C1q Deficiency and Autoimmunity: The Effects of Genetic Background on Disease Expression

Mitchell, Daniel A.; Pickering, Matthew C.; Warren, Joanna; Fossati-Jimack, Liliane; Cortés-Hernández, Josefina; Cook, H. Terence; Botto, Marina; Walport, Mark J.

doi:10.4049/jimmunol.168.5.2538

Cited by 210 publications

(75 citation statements)

References 26 publications

(31 reference statements)

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“…Indeed, there is a prevailing belief that delayed or reduced clearance of apoptotic cells leads to the presentation of apoptotic antigen in the context of inflammatory signals, with resultant autoimmunity (9,12,13). This view is supported by studies in mice in which genetic deficiencies of any number of gene products (for example, C1q (14), the MER receptor tyrosine kinase (15), or MFG-E8 (16)) give rise both to delayed clearance of apoptotic cells and to the development of systemic autoimmune disease.…”

supporting

confidence: 48%

“…According to current models, late apoptotic cells, which have lost membrane integrity and leak their intracellular contents, should behave like necrotic cells and induce an immune response (27). Thus, delayed or impaired clearance of apo-ptotic cells, as observed with targeted deletion of the complement protein C1q (14) or the MER receptor tyrosine kinase (15), is thought to lead to presentation of apoptotic antigen in the context of inflammatory signals, with resultant autoimmunity (Fig. 7).…”

Section: Discussionmentioning

confidence: 99%

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Apoptotic Cells, at All Stages of the Death Process, Trigger Characteristic Signaling Events That Are Divergent from and Dominant over Those Triggered by Necrotic Cells

Patel

Longacre

Hsiao

et al. 2006

Journal of Biological Chemistry

141

175

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Current models of autoimmunity suggest that delayed clearance of apoptotic cells leads to the presentation of apoptotic antigens in the context of inflammatory signals, with resultant autoimmunity. These models implicitly assume that, in contrast to early apoptotic cells (that retain membrane integrity), late apoptotic cells (with compromised membranes) act like necrotic cells (which also lack intact membranes), possibly because of the release of proinflammatory intracellular contents. We showed previously that early apoptotic and necrotic cells induce distinct mitogen-activated protein kinase modules in macrophages with which they interact. Exposure to apoptotic cells led to nearly complete inhibition of both basal and macrophage colony-stimulating factor-induced ERK1/2 by macrophages. In contrast, necrotic cells induced ERK1/2. We show here that apoptotic cells also strongly induced both c-Jun N-terminal kinase and p38, whereas necrotic cells had no detectable effect on c-Jun N-terminal kinase and p38. We also compared the signaling events induced in macrophages by exposure to early apoptotic cells, late apoptotic cells, and necrotic cells. The signaling events induced by late apoptotic cells were identical to and just as potent as those induced by early apoptotic cells. Thus, apoptotic cells are functionally equivalent throughout the cell death process, irrespective of membrane integrity. Moreover, the effects of both early and late apoptotic cells on signaling were dominant over those of necrotic cells. These data show that apoptotic cells do not become proinflammatory upon the loss of membrane integrity and are inconsistent with the notion that delayed clearance alone can lead to autoimmunity.Apoptosis is an active energy-dependent process that generally occurs without inflammation or injury to surrounding tissues (1). Apoptotic cells express surface markers that permit their rapid recognition and ingestion by phagocytes (2, 3). Moreover, the cell membrane of cells undergoing apoptosis remains intact until relatively late (1). Thus, the vast majority of cells dying by apoptosis are cleared by phagocytes while their cell membranes are still intact and before they can release their potentially inflammatory intracellular contents.In this view, the noninflammatory behavior of apoptotic cells is essentially passive in that inflammation is avoided by rapid and efficient clearance of apoptotic cells. In fact, apoptotic cells are also actively antiinflammatory (4, 5). For example, the uptake of apoptotic cells actively inhibits the release of proinflammatory mediators such as interleukin 1 and tumor necrosis factor-␣ by macrophages (m) 2 (4 -6). This contrasts with the effect of necrotic cell uptake, which may lead to m activation and the release of proinflammatory cytokines (7). Based on this differential response to apoptotic versus necrotic cells, antigens derived from cells dying by these two distinct processes are thought to have opposite effects on the activation of T cells (8). The proinflammatory effects of...

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supporting

confidence: 48%

Section: Discussionmentioning

confidence: 99%

Apoptotic Cells, at All Stages of the Death Process, Trigger Characteristic Signaling Events That Are Divergent from and Dominant over Those Triggered by Necrotic Cells

Patel

Longacre

Hsiao

et al. 2006

Journal of Biological Chemistry

141

175

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“…Korb and Ahearn (10) first reported the binding of C1q to apoptotic cells. Subsequently, mice in which the C1q gene had been ablated demonstrated a defect in the kinetics of clearance of apoptotic cells, and, on certain genetic backgrounds, showed accumulation of apoptotic bodies in the kidney and susceptibility to autoimmune disorders (11,49). Miura-Shimura et al (50) recently reported that the presence of a unique insertion polymorphism upstream of the C1q gene in NZB mice leads to development of autoimmune disease.…”

Section: Discussionmentioning

confidence: 99%

Generation of Inhibitory NFκB Complexes and Phosphorylated cAMP Response Element-binding Protein Correlates with the Anti-inflammatory Activity of Complement Protein C1q in Human Monocytes

Fraser

Arora²,

Bohlson³

et al. 2007

Journal of Biological Chemistry

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The interaction of C1q with specific cells of the immune system induces activities, such as enhancement of phagocytosis in monocytes and stimulation of superoxide production in neutrophils. In contrast to some other monocyte activators, C1q itself does not induce pro-inflammatory cytokine production, but rather inhibits the lipopolysaccharide (LPS)-stimulated induction of certain pro-inflammatory cytokines and induces expression of interleukin-10. To investigate the molecular mechanism by which C1q exerts this effect on gene expression, the influence of C1q on the activation of transcription factors of the NFB family and cAMP response element-binding protein (CREB) was assessed. C1q treatment increased B binding activity in freshly isolated human monocytes in a time-dependent fashion as assessed by electrophoretic mobility shift assays. In antibody supershift experiments, anti-p50 antibody supershifted the C1q-induced NFB complex, whereas anti-p65 antibody had little effect, suggesting that C1q induced the translocation of NFB p50p50 homodimers. This is in contrast to the dominant induction of p65 containing complexes in parallel monocyte cultures stimulated with LPS. C1q treatment also induced cAMP response element (CRE)-binding activity as demonstrated by electrophoretic mobility shift assay, increased phosphorylation of CREB, and induction of CRE driven gene expression. In contrast, CREB activation was not detected in LPS-treated monocytes. These results suggest that C1q may modulate the cytokine profile expressed in response to inflammatory stimuli (e.g. LPS), by triggering inhibitory and/or competing signals. Because C1q and other defense collagens have been shown to enhance clearance of apoptotic cells, this regulatory pathway may be beneficial in avoiding autoimmunity and/or resolving inflammation.The transcription factor complexes of the NFB family have attracted widespread attention because of their rapid induction, the wide range of genes whose expression is influenced by these complexes, and the apparent consequences of its induction in several diseases (1). The NFB/Rel family of transcription factors, which include p65, p50, p52, RelB, and c-Rel, form homo-and heterodimers resulting in distinct transcription factor complexes that regulate expression of many different genes (2). In unstimulated cells, NFB is sequestered in the cytoplasm. Upon stimulation, the inhibitory protein IB␣ dissociates from specific pre-existing cytoplasmic NFB complexes, allowing the transcription factors to translocate to the nucleus and initiate the expression of target genes (1). Lipopolysaccharide (LPS) 5 and other pathogen-associated molecules have long been implicated in the inducible expression of many genes in monocytes, including pro-inflammatory cytokines such as tumor necrosis factor-␣, IL-1␣ and -␤, and IL-6 via specific NFB translocation (3). Prolonged LPS activation can also induce expression of anti-inflammatory IL-10 in monocytes, perhaps an important step in regulation of inflammation (4). Studies suggest t...

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“…Interestingly, a group of 12 genes known to be localized in mitochondria (HSPA9B, COX8A, COX7C, AKAP1, BCKDHA, CLPP, FDX1, AMT, DBT, ATP5G3, AK2, and NME4) are identified as significant, and their expression level uniformly declines in older age. A number of age-regulated genes are also known to be involved in renal diseases, including C1QA, CCR1, LYN, PTPRC, and TNFSF13B, which all show increasing expression with age (27)(28)(29)(30)(31). The expression of TRPM6 (a transient receptor potential cation channel) negatively correlates with age, and mutations of this gene cause hypomagnesemia with secondary hypocalcemia (32).…”

Section: Analysis Of Systemic Inflammatory Response Induced By Lpsmentioning

confidence: 99%

Significance analysis of time course microarray experiments

Storey

Xiao

Leek

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

540

593

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Characterizing the genome-wide dynamic regulation of gene expression is important and will be of much interest in the future. However, there is currently no established method for identifying differentially expressed genes in a time course study. Here we propose a significance method for analyzing time course microarray studies that can be applied to the typical types of comparisons and sampling schemes. This method is applied to two studies on humans. In one study, genes are identified that show differential expression over time in response to in vivo endotoxin administration. By using our method, 7,409 genes are called significant at a 1% false-discovery rate level, whereas several existing approaches fail to identify any genes. In another study, 417 genes are identified at a 10% false-discovery rate level that show expression changing with age in the kidney cortex. Here it is also shown that as many as 47% of the genes change with age in a manner more complex than simple exponential growth or decay. The methodology proposed here has been implemented in the freely distributed and open-source EDGE software package.T he identification of genes that show changes in expression between varying biological conditions is a frequent goal in microarray experiments (1). Differential expression can be studied from a static or temporal viewpoint. In a static experiment, the arrays are obtained irrespective of time, capturing only a single moment of gene expression. In a temporal experiment the arrays are collected over a time course, allowing one to study the dynamic behavior of gene expression. A large amount of work has been done on the problem of identifying differentially expressed genes in static experiments (2). Because the regulation of gene expression is a dynamic process, it is also important to identify and characterize changes in gene expression over time. Here we present a general statistical method that identifies genes differentially expressed over time.Several clustering methods have been applied to time course microarray data, including hierarchical clustering (3, 4), principal components-based clustering (5), Bayesian model-based clustering (6), and K-means clustering of curves (7,8). None of these clustering methods is directly applicable to identifying genes that show statistically significant changes in expression over time. The K-means clustering method has been modified to compare expression over time between two groups (9), but this method can only be applied to a few hundred genes at a time because of the computational cost of fitting a single model to all genes simultaneously (7,8). This approach also requires that the statistical significance be calculated under the assumption that the clustering model estimated for one of the groups is true, which is nonstandard and potentially problematic.The method that we propose draws on ideas from the extensive statistical literature on time course data analysis (10, 11), particularly spline-based methods (12-16). It is applicable to detecting changes in exp...

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C1q Deficiency and Autoimmunity: The Effects of Genetic Background on Disease Expression

Cited by 210 publications

References 26 publications

Apoptotic Cells, at All Stages of the Death Process, Trigger Characteristic Signaling Events That Are Divergent from and Dominant over Those Triggered by Necrotic Cells

Apoptotic Cells, at All Stages of the Death Process, Trigger Characteristic Signaling Events That Are Divergent from and Dominant over Those Triggered by Necrotic Cells

Generation of Inhibitory NFκB Complexes and Phosphorylated cAMP Response Element-binding Protein Correlates with the Anti-inflammatory Activity of Complement Protein C1q in Human Monocytes

Significance analysis of time course microarray experiments

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