n ews a n d views
Old HDL learns a new (anti-inflammatory) trick Justin I Odegaard & Ajay Chawla In addition to its canonical role in reverse cholesterol transport, high-density lipoprotein can suppress inflammation in target cells through the induction of Atf3, which encodes a well-known transcriptional repressor. ecades of outcome- and association-based clinical investigation have elevated highdensity lipoprotein (HDL), a class of complex, lipid-laden particles comprising ~100 different proteins, to almost panacean status in both the medical literature and common parlance, where it is known widely as the ‘good cholesterol’1,2. Despite that august reputation, HDL’s activity has until recently been largely explained by reference to reverse cholesterol transport—its originally identified function— despite growing evidence of other important functions subsumed by this particle3,4. Indeed, in this issue of Nature Immunology, De Nardo et al. describe a novel and apparently cholesterol transport–independent mechanism by which HDL exerts a potent anti-inflammatory influence over target cell populations5. The authors begin with a simple and oftendescribed phenomenon—HDL’s inhibition of Toll-like receptor (TLR) ligand–induced inflammation—and proceed to systematically delineate the mechanistic particulars of that effect through the use of a well-integrated combination of simple in vitro experiments and powerful systems biology tools. By that approach, they identify ATF3, a transcriptional repressor linked to such diverse processes as inflammation, pain sensation, neuron biology and cellular stress responses6,7, as a critical mediator of HDL’s anti-inflammatory effects. They show that rather than inhibiting the activation of proximal signaling proteins, HDL instead specifically induces the accumulation of ATF3 at promoters of multiple genes that encode archetypal inflammatory molecules, where it correlates with decreased gene transcription, as well as decreased production and secretion of cytokines by bone marrow–derived macro phages upon activation of TLR9 induced by its ligand CpG (Fig. 1). Congruent with that, HDL’s anti-inflammatory properties, and its potent tissue-protective effects, are entirely Justin I. Odegaard is with the Cardiovascular Research Institute, University of California, San Francisco, California, USA. Ajay Chawla is with the Cardiovascular Research Institute, the Department of Physiology and the Department of Medicine, University of California, San Francisco, California, USA. e-mail: [email protected]
138
lost in mice and cells lacking Atf3 in models of inflammatory liver injury and vascular damage. Despite the clearly demonstrated importance of the ATF3 pathway, other HDL activities are, to all measurable extent, entirely intact in the Atf3–/– context. For example, HDL’s almost definitional property of reverse cholesterol transport is unaffected by Atf3 deficiency in this study, as assessed by gene-expression patterns in the cells being relieved of their cholesterol; that is, the cholesterol-biogenesis program induced by HDL seems to be undisrupted in Atf3–/– cells. Moreover, certain effects of HDL reported elsewhere (such as modulation of leukocyte-endothelial interactions) occur on time scales incompatible with transcriptional regulation3 and thus cannot be attributed to the effects of ATF3, whereas platelets, well-known targets of HDL8, entirely lack nuclei and, thus, as the authors point out, lack any transcription for ATF3 to repress. Thus, the ATF3dependent mechanism(s) identified seem(s) to specifically regulate certain anti-inflammatory functions of HDL but not those relating to cholesterol homeostasis. It is important to note, however, that the present work focuses solely on specific mouse models of inflammation and endothelial damage and provides scant or no data on the broader role of ATF3 in more general inflammatory contexts or in HDL’s other biological activities. Moreover, the
authors’ transcriptional profiling experiments identify many other HDL-responsive genes, including those encoding other transcription factors, with levels of induction similar to (and in some cases surpassing) that of Atf3, which suggests other potential mechanisms by which constituents of HDL exert influence over target cell populations. Indeed, exactly in which constituent of HDL the ability to induce Atf3 resides is unknown, as is how the effect is achieved. The authors’ identification of the HDL-ATF3 anti-inflammatory pathway underscores a broader trend in the field: although it has been long dominated by cholesterol-transport studies to the neglect of other biological functions, HDL research has begun fleshing out a surprising diversity of noncanonical functions subsumed by this particle class. Interest in these new functions has been driven in no small part by the growing appreciation that HDL’s general physiological beneficence is owed to both cholesterol transport–dependent processes and cholesterol transport–independent processes, which highlights the clear fact that this complex and varied particle has numerous discrete biological functions, many of which remain either partially enigmatic or wholly enigmatic. For example, in manners largely unrelated to cholesterol transport, HDL has been described as regulating multiple aspects of the biology of
?
HDL
?
ATF3
?
Il6 Il12b Tnf Inflammation
?
TRAF6–NF-κB TLR ligand (e.g., CpG, R-848 and P3C)
TLR
Target cell
Figure 1 HDL suppresses TLR ligand–induced inflammation via activation of Atf3. In TLR-expressing cells, TLR ligands, such as CpG, R-848 and P3C, trigger robust transcription from archetypal genes encoding inflammatory molecules, such as Il6, Il12b (which encodes IL-12p40) and Tnf, through canonical inflammatory signaling pathways, such as the cascade of the adaptor TRAF6 and the transcription factor NF-kB. However, De Nardo et al. report that in the presence of HDL, ATF3 accumulates on the promoters of those genes and substantially blunts the ability of the TLR axis to upregulate their transcription5. How exactly HDL induces the induction of Atf3 and accumulation of ATF3 and how ATF3 exerts its specific suppressive effects are not yet known. P3, Pam3CSK4 (tripalmitoyl cysteinyl seryl tetralysine).
volume 15 number 2 february 2014 nature immunology
Marina Corral Spence
npg
© 2014 Nature America, Inc. All rights reserved.
D
npg
© 2014 Nature America, Inc. All rights reserved.
n ews a n d views endothelium and vascular smooth muscle, the energy metabolism of adipocytes and skeletal muscle, hematopoiesis, platelet activation and immunity3,4,9–11. Indeed, this study joins many others in underscoring that last category, in which HDL is emerging as a potential regulator of not only innate inflammatory responses to acute stimuli (such as the TLR ligands used in the present study) but also adaptive immunity, including antigen presentation, lymphocyte proliferation and activation bias, and immunological signaling. Perhaps most importantly, HDL can also regulate the low-intensity and prolonged inflammatory states that pervade and drive chronic metabolic dysfunctions such as metabolic syndrome and type 2 diabetes, as well as carcinogenesis and other inflammation-associated disease processes3,4,12. It is also important to note that even its canonical cholesterol-transport roles are being revised and rethought because ‘calculated HDL’ (the accepted standard for HDL measurement in the clinical literature) has proven to be an inadequate predictor of disease risk1,2.
This relative abundance of newly reported functions and correlations stands in sharp contrast, however, to the relative dearth of thorough mechanistic studies defining how exactly HDL influences target cells to achieve those effects. Moreover, the independent and dependent influences of each of these activities on higher-order physiological processes such as cardiovascular and metabolic health, vascular maintenance and immunity remain almost entirely unknown. The work of De Nardo et al. raises each of those general questions in more specific terms5; for example, what is the mechanism by which the HDL complex activates Atf3, how does that contribute to higherorder physiological processes in health and disease and, most importantly, how can that be exploited for therapeutic effect? Moreover, might HDL use that pathway to regulate other target-cell functions or related pathways to similarly target inflammation? Whatever questions are raised, the implications of the accompanying paper are clear: HDL exerts a potent influence over target cells that indicates tantalizing therapeutic potential for the treatment
of inflammatory injury and endothelial damage, in addition to its role in cholesterol homeostasis. With many of the developed world’s major killers thus neatly tied to this particle, HDL seems poised for renewed and refocused therapeutic investigation, despite recent therapeutic disappointments. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Heinecke, J.W. Nat. Med. 18, 1346–1347 (2012). 2. Rader, D.J. & Tall, A.R. Nat. Med. 18, 1344–1346 (2012). 3. Murphy, A.J. et al. Biochim. Biophys. Acta 1821, 513–521 (2012). 4. Zhu, X. & Parks, J.S. Annu. Rev. Nutr. 32, 161–182 (2012). 5. De Nardo, D. Nat. Immunol. 15, 152–160 (2014). 6. Gilchrist, M. et al. Nature 441, 173–178 (2006). 7. Patodia, S. & Raivich, G. Front. Mol. Neurosci. 5, 8 (2012). 8. Lerch, P.G., Spycher, M.O. & Doran, J.E. Thromb. Haemost. 80, 316–320 (1998). 9. Drew, B.G. Nat. Rev. Endocrinol. 8, 237–245 (2012). 10. Mineo, C. & Shaul, P.W. Circ. Res. 111, 1079–1090 (2012). 11. Nofer, J.R., Brodde, M.F. & Kehrel, B.E. Clin. Exp. Pharmacol. Physiol. 37, 726–735 (2010). 12. Norata, G.D. et al. Atherosclerosis 220, 11–21 (2012).
Strength in numbers: comparing vaccine signatures the modular way W Nicholas Haining Gene-expression signatures of the human vaccine response can be complex and noisy. Li et al. develop a new collection of gene-expression modules and use it to compare the response to five different vaccines.
V
accines have improved human health enormously. The trouble is, we are not quite sure how they work. While we know a great deal about some components of the vaccine response, the answers to many important questions remain murky: for example, which features of the vaccine response are required for immunological protection, or whether different vaccines induce similar patterns of immunity. Without answers to these questions, clinical vaccine discovery today looks more like the trial-and-error efforts of Pasteur’s era than the rational design approach of modern drug development. As a result, progress in coming up with effective W. Nicholas Haining is at the Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA, and at the Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. e-mail: [email protected]
vaccines against diseases such as HIV and tuberculosis remains slow. To accelerate vaccine development, several groups have identified gene-expression signatures present in human peripheral blood mononuclear cells (PBMCs) that predict immune responses to yellow fever1,2 and influenza vaccines3. However, the extent of vaccine-induced change in PBMC profiles can be small, and the number of genes measured in a typical gene-expression profiling experiment is large4, making it difficult to distinguish the signal from the noise. In this issue, Li et al.5 provide a new computational resource to make identifying subtle signatures easier and use it to compare the signatures elicited by five different vaccines. The simplest way to analyze gene-expression profiles is to identify individual genes that are differentially expressed between phenotypes or conditions of interest. This can be achieved by comparing profiles from, say, samples obtained before and after vaccination, or samples from
nature immunology volume 15 number 2 february 2014
subjects with varying degrees of vaccineinduced antibody responses, and identifying genes whose difference in expression is greater than would be expected by chance. This gene-bygene approach has been very useful in identifying specific genes that regulate the immune response6, but it tends to ‘ignore’ more complex and subtle patterns evident in genome-scale expression data7. Li et al.5 have developed a new resource to help identify biologically meaningful patterns of gene expression in PBMC profiles from vaccinated subjects, and they use it to ask whether different vaccines elicit unique or shared patterns of immunity. Their study provides both a technical resource for transcriptional analysis and the first comparison of gene-expression signatures elicited by different vaccines. The technical resource they have developed is a compendium of coordinately expressed modules of genes. They identified the modules by analyzing patterns of gene expression present 139
Old HDL learns a new (anti-inflammatory) trick Justin I Odegaard & Ajay Chawla In addition to its canonical role in reverse cholesterol transport, high-density lipoprotein can suppress inflammation in target cells through the induction of Atf3, which encodes a well-known transcriptional repressor. ecades of outcome- and association-based clinical investigation have elevated highdensity lipoprotein (HDL), a class of complex, lipid-laden particles comprising ~100 different proteins, to almost panacean status in both the medical literature and common parlance, where it is known widely as the ‘good cholesterol’1,2. Despite that august reputation, HDL’s activity has until recently been largely explained by reference to reverse cholesterol transport—its originally identified function— despite growing evidence of other important functions subsumed by this particle3,4. Indeed, in this issue of Nature Immunology, De Nardo et al. describe a novel and apparently cholesterol transport–independent mechanism by which HDL exerts a potent anti-inflammatory influence over target cell populations5. The authors begin with a simple and oftendescribed phenomenon—HDL’s inhibition of Toll-like receptor (TLR) ligand–induced inflammation—and proceed to systematically delineate the mechanistic particulars of that effect through the use of a well-integrated combination of simple in vitro experiments and powerful systems biology tools. By that approach, they identify ATF3, a transcriptional repressor linked to such diverse processes as inflammation, pain sensation, neuron biology and cellular stress responses6,7, as a critical mediator of HDL’s anti-inflammatory effects. They show that rather than inhibiting the activation of proximal signaling proteins, HDL instead specifically induces the accumulation of ATF3 at promoters of multiple genes that encode archetypal inflammatory molecules, where it correlates with decreased gene transcription, as well as decreased production and secretion of cytokines by bone marrow–derived macro phages upon activation of TLR9 induced by its ligand CpG (Fig. 1). Congruent with that, HDL’s anti-inflammatory properties, and its potent tissue-protective effects, are entirely Justin I. Odegaard is with the Cardiovascular Research Institute, University of California, San Francisco, California, USA. Ajay Chawla is with the Cardiovascular Research Institute, the Department of Physiology and the Department of Medicine, University of California, San Francisco, California, USA. e-mail: [email protected]
138
lost in mice and cells lacking Atf3 in models of inflammatory liver injury and vascular damage. Despite the clearly demonstrated importance of the ATF3 pathway, other HDL activities are, to all measurable extent, entirely intact in the Atf3–/– context. For example, HDL’s almost definitional property of reverse cholesterol transport is unaffected by Atf3 deficiency in this study, as assessed by gene-expression patterns in the cells being relieved of their cholesterol; that is, the cholesterol-biogenesis program induced by HDL seems to be undisrupted in Atf3–/– cells. Moreover, certain effects of HDL reported elsewhere (such as modulation of leukocyte-endothelial interactions) occur on time scales incompatible with transcriptional regulation3 and thus cannot be attributed to the effects of ATF3, whereas platelets, well-known targets of HDL8, entirely lack nuclei and, thus, as the authors point out, lack any transcription for ATF3 to repress. Thus, the ATF3dependent mechanism(s) identified seem(s) to specifically regulate certain anti-inflammatory functions of HDL but not those relating to cholesterol homeostasis. It is important to note, however, that the present work focuses solely on specific mouse models of inflammation and endothelial damage and provides scant or no data on the broader role of ATF3 in more general inflammatory contexts or in HDL’s other biological activities. Moreover, the
authors’ transcriptional profiling experiments identify many other HDL-responsive genes, including those encoding other transcription factors, with levels of induction similar to (and in some cases surpassing) that of Atf3, which suggests other potential mechanisms by which constituents of HDL exert influence over target cell populations. Indeed, exactly in which constituent of HDL the ability to induce Atf3 resides is unknown, as is how the effect is achieved. The authors’ identification of the HDL-ATF3 anti-inflammatory pathway underscores a broader trend in the field: although it has been long dominated by cholesterol-transport studies to the neglect of other biological functions, HDL research has begun fleshing out a surprising diversity of noncanonical functions subsumed by this particle class. Interest in these new functions has been driven in no small part by the growing appreciation that HDL’s general physiological beneficence is owed to both cholesterol transport–dependent processes and cholesterol transport–independent processes, which highlights the clear fact that this complex and varied particle has numerous discrete biological functions, many of which remain either partially enigmatic or wholly enigmatic. For example, in manners largely unrelated to cholesterol transport, HDL has been described as regulating multiple aspects of the biology of
?
HDL
?
ATF3
?
Il6 Il12b Tnf Inflammation
?
TRAF6–NF-κB TLR ligand (e.g., CpG, R-848 and P3C)
TLR
Target cell
Figure 1 HDL suppresses TLR ligand–induced inflammation via activation of Atf3. In TLR-expressing cells, TLR ligands, such as CpG, R-848 and P3C, trigger robust transcription from archetypal genes encoding inflammatory molecules, such as Il6, Il12b (which encodes IL-12p40) and Tnf, through canonical inflammatory signaling pathways, such as the cascade of the adaptor TRAF6 and the transcription factor NF-kB. However, De Nardo et al. report that in the presence of HDL, ATF3 accumulates on the promoters of those genes and substantially blunts the ability of the TLR axis to upregulate their transcription5. How exactly HDL induces the induction of Atf3 and accumulation of ATF3 and how ATF3 exerts its specific suppressive effects are not yet known. P3, Pam3CSK4 (tripalmitoyl cysteinyl seryl tetralysine).
volume 15 number 2 february 2014 nature immunology
Marina Corral Spence
npg
© 2014 Nature America, Inc. All rights reserved.
D
npg
© 2014 Nature America, Inc. All rights reserved.
n ews a n d views endothelium and vascular smooth muscle, the energy metabolism of adipocytes and skeletal muscle, hematopoiesis, platelet activation and immunity3,4,9–11. Indeed, this study joins many others in underscoring that last category, in which HDL is emerging as a potential regulator of not only innate inflammatory responses to acute stimuli (such as the TLR ligands used in the present study) but also adaptive immunity, including antigen presentation, lymphocyte proliferation and activation bias, and immunological signaling. Perhaps most importantly, HDL can also regulate the low-intensity and prolonged inflammatory states that pervade and drive chronic metabolic dysfunctions such as metabolic syndrome and type 2 diabetes, as well as carcinogenesis and other inflammation-associated disease processes3,4,12. It is also important to note that even its canonical cholesterol-transport roles are being revised and rethought because ‘calculated HDL’ (the accepted standard for HDL measurement in the clinical literature) has proven to be an inadequate predictor of disease risk1,2.
This relative abundance of newly reported functions and correlations stands in sharp contrast, however, to the relative dearth of thorough mechanistic studies defining how exactly HDL influences target cells to achieve those effects. Moreover, the independent and dependent influences of each of these activities on higher-order physiological processes such as cardiovascular and metabolic health, vascular maintenance and immunity remain almost entirely unknown. The work of De Nardo et al. raises each of those general questions in more specific terms5; for example, what is the mechanism by which the HDL complex activates Atf3, how does that contribute to higherorder physiological processes in health and disease and, most importantly, how can that be exploited for therapeutic effect? Moreover, might HDL use that pathway to regulate other target-cell functions or related pathways to similarly target inflammation? Whatever questions are raised, the implications of the accompanying paper are clear: HDL exerts a potent influence over target cells that indicates tantalizing therapeutic potential for the treatment
of inflammatory injury and endothelial damage, in addition to its role in cholesterol homeostasis. With many of the developed world’s major killers thus neatly tied to this particle, HDL seems poised for renewed and refocused therapeutic investigation, despite recent therapeutic disappointments. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Heinecke, J.W. Nat. Med. 18, 1346–1347 (2012). 2. Rader, D.J. & Tall, A.R. Nat. Med. 18, 1344–1346 (2012). 3. Murphy, A.J. et al. Biochim. Biophys. Acta 1821, 513–521 (2012). 4. Zhu, X. & Parks, J.S. Annu. Rev. Nutr. 32, 161–182 (2012). 5. De Nardo, D. Nat. Immunol. 15, 152–160 (2014). 6. Gilchrist, M. et al. Nature 441, 173–178 (2006). 7. Patodia, S. & Raivich, G. Front. Mol. Neurosci. 5, 8 (2012). 8. Lerch, P.G., Spycher, M.O. & Doran, J.E. Thromb. Haemost. 80, 316–320 (1998). 9. Drew, B.G. Nat. Rev. Endocrinol. 8, 237–245 (2012). 10. Mineo, C. & Shaul, P.W. Circ. Res. 111, 1079–1090 (2012). 11. Nofer, J.R., Brodde, M.F. & Kehrel, B.E. Clin. Exp. Pharmacol. Physiol. 37, 726–735 (2010). 12. Norata, G.D. et al. Atherosclerosis 220, 11–21 (2012).
Strength in numbers: comparing vaccine signatures the modular way W Nicholas Haining Gene-expression signatures of the human vaccine response can be complex and noisy. Li et al. develop a new collection of gene-expression modules and use it to compare the response to five different vaccines.
V
accines have improved human health enormously. The trouble is, we are not quite sure how they work. While we know a great deal about some components of the vaccine response, the answers to many important questions remain murky: for example, which features of the vaccine response are required for immunological protection, or whether different vaccines induce similar patterns of immunity. Without answers to these questions, clinical vaccine discovery today looks more like the trial-and-error efforts of Pasteur’s era than the rational design approach of modern drug development. As a result, progress in coming up with effective W. Nicholas Haining is at the Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA, and at the Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. e-mail: [email protected]
vaccines against diseases such as HIV and tuberculosis remains slow. To accelerate vaccine development, several groups have identified gene-expression signatures present in human peripheral blood mononuclear cells (PBMCs) that predict immune responses to yellow fever1,2 and influenza vaccines3. However, the extent of vaccine-induced change in PBMC profiles can be small, and the number of genes measured in a typical gene-expression profiling experiment is large4, making it difficult to distinguish the signal from the noise. In this issue, Li et al.5 provide a new computational resource to make identifying subtle signatures easier and use it to compare the signatures elicited by five different vaccines. The simplest way to analyze gene-expression profiles is to identify individual genes that are differentially expressed between phenotypes or conditions of interest. This can be achieved by comparing profiles from, say, samples obtained before and after vaccination, or samples from
nature immunology volume 15 number 2 february 2014
subjects with varying degrees of vaccineinduced antibody responses, and identifying genes whose difference in expression is greater than would be expected by chance. This gene-bygene approach has been very useful in identifying specific genes that regulate the immune response6, but it tends to ‘ignore’ more complex and subtle patterns evident in genome-scale expression data7. Li et al.5 have developed a new resource to help identify biologically meaningful patterns of gene expression in PBMC profiles from vaccinated subjects, and they use it to ask whether different vaccines elicit unique or shared patterns of immunity. Their study provides both a technical resource for transcriptional analysis and the first comparison of gene-expression signatures elicited by different vaccines. The technical resource they have developed is a compendium of coordinately expressed modules of genes. They identified the modules by analyzing patterns of gene expression present 139
