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      Lupus autoantibodies initiate a maladaptive equilibrium sustained by HMGB1:RAGE signaling and reversed by LAIR-1:C1q signaling

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          Abstract

          Cognitive impairment is a frequent manifestation of neuropsychiatric systemic lupus erythematosus (NPSLE), present in up to 80% of patients and leading to a diminished quality of life. We have developed a model of lupus-like cognitive impairment which is initiated when anti-DNA, anti-N-methyl D-aspartate receptor (NMDAR) cross- reactive antibodies, which are present in 30% of SLE patients, penetrate the hippocampus 1 . This leads to immediate, self-limited excitotoxic death of CA1 pyramidal neurons followed by a significant loss of dendritic arborization in the remaining CA1 neurons and impaired spatial memory. Both microglia and C1q are required for dendritic loss 1 . Here we show that this pattern of hippocampal injury creates a maladaptive equilibrium that is sustained for at least one year. It requires HMGB1 secretion by neurons to bind RAGE, a receptor for HMGB1 expressed on microglia, and leads to decreased expression of microglial LAIR-1, an inhibitory receptor for C1q. The angiotensin converting enzyme (ACE) inhibitor captopril, which can restore a healthy equilibrium, microglial quiescence, and intact spatial memory, leads to upregulation of LAIR-1. This paradigm highlights HMGB1:RAGE and C1q:LAIR-1 interactions as pivotal pathways in the microglial–neuronal interplay that defines a physiologic versus a maladaptive equilibrium.

          Graphical Abstract/Model. Model showing outcomes of DNRAb-mediated neuronal damage.

          Exposure of hippocampal CA1 pyramidal neurons to DNRAbs results in DNRAb binding to NMDARs, mediating excitotoxic death in 30% of neurons. A maladaptive equilibrium begins as a microglial response to apoptotic neuronal debris and progresses as stressed neurons secrete HMGB1, which activate microglia by binding RAGE. Activated microglia secrete proinflammatory cytokines, Type I IFN, and C1q. The secreted HMGB1 acts as a bridge by binding both NMDARs and C1q, which opsonizes synapses for microglial pruning, resulting in a loss of neuronal dendrite branching and spine density. Captopril treatment mediates microglial upregulation of LAIR-1, which induces quiescence when bound by C1q. This allows for a return to a healthy homeostasis and regrowth of dendritic branches and spines. Image created with Biorender.com.

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            Integrated analysis of multimodal single-cell data

            Summary The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce “weighted-nearest neighbor” analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.
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              Massively parallel digital transcriptional profiling of single cells

              Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.
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                Author and article information

                Journal
                Res Sq
                ResearchSquare
                Research Square
                American Journal Experts
                22 May 2023
                : rs.3.rs-2870168
                Affiliations
                [1 ]Center for Autoimmune Musculoskeletal and Hematopoietic Diseases, The Feinstein Institutes for Medical Research, Manhasset, NY;
                [2 ]Northwell Health, Manhasset, NY;
                [3 ]Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
                Author notes
                [*]

                contributed equally

                Author Contributions

                K.R.C. wrote and edited the manuscript and designed, performed, and analyzed experiments. M.M. wrote and edited the manuscript and designed, performed, and analyzed experiments. S.S. wrote and edited the manuscript and designed, performed, and analyzed experiments. B.T. designed, performed, and analyzed experiments. J.W. performed and analyzed experiments. N.T. performed experiments. A.Z. performed and analyzed experiments. N.K. performed and analyzed experiments. C.K. designed, performed, and analyzed experiments and edited the manuscript. J.Z.L. designed and analyzed experiments, edited the manuscript, and oversaw the studies. B.T.V. designed, performed, and analyzed experiments, edited the manuscript, and oversaw the studies. B.D. designed and analyzed experiments, wrote and edited the manuscript, and oversaw the studies.

                Corresponding Author: Dr. Betty Diamond, Center of Autoimmune, Musculoskeletal Hematopoietic Diseases, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY 11030 USA, Tel. 516-562-3830, Fax: 516-562-2953, bdiamond@ 123456northwell.edu
                Article
                10.21203/rs.3.rs-2870168
                10.21203/rs.3.rs-2870168/v1
                10246276
                37292843
                e64c4336-64b9-4438-82c2-2fc580fe0b8f

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

                License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License

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