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BACKGROUNDWhile B cell depletion is associated with attenuated antibody responses to SARS-CoV-2 mRNA vaccination, responses vary among individuals. Thus, elucidating the factors that affect immune responses after repeated vaccination is an important clinical need.METHODSWe evaluated the quality and magnitude of the T cell, B cell, antibody, and cytokine responses to a third dose of BNT162b2 or mRNA-1273 mRNA vaccine in patients with B cell depletion.RESULTSIn contrast with control individuals (n = 10), most patients on anti-CD20 therapy (n = 48) did not demonstrate an increase in spike-specific B cells or antibodies after a third dose of vaccine. A third vaccine elicited significantly increased frequencies of spike-specific non-naive T cells. A small subset of B cell-depleted individuals effectively produced spike-specific antibodies, and logistic regression models identified time since last anti-CD20 treatment and lower cumulative exposure to anti-CD20 mAbs as predictors of those having a serologic response. B cell-depleted patients who mounted an antibody response to 3 vaccine doses had persistent humoral immunity 6 months later.CONCLUSIONThese results demonstrate that serial vaccination strategies can be effective for a subset of B cell-depleted patients.FUNDINGThe NIH (R25 NS079193, P01 AI073748, U24 AI11867, R01 AI22220, UM 1HG009390, P01 AI039671, P50 CA121974, R01 CA227473, U01CA260507, 75N93019C00065, K24 AG042489), NIH HIPC Consortium (U19 AI089992), the National Multiple Sclerosis Society (CA 1061-A-18, RG-1802-30153), the Nancy Taylor Foundation for Chronic Diseases, Erase MS, and the Claude D. Pepper Older Americans Independence Center at Yale (P30 AG21342).

B cell depletion in patients with relapsing-remitting multiple sclerosis (RRMS) markedly prevents new MRI-detected lesions and disease activity, suggesting the hypothesis that altered B cell function leads to the activation of T cells driving disease pathogenesis. Here, we performed comprehensive analyses of CD40 ligand- (CD40L-) and IL-21-stimulated memory B cells from patients with MS and healthy age-matched controls, modeling the help of follicular helper T cells (Tfh cells), and found a differential gene expression signature in multiple B cell pathways. Most striking was the impaired TIGIT expression on MS-derived B cells mediated by dysregulation of the transcription factor TCF4. Activated circulating Tfh cells (cTfh cells) expressed CD155, the ligand of TIGIT, and TIGIT on B cells revealed their capacity to suppress the proliferation of IL-17- producing cTfh cells via the TIGIT/CD155 axis. Finally, [CCR6.sup.+] cTfh cells were significantly increased in patients with MS, and their frequency was inversely correlated with that of [TIGIT.sup.+] B cells. Together, these data suggest that the dysregulation of negative feedback loops between [TIGIT.sup.+] memory B cells and cTfh cells in MS drives the activated immune system in this disease., Introduction Relapsing-remitting multiple sclerosis (RRMS) is a genetically mediated autoimmune disease mediated by mye[Lin.sup.-]reactive T cells attacking the CNS (1-3) and is characterized by inflammatory lesions predominantly in the white [...]

High-dimensional cell phenotyping is a powerful tool to study molecular and cellular changes in health and diseases. CyTOF enables high-dimensional cell phenotyping using tens of surface and intra-cellular markers. To utilize the full potential of CyTOF, we need advanced clustering and machine learning methodologies to enable automated gating of the complex data. Here we show that critical modifications to a machine learning based FlowSOM package and precise parameter optimization can enable us to reliably analyze the complex CyTOF data. We show the impact of key parameters on clustering outcomes while addressing bugs within the publicly available package. We modified the FlowSOM pipeline to fix the bugs, enable scalability to handle large datasets and perform parameter optimization. We further validated this modified pipeline on a substantial external immunological dataset demonstrating the need of data-specific tailored parameter optimization to ensure reliable definition and interrogation of immune cell populations associated with immune disorders. Optimized FlowSOM pipeline for reliable clustering of high-dimensional cytometry data. [ABSTRACT FROM AUTHOR]

High-dimensional cell phenotyping is a powerful tool to study molecular and cellular changes in health and diseases. CyTOF enables high-dimensional cell phenotyping using tens of surface and intra-cellular markers. To utilize the full potential of CyTOF, we need advanced clustering and machine learning methodologies to enable automated gating of the complex data. Here we show that critical modifications to a machine learning based FlowSOM package and precise parameter optimization can enable us to reliably analyze the complex CyTOF data. We show the impact of key parameters on clustering outcomes while addressing bugs within the publicly available package. We modified the FlowSOM pipeline to fix the bugs, enable scalability to handle large datasets and perform parameter optimization. We further validated this modified pipeline on a substantial external immunological dataset demonstrating the need of data-specific tailored parameter optimization to ensure reliable definition and interrogation of immune cell populations associated with immune disorders. [ABSTRACT FROM AUTHOR]

Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.

Autoimmunity has long been linked to myocarditis and its sequela, dilated cardiomyopathy, the leading causes of heart failure in young patients. However, the underlying mechanisms are poorly defined, with most clinical investigations focused on humoral autoimmunity as the target for intervention. Here, we show that the α-isoform of myosin heavy chain (α-MyHC, which is encoded by the gene Myh6) is the pathogenic autoantigen for [CD4.sup.+] T cells in a spontaneous mouse model of myocarditis. Further, we found that Myh6 transcripts were absent in mouse medullary thymic epithelial cells (mTECs) and peripheral lymphoid stromal cells, which have been implicated in mediating central and peripheral T cell tolerance, respectively. Transgenic expression of α-MyHC in thymic epithelium conferred tolerance to cardiac myosin and prevented myocarditis, demonstrating that α-MyHC is a primary autoantigen in this disease process. Remarkably, we found that humans also lacked α-MyHC in mTECs and had high frequencies of α-MyHC-specific T cells in peripheral blood, with markedly augmented T cell responses to α-MyHC in patients with myocarditis. Since α-MyHC constitutes a small fraction of MyHC in human heart, these findings challenge the longstanding notion that autoimmune targeting of My HC is due to its cardiac abundance and instead suggest that it is targeted as a result of impaired T cell tolerance mechanisms. These results thus support a role for T cell-specific therapies for myocarditis., Introduction Myocarditis is a major cause of heart disease in young patients and a common precursor of heart failure due to dilated cardiomyopathy (1-3). The prognosis for dilated cardiomyopathy is [...]

The frequencies of antigen-specific CD4+ T cells in samples of human tissue have been difficult to determine accurately ex vivo, particularly for autoimmune diseases such as multiple sclerosis or type 1 diabetes. Conventional approaches involve the expansion of primary T cells in vitro to increase the numbers of cells, and a subsequent assessment of the frequencies of antigen-specific T cells in the expanded population by limiting dilution or by using fluorescently labeled tetramers of peptide-loaded major histocompatibility complex (MHC) receptors. Here we describe an alternative approach that uses arrays of subnanoliter wells coated with recombinant peptideloaded MHC class II monomers to isolate and stimulate individual CD4+ T cells in an antigen-specific manner. In these experiments, activation was monitored using microengraving to capture two cytokines (IFN[gamma] and IL17) released from single cells. This new method should enable direct enumeration of antigen-specific CD4+ T ceils ex vivo from clinical samples. 10.1021/ac9024363

Migration toward pathology is the first critical step in stem cell engagement during regeneration. Neural stem cells (NSCs) migrate through the parenchyma along nonstereotypical routes in a precise directed manner across great distances to injury sites in the CNS, where they might engage niches harboring local transiently expressed reparative signals. The molecular mechanisms for NSC mobilization have not been identified. Because NSCs seem to home similarly to pathologic sites derived from disparate etiologies, we hypothesized that the inflammatory response itself, a characteristic common to all, guides the behavior of potentially reparative cells. As proof of concept, we show that human NSCs migrate in vivo (including from the contralateral hemisphere) toward an infarcted area (a representative CNS injury), where local astrocytes and endothelium up-regulate the inflammatory chemoattractant stromal cell-derived factor 1[alpha] (SDF-1[alpha]). NSCs express CXC chemokine receptor 4 (CXCR4), the cognate receptor for SDF-1[alpha]. Exposure of SDF-1[alpha] to quiescent NSCs enhances proliferation, promotes chain migration and transmigration, and activates intracellular molecular pathways mediating engagement. CXCR4 blockade abrogates their pathology-directed chain migration, a developmentally relevant mode of tangential migration that, if recapitulated, could explain homing along nonstereotypical paths. Our data implicate SDF-1[alpha]/CXCR4, representative of the inflammatory milieu characterizing many pathologies, as a pathway that activates NSC molecular programs during injury and suggest that inflammation may be viewed not simply as playing an adverse role but also as providing stimuli that recruit cells with a regenerative homeostasis-promoting capacity. CXCR4 expression within germinal zones suggests that NSC homing after injury and migration during development may invoke similar mechanisms. human stem cells | homing | chain migration | stroke | hypoxia-ischemia

Abstract Background RNA isolation and purification steps greatly influence the results of gene expression profiling. There are two commercially available products for whole blood RNA collection, PAXgene™ and Tempus™ blood collection tubes, and each comes with their own RNA purification method. In both systems the blood is immediately lysed when collected into the tube and RNA stabilized using proprietary reagents. Both systems enable minimal blood handling procedures thus minimizing the risk of inducing changes in gene expression through blood handling or processing. Because the RNA purification steps could influence the total RNA pool, we examined the impact of RNA isolation, using the PAXgene™ or Tempus™ method, on gene expression profiles. Results Using microarrays as readout of RNA from stimulated whole blood we found a common set of expressed transcripts in RNA samples from either PAXgene™ or Tempus™. However, we also found several to be uniquely expressed depending on the type of collection tube, suggesting that RNA purification methods impact results of differential gene expression profiling. Specifically, transcripts for several known PHA-inducible genes, including IFNγ, IL13, IL2, IL3, and IL4 were found to be upregulated in stimulated vs. control samples when RNA was isolated using the ABI Tempus™ method, but not using the PAXgene™ method (p < 0.01, FDR corrected). Sequenom Quantiative Gene Expression (QGE) (SanDiego, CA) measures confirmed IL2, IL4 and IFNγ up-regulation in Tempus™ purified RNA from PHA stimulated cells while only IL2 was up-regulated using PAXgene™ purified (p < 0.05). Conclusion Here, we demonstrate that peripheral blood RNA isolation methods can critically impact differential expression results, particularly in the clinical setting where fold-change differences are typically small and there is inherent variability within biological cohorts. A modified method based upon the Tempus™ system was found to provide high yield, good post-hybridization array quality, low variability in expression measures and was shown to produce differential expression results consistent with the predicted immunologic effects of PHA stimulation.