Monocytes and macrophages form the major cellular component of the innate immune system, with roles in tissue development, homeostasis, and host defense against infection. Environmental factors were shown to play a significant part in determining innate immune responsiveness, and this included systemic conditions, such as circulating glucose levels, gut microflora, time of year, and even diurnal rhythm, which had a direct impact on innate immune receptor expression. Although the underlying molecular processes are just beginning to emerge, it is clear that environmental factors may alter epigenetic states of peripheral blood monocytes and resident tissue macrophages. We conclude that some measure of cellular ground state must become an essential part of the analysis of myeloid responsiveness or infectious susceptibility.

Nonspecific models of innate immunity have been invaluable in revealing the molecular basis of pathogen recognition, but the term “nonspecific” is somewhat outdated, because it implies that the cellular effectors are universally equipped to recognize and respond to pathogens. According to the nonclonal model of innate immunity first described by Charles Janeway (1), myeloid cells are armed with pattern recognition receptors (PRRs) that enable immediate recognition of infectious agents. This, in turn, elicits nonspecific responses, such as phagocytosis and cytokine and chemokine release aimed at rapid removal of the infectious agent (2). The term “nonspecific” was coined to discriminate between the rapid action of innate cells and the slower selection/expansion required for Ag-specific lymphocyte responses. This does not encompass the ability of innate cells to adapt to local, systemic, or environmental events. Any variation in the repertoire of available PRRs, in receptor-mediated signaling events, or in the underlying phenotype of an innate immune cell must alter the initial recognition or response to a pathogen and drive early specification of host–pathogen interactions. Such variation is evidenced by recent descriptions of a number of functionally distinct macrophage subsets that can be broadly categorized in terms of ontogeny (35), homeostatic role (68), or maturation status (911). This led us to ask whether there is any such thing as a “typical” innate immune cell or a common “ground state.”

Given the global molecular-profiling resources at our disposal, it should be possible to describe this “ground state” or, alternatively, the different states that underlie a spectrum of innate phenotypes. This includes assessment of the ground state of a circulating monocyte, which has largely been addressed in the context of the CD14/CD16 paradigm (12), or perturbations associated with different pathologies (13). However, if circulating monocyte phenotypes can be influenced by systemic or local factors or even set during myelopoiesis, then it is possible that there is no absolute or typical ground state. This review assesses the concept of ground state in monocytes and macrophages and evaluates a role for chromatin remodeling or epigenetic status in regulating this process.

Macrophages sit along a highly dynamic phenotypic spectrum that has inflammatory (M1) and alternatively activated (M2) states at its extremes (9). IFN-γ is the archetypal activator of classical M1 macrophages, acting via JAK signaling to the transcriptional activator STAT1 (14). In human monocyte–derived macrophages, IFN-γ drives histone acetylation associated with the promoters and enhancers of IFN target genes (14). This produces a chromatin state that is more permissive of transcription factor binding and transcriptional programs that are more stable in the IFN-γ–treated state, resulting in enhanced responsiveness to TLR signaling. M2 macrophages are also the result of a JAK-STAT–signaling program. In mice, IL-4/JAK/STAT6 restricts proinflammatory cytokines and promotes profibrotic phenotypes (15). Variations in the M2 phenotype were shown for mouse macrophages primed with IL-10 or IL-13 (reviewed in Ref. 16), as well as human monocytes differentiated to M2-like macrophages by CSF-1 or IL-3–4 signaling via CSF1R (17). Many of the immunosuppressive aspects of the M2 phenotype are also seen in tumor-associated macrophages (reviewed in Ref. 18), but the diversity of tumor microenvironments and the consequent functional diversity in tumor-associated macrophage subsets suggest that there are many ways to polarize macrophage phenotypes.

The induction of a macrophage-transcriptional program is associated with changes in the histone code, via recruitment of Jumonji domain containing-3 (JMJD3) to the promoters of inducible genes. JMJD3 is a demethylase that converts the repressive chromatin mark of histone H3K27 trimethylation to transcriptionally active H3K27 monomethylation (Fig. 1) (19). JMJD3 activity is necessary for an M2 phenotype (20, 21) but is only restricted to M2 genes under M2-differentiation conditions. Indeed, it is both a target of LPS-TLR4 signaling (transcriptionally induced in response to TLR4 activation) and a regulator of TLR signaling, because it modulates H3K27 methylation at many LPS-inducible promoters (19, 22). Although additional factors must be at play to specify the recruitment of JMJD3 to the M1 or M2 gene network, the specification of these networks requires JMJD3-dependent chromatin modifications that drive long-term transcriptional programs.

FIGURE 1.

Schematic representation of an immune gene in the context of closed (upper panel) or open (lower panel) chromatin. Compacted DNA is represented by the close association of nucleosomes, represented by blue histones wrapped with yellow DNA; it may be associated with DNA CpG methylation (red circles). Arrow indicates direction of transcription. Red “X” indicates silencing of transcription. Closed chromatin is associated with loss of acetylation (yellow rectangles) on histone H4 tails and gain in trimethylation (triple red hexagons) on histone H3 tails. Open DNA is represented by the loose association of nucleosomes and usually is associated with no DNA methylation (open circles). Open chromatin is associated with gain of acetylation (yellow rectangles) on histone H3 and H4 tails trimethylation becoming monomethylation (red hexagons) on histone H3 tails. Bmal1, brain and muscle ARNT-like protein; DNMT, DNA methyltransferase; HAT, histone acetyltransferase; HDAC, histone deacetylase; NCOR, nuclear receptor corepressor; POL II, RNA polymerase II; TET2, Tet methylcytosine dioxygenase 2; TF, transcription factor.

FIGURE 1.

Schematic representation of an immune gene in the context of closed (upper panel) or open (lower panel) chromatin. Compacted DNA is represented by the close association of nucleosomes, represented by blue histones wrapped with yellow DNA; it may be associated with DNA CpG methylation (red circles). Arrow indicates direction of transcription. Red “X” indicates silencing of transcription. Closed chromatin is associated with loss of acetylation (yellow rectangles) on histone H4 tails and gain in trimethylation (triple red hexagons) on histone H3 tails. Open DNA is represented by the loose association of nucleosomes and usually is associated with no DNA methylation (open circles). Open chromatin is associated with gain of acetylation (yellow rectangles) on histone H3 and H4 tails trimethylation becoming monomethylation (red hexagons) on histone H3 tails. Bmal1, brain and muscle ARNT-like protein; DNMT, DNA methyltransferase; HAT, histone acetyltransferase; HDAC, histone deacetylase; NCOR, nuclear receptor corepressor; POL II, RNA polymerase II; TET2, Tet methylcytosine dioxygenase 2; TF, transcription factor.

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Even transient events can impose long-term transcriptional changes with concomitant phenotypic consequences: tolerance originally was considered a transient period during which macrophages are temporarily refractory to restimulation with the same pathogenic ligand (23). In mouse, the majority of genes suppressed during LPS tolerance are targets of the p50 subunit of NF-κB, which drives remodeling of transcriptional complexes on the promoters of inflammatory genes by recruiting histone deacetylases HDAC3 and HDAC4, as well as the nuclear corepressor (Fig. 1) (24). This forms a repressive complex that can be reset to allow reactivation of the inflammatory program after a period of recovery. Tolerance is not as transient as once thought: global transcriptome and histone profiling of LPS tolerance in mouse bone marrow–derived macrophages demonstrated some longer-term effects (25, 26). Even after 4 d of recovery, LPS tolerance led to long-term loss of IL-10 and costimulatory molecules CD80 and CD86, as well as upregulation of a number of chemokine receptors. It is not yet clear whether additional chromatin modifications are associated with these longer-term changes in the tolerance-recovered macrophage. The levels of the p50 subunit remain high (24), but genes that do not reset to pre-LPS levels appear to be regulated in a p50-independent manner (25), and histone marks classically associated with actively transcribed genes can be found at the tolerance-resistant loci (26).

Nucleosome remodeling is considered to be a dynamic modifier of chromatin state. In contrast, DNA methylation is an epigenetic event generally considered to be mitotically inherited and is associated with chromatin compacting and gene silencing. The hierarchical model of differentiation expects progressive silencing of all but lineage-restricted genes, and this is consistent with increasing genome-wide DNA methylation acquired during hematopoiesis. Maps of DNA methylation during mouse hematopoiesis illustrate the sequential restriction of gene programs to lineage-specific expression networks (27); these observations have been recapitulated to some degree in comparisons of in vitro–differentiated human myeloid cells and lymphocytes with progenitor cells (28). The regulatory elements of expressed genes correspondingly demonstrate extensive hypomethylation, which expands into the transcribed region of each gene (28, 29). Even within the mature circulating myeloid lineage, a genome-wide study on human blood cells demonstrated that DNA methylation between mononuclear cells and granulocytes differs on average by 22%, mainly impacting a subset of 300 genes involved in immune function (30). Intriguingly, loss of maintenance DNA methyltransferase Dnmt1 in mouse leads to aberrant maturation of B cell and T cell subsets but less so myeloid-restricted cells (31, 32). However, mature myeloid cells do not entirely fit a typical developmental model of progressive epigenetic silencing: human monocytes are remarkably fluid in epigenetic terms, given observations that loss of methylation occurs during differentiation to macrophages, dendritic cells (33), or osteoclasts, in a TET2-dependent manner (Fig. 1) (34). Polarization of both mouse and human macrophages requires global loss of DNA methylation, as well as nucleosome remodeling at promoters and enhancers, to reactivate genes that would be otherwise silent.

These observations underline the importance of understanding the epigenetic landscape when considering the phenotypic ground state of monocyte subsets or monocyte-derived cells. However, the majority of studies on macrophage chromatin used human monocyte–derived or mouse bone marrow–derived cells differentiated ex vivo. Very little is known about the chromatin of tissue macrophages, which differentiate in situ as part of the development of that tissue (35) and which have important homeostatic functions in addition to their roles in innate immune surveillance (35).

Tissue macrophages exemplify the concept that the baseline state of myeloid cells is functionally variable. The recent availability of atlas projects, which systematically profile the gene expression of mouse tissue-resident macrophages, provided unprecedented resolution on these highly contextual ground states (6). These reveal that expression of PRRs is highly variable across mouse tissue subsets. For example, C-type lectin receptor family members have discrete patterns of expression in different tissues: Clec4d (Mcl) expression is most common in unstimulated mouse peritoneal and lung macrophages, whereas Clec4e (Mincle) is predominantly expressed by recruited inflammatory macrophages and neutrophils. This pattern may be advantageous given the pathogens that they commonly recognize: Clec4e and Clec4d are important in recognizing and phagocytizing Candida albicans and Mycobacterium tuberculosis (36, 37), but Clec4e seems to be more important during secondary infections (38). Likewise, Clec9a expression is restricted to splenic macrophages, where it has an essential role in cross-presenting Ag to T cells (39, 40). This suggests that these restricted patterns of PRR expression have important functional roles.

Tissue macrophages are also regulated by environmental cues, and this is evidenced by the correlations emerging among gut microbiota, immune responsiveness of resident and infiltrating macrophages, and underlying disease phenotypes, such as colitis. For example, alteration in commensal bacteria populations is associated with inflammatory bowel disease in humans and enhanced cellular responses to dextran sodium sulfate–induced colitis in germ-free mice (41, 42). Commensal bacteria in the gut participate in synthesis and absorption of a variety of nutrients and metabolites, including bile acids, lipids, short-chain fatty acids, and vitamins, which modulate immune functions at several levels. Some of these microbial metabolites bind to PRRs, such as Dectin-1 (43) and GPR43 (41), to downregulate inflammatory signaling. Other PRRs, including TLR1, TLR3, and TLR4, are not expressed in human intestinal macrophages (44). In contrast, loss of related receptor Tlr2 in mouse intestinal macrophages actually worsens inflammatory outcomes during experimental colitis (45), indicating that a restricted TLR-signaling network is itself important in maintaining healthy intestinal homeostasis. Interestingly, “training” mouse or human hematopoietic progenitor cells by exposing them to a Tlr2 ligand impacts on the responsiveness of subsequently differentiated monocytes and macrophages by reducing, but not ablating, the inflammatory cytokine production (46). It is not known whether the same principle is at play in tissue macrophages, which are derived from progenitors also resident in that tissue. Mouse atlas projects (6) infer that differential expression of PRR is symptomatic of a wider-ranging tissue-specific transcriptional network; however, further studies that include epigenetic correlates are needed to understand how these phenotypic states are initiated and maintained, particularly in barrier tissues like mucosa, lung, and gut.

Just as the tissue atlas projects in mouse have yielded invaluable information on the transcriptional networks of mature macrophages, the question of a common ground state for circulating immune cells can be addressed by examining their core transcriptional networks and how these vary across different individuals or with age or health status. Human monocytes, CD14+/− CD16+/− monocyte subsets, and monocyte-derived cell types have been profiled under a wide range of pathogenic and inflammatory conditions: more than 8000 human peripheral blood monocyte datasets are available in the Gene Expression Omnibus alone (47). Integrating these data to identify transcriptional phenotypes is a major bioinformatics challenge, particularly because most of these datasets profile a small number of donors under relatively few conditions. Two exemplar studies took parallel approaches and used PBMCs to demonstrate that leukocyte expression can be summarized successfully by a number of distinct transcriptional states that are reproducible across many datasets (13, 48).

The first of the aforementioned studies examined expression patterns in individual datasets, across >200 independently derived PBMC transcriptome studies (13). The investigators looked for genes whose dynamic expression profiles were recurrent in at least six disease conditions. Clusters of genes that shared the same expression pattern were summarized into 28 expression “modules,” and these were reported to define eight disease conditions. It is obvious that a large number of genes would be differentially expressed between PBMCs taken from healthy individuals and from patients with an inflammatory disease; however, identifying a coherent or functional pattern from these genes is less obvious. The usefulness of the Chaussabel modular approach derives from its identification of coordinate patterns that arise again and again in different diseases and in different individuals, which are likely to be functionally related, and so are descriptive of common inflammatory processes.

The second study addressed the same principle of shared-expression modules, testing and recapitulating the 28 modules identified in the study by Chaussabel et al. (13), this time in PBMCs from healthy individuals from a U.S. population (48), as well as subjects from Morocco (49) and Australia (50). Rather than clustering individual gene profiles, the investigators used a modified principal-component analysis to identify nine expression axes. Each axis is the composite of many genes, collapsed into a single mathematical vector that identifies variation between the samples. The axes are ranked, such that the first explains the largest proportion of variation in the data. The expression axes themselves can be examined across different datasets using a regression-correlation approach. Although the absolute ranking of each axis changed between populations, the composition and behavior of genes within the axes remained highly correlated across all of the datasets examined.

All of these studies demonstrated that, even in healthy individuals, the baseline-expression states of peripheral WBCs sit across complex axes of gene expression variation that are highly reproducible across internationally diverse populations, as well as between mother and neonate pairs (49, 50). PBMCs are commonly used for large-scale studies for pragmatic reasons: the RNA is stabilized in the blood collection tubes, removing the option of isolating CD14+ monocytes. These studies profile a mixture of peripheral blood cells and so may reflect differences in the proportion of granulocytes, monocytes, and lymphocytes that make up each blood sample, rather than a change in steady-state gene expression per se. Two of the nine expression axes (axes 1 and 5) were highly correlated with total neutrophil counts, as well as the lymphocyte/neutrophil ratio of the collected blood samples (48). Nevertheless, the investigators of all four of the PBMC studies noted a high degree of stability in the proportion of monocytes and lymphocytes, which made up the majority of cells in each sample. Although an imperfect surrogate for monocyte expression, we can assume that changes in the dominant gene-expression profiles of these cells contribute to the blood-expression axes. Most axes included pan-cellular inflammatory markers, and axis 5 was also notable because it represented the TLR pathway, and relative expression of the receptors was highly correlated with expression of their downstream-signaling effectors. Although these studies are consistent with the concept of a definable circulating monocyte expression state, more work is needed to show this definitively.

The major driver in the Moroccan and Australian neonate profiles was not health status of the mother or obvious genetic factors, but rather the postcode in which they were born, suggesting a strong environmental component (49, 50). An unrelated study of 97 infants set out to compare responsiveness of PBMCs to TLR ligands (51). Although the investigators showed predictable responsiveness to most TLR agonists, TLR7/8 activation was profoundly reduced in healthy children from South Africa (ethnicity/genotype was not provided). Regardless of country of origin, the amplitude of PRR responses showed high donor–donor variability, accounting for almost a quarter of the variation observed on the first principal component of the study. Both groups highlight that the baseline expression of PRRs and responsiveness of circulating cells to TLR agonists are surprisingly variable from donor to donor, even early in life.

The identification of these expression axes in infants suggests that the ground state phenotype of circulating cells may be heritable, and certainly genetic polymorphism was predicted to be one of the drivers of the axes of expression variation (48). Common polymorphisms associated with diseases that have known monocyte etiology largely reside in gene-regulatory elements, such as enhancers or promoters, resulting in either loss or enhanced binding of transcription factors to core inflammatory genes (12, 29, 52, 53). Several additional studies identified genomic variants that are strongly correlated with gene expression differences (expression quantitative trait locus [eQTL]), and this demonstrates an important role for genetic background in the expression state of peripheral blood cells. eQTLs are major contributors to the baseline expression of immune genes and have a significant impact on the susceptibility of an individual to a range of pathogens, such as M. tuberculosis infection. For example, in a recent study of 65 individuals, 102 eQTLs were identified in monocyte-derived dendritic cells prior to M. tuberculosis infection, and an additional 96 eQTLs were identified in infected cells, which together influenced the expression of >198 genes (54). The strength of these associations among a relatively small cohort demonstrates the large effect that these polymorphisms can have on expression phenotypes of myeloid cells. Among these were variants that were highly correlated with the secretion of inflammatory proteins, such as IL-1Ra, and likely to impact on the outcome of M. tuberculosis infection. Similar eQTLs were identified in a study of M. tuberculosis infection in human macrophages (55), and there is evidence that eQTLs identified in circulating human monocytes also reflect the capacity for lung macrophages to respond to the disease (56).

The idea that altered activation states in peripheral blood monocytes or monocyte-derived cells might provide insight into chronic conditions was demonstrated in a recent survey of human monocyte–derived macrophages responding to 28 stimuli (57). The study also exploited the idea that global patterns of gene expression can be summarized into “meta-patterns,” or expression axes. Although this was a study of ex vivo–stimulated cells, the patterns of macrophage activation were representative of in vivo chronic conditions. Specifically, the investigators also examined alveolar macrophages isolated from the lungs of smokers, nonsmokers, and donors with chronic obstructive pulmonary disease. The baseline activation state of macrophages from each group was distinct; by comparing these patterns with the macrophage-activation axes, it was possible to define these transcriptional changes in terms of the acquisition of a glucocorticoid-like module in the smoker cohort and the loss of a type-II IFN signature in the chronic obstructive pulmonary disease cohort. Taken together, these landmark transcriptional surveys demonstrate an important role for genetic, environmental, and inducible factors in dictating the ground state of circulating cells, including monocytes, and monocyte-derived cell phenotypes.

Inflammatory responsiveness reflects the sum of the entire molecular-signaling network, and considering this entire network across individual monocyte datasets is difficult to do systematically. However, evaluation from the perspective of one molecular class can provide a useful window on a more global process. The window that we chose reflected the concept that the expression of PRRs dictates the capacity of a cell to respond to pathogenic challenge. It is clear that PRRs and their downstream-signaling pathways are tightly regulated by many cues, such as the local tissue environment (58). Furthermore, systemic factors, including sunlight and vitamin D (59), depression (60), and metabolic syndrome (61), are correlated with changes in circulating innate immune phenotypes and subsequent inflammatory outcomes. These suggest a number of common variables that may impact the myeloid ground state.

Aging is often accompanied by increased susceptibility to infection (62, 63). Although this decrease in immune fitness is undoubtedly the outcome of many factors, there is evidence that the chronically altered ground state of innate cells is a major component. For example, splenic and peritoneal macrophages from aged mice express significantly decreased levels of all TLRs compared with young animals, and this is accompanied by reduced proinflammatory responses to TLR agonists (64). Similarly, the expression of TLR3 and TLR8 in human myeloid dendritic cells, as well as TLR7 expression in plasmacytoid dendritic cells, is significantly lower in older adults compared with young adults (65), and this is associated with a decreased capacity to produce antiviral cytokines.

Aging is one variable associated with major methylation changes in PBMCs. Two separate studies collectively examined >1100 individuals to show that lineage-specific methylation patterns were progressively lost in older individuals, and hypermethylation also was seen in a small number of overrepresented loci (66, 67). Interestingly, both studies reported transcription factors as the most common class of proteins silenced via hypermethylation during the aging process.

The highest incidence of some diseases, including tuberculosis, occurs in winter. Innate immune cell functions change during different seasons throughout the year: a 10-y longitudinal study in Finland demonstrated that alterations in activities of healthy human neutrophils strongly correlated with seasonal changes (68). The magnitude of adhesive activity of summer group neutrophils in response to stimulators was significantly higher than that of winter group neutrophils, and this included their bactericidal activity. These functional changes correlated with the expression pattern of CD11b/CD18, which were at their highest levels in the summer neutrophil group.

The expression of PRRs on monocytes and neutrophils also fluctuates with the seasons. A recent study of 49 donors, including a small number of donors surveyed longitudinally, revealed a surprising pattern for CLEC4E, which was reciprocally expressed between monocytes or neutrophils (69). The majority of individuals showed preferential expression of CLEC4E on monocytes, but this pattern was reversed dramatically during autumn/winter, during which time most donors expressed the protein exclusively on neutrophils. The expression of CLEC4E on monocytes altered their responsiveness to Candida albicans; CLEC4E+ monocytes were less effective at phagocytosis and clearance, but they produced a stronger cytokine response to Candida challenge. Although relatively little has been reported on the seasonality of mucosal or systemic Candida infections (70, 71), CLEC4E is also a key component of host responses to M. tuberculosis, which does have a well-documented seasonality (72, 73).

The molecular events driving seasonal variation in immune function are not well characterized. Perhaps the most promising avenue for investigation is the recent observation that proteins responsible for diurnal (daylight/nighttime) variation of the mammalian circadian clock have a profound influence on monocyte function (reviewed in Ref. 74). Peripheral blood monocytes taken from mice kept under regimented light/dark conditions express the circadian genes Nr1d1 and Dbp in a reciprocal pattern to their transcriptional regulator Bmal1 (75). Together, these genes form part of the core molecular circuitry that responds to light and season and which has adapted to the climate extremes inhabited by different populations (76). The expression of the circadian genes was associated with trafficking of peripheral blood monocytes from the bone marrow to blood and spleen, with particular impact on the availability of Ly6Chi monocytes. Bmal1 was shown to regulate this diurnal monocyte trafficking by recruiting the polycomb repressor complex 2 (PRC2) to the promoters of Ccl2, Ccl8, and S100a8, thus synchronizing their downregulation in the early hours of the morning (Fig. 1). Mice were most susceptible to the bacterial pathogen L. monocytogenes when infected first thing in the morning, and this correlated with PRC2 repression of the chemokines and poor subsequent mobilization of Ly6Chi monocytes to the site of infection (75). NR1D1 (alias Rev-erb α) was described as a global transcriptional repressor of mouse macrophages, transiently silencing the enhancers of inflammatory genes (77). The importance of diurnal variation in macrophage function indicates that daylight rhythms, seasonal variation in light, and presumably other lifestyle factors that alter circadian gene expression (e.g., jetlag and shift work) fundamentally impact monocyte functions by altering the chromatin state of key inflammatory genes.

Circulating glucose and insulin levels have acute effects on PBMC receptor levels, with high glucose increasing TLR1, TLR2, and TLR4 expression (78). High glucose is a proinflammatory stressor, driving epigenetic changes in monocytes that result in increased expression of NF-κB, as well as facilitated binding of NF-κB subunits to the promoters of the inflammatory cytokines TNF and IL6 (79, 80). These epigenetic changes include increased histone acetyltransferase activity, with a coordinate reduction in histone deacetylase 2, which, under high-glucose conditions, enhance binding of NF-κB to its target genes (81).

Large fluxes in circulating glucose/insulin lead to chronic changes; the transcriptomes of monocytes from individuals with type I diabetes have characteristically perturbed profiles that are predictive of clinical features, including the initial severity and trajectory of the disease (82, 83). The increased expression of inflammatory mediators, such as TNF, is coincident with decreased expression of PRRs, including AIM2, TLR4, TLR5 and TLR11, IFI16, NLR family member X, and NLR family CARD domain containing 4, although not all receptors were commonly lost in all patients or in all studies (82, 84).

Increased TLR2, TLR4, and TLR5 expression was observed in peripheral blood monocytes, synovial fluid, and synovial tissue macrophages of individuals with chronic inflammatory disease, such as rheumatoid arthritis, and the expression of these receptors was strongly correlated with levels of TNF (85). These examples emphasize the link between the baseline inflammatory potential of circulating innate immune cells and chronic metabolic stressors and suggest that better understanding of circulating myeloid ground states might improve clinical strategies in the management of chronic diseases.

The concept of nonspecific effectors of innate immunity has helped us to understand the molecular events of pathogen recognition in the past decades. This model has evolved to include monocyte and macrophage phenotypes that are preset by the local environment, which include the trained immunity of low-dose exposure to pathogen, tolerance resulting from sustained or high-dose infectious challenge, or cells that are polarized toward highly inflammatory or reparative phenotypes. The notion of a universal, nonspecific innate responder is further challenged by the wide adoption of high-throughput genomic studies, which reveal the lack of any common ground state of tissues or circulating myeloid cells. Rather, the inflammatory potential of circulating monocytes is dependent on phenotypes that can be fundamentally altered by environmental factors, such as daylight or metabolic state, stress, or even postcode. Multiple possible ground states in the general population are characterized by a spectrum of well-defined expression axes, which collectively describe the availability of PRRs, transcription factors, and their signaling networks and are influenced by donor-dependent genetic polymorphisms, as well as environmentally driven chromatin modifications.

Two of the major gaps in current practice are 1) understanding common mechanisms leading to variation in innate immune networks across the healthy population, in longitudinal studies, and in disease cohorts and 2) performing a broader survey of the chromatin changes determined during the differentiation of myeloid cells and the influence of clinical variables, lifestyle, and environmental factors on the myeloid epigenome and how this impacts establishing a circulating ground state. This interface among the developmental program of gene expression, genetics, and environment provides an enriched model with which to understand the role of innate immune cells in host defense and chronic disease.

We thank Suzanne Butcher for critical reading of this manuscript and Silvia Manzanero for technical assistance with producing the figure.

This work was supported by Australian National Health and Medical Research Council Project Grant APP1057846 (to C.A.W.). C.A.W. is the recipient of a Queensland Government Smart Futures Fellowship and receives funding from the University of Glasgow.

Abbreviations used in this article:

eQTL

expression quantitative trait locus

JMJD3

Jumonji domain containing-3

M1

inflammatory

M2

alternatively activated

PRC2

polycomb repressor complex 2

PRR

pattern recognition receptor.

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The authors have no financial conflicts of interest.