The role of B cells in primary progressive multiple sclerosis

The success of ocrelizumab in reducing confirmed disability accumulation in primary progressive multiple sclerosis (PPMS) via CD20-targeted depletion implicates B cells as causal agents in the pathogenesis of PPMS. This review explores the possible mechanisms by which B cells contribute to disease progression in PPMS, specifically exploring cytokine production, antigen presentation, and antibody synthesis. B cells may contribute to disease progression in PPMS through cytokine production, specifically GM-CSF and IL-6, which can drive naïve T-cell differentiation into pro-inflammatory Th1/Th17 cells. B cell production of the cytokine LT-α may induce follicular dendritic cell production of CXCL13 and lead indirectly to T and B cell infiltration into the CNS. In contrast, production of IL-10 by B cells likely induces an anti-inflammatory effect that may play a role in reducing neuroinflammation in PPMS. Therefore, reduced production of IL-10 may contribute to disease worsening. B cells are also capable of potent antigen presentation and may induce pro-inflammatory T-cell differentiation via cognate interactions. B cells may also contribute to disease activity via antibody synthesis, although it\u27s unlikely the benefit of ocrelizumab in PPMS occurs via antibody decrement. Finally, various B cell subsets likely promulgate pro- or anti-inflammatory effects in MS

B Cells Migrate into Remote Brain Areas and Support Neurogenesis and Functional Recovery after Focal Stroke in Mice

Lymphocytes infiltrate the stroke core and penumbra and often exacerbate cellular injury. B cells, however, are lymphocytes that do not contribute to acute pathology but can support recovery. B cell adoptive transfer to mice reduced infarct volumes 3 and 7 d after transient middle cerebral artery occlusion (tMCAo), independent of changing immune populations in recipient mice. Testing a direct neurotrophic effect, B cells cocultured with mixed cortical cells protected neurons and maintained dendritic arborization after oxygen-glucose deprivation. Whole-brain volumetric serial two-photon tomography (STPT) and a custom-developed image analysis pipeline visualized and quantified poststroke B cell diapedesis throughout the brain, including remote areas supporting functional recovery. Stroke induced significant bilateral B cell diapedesis into remote brain regions regulating motor and cognitive functions and neurogenesis (e.g., dentate gyrus, hypothalamus, olfactory areas, cerebellum) in the whole-brain datasets. To confirm a mechanistic role for B cells in functional recovery, rituximab was given to human CD20+ (hCD20+) transgenic mice to continuously deplete hCD20+-expressing B cells following tMCAo. These mice experienced delayed motor recovery, impaired spatial memory, and increased anxiety through 8 wk poststroke compared to wild type (WT) littermates also receiving rituximab. B cell depletion reduced stroke-induced hippocampal neurogenesis and cell survival. Thus, B cell diapedesis occurred in areas remote to the infarct that mediated motor and cognitive recovery. Understanding the role of B cells in neuronal health and disease-based plasticity is critical for developing effective immune-based therapies for protection against diseases that involve recruitment of peripheral immune cells into the injured brain

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

Sex-based differences in effector cells of the adaptive immune system during Alzheimer's disease and related dementias

Neurological conditions such as Alzheimer's disease (AD) and related dementias (ADRD) present with many challenges due to the heterogeneity of the related disease(s), making it difficult to develop effective treatments. Additionally, the progression of ADRD-related pathologies presents differently between men and women. With two-thirds of the population affected with ADRD being women, ADRD has presented itself with a bias toward the female population. However, studies of ADRD generally do not incorporate sex-based differences in investigating the development and progression of the disease, which is detrimental to understanding and treating dementia. Additionally, recent implications for the adaptive immune system in the development of ADRD bring in new factors to be considered as part of the disease, including sex-based differences in immune response(s) during ADRD development. Here, we review the sex-based differences of pathological hallmarks of ADRD presentation and progression, sex-based differences in the adaptive immune system and how it changes with ADRD, and the importance of precision medicine in the development of a more targeted and personalized treatment for this devastating and prevalent neurodegenerative condition

Inebilizumab, a B Cell-Depleting Anti-CD19 Antibody for the Treatment of Autoimmune Neurological Diseases: Insights from Preclinical Studies

Exaggerated or inappropriate responses by B cells are an important feature in many types of autoimmune neurological diseases. The recent success of B-cell depletion in the treatment of multiple sclerosis (MS) has stimulated the development of novel B-cell-targeting therapies with the potential for improved efficacy. CD19 has emerged as a promising target for the depletion of B cells as well as CD19-positive plasmablasts and plasma cells. Inebilizumab (MEDI-551), an anti-CD19 antibody with enhanced antibody-dependent cell-mediated cytotoxicity against B cells, is currently being evaluated in MS and neuromyelitis optica. This review discusses the role of B cells in autoimmune neurological disorders, summarizes the development of inebilizumab, and analyzes the recent results for inebilizumab treatment in an autoimmune encephalitis mouse model. The novel insights obtained from these preclinical studies can potentially guide future investigation of inebilizumab in patients

Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis

Abstract Background Deep sequencing of lymphocyte receptor repertoires has made it possible to comprehensively profile the clonal composition of lymphocyte populations. This opens the door for novel approaches to diagnose and prognosticate diseases with a driving immune component by identifying repertoire sequence patterns associated with clinical phenotypes. Indeed, recent studies support the feasibility of this, demonstrating an association between repertoire-level summary statistics (e.g., diversity) and patient outcomes for several diseases. In our own prior work, we have shown that six codons in VH4-containing genes in B cells from the cerebrospinal fluid of patients with relapsing remitting multiple sclerosis (RRMS) have higher replacement mutation frequencies than observed in healthy controls or patients with other neurological diseases. However, prior methods to date have been limited to focusing on repertoire-level summary statistics, ignoring the vast amounts of information in the millions of individual immune receptors comprising a repertoire. We have developed a novel method that addresses this limitation by using innovative approaches for accommodating the extraordinary sequence diversity of immune receptors and widely used machine learning approaches. We applied our method to RRMS, an autoimmune disease that is notoriously difficult to diagnose. Results We use the biochemical features encoded by the complementarity determining region 3 of each B cell receptor heavy chain in every patient repertoire as input to a detector function, which is fit to give the correct diagnosis for each patient using maximum likelihood optimization methods. The resulting statistical classifier assigns patients to one of two diagnosis categories, RRMS or other neurological disease, with 87% accuracy by leave-one-out cross-validation on training data (N = 23) and 72% accuracy on unused data from a separate study (N = 102). Conclusions Our method is the first to apply statistical learning to immune repertoires to aid disease diagnosis, learning repertoire-level labels from the set of individual immune repertoire sequences. This method produced a repertoire-based statistical classifier for diagnosing RRMS that provides a high degree of diagnostic capability, rivaling the accuracy of diagnosis by a clinical expert. Additionally, this method points to a diagnostic biochemical motif in the antibodies of RRMS patients, which may offer insight into the disease process