐generation sequencing technologies in diverse ethnic groups to fully appreciate their role in neurological diseases. Introduction Rare or common neurological diseases are associated with an impaired central nervous system (CNS) and/or peripheral nervous system (PNS). Neurological disease impacts approximately 1 billion individuals around the world, comprising individuals of all age groups and races, in diverse geographical locations and with diverse socio‐economic status.1 Together, neurological diseases represent 7·1% of the total global burden of disease, evaluated in disability‐adjusted life years, across all causes and ages.2 Despite significant progress in the management of many neurological diseases, we are still lacking complete and coherent models of pathogenesis, and as a result the repertoire of available therapies is imperfect. Recent advances in genomic sciences have set in place the foundation for understanding and decoding the rules of inheritable risk for chronic neurological diseases, which may translate into improved prognosis of outcomes and new therapeutic options. The genetic signals associated with susceptibility to the majority of neurological diseases remains inadequately explained due to the heterogeneous and multifactorial nature of these complex traits.3 Myriad genetic, immunological and environmental factors may contribute to an individual's susceptibility to neurological disease. However, the clear implication of genetic factors in the causation of many neurological diseases has been gleaned from heritability studies in families, twins and adopted individuals.3 Familial studies have reported increased incidence of several neurological diseases in offspring or siblings of affected individuals, twin studies have reported higher disease concordance in monozygotic than in dizygotic twins and studies in adopted individuals have suggested a high disease concordance in monozygotic twins raised in diverse environments. Genes encoding antigen‐presenting molecules within the human major histocompatibility complex (MHC) account for the highest component of the genetic risk for many neurological diseases. Risk or protection for a variety of neurological diseases, including multiple sclerosis, neuromyelitis optica, Parkinson's disease, Alzheimer's disease, schizophrenia, myasthenia gravis and amyotrophic lateral sclerosis, has been mapped to this region (Fig. 1). However, the precise mechanisms underpinning these effects in these neurological diseases remain elusive. Here, we aim to review and discuss the decades long research on the influence of genetic variation at immunogenetic loci in neurological disease. We focus primarily on the well‐studied loci of the MHC, and later turn our attention to the killer immunoglobulin‐like receptor (KIR) complex, whose protein products functionally interact with some loci of the MHC. The human major histocompatibility complex region and neurological disease The balance of innate and adaptive immunity is now appreciated as an important component in the determination of neurological disease outcome. The molecules encoded by the major histocompatibility complex (MHC) regions regulate the innate and adaptive arms of human immune response through antigen presentation, inflammation regulation and the complement system and the impact of this region in various immune‐mediated conditions, including neurological diseases, has long been recognized.4-9 The human MHC gene family maps to chromosome 6. With a size of nearly 5 Mbp it encodes approximately 165 protein‐coding genes, many of them immune‐related,10 and comprises approximately 0·13% of the human genome.9 After the first discovery of the mouse MHC in 193611 the human equivalent, the human leucocyte antigen (HLA), was subsequently mapped and extensively studied for both gene content and allelic variation. Thus, the HLA region became the most investigated region in vertebrate genomes. This region is considered the densest region of the human genome and with the effort of the MHC sequencing consortium the complete sequence and gene map of this region was first generated in 1999.12 The HLA region is characterized by an extreme level of polymorphism and extensive patterns of linkage disequilibrium (LD), which varies among populations. The genes of this region are divided into five subregions: (i) the extended class I, (ii) class I, (iii) class III, (iv) class II and (v) extended class II regions.9 The extended MHC region comprises greater than 400 annotated genes and pseudogenes.10 The HLA class I region consists of three classical loci, HLA‐A, HLA‐B and HLA‐C, along with three non‐classical loci: HLA‐G, HLA‐E and HLA‐F. The non‐classical HLA class I molecules are characterized by a more limited degree of polymorphism compared to the their classical counterparts.9 HLA class I molecules are expressed on all nucleated cells and their main function is presentation of non‐self antigens originated from intracellular sources to cytotoxic (CD8+) T‐cells for killing of the antigen‐presenting cells (APCs).13 Similarly, the class II region of HLA comprises three classical loci, HLA‐DP, HLA‐DQ and HLA‐DR, along with two non‐classical loci, HLA‐DO and HLA‐DM.9 The genes of classical HLA class II loci are expressed on the surface of professional APCs, which generally present antigens of extracellular origin,14 such as those derived from food (metabolites) or bacteria for the presentation to helper (CD4+) T‐cells. The HLA class III region consists of inflammatory regulatory genes, such as complement (C2, C4, CFB), cytokine genes (e.g. TNF, LTA, LTB) and other genes with non‐immune or unknown functions.9 The CNS is considered an immune privileged site, and it was long considered that typical neurons did not express HLA class I. However, this notion was rejected following the detection of HLA class I mRNA and/or protein expression in various neuronal populations, comprising motor nuclei, substantia nigra pars compacta,15, 16 dorsal root ganglia neurons,17 dopaminergic nigral cells,18 developing and adult hippocampal pyramidal cells,19, 20 sensory neurons of the vomeronasal organ,21, 22 brainstem,15, 18 and spinal,15, 23 motor neurons and cortical pyramidal cells.16, 20 More recently, a direct link has been established for HLA class I in functional and structural synapse pruning in the CNS.24, 25 Further, the capacity of microglia, the brain's resident macrophage, to present antigen through the class II MHC to T‐cells permits these typically quiescent cells to perform an important role in determining the clinical outcome of various neurological diseases. The roles of microglia in several neurological diseases are well documented.26-28 Taken together, the HLA loci are vital for shaping cellular adaptive immune responsiveness, and their impact upon human health and disease has long been appreciated. During the course of four decades, the impact of variation in HLA has been studied with respect to neurological disease. A time‐line of the crucial findings of MHC and KIR loci in relevance to neurological diseases are presented in Fig. 2. In the following sections, we discuss the role of HLA class I and II molecules in these diverse and often debilitating diseases (Table 1). Neurological diseases MHC class II MHC class I References Predisposing Protective Predisposing Protective Multiple sclerosis DRB1*15:01, DRB1*15, DRB1*08:01, DRB1*04:05, DRB1*03:01; DRB1*13:03; DRB1*13∼DQA1*05:01∼DQB1*03:01 DRB1*14:01, DRB1*11, DRB1*13‐DQB1*06:03, DQA1*01:01‐DRB1*15:01, DQB1*03:01‐ DQB1*03:02 A*03, *0301; B*07 A*02:01; B*44:02, *44, *38:01, *55:01; C*07, *05 5, 29, 30, 35-41, 50-55, 57-64 Neuromyelitis optica DPB1*05:01, DPB1*03:01, DRB1*12, DRB1*16:02, DRB1*03 DRB1*09:01 – – 66-76 Parkinson DRA, DRB5, DRB1, DRB1*04, DRB1*04:03, DRB1*03, DRB1*03:01 DRB1*04:06, DRB1*04:04, DQA1*03:01 B*07:02, *17, *18; C*07:02 C*03:04 4, 77, 78, 84, 86, 87, 89 Alzheimer's DR1, DR2, DR3, DRB1*03, DPB1, DRB5‐DRB1, DRA DR4, DR6 A*02 B*07:02, A*03:01 8, 94-101, 104 Schizophrenia DRB1*01:01, DRB1*03:01:01, DRB1*03:01:02, DQA1 DRB1*03:01, DRB1*04, DRB1*06 B*08:01, C*01:02 A*03, *011, *02; B*27, *51 107, 108, 111, 114, 117, 118 Myasthenia gravis DQB1*05:02, DRB1*03, DRB1*04, DQB1*02, DQB1*03, DRB1*09, DRB1*15:01, DQB1*05:02, DRB1*16, DQA1*03:02/DQB1*03:03:02 DRB1*08, DRB1*13:01, DQA1*05:01 B*08, C*07:01 – 63, 121-125, 130, 132, 133, 138 Amyotrophic lateral sclerosis – – A*03, A*02, A*28; B*40, B*35, C*04 A*09, HLA‐F 7, 140-142, 145, 146 HLA and multiple sclerosis The neurological disease most clearly and consistently associated with variation in the HLA region is multiple sclerosis (MS). The first evidence for the association of HLA class I antigens with MS was published in 1972,29 with risk for MS initially reported to be associated with HLA‐A*03 and HLA‐B*0729, 30 on the basis of their serological specificity.29-32 It later became apparent that these class I alleles were part of an extended class I and class II haplotype, associated with the serological determinant Dw2,33 later renamed DR2.34 The advancement in HLA genotyping approaches and continuous investigation of this region in MS ultimately revealed that the DR2 specificity has two distinctive molecular allotypes, DR*15 and DR*16, and the correlation with MS was pinpointed to DRB1*15:01,35 a subtype of DRB1*15.36 In illustration of the strength and consistency of this association in individuals with European ancestry, a Human Genome Epidemiology (HuGE) report reviewing 72 published studies from 1993 to 2004 observed a significantly increased frequency of DRB1*15:01 among MS patients in the vast majority.37 Reports of non‐association of DRB1*15:01 with MS, in almost every instance, was performed in cohorts of non‐European ancestry. Recently, GWAS performed in collaboration with the International Multiple Sclerosis Genetics Consortium (IMSGC) and the Wellcome Trust Case Control Consortium 2 (WTCCC2) project confirmed that the main susceptibility signal for MS maps to the DRB1 in the class II region of the MHC, and describes up to 10·5% of the genetic variance underlying risk.5 DRB1*15:01 revealed the strongest effect with an average odds ratio (OR) of 3·08, and all additional DRB1 associations emerge to describe less than 2% of the residual variance.5 Similar to other autoimmune diseases, DRB1*15:01 in MS susceptibility adheres to an additive model in a dose‐dependent manner with zero, one or two copies of the causal allele accounting for increased risk, respectively.38, 39 Along with the augmented risks for DRB1*15:01 homozygous genotypes, an epistatic effect for MS risk has been reported for carriers of the DRB1*15:01/*08:01 heterozygous genotype, with an augmented risk compared to other heterozygous DRB1*15:01 genotypes,40 while DRB1*08:01 alone was not observed to be a risk allele. However, a report in an Ashkenazi Jewish cohort suggested an independent association of DRB1*08:01 when considering clinical subgroups, with a weak significant signal observed only in primary progressive patients.41 Moreover, DRB1*15:01 is the most consistently reported MS susceptibility marker of disease severity. An effect of age and gender along with DRB1*15:01 has also been reported, and it was suggested that female MS patients carrying the DRB1*15:01 haplotype have an earlier age of disease onset.42, 43 In an attempt to correlate DRB1*15:01 with disease progression or severity, this allele was associated with the existence of oligoclonal bands and increased immunoglobulin (Ig)G levels in the cerebrospinal fluid (CSF) of MS cases.44, 45 In contrast, there has been no consistent reporting of other MS predisposing DRB1 alleles with respect to disease progression or severity.38, 46 DRB1*15:01 is most often observed in European populations as a segment of an extended haplotype with DQA1*01:02 and DQB1*06:02, and therefore it has been considered challenging to discriminate the main casual allele or locus. Imputation of classical HLA alleles from single nucleotide polymorphism (SNP) data demonstrated DRB1 as a primary risk locus in Europeans, and revealed that the majority of the effect attributed to DQB1*06:02 can be elucidated primarily by association with DRB1*15:01.47 As the HLA region displays varied patterns of linkage disequilibrium between populations, cross‐population analysis can be explanatory in unravelling the predisposing locus from a multilocus association. Examination of the African American MS cohort indicated risk to be strongly attributable to DRB1*15.48 In the same study, the evaluation of alternate DQB1*06:02 haplotypes without DRB1*15 suggested no difference between cases and controls, eliminating DQB1*06:02 as the primary allele of the association signal.48 This observation has been strengthened by a study in a population from Martinique with African ancestry.49 Non‐European studies suggested a correlation of DRB1*15 and DRB1*04:05 with MS in Japanese50 and Asian populations, respectively.50, 51 The same studies have reported the association of DRB1*04:05 with a clinically diverse disease course described by earlier onset age, decreased severity50 and a lack of brain lesions.51 Similarly, in Europeans the detection of a correlation of DRB1*04:05 with MS in Sardinian,52, 53 Sicilian53 and African American54 populations provided a coherent model for DR4 with MS aetiology. Additionally, the correlation of DRB1*03:01 and DRB1*13:03 was first detected in Sardinian55 and Israeli Ashkenazi and non‐Ashkenazi Jewish MS41 patients, respectively, but this allele is extremely common throughout Europe, Africa and Asia. In contrast to DRB1*03:01, DRB1*13:03 has been rarely found at population frequencies higher than 3% worldwide, but the correlation with MS shows effect sizes.56 A study in Canadian multiplex MS families found over‐transmission of the DRB1*13˜DQA1*05:01˜DQB1*03:01 haplotype;57 however, this study did not evaluate the DRB1 locus at high resolution. This haplotype is almost constantly linked with the DRB1*13:03 allele in Europeans, whereas the other common subtypes of DRB1*13 allele, such as of DRB1*13:01 and DRB1*13:02, are usually located on other DQA1˜DQB1 haplotypes; these additional DR*13 haplotypes were not observed to be over‐transmitted in the Canadian study. Protective effects for HLA have also been observed in some studies. The protective effect of HLA class II alleles was seen for DRB1*14:01 in the European MS cohort,39, 40 while DRB1*11 was protective in both a Brazilian58 and a Canadian MS cohort.59 Similarly, the DRB1*13˜DQB1*06:03 haplotype was protective in Finnish60 and Canadian MS families.57 Another study confirmed interactions involving pairs of HLA class II alleles: DQA1*01:01‐ DRB1*15:01 and DQB1*03:01‐ DQB1*03:02, with a protective effect in MS.61 In the same study, HLA class I‐mediated protection has also been observed for HLA‐A*02:01, HLA‐B*44:02, HLA‐B*38:01 and HLA‐B*55:01.61 More recently, HLA‐B*44‐mediated protection was also reported in MS.62 Similarly, an imputation study revealed protection by the high‐resolution HLA‐B*44:02 genotype in MS.63 Finally, HLA‐B*44:02 was observed in LD with HLA‐C*05, which independently demonstrated protection for MS in the absence of DRB1 risk alleles;64 thus, it is challenging to discriminate whether these observations reflect a single effect through strong LD. HLA and neuromyelitis optica Neuromyelitis optica (NMO) was initially considered a variant of MS, but the identification of antibodies for aquaporin 4 (AQP4) or NMO IgG considerably transformed clinical discernment of the disease as an independent entity.65 This led investigators to evaluate the potential role of the HLA region in the aetiology of NMO. Numerous reports in Japanese populations, where the prevalence of NMO is higher than in European populations, suggested DPB1*05:01 as a predisposing allele and DRB1*09:01 with a protective effect.66-68 These results were confirmed in a replication study on a southern Han Chinese NMO cohort.69 Later, additional HLA class II alleles were found to be predisposing in NMO, including DPB1*03:01,70 DRB1*1271 and DRB1*16:02.68, 69 Meanwhile, in contrast to Asian populations,69 DPB1*05:01 revealed no association with NMO in a French population, but DRB1*03 was shown to be a susceptibility marker.66, 67, 72 Similarly, DRB1*03 has been also observed with increased risks for NMO among Brazilian mulattos,73 Afro‐Caribbeans74 and Mexican Mestizos,75 but not in Muslim Arabs.76 It is important to consider that as DRB1*03 is comparatively less frequent and DPB1*05:01 is more frequent in Asian population, there may be inadequate power to detect the risk for DRB1*03 in Asian populations and DPB1*05:01 in European populations, yielding these varied results. HLA and Parkinson's disease The association of HLA with Parkinson's disease (PD) was first reported more than 4 decades ago.77 This study reported an increased risk for PD attributable to the HLA‐B*17 and ‐B*18 antigens.77 However, subsequent studies failed to replicate the association of HLA class I antigens with PD.4, 78 Genomewide association studies (GWAS) provided a new angle for investigating common complex traits such as PD.4, 78 Evaluation of more than a million SNPs in large sample sizes considerably enhanced the statistical power of the associations. Breakthrough discoveries made by two GWAS recognized SNPs in the HLA‐DR region to be associated with PD, confirming the immune component in pathogenesis of PD.4, 78 Hamza et al.4 suggested the association of rs3129882, a non‐coding variant in HLA‐DRA with PD in Americans of European ancestry, while a large‐scale imputation‐based approach applied in a meta‐analysis of five GWAS with data generated from US and European cohorts identified chr6: rs32588205 A/G SNP located in the intronic region of HLA‐DRB5 locus with augmented risk for PD under an additive model.78 Because the HLA‐DRA locus is mostly monomorphic and less often identified in HLA disease association studies, attempts to replicate this observation have generated varied and conflicting results.79-85 Similarly, the HLA‐DRB5 locus is in strong LD with HLA‐DRB1 and only present in approximately 20% of the population, and thus this association has also been challenging to decipher. In an attempt to replicate the finding of a GWAS‐reported association of rs3129882 in HLA‐DRA locus, two studies in different populations used a candidate gene approach and confirmed the association of rs3129882 variants with increased risks of PD. The first was conducted in a small cohort of 284 Chinese Han cases and 258 controls from Mainland China,79 and the second in 520 Iranian cases and 520 controls.80 Meanwhile, a meta‐analysis of five case–control studies with a total of 2230 PD cases and 2262 controls from Mainland China, Taiwan, Singapore and Malaysia reported no association of HLA‐DRA rs3129882 variants with PD.85 Subsequently, a study performed in three different European‐ancestry cases and controls from the United States, Ireland and Poland in a comparatively larger cohort of 1313 cases and 1305 controls observed no association of rs3129882 variants with PD under an additive or dominant model.81 However, the same study found a protective effect of GG genotype in the Irish, Polish and combined cohorta under a recessive model.81 Finally, no association with rs3129882 was reported in two GWAS: the first conducted in a relatively homogeneous Ashkenazi Jewish (AJ) population from New York comprised of 2050 cases and 1836 controls;82 and the second in the largest single PD GWAS cohort of 3400 cases and 29 000 controls.83 A French case–control PD study revealed an association of rs660895 within the HLA‐DRB1 locus, which is significantly more polymorphic than HLA‐DRA and, unlike HLA‐DRB5, present in all individuals and is frequently associated with disease.84This study used an imputation approach to infer HLA alleles from SNP data, and suggested a protective effect for DRB1*04.84 Another study reported an association of DRB1*03 with increased risks to PD in individuals with European ancestry.86 Subsequently, these results were confirmed in another study performed on 567 PD Han Chinese patients and 746 controls from Guangdong province of the China, and suggested the strongest association for PD causation with DRB1*03:01, the most common subtype of DRB1*03 allele.87 Meanwhile, the same study has also found a decreased frequency of DRB1*04:06 in PD cases compared to controls, suggesting a protective effect.87 Interestingly, the DRB1*04:06 allele, a subtype of DRB1*04, is rare in European populations; however, it is common in Asian populations (http://www.allelefrequencies.net).88 DRB1*04:03, another subtype of DRB1*04, has been reported to be more frequent among PD cases in Han Chinese.87 Whether DRB1*04:06 displays a susceptible effect in European ancestry populations still needs to be evaluated. A more recent and large study implicated structural and regulatory variants in the HLA region.89 This study suggested that rs3129882 located in intron‐1 and the closely linked rs9268515 and rs2395163 SNPs positioned in intergenic region remained significant regardless of HLA alleles.89 Further, this study used an imputation approach and suggested an increased risk for B*07:02 ˜ C*07:02 ˜ DRB5*01 ˜ DRB1*15:01 ˜ DQA1*01:02 ˜ DQB1*06:02 haplotype and a protective effect for C*03:04, DRB1*04:04 and DQA1*03:01 alleles.89 However, when they conditioned on the associated SNPs, only C*03:04 and DRB1*04:04 alleles remained significant.89 Finally, this study concluded that rs3129882 and rs2395163 SNPs are in expression quantitative trait loci (eQTLs) for HLA‐DR and HLA‐DQ, and suggested that HLA gene expression might impact PD.89 HLA and Alzheimer's disease Like MS and PD, the first report of a role for HLA in Alzheimer's disease (AD) was published in the 1970s.90 Since then, multiple studies have evaluated the role of HLA class I91-94 and class II genes in AD.95-99 The early findings of an association with HLA‐A*02 in AD were inconsistently replicated. While some studies confirmed a role for this antigen,94, 100 others failed to replicate any association.91 Most of these studies suffered from small sample sizes, but two most well‐powered studies failed to find any association of HLA‐A*02 with AD.92, 93 More recently, a trend for association of SNPs in the HLA‐A locus with atrophy of brain structures has been reported, although the corrected P‐values in this study would be considered marginal.94 The role of HLA class II antigens has also been investigated in the pathophysiology of AD. Curran et al.95 showed that DR1, DR2 and DR3 antigens, in the absence of apolipoprotein E (APOE) risk alleles, are associated with an increased risk for developing late‐onset AD, whereas DR4 or DR6 antigens appear to be associated with a decreased risk of AD. Aisen et al.96 suggested that DR4 might exert a protective influence in AD via modulation of glial activity. A later study also showed that risk for AD in older late‐onset cases is associated with DRB1*03 in APOE4‐negative individuals.97 However, as is the case for HLA‐A*02, these studies have suffered from small sample sizes. Large‐scale GWAS have also provided evidence for the involvement of HLA class II in AD. Analysis of genomewide copy number variation (CNV) suggested a susceptible association for DPB1 in AD.98 A subsequent GWAS meta‐analysis in 17 008 late‐onset cases and 37 154 controls with European ancestry identified a SNP from the DRB5–DRB1 region to be associated with late‐onset AD risk.99 The association of this SNP was replicated in a Chinese cohort,101 and further work showed that this SNP is associated with cis‐gene expression levels of DRB1 in the temporal cortex and cerebellum.102 Nettiksimmons et al.103 showed an association of the DRB5–DRB1 clusters with cognitive decline at the gene‐level, and more recently methylation of DRB5 in the brain was associated with pathological AD, with another peak of association in DRA.104 Yokoyama et al.105 determined that variants associated with autoimmune disease are also associated with AD and found that a SNP close to DRB5 is associated with AD and psoriasis. The authors also showed that although DRB5 transcript expression is not altered in AD brains, there is an increase in transcript expression for DRA in AD brains compared to control brains. Finally, an HLA imputation‐based analysis of 5919 European‐ancestry AD Caucasian patients and 5771 controls identified the extended haplotype A*03:01˜B*07:02˜DRB1*15:01˜DQA1*01:02˜DQB1*06:02 as being associated with AD risk (P = 9·6 × 10−4, OR = 1·21)8 in individuals who are negative for APOE 4.8 The authors also found an association of the class I haplotype A*03:01~B*07:02, with higher CSF amyloid levels and a dose‐dependent association of the DR15 haplotype with greater rates of cognitive decline and baseline levels of chemokine CC‐4.8 HLA and schizophrenia The first evidence for a probable role of HLA in schizophrenia (SCZ) was described in 1974.106 Thereafter, multiple linkage studies provided some evidence for a susceptibility locus on the short arm of chromosome 6.107, 108 These studies correlated numerous class I and class II alleles with SCZ.107, 108 However, subsequent studies failed to replicate these initial findings.107, 108 More recently, publication of the first GWAS and meta‐analysis in SCZ made possible the study of the HLA region at higher resolution.6 A meta‐analysis of three GWAS identified several MHC region variants associated with SCZ in individuals with European ancestry.6, 108-110 Some of these were consistently replicated or found in other populations.108, 111-113 However, it is interesting to note that most of the significant variants correlated with SCZ in the meta‐analysis were located in the extended MHC regions, near a cluster of histone genes comprising a position upstream of the class I region, along with a few additional immune genes such as ribonuclease P21 (RPP21) located in class I region and neurogenic locus notch homologue 4 (NOTCH4) located in the extended class II region.109 Subsequently, GWAS analysis performed in SCZ cases from Asia replicated the findings of the European GWAS, and additionally recognized a few novel variants in Chinese112 and Japanese populations.113 Similarly, the rs9272219 and rs9272535 variants in the DQA1 gene revealed a moderate association with SCZ.111 An HLA imputation study showed an association of the risk allele HLA‐C*01:02 in addition to trends for association of the protective alleles DRB1*03:01 and B*08:01.114 A GWAS in Ashkenazi Jews showed supportive evidence for association of the HLA region with SCZ in this population.115 Finally, an eQTL study strengthened these results by providing evidence that the TRIMP26, RNF5 and DRB3 genes, located within the MHC region, are regulated by the top SNPs recognized by meta‐analysis of GWAS data.116 In addition to GWAS results, previous reports suggested an increased frequency of DRB1*01:01 and a decreased frequency of DRB1*04 among SCZ patients.117, 118 However, it is important to note that all HLA association studies performed in SCZ to date have either used low‐resolution genotyping methods or GWAS/SNP imputation approaches. The lack of consistent findings suggest that high‐resolution HLA genotyping approaches will be required to fully appreciate the role of HLA variants in SCZ. More recently, a well‐powered study associated SCZ risk with complex variation in complement component 4 (C4) genes, also located within the MHC.119 This study found that C4 alleles produced extensively varying levels of C4A and C4B expression in the brain, with each common C4 allele correlating with SCZ in proportion to its ability to produce higher expression of C4A.119 The findings of this study highlight the role of complement genes in pathophysiology of SCZ, and these observations open new frontiers for future investigations of genetic variation in complement genes with SCZ in other ethnic groups in the quest to find a coherent model for SCZ. HLA and myasthenia gravis The first report of an HLA association with myasthenia gravis (MG) was published in 1976.120 Thereafter, several studies have reported evidence of association of HLA antigens/alleles with MG. An Italian study identified DQB1*05:02 as being associated with MG,121 while a Tunisian study identified the DRB1*03, DRB1*04, DQB1*02 and DQB1*03 alleles as possible predisposing factors for MG.122 DRB1*03 was then subsequently found to be associated with MG in a Portuguese study.123 Meanwhile, in a northern Han Chinese population, DRB1*09 was associated with risk of MG, while DRB1*08 was protective.124 A GWAS published in 2012 on North Europeans identified the class I SNP rs7750641 as the strongest signal in MG, and further imputation analysis identified HLA‐B*08 as being the major risk allele.125 Similarly, an imputation study observed a risk association for HLA‐C*07:01 with MG.63 There is strong LD between HLA‐C*07:01 and HLA‐B*08, but the latter revealed a marginally weaker association than HLA‐C*07:01 in the same study.63 Examinations of age of onset effects of HLA in MG have yielded mixed results. Although multiple studies have reported the extended HLA haplotype, namely A1‐B8‐DR3‐DQ2, as being associated specifically with early onset of MG (EOMG) in individuals with European ancestry, it is unclear whether the signal maps in class I or class II genes.126-128 Interestingly, the A allele of the SNP rs1800629 at position 308 nucleotides upstream from the transcription initiation site of tumour necrosis factor‐alpha (TNF‐α) has been linked to higher expression level and higher serum levels of TNF‐α in MG by several studies, and this SNP is known to be in LD with the HLA A1‐B8–DR3 haplotype.129 Confounding interpretation of these results, DRB1*13:01 was found to be protective for EOMG in a Norwegian population,130 while a GWAS performed in a European population by Renton et al.131 found a peak of association for EOMG at DQA1. The Norwegian study identified DRB1*15:01 as being associated with the risk of late onset of MG (LOMG), while DRB1*13:01 was also found to be protective in LOMG.130 In an Italian cohort, DQB1*05:02 and DRB1*16 have been reported as being associated with LOMG.132 Renton et al.131 found a peak of association for LOMG at HLA‐DQA1, which was distinct from that observed in the same GWAS in EOMG. Another GWAS showed three distinct and largely independent association peaks for LOMG corresponding to MHC class II, HLA‐A and MHC class III SNPs, while imputation of HLA alleles showed a protective effect of DQA1*05:01.133 Additional studies have sought to elucidate an association of HLA with specific subtypes of MG. Four studies found an association of DQ5 with the specific subgroup of muscle‐specific kinase (MuSK) antibody‐positive (Ab+) MG patients.134-137 A Turkish study also found that DRB1*14 and DRB1*16 were associated with this specific subgroup,136 whereas in a Serbian cohort, DRB1*13 seems to be completely absent in this specific patient population.137 It has been hypothesized that childhood‐onset ocular MG in southern Han Chinese may present a particular subgroup of distinct genetic background, correlating with the haplotype DQA1*03:02/DQB1*03:03:02.138 Later, the haplotype HLA‐B*46:01‐DRB1*09:01 was found to be associated with juvenile ocular MG in the same population.139 However, it is important to note that all studies involved cohorts of, at most, a few hundred individuals, making it difficult to fully elucidate the role of HLA in MG. HLA and amyotrophic lateral sclerosis A very limited number of genetic association studies have evaluated the HLA region in amyotrophic lateral sclerosis (ALS). During the 1980s, a few studies with low‐resolution genotyping sought to examine HLA in ALS.140-142 Initial studies found no correlation between HLA antigens and ALS in patients from California143 and Guam.144 Later, a significantly increased frequency of HLA‐A*03 was reported in an ALS cohort from the greater Boston area140 and Israel.141 Similarly, HLA‐A*02 and ‐A*28 have been shown to be more frequent in ALS cases recruited from Glasgow and Scotland,145 while an increased frequency of HLA‐B*40 was found in an ALS cohort from Finland.142 A study from the greater New York area observed HLA‐Bw35 and ‐Cw4 more frequently in ALS cases, and a trend towards decreased frequency was also found for HLA‐A*09.146 These initial findings were marked by substantial inconsistency in identification of a link between a particular HLA antigen and ALS across study populations, suggesting perhaps that HLA determinants may not play a major role in susceptibility to this diseases. Thereafter, almost three decades passed without HLA association studies conducted in ALS. However, a recent study demonstrating that overexpression of a single non‐classical HLA class I molecule, HLA‐F, resulted in protection of human motor neurons from ALS astrocyte‐mediated toxicity, coupled with a role for the killer cell immunoglobulin‐like receptor KIR3DL2,7 clearly indicated an immune component in ALS pathogenesis. Finally, an association study published in 2017 in a Chinese Han population indicated a role for HLA class II in ALS.147 While inconclusive, these more recent investigations suggest an immunogenetic component to ALS, warranting further study. The killer‐immunoglobulin‐like receptor (KIR) complex: a new horizon in the immunogenetics of neurological disease The KIR complex was first defined in 1986,148 and was initially recognized as KIR inhibitory receptors. The family of the KIR proteins are mainly expressed on natural killer (NK) cells149 and a small percentage of T‐cells.150 The KIR complex maps on the long arm of human chromosome 19q13·4, and is considered as a crucial component of innate and adaptive immunity. Although KIR and HLA are members of two different gene families, the interaction of KIR with their cognate HLA class I ligands serves as a functional bridge in the regulation of NK cell functions and maintenance of immune homeostasis. KIR are inhibitory and stimulatory surface receptors that regulate NK cell function and responsiveness.151 All these receptors consist of either two (2D) or three (3D) extracellular immunoglobulin domains (D). The transmembrane and cytoplasmic domains govern the functional characteristics of these receptors. The inhibitory receptors consist of long (L) cytoplasmic tails comprising immunoreceptor tyrosine‐based inhibitory motifs (ITIMs), whereas stimulating receptors possess short (S) cytoplasmic tails and link to the stimulating adaptor DAP12 through a charged residue in the transmembrane domain. However, KIR2DL4 is an exception, and despite having a long cytoplasmic tail with an ITIM transmits a positive signal through its interaction with the stimulating adaptor FceR1γ.152, 153 Specific KIR molecules recognize one or more of four epitopes of HLA class I molecules. In contrast to the T‐cell receptor, KIR bind to the upper face of the HLA class I molecule, creating contact with the N‐terminal part of the α1 helix, the C‐terminal part of the α1 helix, and the bound peptide.154 Genetic variation in the class I α1 helix governs the three major epitopes perceived by KIR, HLA‐C1, ‐C2 and ‐Bw4. The inhibitory KIR2DL1 and KIR2DL2/3 and the stimulating KIR2DS1, KIR2DS2 and KIR2DS4 interact divergently with the reciprocally unique C1 or C2 epitopes carried by all HLA‐C allotypes and a small subset of HLA‐B molecules.155-157 KIR3DL2, KIR2DS2 and KIR2DS4 recognize a subset of HLA‐A allotypes transmitting the A*03/A*11 epitope (e.g. A*11:01).56 Finally, KIR3DL1/S1 binds subsets of HLA‐A and ‐B allotypes that carry the Bw4 epitope (e.g. A*24:02).56 In contrast, HLA‐B alleles with the Bw6 epitope do not bind with any KIRs. Adding further complexity, these receptor interactions are further tuned by allelic variations of KIR and HLA class I and by the sequence of the bound peptide.158-161 The KIR gene complex exhibits extensive heterogeneity in gene content at both intra‐ and interpopulation levels. KIR haplotypes comprise from four to 14 genes and, based on their genomic structure, are divided into two groups, termed A and B.162 The group A haplotype is characterized by a single configuration of seven genes that express predominantly inhibitory KIR, and all remaining configurations are termed B haplotypes. As an indication of probable functional differences between them, B haplotypes typically express more activating KIR than A haplotypes.163-165 The haplotypes are formed from combinations of unique centromeric and telomeric gene‐content motifs, which also belong to the A or B groups. Although a huge number of unique haplotypes are described, a few comparatively common haplotypes repeatedly account for greater than 90% of the KIR haplotypic variation detected within a specific population, and are observed throughout major ethnic groups.166, 167 Our recent work and that of others has shown that the prevalence of KIR haplotypes and specific combinations of cognate KIR and HLA allotypes are associated in autoimmune162, 168-170 and infectious diseases such as human immunodeficiency virus (HIV) and hepatitis C,171-174 cancer,175, 176 and are critical to the success of solid organ and haematopoietic stem cell transplant (HCT)177-180 and pregnancy.181-185 Although the correlation of HLA variation with neurological disease has been well documented, there is a paucity of studies aiming to evaluate the impact of NK cells or their receptors, including KIR in these diseases. As HLA class I molecules function as the primary ligand for several KIRs, it is possible that the class I association signals perceived for various diseases is, in fact, related to KIR function. In various neurological diseases, such as MS,29, 30, 63, 186 myasthenia gravis,126-128 schizophrenia,107, 108, 114 Parkinson's disease,77, 89 Alzheimer's disease8, 94, 100 and amyotrophic lateral sclerosis,140, 141, 145, 146 the alleles of HLA‐A, ‐B and ‐C that are recognized to function as cognate ligands for their respective KIR genes have been linked with disease (Table 2). Here, it is important to note that the majority of the identified HLA class I association with various neurological diseases described used an imputation approach from data obtained through GWAS rather than direct assay. Meanwhile, a direct link of KIR allele variations with neurological diseases has not been observed in GWAS, very possibly because of a limited number of markers in the KIR region on all common available GWAS platforms. An insufficiency of appropriate reference alignments has traditionally impeded incorporation of KIR exclusive SNPs on the available GWAS platforms, and the large diversification of gene‐content in KIR haplotypes is characteristically discordant with standard quality thresholds. Finally, the Immunochip, which is exclusively enriched for markers in the KIR chromosomal region, predominantly recognizes non‐coding variants on the common group A haplotype that mainly comprises inhibitory KIRs.187 To date, therefore, the majority of described KIR correlations with immune diseases,188 including multiple sclerosis189-191 and schizophrenia,192 used approaches which determine only KIR gene content variation. KIR genotyping approaches that determine gene content are usually impotent to discriminate copy number, but rather assess only presence/absence. As copy number has repercussions on the immune reactions,193 this further hinders the capacity to detect any locus level associations with disease. Additionally, strong LD within gene content haplotypes166, 194 creates another hurdle in the determination of the causative locus. Neurological disease HLA class I associations Potential KIR receptors References Multiple sclerosis HLA‐B*07, *44, *44:02, *37:01, *38:01; HLA‐C*07, *05; HLA‐A*02:01, *03, *0301 KIR3DL1S1; KIR2DL1, KIR2DL2/3, KIR2DS1, KIR2DS2, KIR2DS4, KIR3DL2 29, 30, 60-64 Parkinson's disease HLA‐B *17, *07:02, HLA‐C*07:02, *03:04 KIR3DL1S1, KIR2DL2/3, KIR2DS2, KIR2DS4, KIR3DL2 77, 89 Alzheimer's disease HLA‐B*07:02, HLA‐A*03:01, *02 KIR3DL2, KIR2DS4 8, 94, 100 Schizophrenia HLA‐B*27, *51; HLA‐C*01:02, HLA‐A*03, *011, *02 KIR3DL1S1; KIR2DL2/3, KIR2DS2, KIR2DS4; KIR3DL2 107, 108, 114 Myasthenia gravis HLA‐B*08; HLA‐C*07:01 KIR2DL2/3, KIR2DS2, KIR2DS4 63, 125 Amyotrophic lateral sclerosis HLA‐A*09, *02, *03, HLA‐C*04, HLA‐F KIR3DL1S1, KIR2DL1, KIR2DS1, KIR2DS4, KIR3DL2 7, 140, 141, 145, 146 A limited number of studies has examined the association of KIR gene content variation to date with neurological diseases, the majority of them in multiple sclerosis189-191 and one in schizophrenia.192 A study conducted on a relatively small sample size of 200 schizophrenia patients and 561 controls in European Polish populations have found no correlation of either KIR gene frequency or KIR gene ligands with disease.192 There could be two probable reasons for the non‐association of KIR variation with SCZ. First, the genotyping method for KIR varied considerably, and the differential accuracy of genotyping approaches due to the strong homology between KIR gene or possible amplification biases contingent upon sample quality makes it difficult to calculate KIR gene frequencies precisely. The second limitation is that this study genotyped only for epitopes HLA‐ABw4+, HLA‐B Bw4Ile, Bw4Thr, HLA‐C1 and ‐C2 but did not genotype for particular HLA‐A, ‐B and ‐C alleles, limiting the ability to analyse the interaction of KIR with specific HLA allotypes. Numerous reports of KIR gene content studies in MS from European populations have suggested a role for KIR loci in disease predisposition. Lack of the inhibitory KIR2DL3 has been suggested in MS susceptibility,195 implicating either KIR2DL2 (which segregates as the alternate allele of the same locus) or the closely associated KIR2DS2 in disease. Subsequently, a study has observed the increased incidence of KIR2DL5 and KIR3DS1 in MS cases compared to controls.196 Finally, two other reports in Portuguese and Italian MS cohorts determined a diverse telomeric locus, KIR2DS1, as protective.197, 198 Similarly, our study in an African American MS cohort revealed a strong protective effect for KIR3DL1 in combination with HLA‐A and ‐B alleles bearing the Bw4 motif.191 Finally, the up‐regulated expression of KIR2DL5A was observed in early Alzheimer's disease.199 Although these initial observations are encouraging, an extensive assessment of KIR allele‐level variation in a set of established and well‐characterized cohorts encompassing a wide range of neurological diseases in several different ethnicities, and their correlation with KIR expression, is needed to fully appreciate the role of these critical immune receptors in disease susceptibility and prognosis. Notably, both immunoregulatory dysfunction and activated inflammatory mediator pathways have been suggested in the pathophysiology of neurological diseases, particularly PD,200,201 MS202 and MG,203 as well as many other neurological diseases.204 The reported disease association of HLA variations bolsters this notion. KIR, through the NK cell, regulates the production of cytokine and chemokines.205 As cytokine and chemokines regulate neuroinflammation,206 it remains a plausible hypothesis that KIR allelic variation may influence the course of various neurological diseases through neuroinflammatory pathways. Accumulating evidence suggests a role for NK cells in various neurological diseases, such as MS,207-209 NMO,210 PD,211, 212 AD,213 SCZ,214 myasthenia gravis215 and ALS,216 strengthening the notion that KIR variation may be important in disease predisposition and/or development. NK cells are a key component of innate immunity and act as a first line of defence in resisting infections, but may also be involved in the induction of neurological diseases, and accumulate in specific neuronal cells or tissues in some diseases.215-219 In the MS murine model, experimental autoimmune encephalomyelitis (EAE), studies suggested a role for NK cells in down‐regulation of disease progression.207-209 In the meantime, enhanced predisposition and disease severity in EAE has been linked with NK cells in concurrence with individual cytokines.218, 219 Studies in humans suggested an immunoregulatory role for NK cells in MS, causing an abatement of the inflammatory pathways.220, 221 In contrast, in‐vitro studies demonstrated that NK cells can straightforwardly lyse neural tissue, and may consequently contribute to tissue injury in MS.222, 223 While the immunobiology of NK cells in certain neurological diseases such as MS has been explored, comparatively less is known about the specific role of NK cells in other neurological diseases, such as NMO, PD, AD, SCZ, MG and ALS. The results of NK cell studies in MS continue to be controversial, and fail to point to a coherent model. Thus, understanding the precise role of KIR variation in immunopathogenesis of neurological diseases may open new horizons for identification of biomarkers or could pave the way for new therapeutic approaches. Consideration of HLA and KIR regulatory region variation in neurological disease The emergence of next‐generation sequencing enhanced our ability to determine the HLA and KIR sequences at a very high‐resolution level. This provides the opportunity to determine the role of both coding and non‐coding HLA and KIR region variations in a variety of neurological diseases, given that the non‐coding regions of the human genome including HLA and KIR regions contain regulatory elements, such as promoters, enhancers and untranslated regions (UTRs); these are the strong candidate regions for pathogenic variation and participate directly in the determination of the abundance of expressed genes. In current laboratory practice almost all the reported HLA alleles, either in the disease association studies or in the databases, have used genotyping approaches that only sequenced through exons 2 (class I and class II) and 3 (class I), and this limits our ability to analyse HLA non‐coding variations. HLA non‐coding variations such as SNPs or small insertion/deletions (indels), as well as larger‐scale copy number variants (CNV) present in regulatory regions, could impact the course of neurological diseases through alteration of gene expression. Non‐coding variation in HLA has already been associated clearly with disease. For example, variation in the 3′UTR of HLA‐DPB1 is linked with spontaneous clearance of hepatitis B virus in both Japanese and US populations.224, 225 The proposed mechanism for enabling viral clearance might be linked to the rs9277534 A/G SNP, which describes HLA‐DP cell‐surface expression.225 Similarly, rs2281389 is a non‐coding region variant in HLA‐DP linked with acute graft‐versus‐host disease (GVHD).226 However, rs2281389 variants are not detectable through standard genotyping approaches. Finally, a promoter region SNP of HLA‐C has been reported to be linked with control of HIV infection, and cell surface expression of the HLA molecule was identified to be in LD with a 3′UTR variant that regulates binding of micro‐RNA, the putative source of the expression variation.227 Distorted patterns of gene expression are a characteristic of many neurological diseases, such as MS, Alzheimer's disease and schizophrenia, and in various cases these altered gene expressions can be correlated straightforwardly to genomic/pathogenic variations.228-230 These findings support the hypothesis of a robust association between anomalous gene expression and neurological diseases, suggesting that variants in non‐coding regulatory elements are outstanding candidates for some of the observed missing heritability in neurological diseases. The identification of many null or expression variants of common HLA alleles will improve our understanding of their role in immune functions. Recently, a variant of the multiple sclerosis‐linked allele HLA‐B*44:02 has been determined that produces only a soluble, rather than cell surface, molecule; a point mutation at the end of intron 4 alters the exon 5 splice site.231 Meanwhile, this variant is not appreciable through standard genotyping approaches, and hence these alleles are usually genotyped as B*44:02; similarly, the actual population‐level frequency of the marginal allele is not recognized. Moreover, if the non‐surface‐expressed variant of this allele is common, this might elucidate the link to disease. Taken together, these data recommend that the genotyping of regulatory regions variants may improve our understanding about the role of HLA and KIR in neurological disease. Concluding remarks and future perspective Taken together, the findings of HLA and KIR association studies are consistent with a polygenic model of inheritance in the heterogeneous and multifactorial nature of complex traits in various neurological diseases. The majority of the neurological diseases, such as MS, NMO, PD, AD, SCZ, MG and ALS, are considerably more common among individuals transmitting specific HLA alleles. This further strengthens the decades‐long contention of a strong immune component in the determination of clinical outcomes of neurological diseases. Looking to the future of immunogenetics in neurological diseases, we recommend focus upon high‐resolution genotyping for both HLA and KIR. Investigating both coding and non‐coding region variation in these immunogenetic loci using high throughput high‐resolution technologies in groups with diverse ancestries will almost certainly be required to fully appreciate their role in neurological diseases. There are only limited examinations of HLA and KIR variations at transcriptomics and proteomics levels; therefore, the functional assessment of both allelic and regulatory regional variation is highly desirable. The impact of micro‐RNA on diverse HLA and KIR alleles in regulatory regions also needs to be evaluated in neurological diseases in order to recognize the significance of epigenetic factors in disease pathophysiology. Finally, our recent observation, that certain human metabolites occupy the P4 pocket of MS‐susceptible DRB1*15:01 haplotype in most populations and could be implicated in autoimmunity,232 suggest that similar investigations of both HLA class I and class II molecules in an allele‐specific manner could be undertaken. This approach might be advantageous to weight or group together various HLA genes and alleles that are involved in predisposition across diseases. The functional assessment of binding of human metabolites with HLA class I and class II molecules, and investigation of their impact upon T‐cell proliferation and responsiveness, could pave the way for designing novel therapies, leading to a step closer to reaching the goal of personalized medicine. Acknowledgements The authors are supported by grants from National Institutes of Health (U19NS095774, R01AI128775). Disclosures None to declare. References Citing Literature Number of times cited according to CrossRef: 9 Marja‐Liisa Lokki and Riitta Paakkanen, The complexity and diversity of major histocompatibility complex challenge disease association studies, HLA, 93, 1, (3-15), (2018). Wiley Online Library Valerii Voinov, Plasmapheresis in Treatment of Myasthenia Gravis, Myasthenia Gravis [Working Title], 10.5772/intechopen.81354, (2018). Crossref Brian W. Kunkle, Benjamin Grenier-Boley, Rebecca Sims, Joshua C. Bis, Vincent Damotte, Adam C. 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Original Article from The New England Journal of Medicine — Placebo-Controlled Trial of an Oral BTK Inhibitor in Multiple Sclerosis

Microglia are the resident macrophages of the central nervous system (CNS). They are a heterogenous, exquisitely responsive, and highly plastic cell population, which enables them to perform diverse roles. They sense and respond to the local production of many different signals, including an assorted range of cytokines. Microglia respond strongly to interleukin‐6 (IL‐6) and members of the type I interferon (IFN‐I) family, IFN‐alpha (IFN‐α), and IFN‐beta (IFN‐β). Although these cytokines are essential in maintaining homeostasis and for activating and regulating immune responses, their chronic production has been linked to the development of distinct human neurological diseases, termed “cerebral cytokinopathies.” IL‐6 and IFN‐α have been identified as key mediators in the pathogenesis of neuroinflammatory disorders including neuromyelitis optica and Aicardi‐Goutières syndrome, respectively, whereas IFN‐β has an emerging role as a causal factor in age‐associated cognitive decline. One of the key features that unites these diseases is the presence of highly reactive microglia. The current understanding is that microglia contribute to the development of cerebral cytokinopathies and represent an important therapeutic target. However, it remains to be resolved whether microglia have beneficial or detrimental effects. Here we review and discuss what is currently known about the microglial response to IL‐6 and IFN‐I, based on both animal models and clinical studies. Foundational knowledge regarding the microglial response to IL‐6 and IFN‐I is now being used to devise therapeutic strategies to ameliorate neuroinflammation and promote repair: either through targeting microglia, or by targeting the reduction of CNS levels or downstream biological pathways of IL‐6 or IFN‐I.