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Vanessa Sancho-Shimizu Petter Brodin Aurlie Cobat Catherine M. Biggs Julie Toubiana Carrie L. Lucas Sarah E. Henrickson Alexandre Belot MIS-C@CHGE Stuart G. Tangye Joshua D. Milner Michael Levin Laurent Abel Dusan Bogunovic Jean-Laurent Casanova Shen-Ying Zhang 《The Journal of experimental medicine》2021,218(6)
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Mario Nuvolone Veronika Kana Gregor Hutter Daiji Sakata Steven M. Mortin-Toth Giancarlo Russo Jayne S. Danska Adriano Aguzzi 《The Journal of experimental medicine》2013,210(12):2539-2552
Prnp−/− mice lack the prion protein PrPC and are resistant to prion infections, but variable phenotypes have been reported in Prnp−/− mice and the physiological function of PrPC remains poorly understood. Here we examined a cell-autonomous phenotype, inhibition of macrophage phagocytosis of apoptotic cells, previously reported in Prnp−/− mice. Using formal genetic, genomic, and immunological analyses, we found that the regulation of phagocytosis previously ascribed to PrPC is instead controlled by a linked locus encoding the signal regulatory protein α (Sirpa). These findings indicate that control of phagocytosis was previously misattributed to the prion protein and illustrate the requirement for stringent approaches to eliminate confounding effects of flanking genes in studies modeling human disease in gene-targeted mice. The plethora of seemingly unrelated functions attributed to PrPC suggests that additional phenotypes reported in Prnp−/− mice may actually relate to Sirpa or other genetic confounders.The cellular prion protein PrPC, encoded by the Prnp gene, is tethered to the membrane of most mammalian cells by a glycosylphosphatidylinositol anchor. Conversion and aggregation of PrPC into a misfolded conformer (termed PrPSc) triggers transmissible spongiform encephalopathies, also termed prion diseases (Aguzzi and Calella, 2009). Disparate functions have been ascribed to PrPC on the basis of phenotypes described in Prnp−/− mice (Steele et al., 2007; Linden et al., 2008), yet none of these functions has been clarified mechanistically, and their validity was frequently challenged.All currently available Prnp−/− lines were generated using embryonic stem (ES) cells derived from the 129 strain of Mus musculus. Typically, chimeric founder mice were crossed with WT (Prnpwt/wt) mice of the C57BL/6 strain (B6; Sparkes et al., 1986). Consequently, congenic Prnpwt/wt and Prnp−/− mice may differ at additional polymorphic loci (Smithies and Maeda, 1995; Gerlai, 1996). We hypothesized that co-segregation of linked genes may have confounded the attribution of functions to PrPC based on phenotypes observed in Prnp−/− mice (Collinge et al., 1994; Lledo et al., 1996; Walz et al., 1999; Rangel et al., 2007; Laurén et al., 2009; Calella et al., 2010; Gimbel et al., 2010; Ratté et al., 2011; Striebel et al., 2013).
Open in a separate windowThe present study is based on the analysis of mice carrying seven independently generated Prnp-null alleles. PrnpEdbg/Edbg and PrnpRcm0/Rcm0 were always crossed to isogenic 129/Ola mice, whereas all other Prnp−/− mice were crossed to B6 mice and then kept on a mixed B6 and 129 background or further backcrossed to B6 or other strains.Here we selected a cell-autonomous phenotype previously reported in congenic B6.129-PrnpZrchI/ZrchI mice (Büeler et al., 1992): inhibition of phagocytosis of apoptotic cells (de Almeida et al., 2005). We used RNA sequencing to identify genes linked to Prnp and expressed in macrophages that may influence this phenotype. We report genetic and functional evidence that the regulation of phagocytosis previously ascribed to Prnp−/− is instead controlled by the closely linked gene signal regulatory protein α (Sirpa; Matozaki et al., 2009). 相似文献
Table 1.
Prnp KO mouse lines analyzed in this studyPrnp KO mouse line | ES cells | Origin of ES cells | Strain of partner of chimeric mouse | Location of colony | Reference |
PrnpZrchI/ZrchI | AB1 | 129S7/SvEvBrd | B6 | Zurich, Switzerland | Büeler et al. (1992) |
PrnpNgsk/Ngsk | J1 | 129S4/SvJae | B6 | Nagasaki, Japan | Sakaguchi et al. (1995) |
PrnpEdbg/Edbg | E14 | 129/Ola | 129/Ola | Edinburgh, Scotland, UK | Manson et al. (1994) |
PrnpGFP/GFP | HM-1 | 129/Ola | B6 | Cambridge, MA | Heikenwalder et al. (2008) |
PrnpRkn/Rkn | E14 | 129P2/OlaHsd | B6 | Wako-shi, Japan | Yokoyama et al. (2001) |
PrnpZrchII/ZrchII | E14.1 | 129/OlaHsd | B6 | Zurich, Switzerland | Rossi et al. (2001) |
PrnpRcm0/Rcm0 | HM-1 | 129/Ola | 129/Ola | Edinburgh, Scotland, UK | Moore et al. (1995) |
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Matev Rumpret Helen J. von Richthofen Victor Peperzak Linde Meyaard 《The Journal of experimental medicine》2022,219(1)
Pathogen- and damage-associated molecular patterns are sensed by the immune system’s pattern recognition receptors (PRRs) upon contact with a microbe or damaged tissue. In situations such as contact with commensals or during physiological cell death, the immune system should not respond to these patterns. Hence, immune responses need to be context dependent, but it is not clear how context for molecular pattern recognition is provided. We discuss inhibitory receptors as potential counterparts to activating pattern recognition receptors. We propose a group of inhibitory pattern recognition receptors (iPRRs) that recognize endogenous and microbial patterns associated with danger, homeostasis, or both. We propose that recognition of molecular patterns by iPRRs provides context, helps mediate tolerance to microbes, and helps balance responses to danger signals.Pattern recognition receptors (PRRs) recognize molecular patternsThe immune system needs to recognize and correct deviations from normal physiology, such as harmful contact with a microbe, disruption and damage of healthy tissue, and malignant transformation of cells. To sense the presence of microbes, the immune system employs a set of PRRs (Janeway, 1989). At present, five classes of PRRs have been defined: the TLRs and the C-type lectin receptors, which are both localized to cell or endosomal membranes; the cytoplasmic NOD-like receptors and RIG-I–like receptors; and additional cytoplasmic DNA sensors, such as cyclic GMP-AMP synthase (Gong et al., 2020; Takeuchi and Akira, 2010). PRRs recognize highly conserved components of microbes, termed pathogen-associated molecular patterns (PAMPs; Akira et al., 2006; Medzhitov and Janeway, 2002). In addition, PRRs sense endogenous molecules associated with damaged and dying cells termed danger- or damage-associated molecular patterns (DAMPs). Many factors are currently considered DAMPs, among which are S100 proteins, heat shock proteins (Hsps), high mobility group box 1 protein (HMGB1), and different glycans such as heparan sulfate (Chen and Nuñez, 2010; Matzinger, 1994; Matzinger, 2002).The self–nonself model of microbe recognition, first introduced by Frank Macfarlane Burnet and later refined by Charles Janeway, explains how the innate immune system recognizes pathogens through molecular patterns (Burnet, 1959; Janeway, 1989). Because pathogens constantly evolve, they cannot be recognized individually, as this would require an infinite number of receptors. To circumvent this problem, the immune system recognizes components of microbial cells that are highly conserved (but not identical) among microbes and cannot be subject to quick change or removal by the microbe because they are essential for its survival (Bianchi and Manfredi, 2009). These groups of structurally similar molecules are called PAMPs. One of the first PAMPs to be discovered was LPS of Gram-negative bacteria, which is detected by TLR4, providing activating signals that drive adaptive immunity (Medzhitov et al., 1997; Poltorak et al., 1998). Soon after, many additional PAMPs were discovered, such as the lipoteichoic acid (LTA) of Gram-positive bacteria (Schwandner et al., 1999). Later, Polly Matzinger extended the family of “molecular patterns” by presenting the danger theory of immunity, introducing DAMPs. The term DAMP has since been used in the literature to denote both damage- and danger-associated molecular patterns. Unlike PAMPs, DAMPs are not defined structurally, and there is (following Janeway’s argument) little need for that: there are only a finite number of host molecules. Instead, DAMPs are defined contextually: they signal danger, and what is dangerous in one place is not necessarily dangerous in another. Such a model is not easily addressed experimentally because of this elusive definition of danger (Pradeu and Cooper, 2012). As highlighted by Pradeu and Cooper (2012), Matzinger later clarified that while the model is theoretical, the idea behind it is that the immune system responds to damage (Matzinger, 2002), and damage signals are much easier to define than danger signals. Since then, many more groups of molecular patterns have been put forward, among which are resolution-, metabolism-, commensal-, and homeostasis-associated molecular patterns (HAMPs; Cario et al., 2002; Greslehner, 2020; Li et al., 2019; Shields et al., 2011; Wang et al., 2020). Under the term molecular pattern, we now classify groups of molecules that signal the occurrence of a particular event, that elicit similar effects, and that may share common structural features.Immune responses are context dependentThe same molecular pattern does not always evoke the same response. Different microbes inevitably colonize barrier tissues such as the skin and gastrointestinal tract, and most of them are not harmful or even provide benefit to the host, yet still express PAMPs. Similarly, while tissue damage and cell death can be pathologic, cell death can also be part of normal physiology and tissue renewal. To distinguish harmless from potentially harmful circumstances, the immune system must correctly interpret the activating signals molecular patterns are delivering, and therefore the threshold for immune system activation needs to vary by context. Tissues that are highly exposed to microbes, such as the gut and skin, require a high activation threshold to tolerate most microbes, whereas in the circulation, a low activation threshold is required to respond to all microbes (Fig. 1). Furthermore, not all tissues can tolerate tissue damage to the same extent. In situations where inflammatory responses result in more damage to the organism than the disturbance itself, not responding to disturbances is the best strategy (Medzhitov et al., 2012). Following this argument, the threshold for immune activation needs to be higher in organs with low regenerative capacity, such as the heart or brain, where an inflammatory response can lead to detrimental consequences, versus organs with a high regenerative capacity, such as the liver (Fig. 1). Hence, the immune response needs to be context dependent, and it is not clear how context for molecular pattern recognition is provided.Open in a separate windowFigure 1.The optimal threshold for activation is context dependent. The required threshold for activation of immune cells differs per location and depends on (1) the tolerance of the organ for immune pathology and (2) the tolerance to microbial exposure. Organs with a high regenerative capacity, such as the liver, are more able to deal with immunopathology than organs with low regenerative capacity, such as the heart or the brain. The gut and skin are constantly exposed to microbes, most of which are harmless or beneficial and should be tolerated. The eye can tolerate a certain amount of microbial exposure, and the cost of responding to a microbial stimulus will be high, so a high threshold will ensure the response occurs only when needed. In different organs, either tolerance for microbes or tolerance for immunopathology may be more important in determining the optimal threshold for activation.Immune inhibitory receptors dampen immune system activationImmune inhibitory receptors are germline-encoded innate receptors relaying inhibitory signals to immune cells. Much about their functioning has been learned by studying programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte protein 4 (CTLA-4), and killer cell Ig-like inhibitory receptors on NK cells (Long, 2008; Ravetch and Lanier, 2000; Rowshanravan et al., 2018). Inhibitory receptors attenuate activating signals coming from activating receptors and fine-tune the level of activation of an immune cell. Most of them relay the inhibitory signals via one or more immunoreceptor tyrosine-based inhibitory motifs (ITIMs) present in their cytoplasmic tails. ITIMs have the consensus sequence V/L/I/SxYxxV/L/I (Vivier and Daëron, 1997). When immune inhibitory receptors are activated by their ligands, the ITIMs recruit tyrosine phosphatases, which dephosphorylate the cytoplasmic tails of activating receptors or key molecules in their signaling pathways (Coxon et al., 2017; Gergely et al., 1999). The ligands for many inhibitory receptors are still unknown, while some single-molecule ligands have been identified for others. We previously argued that immune inhibitory receptors regulate immune responses in different ways. They may set a threshold for immune cell activation by preventing activating receptor signaling in certain contexts or dampen activating receptor signaling after it has already happened. The mode of action of any inhibitory receptor depends on the expression pattern of the receptor and the availability of its ligand (Rumpret et al., 2020). By providing an inhibitory signal, inhibitory receptors give additional information on the context in which an activating signal is sensed, thereby adjusting the immune response to the specific situation.Some activating PRRs, under specific circumstances, can also demonstrate inhibitory functions. For example, TLR4 signaling from the cell membrane typically evokes proinflammatory responses, while TLR4 signaling from the endosome also triggers antiinflammatory responses (Kagan, 2012; Siegemund and Sauer, 2012). Here, we discuss the concept of inhibitory pattern recognition receptors (iPRRs). We specifically focus on canonical inhibitory receptors that use ITIM-dependent inhibitory signaling pathways to relay their signals, resulting in inhibitory functions. We define a group of immune inhibitory receptors that recognize DAMPs, HAMPs, and PAMPs and classify these inhibitory receptors as iPRRs. We propose that, just like most activating PRRs (Gong et al., 2020), most iPRRs recognize both microbial and endogenous patterns (Fig. 2). We propose that iPRRs constitute the inhibitory counterparts of activating PRRs and provide context to the activating signals coming from activating PRRs.Open in a separate windowFigure 2.iPRRs and their endogenous and microbial ligands. The currently known group of iPRRs consist of CD300a/f, Siglecs 2, 3, and 5–11, CEACAM1, LILRB1 and LILRB3, TIGIT, poliovirus receptor (PVR), LAIR-1, and SIRL-1. The upper part of the figure displays endogenous ligands, and the bottom part displays the microbial ligands for iPRRs. For most receptors, both endogenous and exogenous ligands have been identified. Protein ligands are depicted as rectangles, lipids as circles, and carbohydrates as hexagons. All inhibitory receptors depicted are composed of Ig domains, and the number of Ig domains is schematically depicted for each receptor. In humans, most of these receptors are located in the chromosomal region 19q13, except CD300a/f (17q25) and TIGIT (3q13). *, LTA is a ligand for the mouse orthologue of the human LILRB3. PSM, phenol-soluble modulin; S100s, S100 proteins; SIA, sialic acid.iPRRs recognize DAMPsUpon the occurrence of damaged or dying cells, different DAMPs can arise and promote inflammation, leading to tissue repair but also immunopathology (Gong et al., 2020). Multiple inhibitory receptors could potentially tune DAMP-induced inflammatory responses (Fig. 2; Arnold et al., 2013; Brewer et al., 2019; Carlin et al., 2007; Chang et al., 2014; Chen et al., 2009; Choi et al., 2011; Conners et al., 2008; Fong et al., 2015; Gur et al., 2015; Gur et al., 2019; Jones et al., 2016; Klaile et al., 2017; Königer et al., 2016; Korotkova et al., 2008; Kumawat et al., 2019; Lebbink et al., 2009; Macauley et al., 2014; Nakayama et al., 2012; Rumpret et al., 2021a; Rumpret et al., 2021b; Simhadri et al., 2012; van Sorge et al., 2021; Virji et al., 1996; Yu et al., 2009). The sialic acid–binding Ig-like lectin (Siglec)-10–CD24 complex recognizes HMGB1, Hsp70, and Hsp90 and limits the immune response to damaged cells (Chen et al., 2009). It thereby limits harmful inflammatory responses in conditions such as sepsis (Chen et al., 2011), infection (Chen et al., 2013), and liver damage. Indeed, CD24−/− mice die of sublethal doses of acetaminophen-induced liver injury (Chen et al., 2009). Siglec-5 recognizes Hsp70 and delivers antiinflammatory signals to monocytes, which results in decreased production of TNFα and IL-8 in cells stimulated with LPS (Fong et al., 2015). Similarly, CD85j (leukocyte Ig-like receptor subfamily B member 1 [LILRB1]; Arnold et al., 2013) and signal inhibitory receptor on leukocytes 1 (SIRL-1; Rumpret et al., 2021a) recognize S100 proteins, another group of prototypical DAMPs. Blocking SIRL-1 enhances S100-induced release of reactive oxygen species in human neutrophils (Rumpret et al., 2021a). SIRL-1 additionally recognizes another DAMP, the antimicrobial peptide LL-37 (Rumpret et al., 2021b). LILRB3 recognizes a cytokeratin-associated protein, a cytoskeleton protein that is exposed in the extracellular environment after necrotic cell death and is recognized by the activating receptor LILRA6 (Jones et al., 2016). Thus, several iPRRs recognize DAMPs.Die. Where? How?Cells can die in either an immunologically silent manner (apoptosis) or an immunogenic and proinflammatory manner; the latter can be a controlled process (such as necroptosis and pyroptosis) or an uncontrolled process (necrosis). Apoptotic cells are recognized, engulfed by phagocytes, and degraded intracellularly. In contrast, membranes of cells that die via immunogenic cell death (ICD) are ruptured, and intracellular components are released into the local microenvironment, many of which are regarded as DAMPs by neighboring cells (Bedoui et al., 2020). Interestingly, the type of ICD may determine which type of DAMP is released. This is illustrated by the finding that HMGB1 release can occur after both necroptosis and pyroptosis, while release of S100, Hsp70, and Hsp90 only occurs upon necrosis and/or necroptosis, but not in the context of pyroptosis (Frank and Vince, 2019). Thus, ICD results in the release of DAMPs and sets off a chain reaction, since DAMPs themselves induce ICD in cells that recognize them. This inflammatory chain reaction can be unwanted and highly dangerous, particularly in locations with low regenerative capacity (Fig. 1). Mechanical stress, such as brain trauma, can induce both apoptosis and ICD via necrosis (Vourc’h et al., 2018). The balance between these two types of cell death in cases of mechanical stress varies between tissues and seems to shift more toward necrosis upon increased levels of stress and duration of stress (Takao et al., 2019; Valon and Levayer, 2019; Vourc’h et al., 2018). A recent review posits that a certain level of plasticity exists between apoptosis and ICD: inflammasomes, multiprotein oligomers that form intracellularly upon recognition of PAMPs or DAMPs and usually activate ICD, can drive apoptosis when specific molecules (caspase 1 or gasdermin D) are inhibited (Bedoui et al., 2020). iPRR could provide this inhibitory signal upon recognition of DAMPs, resulting in the immediate dampening of an inflammatory chain reaction by steering the response away from ICD and toward apoptosis. Consequently, one can imagine that if inhibitory signaling occurs swiftly in sterile stress conditions, such as ischemia–reperfusion injury or trauma, inflammatory responses can be avoided. Importantly, sterile stress conditions do not always result in measurable inflammatory responses, and it is conceivable that cells in specific essential tissues do not respond to the initial release of DAMPs altogether. Since dependence on a rapid switch from ICD toward apoptosis is a risky bet for essential tissues, a more rapid alternative would be if DAMPs that bind iPRRs directly rendered the cells unresponsive.iPRRs recognize molecules associated with homeostasisAs opposed to DAMPs, which typically are associated with danger and damage, HAMPs have previously been proposed to inhibit immune activation (Li et al., 2019; Sun et al., 2018; Wang et al., 2016). HAMPs have various properties and mechanisms of action; for example, lysophospholipids bind G protein–coupled receptors (Wang et al., 2016), and IL-35 binds cytokine receptors (Li et al., 2019). Already before the introduction of the concept of HAMPs, the guard theory of immunity was established in plants. The guard theory proposes that rather than sensing insults such as pathogens directly, the immune system recognizes the consequences of these insults for the organism. This is reflected by changes in the levels of the guard proteins, triggering immune responses (Dangl and Jones, 2001). Multiple lines of evidence suggest that the foundations of the guard theory also apply to the animal immune system (Medzhitov, 2009). Thus, HAMPs in animals and humans may be seen as a parallel to the preceding guard theory. Here, we discuss HAMPs that ligate immune inhibitory receptors.When cells undergo apoptosis, lipids such as phosphatidylserine (PS) and phosphatidylethanolamine (PE) are exposed on the cell surface and signal tissue-resident immune cells to find and dispose of the dying cells without triggering inflammation (Arandjelovic and Ravichandran, 2015; Gordon and Plüddemann, 2018; Segawa and Nagata, 2015). PS and PE are sensed by inhibitory members of the CD300 family of immune receptors, CD300a and CD300f (Choi et al., 2011; Simhadri et al., 2012). These interactions primarily result in dampening of mast cell activation by apoptotic cells, preventing inflammatory responses (Nakahashi-Oda et al., 2012). In line with this, CD300a−/− mice develop exacerbated joint inflammation in an antigen-induced arthritis model (Valiate et al., 2019). In addition to apoptotic cells, viable cells can also transiently expose PS and PE, which may occur under inflammatory conditions (Arandjelovic and Ravichandran, 2015; Gong et al., 2020; Ravichandran, 2010), suggesting that additional layers of regulation may be needed to prevent phagocytosis of nonapoptotic cells. Indeed, it has been shown that CD300a/f ligation by PS and PE also negatively regulates phagocytosis of apoptotic cells (Ju et al., 2008; Simhadri et al., 2012). It is possible that a similar regulatory circuit is in place to prevent phagocytosis of PS- or PE-bearing nonapoptotic cells. Furthermore, all host cells express diverse sialylated glycan structures, and these sialic acids are effectively a molecular pattern associated with self and homeostasis. Sialylated glycans are sensed by immune receptors of the Siglec family (reviewed in Macauley et al., 2014). Most Siglecs (human Siglec 2, 3, and 5–11) harbor an ITIM motif and are inhibitory receptors. Each Siglec exhibits preferential recognition of a different sialylated glycan. Siglecs participate in immune surveillance and provide the immune system with inhibitory signals to prevent reactivity against self. It has recently been shown that, in addition to cell surface proteins and lipids, small RNAs can be modified with glycans and tethered to the cell membrane of diverse cells under homeostatic conditions, emphasizing the role glycans play in the maintenance of homeostasis (Flynn et al., 2021). In line with this, the lack of Siglec signaling is associated with autoimmune disease. Mice double-deficient for Siglec-G and Siglec-2 spontaneously develop systemic lupus erythematosus–like systemic autoimmune disease upon aging (Jellusova et al., 2010). Other mechanisms of the host’s own molecules preventing activation of the immune system have recently been demonstrated: for example, the inhibitory properties of select endogenous lipids on interactions between CD1a and TCR, effectively preventing T cell responses (Cotton et al., 2021). It remains to be determined whether similar molecules can also deliver inhibitory signals to immune cells via inhibitory receptors.Some molecular patterns elicit activating and inhibitory signalsSeveral molecular patterns can be recognized by both inhibitory and activating receptors. The inhibitory receptor leukocyte-associated Ig-like receptor 1 (LAIR-1) recognizes a HAMP present in different transmembrane and extracellular matrix–associated collagens as well as collectins, leading to negative regulation of inflammatory responses, such as airway inflammation during viral infection (Kumawat et al., 2019; Lebbink et al., 2009). Collagens are also recognized by the activating receptor osteoclast-associated Ig-like receptor (OSCAR), through which they can promote inflammation (Barrow et al., 2011; Schultz et al., 2016). Further, a few Siglec receptors are activating (Macauley et al., 2014), indicating there may be instances where sialylated glycans instigate immune activation. The relative expression of activating and inhibitory receptors on immune cells in a given situation, together with other potential environmental cues, will thus determine to what extent a cell becomes activated by these molecular patterns.iPRRs can deliver potent inhibitory signals to immune cells and attenuate or halt immune system activation. Therefore, they are often exploited by tumors to evade the immune system. For instance, many tumors highly express diverse collagens, dampening antitumor immune responses through LAIR-1 activation on immune cells (Peng et al., 2020; Rygiel et al., 2011). Similarly, various tumor types up-regulate sialylated ligands for inhibitory Siglec receptors, resulting in a dampened antitumor immune response (Fraschilla and Pillai, 2017; Jandus et al., 2014; van de Wall et al., 2020). CD155, the ligand for inhibitory receptor T cell immunoreceptor with Ig and ITIM domains (TIGIT), is also up-regulated on tumor cells and inhibits T cell antitumor immune responses (Braun et al., 2020; Dougall et al., 2017). Up-regulation of inhibitory receptor ligands in tumor tissues thus appears to be a strategy of immune evasion in cancer.iPRRs recognize microbial molecular patternsSimilar to how the occurrence of DAMPs does not always result in inflammation, microbial PAMPs do not always relay inflammation-promoting signals. Most microbes do not behave as either strictly pathogens or strictly commensals. Microbes with high pathogenic potential can also exist as harmless colonizers of the host, and commensal microbes can cause disease when they behave in an atypical way. Activating PRRs alone cannot differentiate between these situations, and it has thus been suggested that the immune system makes distinctions between pathogenic and nonpathogenic microbes through an integrated system of signals rather than one particular signal (Greslehner, 2020; Swiatczak et al., 2011). We argue that iPRRs may provide these additional signals.Immune inhibitory receptors have been shown to interact with microbes, but since these interactions have been predominantly studied in experimental models of infection, it is commonly thought that iPRR–microbe interactions mediate immune evasion by the microbe (Van Avondt et al., 2015). Since most microbes are not strictly pathogens, it is reasonable to think that the interaction of microbial ligands with inhibitory receptors could contribute to symbiosis. Multiple iPRRs recognize microbial ligands (Fig. 2). Staphylococcus aureus, a bacterium that commonly colonizes the human skin and nasal mucosa, interacts with the mouse paired Ig-like receptor B (PIR-B, orthologue of human LILRB3) through LTA, thereby limiting proinflammatory cytokine production. Indeed, PIR-B−/− mice infected with S. aureus show decreased survival compared with wild-type mice (Nakayama et al., 2012). LTA is a PAMP and an essential component of the cell wall universally expressed not only by S. aureus, but also by other related, less pathogenic species. The inhibitory receptor PIR-B/LILRB3 could thus regulate the host interaction with S. aureus in a noninflammatory context through recognition of PAMPs.As discussed above, endogenous sialic acids are a molecular pattern associated with self and homeostasis, and they interact with different inhibitory Siglec receptors. Sialic acids present on the surface of group B streptococcus (GBS) likewise interact with inhibitory Siglecs (Carlin et al., 2007; Chang et al., 2014). The sialic acid is common to all GBSs, which is not a strict pathogen but rather an opportunist. CD33 Siglecs are expressed in skin-resident Langerhans cells, which could allow for interaction between Langerhans cells and GBS, resulting in an inhibitory signal and thus promoting the colonizing lifestyle of GBS. Other inhibitory receptors interacting with bacteria are SIRL-1, which recognizes staphylococcal phenol-soluble modulins (Rumpret et al., 2021b), and TIGIT, which recognizes a ligand expressed by the oral commensal bacterium Fusobacterium nucleatum (Gur et al., 2015). The functional roles of these interactions are yet to be fully explored.A particularly prominent binder of microbial ligands is the inhibitory receptor carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1). On immune cells, CEACAM1 is restrictively expressed on activated cells, whereas it is constitutively expressed by epithelial cells (Gray-Owen and Blumberg, 2006; Huang et al., 2015). It binds many different microbial ligands, such as bacterial Dr adhesins of Escherichia coli (Korotkova et al., 2008), the Opa protein of Neisseria meningitidis, Neisseria gonorrhoeae (Virji et al., 1996) and commensal Neisseria species (Toleman et al., 2001), adhesin UspA1 of Moraxella catarrhalis (Conners et al., 2008), the HopQ adhesin of Helicobacter pylori (Königer et al., 2016), CbpF adhesion of Fusobacterium sp. (Brewer et al., 2019; Gur et al., 2019), the streptococcal β protein (van Sorge et al., 2021), and an unidentified ligand in the fungus Candida sp. (Klaile et al., 2017). Although most of these microbes can be pathogenic, they do not always cause disease. Moreover, the absence of CEACAM1 has been shown in mouse models to predispose to colitis (Jin et al., 2016; Nagaishi et al., 2006). Together, these data indicate that CEACAM1 may have a tolerizing function in host–microbe interactions rather than serving only as a means for immune evasion.Concluding remarks and future perspectivesHere, we define a group of inhibitory receptors that can be classified as iPRRs. We argue that iPRRs, like their activating counterparts, recognize molecular patterns (Akira et al., 2006; Alvarez et al., 2008; An and Brodsky, 2016; Angata et al., 2002; Arakawa et al., 2018; Arnold et al., 2013; Brewer et al., 2019; Brown and Crocker, 2016; Carlin et al., 2007; Chang et al., 2014; Chen et al., 2009; Choi et al., 2011; Conners et al., 2008; Dougall et al., 2017; Fong et al., 2015; Gray-Owen and Blumberg, 2006; Gur et al., 2015; Gur et al., 2019; Han et al., 2005; Jones et al., 2016; Klaile et al., 2017; Königer et al., 2016; Korotkova et al., 2008; Kretschmer et al., 2010; Kumawat et al., 2019; Lebbink et al., 2009; Lewis Marffy and McCarthy, 2020; Liu et al., 2014; Macauley et al., 2014; Nakayama et al., 2012; Nakayama et al., 2007; Nuñez et al., 2018; Pende et al., 2006; Pérez-Oliva et al., 2011; Prantner et al., 2020; Rumpret et al., 2021a; Rumpret et al., 2021b; Segawa and Nagata, 2015; Simhadri et al., 2012; Sims et al., 2010; Steevels et al., 2013; van Sorge et al., 2021; Virji et al., 1996; Young et al., 2008; Yu et al., 2009; Zenarruzabeitia et al., 2015). This recognition provides context- and location-dependent signals to help shape the immune response. We indicate that most of the iPRRs discussed here are able to recognize both endogenous and microbial patterns (Fig. 2). The relative expression of activating and inhibitory PRRs and the integration of their signals ultimately determines the strength of an immune response to microbes or damage. This allows a differential response to tissue damage in different organs, depending on their susceptibility to immunopathology (Fig. 1). For example, in tissues that have low regenerative capacity, such as the brain, increased expression of iPRRs could provide a higher activation threshold and prevent the release of DAMPs that leads to inflammation and further tissue damage (Ashour et al., 2021). We also point out that endogenous patterns can signal “safety” via iPRRs to ensure that commonly occurring events such as apoptosis do not trigger the immune system. Similarly, there may be microbial patterns ensuring that harmless microbes colonizing the host do not bring about inflammatory responses (Fig. 3). For example, in the blood, microbial patterns such as LTA are recognized by activating PRRs. In contrast, in other anatomic locations such as the skin, iPRRs could also signal in response to these patterns, abrogating their potential to trigger inflammatory responses. We argue that the interactions between iPRRs and their microbial ligands may thus be vital for establishing and maintaining commensal–host homeostasis and suggest that studies in this direction are needed to examine this hypothesis. Further exploration of possible additional iPRRs, their ligands, and their expression patterns will provide a better understanding of the interactions of the host with its microbiota and the contextual regulation of septic and sterile inflammation.Table 1.Overview of different properties of iPRRs
Open in a separate windowOSCAR, osteoclast-associated Ig-like receptor; PVR, poliovirus receptor; RAGE, receptor for advanced glycation end products.Open in a separate windowFigure 3.The integration of activating and inhibitory signals determines the outcome of the immune response. When damage or a dangerous microbe should not be tolerated, DAMPs and PAMPs signal through activating PRRs to mount an immune response. However, when it is more beneficial for the host to tolerate damage or a harmless microbe, then the same DAMP or PAMP, or a different pattern, can concomitantly signal an iPRR to inhibit the immune response. The relative expression of PRRs and iPRRs and their respective ligands determine the strength of the resulting immune response.Finally, iPRRs can be exploited to treat or prevent disease. The increased understanding of the function of inhibitory receptors has led to significant advances in the treatment of cancer. PD-1 and CTLA-4 have proven their potential as therapeutic targets on T cells for cancer immunotherapy (Ribas and Wolchok, 2018). Innate cells such as NK cells, innate lymphoid cells, and different myeloid cell types are also important in anticancer immune responses. These cells can directly contribute to tumor removal and additionally modulate antitumor T cell responses by steering T cell activation. Different iPRRs expressed on these cells, such as TIGIT and CD96, are already being explored as additional therapeutic targets (Dougall et al., 2017). With an increased understanding of the properties of iPRRs and their ligands, we expect that more of these receptors will be used as targets for immunotherapy. 相似文献
iPRR | iPRR expression | iPRR structure | Signaling pathway | Endogenous ligand | Endogenous ligand expression | Microbial ligand | Activating receptor for the same ligand |
---|---|---|---|---|---|---|---|
CD300a/f | Broad on immune cells, upregulated on activation | Ig-like | ITIM | PS, PE | Exposed in programmed cell death | — | Tim4 |
CEACAM‑1 | Broad on immune, epithelial, and endothelial cells | Ig-like | ITIM | CEACAM1 and other CEACAMs | Constitutive | Ig fold proteins | Other CEACAMs |
LAIR-1 | Broad on immune cells; on activation, upregulated on neutrophils and downregulated on T cells | Ig-like | ITIM | Collagen | Constitutive | — | OSCAR |
LILRB1 (CD85j) | Neutrophil, monocyte, dendritic cell, and NK cell, upregulated on activation | Ig-like | ITIM | S100 proteins | Upon cell damage | — | TLR4, RAGE |
LILRB3 (CD85a) | Neutrophil, monocyte, dendritic cell | Ig-like | ITIM | Unknown cytokeratin-associated ligand | Upon cell damage | Unknown in S. aureus (LTA shown for mice ortholog PIR-B) | TLR2/6 |
PVR | Dendritic cell, upregulated on activation | Ig-like | ITIM | Nectin-3 | Constitutive | Poliovirus | — |
Siglec 2, 3, 5–11 | Broad on immune cells, differs per receptor | Ig-like | ITIM | Sialic acids | Constitutive | Sialic acids | Siglec 14–16 |
Siglec 2, 3, 5–11 | Broad on immune cells, differs per receptor | Ig-like | ITIM | Hsp70 | Upon cell damage | — | TLR4, RAGE |
Siglec 10 | B cell, eosinophil, monocyte | Ig-like | ITIM | HMGB1, Hsp90 | Upon cell damage | — | TLR4, RAGE |
SIRL-1 | Neutrophil, monocyte, downregulated on activation | Ig-like | ITIM | LL-37, S100 proteins | Upon cell damage and immune activation | Phenol-soluble modulins of Staphylococcus | TLR4, RAGE, FPR2 |
TIGIT | T cell, NK cell, upregulated on activation | Ig-like | ITIM | DNAM-1, TIGIT | TIGIT upregulated on activation | Unknown in F. nucleatum | DNAM-1 |
14.
15.
16.
Samarth S. Durgam Maria-Luisa Alegre Anita S. Chong 《The Journal of experimental medicine》2022,219(5)
Pregnancy is recognized as a spontaneously acquired state of immunological tolerance by the mother to her semi-allogeneic fetus, but it is a major cause of allosensitization in candidates for organ transplantation. This sensitization, assessed by the presence of anti-HLA IgG, contributes to sex disparity in access to transplantation and increases the risk for rejection and graft loss. Understanding this dual tolerance/sensitization conundrum may lead to new strategies for equalizing access to transplantation among sexes and improving transplant outcomes in parous women. Here, we review the clinical evidence that pregnancy results in humoral sensitization and query whether T cell responses are sensitized. Furthermore, we summarize preclinical evidence on the effects of pregnancy on fetus-specific CD4+ conventional, regulatory, and CD8+ T cells, and humoral responses. We end with a discussion on the impact of the divergent effects that pregnancy has upon alloantigen re-encounter in the context of solid organ transplantation, and how these insights point to a therapeutic roadmap for controlling pregnancy-dependent allosensitization.IntroductionThe fact that multiple successive pregnancies with the same male partner can be brought to term successfully suggests that the immunological response to a semi-allogeneic fetus is diametrically opposite to the responses elicited by genetically comparable transplanted organs. Peter Medawar in 1953 (Medawar, 1953) discussed this “immunological paradox of pregnancy,” and since then, there have been extensive investigations into how the fetus avoids rejection. A plethora of immune regulatory mechanisms has been uncovered within the uterine environment, including enrichment in regulatory T cells (Tregs), natural killer cells, regulatory macrophages, entrapment of APCs, and chemokine gene silencing of decidual stromal cells (PrabhuDas et al., 2015). Systemic factors that prevent fetal rejection have also been identified, including immune modulation by pregnancy-related hormones and release of tolerogenic placental debris, which may contribute to the preferential systemic expansion of fetus-specific Tregs and acquired dysfunction by conventional T cells (Tconvs) and CD8+ T cells. Since the majority of these mechanisms either act locally or only during pregnancy, it was assumed that T cell tolerance would manifest itself only in the context of subsequent pregnancy, and that encounter with the same alloantigens in the context of a solid organ transplant, in the absence of local or systemic pregnancy-induced immunomodulation, would trigger allograft rejection.The emphasis on T cells as the major mediator of allograft rejection and on T cell tolerance as a means to achieve transplantation tolerance parallels the focus on the constraint of T cells in pregnancy. Thus, despite studies in the 1980s by Bell and Billington (Bell and Billington, 1981; Bell and Billington, 1983; Bell and Billington, 1986) that pregnancy can elicit paternal-reactive antibodies, how pregnancy sensitizes B cell responses while maintaining T cell tolerance to the semi-allogeneic fetus has remained an under-investigated topic in preclinical models (PrabhuDas et al., 2015). In contrast and driven by the ease in quantifying HLA-specific antibodies but difficulty in assessing HLA-specific T cell responses, clinical studies in solid organ transplantation have revealed that pregnancy is a highly sensitizing event that results in the production of fetus-reactive anti-HLA antibodies, and the presence of these antibodies limits access to transplantation and contributes to increased risk of transplant rejection. In this review, we focus on the contrasting effects of pregnancy on these two arms of the adaptive immune system, and on how these pregnancy-shaped responses are recalled by alloantigens that are shared between offspring and transplanted allograft.Clinical impact of pregnancy alloimmunization in organ transplantationHumoral sensitizationThe effect of pregnancy on the immune system was first reported by J.J. Rodd in 1959 when he described peripartum women experiencing an increased number of blood transfusion reactions (Van Rood et al., 1958). It was this observation that allowed for the discovery of anti-HLA antibodies from the sera of pregnant women (Van Rood et al., 1958). Anti-HLA antibodies are produced during the first trimester of a pregnancy and increase in titer over the gestational course and with multiple pregnancies (Lee et al., 2011). During the postpartum phase, antibody levels rise in the first 90 d and gradually disappear in 50% of postpartum women over a 1–2 yr period (Cecka, 2010; Masson et al., 2013). Anti-HLA antibody titers following kidney transplantation increase more robustly in patients having had prior pregnancies than in those having received previous transplantation or transfusion, suggestive of robust pregnancy-induced memory B cells (Higgins et al., 2015). Notably, although pregnancy-induced alloantibodies can diminish with time, alloreactive memory T and B cells can persist (Senn et al., 2021). Thus, anti-HLA antibodies and memory B cells induced by semi-allogeneic pregnancies play a pivotal role prior to and after transplantation, especially for multiparous women.Historically, anti-HLA antibody titers were measured by the panel-reactive antibody (PRA) technique through a complement-dependent cytotoxicity assay; however, the major limitation of this method is its inconsistency and lack of HLA specificity. In 2009, the United Network for Organ Sharing implemented measuring sensitization using single HLA-coated beads, an assay that precisely identifies specific HLA antigen targets (Cecka, 2010). A computer algorithm generates a calculated PRA (cPRA) according to the HLA frequencies derived from the donor population with the goal of providing consistently accurate results on the extent of sensitization of transplant candidates and the chances for a highly sensitized candidate to find a compatible organ donor. Around 30% of pregnant women are sensitized when measured via complement-dependent cytotoxicity assay, whereas 50–75% of women were found to be sensitized by pregnancy when the single HLA bead assay was used (Bromberger et al., 2017). Furthermore, a retrospective analysis of the United Network for Organ Sharing registry’s waitlist pool showed that individuals with a cPRA >98% were over-represented by women by ~60% (Redfield et al., 2016). Cumulatively, these data reveal the detrimental impact of pregnancy in women in need of a transplant and the disparity it creates toward identifying a suitable donor organ and having a successful post-transplantation course.Living donor kidney transplantation has better outcomes compared to kidney transplantation from deceased donors (Roodnat et al., 2003). However, 30% fewer women received living donor kidney transplantation as compared with men despite comparable referrals (Bromberger et al., 2017; Roodnat et al., 2003). Pregnancy was identified as a major contributor to this disparity, as postpartum women were increasingly incompatible with their spouse and offspring compared with men (Bromberger et al., 2017). Furthermore, parous women are at a higher risk of being sensitized to unrelated donors sharing an allele of the partner or offspring (Gibney et al., 2006; Vaidya et al., 2006). Child-specific sensitization measured by single-HLA bead assay was detected at the HLA-A/B/C/DR loci in 28–38% of 301 multiparous women analyzed (Honger et al., 2013), with child-specific HLA-B loci being the most sensitizing followed by HLA-A > HLA-DRB1 > HLA-C (Dankers et al., 2003; Honger et al., 2013). Furthermore, by quantifying mother/child mismatches by the number of mismatched HLA eplets, where an eplet is defined as the cluster of amino acids representing the smallest functional unit of structural epitopes on the HLA molecule targeted by B cell receptor and antibodies, the rate of child-specific sensitization increased with the presence of ≥20 mismatched eplets (Honger et al., 2013). These observations are reminiscent of eplet-load mismatch between the organ donor and the recipient predicting de novo anti-HLA antibody production by the host and reduced graft survival, and thus underscories the detrimental effects of pregnancy-induced humoral sensitization (Philogene et al., 2020; Sapir-Pichhadze et al., 2020).T cell sensitizationIn contrast to the abundant evidence that fetus-specific B cell responses are induced during pregnancy and the barrier they pose to transplantation, the effects of pregnancy-induced effector T cell responses on subsequent transplantation are more opaque. Specifically, although it is clear that maternal T cells acquire tolerance to the semi-allogeneic fetus, it is uncertain whether this T cell tolerance extends to subsequent organ allografts sharing antigens with the fetus. Early observations that fetal-derived stem cells can persist in low numbers in the mother’s circulation for as long as 27 yr, a phenomenon termed peripheral fetal microchimerism (Nelson, 1998), prompted the hypothesis that this microchimerism mediates long-term fetus-specific tolerance in mothers and promotes the acceptance of grafts from their offspring (Starzl et al., 1993). However, several studies testing the correlation between donor/recipient kinship and allograft fate have reported comparable outcomes between groups receiving grafts from offspring versus non-offspring (Cohen et al., 2018; Ghafari, 2008; Mahanty et al., 2001). A recent retrospective analysis performed using the Organ Procurement and Transplant Network living donor liver transplant database revealed that 1-, 5- and 10-yr allografts and patient survival was poorer among mothers who received the organ from their offspring as compared with unrelated living donors (Dagan et al., 2020). A major caveat of such studies is the potential pro-rejection effects of pregnancy-sensitized B cells even when pregnancy-induced antibodies have diminished; as a result, the contribution of pregnancy-primed T cells, either pro-rejection or pro-tolerogenic, may be obscured. Indeed, Senn et al. (2021) reported that women with prior pregnancies receiving kidneys from their husband consistently had a higher rate of antibody-mediated rejection compared with women with prior pregnancies receiving kidneys from other living or deceased donors.A limited number of studies have attempted to directly quantify ex vivo donor-specific T cell responses arising during normal human pregnancy using proliferation, cytokine production, or cellular cytotoxicity as readouts. When IL-4 and IFNγ ELISPOT assays were used to quantify PBMC responses from non-pregnant versus pregnant women to paternal or pooled alloantigens, Mjosberg et al. (2007) reported that pregnancy did not result in increased paternal-specific IL-4 or IFNγ responses. Furthermore, removal of Tregs resulted in non-specific increases in IFNγ responses and paternal-specific augmentation in IL-4 production. Collectively, their study suggested an absence of pregnancy-specific sensitization of T cells, while also hinting at postpartum Tregs controlling fetus-specific IL-4 responses and broadly controlling IFNγ responses. Notably, reduced frequencies of circulating FoxP3+ Tregs were observed with spontaneous preterm birth, preeclampsia, and recurrent spontaneous miscarriages compared to healthy pregnancies suggesting a more systemic effect of Tregs (Dimova et al., 2011; Inada et al., 2015; Inada et al., 2013; Kisielewicz et al., 2010; Koucky et al., 2014; Mjosberg et al., 2010; Nadkarni et al., 2016; Schober et al., 2012; Tilburgs et al., 2008; Tsuda et al., 2018).Pregnancy-induced Tregs are critical for promoting both primary and secondary pregnancies by suppressing T cell proliferation and cytokine production not only in secondary lymphoid organs but also in the placenta (Salvany-Celades et al., 2019). Expansion of Tregs in the decidual tissue has been prostulated to suppress fetus-specific responses locally (Tilburgs et al., 2008; Erlebacher, 2013). Notably, three different Treg populations have been identified at the maternal–fetal interface: CD25HIFOXP3+, PD1HIFOXP3−IL-10+, and TIGIT+FOXP3dim Tregs. Decidual CD25HIFOXP3+ Tregs were able to suppress the proliferation and IFNγ and TNFα production by CD4+ and effector CD8+ T cells in vitro, whereas decidual PD1HI Tregs and TIGIT+ Tregs inhibited CD4+ but not effector CD8+ T cells. However, whether pregnancy-induced Tregs are most potent in the decidua or whether they can also dominantly suppress T cell responses to offspring-matched allografts in secondary lymphoid organs is currently unknown.CD8+ T cell responses to fetus-specific minor antigens have been more consistently reported to develop during pregnancy compared to CD4+ T cell responses (Linscheid and Petroff, 2013). Lissauer et al. (2012) assayed fetal-specific CD8+ cytotoxic responses using MHC-peptide dextramer multimers bearing a HY-immunodominant peptide in women pregnant with a male fetus. These CD8+ T cells expanded during pregnancy and persisted in the post-natal period in 50–62% of pregnant women. Furthermore, the fetal-specific CD8+ T cells retained their ability to proliferate, secrete IFNγ, and lyse target cells. These observations corroborated previous studies (Bouma et al., 1996; James et al., 2003; Mommaas et al., 2002; Piper et al., 2007; Verdijk et al., 2004) and suggested that fetal-specific CD8+ T cells expand during pregnancy and persist postpartum. It is tempting to speculate that preservation of fetus-CD8+ T cell responses during pregnancy, especially in the decidua, may have been evolutionarily selected to ensure the development of protective immunity for the developing fetus against viral infections, given that the fetus is haplo-identical to the mother, and thus maternal HLA-restricted CD8+ responses will recognize virally infected fetal cells (Tilburgs and Strominger, 2013; van Egmond et al., 2016). Indeed, observations that the decidua contains a higher percentage of CD8+ T cells and a lower percentage of CD4+ T cells compared with the peripheral blood is consistent with this possibility (Tilburgs et al., 2009; van Egmond et al., 2016).Potentially divergent fates of fetus-specific T cell subsets, together with a paucity of studies examining fetus-specific T cell responses in the extended postpartum period, make it difficult to definitively conclude if pregnancy-primed T cells are functionally tolerant or sensitized to fetal antigens presented in the context of a solid organ transplant. The ex vivo quantification of fetus-specific T cell responses is technically challenging and complicated by the increased frequency of pregnancy-induced Tregs (Salvany-Celades et al., 2019). Furthermore, ex vivo observations may not necessarily predict how these cells will behave in vivo after transplantation with organs sharing HLA antigens with the fetus. In vivo studies in postpartum recipients suggest that poorer outcomes are complicated by pregnancy-induced humoral sensitization (Author No. of transplants Outcome Terasaki et al. (1995) Husband-to-mother: n = 368 Comparable allograft survival between spousal donor and unrelated living donor. Pregnancy is a risk factor for loss of allograft Child-to-mother: n = 1,411 Mahanty et al. (2001) Offspring-to-mother: n = 874 Fetal tolerance did not translate to a superior allograft survival from offspring donors. Multiple pregnancy trended towards poor allograft survival Unrelated living donor to mother: n = 310 Cohen et al. (2003) Offspring-to-parent: n = 3,370 Comparable death censored 5-yr allograft survival in offspring-to-parent compared to unrelated living donor Unrelated living donor: n = 8,351 Deceased donor: n = 44,792 Miles et al. (2008) Offspring to mother: n = 3,124 Comparable and poor allograft survival in offspring-to-parent and parent-to-offspring transplants Parent to offspring: n = 6,076 Ghafari (2008) Offspring-to-mother: n = 12 Unrelated living donor allografts survival was significantly higher compared to offspring and husband donor allografts Husband-to-mother: n = 9 Unrelated living donor: n = 150 Choi et al. (2012) Offspring-to-mother: n = 49 Comparable 5- and 10-yr kidney graft survival between offspring-to-mother and offspring-to-father transplant. Mother-to-child had worse outcome Parent-to-offspring: n = 146 Redfield et al. (2016) Highly sensitized: n = 7,145 Increased graft loss by 23% among women with a history of pregnancy and transfusion compared to non-sensitized Non-sensitized: n = 100,147 Cohen et al. (2018) Offspring-to-mother: n = 1,332 Comparable allograft survival between offspring and unrelated living donor transplant to mother Unrelated living donor: n = 1,435 Dagan et al. (2020) Offspring-to-mother: n = 148 Offspring donor allograft survival lower compared to unrelated living donor Unrelated living donor: n = 93 Male offspring donor resulted in poorer survival compared to female offspring donor Senn et al. (2021) Husband-to-mother: n = 25 Poor allograft survival among mothers who received allograft from spouse compared to unrelated living donor or deceased donor Unrelated living donor: n = 52 Deceased donor: n = 120