Introduction

Inflammation is an evolutionarily conserved body response for protecting the host from potentially lethal stresses [1]. It is often understood as a process to isolate and eliminate pathogens or other non-self or intolerant agents by immune cells [2] followed by processes that resolve inflammation, repair damaged tissues and restore homeostasis [3]. However, when the transition to tissue repair fails, inflammatory processes can persist and cause harm [4]. It is well documented that chronic inflammation, often viewed as subclinical, contributes to chronic disease processes leading to obesity, diabetes, atherosclerosis, rheumatoid arthritis and cancer [4]. In addition, inflammation in response to continuous exposure to infectious agents [5–7] and environmental toxins [8, 9] may contribute to childhood undernutrition and developmental deficits in impoverished areas of the world where poor sanitation and frequent infections are common.

An observable characteristic of inflammation is an increase or decrease in the release and concentration of certain proteins in the bloodstream, a process regarded as an acute phase reaction, although it can occur in response to either acute or chronic inflammatory stress [1]. At least 50 acute phase proteins (APP) are known to increase or decrease by at least 25% in humans, a commonly used cut-off, from their baseline concentrations during inflammation [10, 11]. This quantitative alteration is mainly regulated by inflammatory mediators that induce reactions within innate and adaptive immune, neuroendocrine, vascular endothelial, hematopoietic, metabolic, and other defense and repair systems [10]. Due to these systemic effects, APPs are widely used as clinical diagnostic and prognostic indicators of disease processes [12]. Also, APPs are often recommended for use in population studies as correction factors for assessing status with respect to micronutrients, whose indicator concentrations may decrease (e.g., serum retinol for vitamin A) or rise (e.g, serum ferritin for iron) with inflammation [13–15]. Although large in number, only a few APP, primarily α-1-acid glycoprotein (AGP) and C-reactive protein (CRP), are typically assessed in population studies as indicators of inflammation [15]. This is because their responses and prognostic values are different and well-defined, with concentrations that reliably increase during infection, responding to numerous systemic infections and other pathological conditions, and decrease with resolution [10, 14, 16]. Yet this nearly sole reliance on AGP and CRP may also, in part, be due to an incomplete understanding of the many and varied molecular mediators and responders to inflammation, a general inability to measure and interpret their responses to inflammatory stresses, limited resources to quantify multiple APPs, and a general lack of awareness in the public health research community of the highly varied dynamics of inflammation that coexist in populations.

The unbiased approach of plasma proteomics offers a unique opportunity to discover, quantify and explore the utility of a wider array of proteins that respond to, initiate, maintain and resolve inflammation. In a given population, all phases of the inflammatory response are likely to be present, highlighting the potential utility of accessing and interpreting a larger inventory of biomarkers with which to understand homeostatic mechanisms, disease processes, types of inflammation and the range of inflammatory exposures in an environment.

In this population study of 6–8 year old Nepalese children [17], we rely primarily on the circulating concentration of AGP to define inflammation as a continuous measure. AGP, or orosomucoid (ORM), is present in plasma as a mixture of ORM1 and ORM2 each of which is encoded by two tandomly arranged genes, ORM1 and ORM2 [18]. Because the concentration of AGP slowly rises and remains elevated during recovery or convalescence, AGP may be considered more sensitive in detecting chronic and subclinical inflammation in populations than CRP, which tends to react, spike and resolve more quickly, and thus be less often detected in prevalence surveys [14]. We refer to the entire set of plasma proteins that definitively and quantitatively co-vary with AGP, as a “population plasma inflammasome” whose members may include but extend beyond classical acute phase proteins, contain proteins of hepatic origin as well as those secreted or leaked from extra-hepatic tissues [19, 20], and include proteins involved in constitutive and induced homeostatic immune, coagulative and repair processes associated with inflammation. We verify the reliability of this set of inflammatory proteins by repeating the same analysis using CRP, and evaluating overlap. We distinguish the compound term, population plasma inflammasome, from “inflammasome”, used to describe an intracellular multiprotein complex that is responsible for activating the processing of pro-inflammatory cytokines [21]. While limited animal and human subject experimentations have described an endotoxin-induced plasma inflammasome and compilations of inflammatory plasma proteins from databases for clinical use exist in the literature [22–24], definition of a human population plasma inflammasome remains incomplete.

In this population sample [17], 31% and 6% of children exhibited elevated plasma concentrations of AGP and CRP above conventional, clinical disease thresholds of 1g/L and 5 mg/L, respectively, reflecting a population affected by chronic inflammation [13] but not acutely ill, providing an opportunity to explore markers of low-grade (“subclinical”) inflammation that may nonetheless be useful for population assessment [25]. We hypothesized the existence of a quantifiable population plasma inflammasome, defined as a suite of plasma proteins tracking AGP with high confidence, which we verified by also evaluating their concordance of association with plasma CRP concentrations.

Materials and Methods

Results

Study participant characteristics

Demographic, nutritional, and health characteristics of study children (Table 1) were similar to children in the original, larger follow-up cohort [28]. Children were undernourished, compared to the WHO reference population, reflected by prevalence rates of 40%, 15%, and 50% for stunting, thinness, and underweight. More than half and approximately 30% of children consumed dairy food and dark green leafy vegetables equal to or greater than 3 times in the past week, respectively, but meat, fish, and eggs were less frequently consumed by children. Approximately 8% of children reported at least one episode of fever in the past week, but the prevalence of other symptoms was low (<5%). Fourteen percent of children reported any symptoms of fever, diarrhea, productive cough, or rapid breathing in the past week. Median (interquartile range) of plasma AGP and CRP concentrations were 0.84 (0.70, 1.05) g/L and 0.28 (0.13, 0.78), with 30% and 6% of children having an elevated AGP concentration (>1 g/L) and CRP (>5 mg/L) concentrations, respectively.

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Table 1. Demographic, nutritional, and health characteristics of 6–8 year old children in rural Nepal (n = 500).^a

https://doi.org/10.1371/journal.pone.0144279.t001

Plasma proteins associated with AGP

A total of 3,933 proteins were identified and quantified among 72 iTRAQ experiments required to analyze the 500 child plasma samples, of which 982 proteins were quantified in >10% of all samples (n>50). Ninety-nine proteins (~10% of all proteins adequately quantified) significantly co-varied with plasma AGP passing a Bonferroni corrected significance level, of which 41 and 58 proteins were positively and negatively associated with AGP, respectively. Among proteins positively associated with AGP, TNFAIP3 interacting protein 1 (Gene symbol: TNIP1) (P = 7.6x10^-112) and orosomucoid 1 (ORM1) (P = 4.6x10^-101) showed the strongest associations, followed by orosomucoid 2 (ORM2) (P = 3.1x10^-54) (Table 2). Lumican (LUM) (P = 9.1x10^-27) and cartilage oligomeric matrix protein (COMP) (P = 5.7x10^-23) were most strongly associated among negative correlates (Table 3). A volcano plot shows distinct patterns within the population plasma inflammasome (Fig 1A–1C). Specifically, the percent change in AGP (95% confidence intervals) and strength of significance of association varied more widely within the group of positively than negatively associated proteins. A 86.6 (76.2, 97.6)% and 105.3 (87.4, 124.8)% increase in AGP concentration was associated with a 100% (two-fold) increase in relative abundance of ORM1 and ORM2, respectively (Fig 1C). A comparable 73~105% increase in AGP was also associated with a 100% increase in complement components 2, 5, and 9 (C2/5/9) and complement factors F and I (CFB and CFI). On the other hand, a smaller 15~18% increase in AGP was associated with a 2-fold rise in other acute phase proteins such as CRP, haptoglobin (HP), and serum amyloid A 1 and 2 (SAA1/2) (Fig 1C). Overall, a narrower range in reduction in AGP, 20~40%, was associated with a 2-fold increase in the relative abundance of 46 out of the 58 negatively associated proteins (Fig 1A). A total of 206 plasma proteins passed a false discovery significance threshold of q<0.01 (~20% of all analyzed), representing a larger plasma proteome that appears to covary with plasma AGP, as listed in Supporting Information (S1 and S2 Tables).

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Fig 1. Volcano plot of plasma proteins associated with plasma α-1-acid glycoprotein (AGP) in 6–8 year old children in rural Nepal.

Plot (A) and (C) are enlarged rectangles in plot (B). (A) Plasma proteins negatively associated with AGP, presented by gene symbol (n = 58); (B) Plasma proteins associated with AGP were colored in red and blue (n = 99); (C) Plasma proteins positively associated with AGP, presented by gene symbol (n = 41). x- and y-axes are logarithmic.

https://doi.org/10.1371/journal.pone.0144279.g001

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Table 2. Plasma proteins positively associated with plasma α-1-acid glycoprotein (AGP) in 6–8 year old children in rural Nepal, ordered by P.^a

https://doi.org/10.1371/journal.pone.0144279.t002

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Table 3. Plasma proteins negatively associated with plasma alpha-1-acid glycoprotein (AGP) in 6–8 year old children in rural Nepal, ordered by P.^a

https://doi.org/10.1371/journal.pone.0144279.t003

Separate verification analyses identified 41 (S3 Table) and 40 (S4 Table) proteins that were positively and negatively associated with CRP, respectively, passing the same Bonferroni corrected significance level as applied to the AGP analysis, of which 72 proteins were associated with both AGP and CRP. The 9 “non-overlapping” CRP-associated proteins (marked in red in S3 and S4 Tables) were still associated with AGP but less significantly (all P < 0.003). In addition, 27 proteins were differentially abundant between children with at least one episode of any morbidity symptom (fever, diarrhea, productive cough or rapid breathing) and children without any symptoms, passing a false discovery significance threshold of q <0.01 (S5 Table). All but one of the 27 proteins associated with morbidity symptoms were strongly correlated with AGP.

We anticipated that proteins positively and negatively associated with AGP would also be correlated with each other. The correlation matrix, shown in Fig 2A, shows that plasma proteins positively associated with AGP were more highly correlated with each other (i.e., darker blue cells) than plasma proteins negatively associated with AGP (i.e., lighter blue cells). There were 83 and 5 protein-pairs, respectively, whose correlation coefficients (r) were greater than 0.6 within the positive and negative population plasma inflammasomes. Within the former, high correlations were observed among pairs involving ORM1-TNIP1-MAP3K14-COG3-ACTR5-NOM1 (all r >0.80), especially between LBP-ELL3 (r = 0.92), and LRG1-EVI5 (r = 0.86).

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Fig 2. Correlation matrix and bi-plots from principal components (PC) analysis using plasma proteins associated with α-1-acid glycoprotein in 6–8 year old children in rural Nepal.

(A) Bottom-triangle is the correlation matrix of plasma proteins positively associated with AGP (Group1). Upper-triangle is the correlation matrix of plasma protein negatively associated with AGP (Group 2 & 3). (B and C) Bi-plot was constructed by the first three principle components. Color depicts representative tissue origins or subcellular localization of proteins: black-intracellular space; green-hepatic origin and secreted into plasma; red-extracellular matrix; blue-extracellular matrix membrane binding. Proteins with PC1 less than 0 were assigned into group 1, proteins with PC1 and PC2 greater than 0 were assigned into group 2, and proteins with PC1 greater than 0 and PC2 less than 0 were assigned into group 3 (4 proteins were not included due to missing values and lack of information about subcellular localization).

https://doi.org/10.1371/journal.pone.0144279.g002

As expected, principal components (PC) analysis divided the population plasma inflammasome into proteins that were positively (PC1<0, referred to as Group 1) and negatively associated with AGP (PC1>0). (Fig 2B). However, two subgroups further emerged among proteins negatively associated with AGP. PC2 partitioned negatively associated proteins into two groups (Group 2 vs. Group 3) and PC3 separated two proteins (S100A8 and S100A9) from the rest of the proteins (Fig 2C). To better understand the unexpected partitioning among plasma proteins negatively correlated with AGP, we investigated cellular localization of the proteins. Proteins in PC2 are known to be mainly produced by the liver and secreted into the bloodstream (green) and proteins in PC3 are largely produced by extra-hepatic tissues and localized in extracellular matrix regions (red and blue).

Localization and functions of plasma proteins associated AGP

Proteins associated with AGP are summarized by their most often described cellular localization and biological or molecular functions in Table 4. More than half of the proteins positively associated with AGP were primarily extracellular, secreted into circulation from the liver, and known to promote or regulate innate immune responses and inhibit oxidative activity. These included ORM1/2, CRP, SAA 1/2/4, bacterial lipopolysaccharide binding protein (LBP), LRG1 (a protein involved in granulocyte differentiation), components of the complement cascade, free hemoglobin scavengers, a copper-carrier, and several protease inhibitors. Other positively associated proteins are mainly localized in the membrane or intracellular space and involved in diverse functions, including leukocyte recruitment and trafficking, cell signaling, transcription, translation, DNA repair, protein methylation, modulation of cell cycle, cytokinesis and cytoskeleton, and endoplasmic reticulum-Golgi vesicle transport.

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Table 4. Cellular localizati4on and molecular/biological functions of plasma proteins associated with α-1-acid glycoprotein (AGP) in 6–8 year old children in rural Nepal.^a

https://doi.org/10.1371/journal.pone.0144279.t004

About half of the proteins negatively correlated with AGP (i.e., that decline in relative abundance with inflammation) are also considered hepatic proteins released into the bloodstream, but more involved in transport and metabolism of nutrients and small molecules (e.g., RBP4 and TTR for vitamin A; apolipoproteins A1/A2/H/M for lipid or cholesterol transport and metabolism; and AHSG for calcium and phosphate metabolism), sex hormone and growth factor binding (e.g., SHBG and IGFALS) or serine endopeptidase or proteinase inhibition in regulating blood coagulation and complement cascades, among other roles. Other negative correlates are physical constituents of the extracellular matrix (ECM), including collagens [e.g, collagen types VI α1 and 3 (COL6A1, COL6A3)], glycoproteins, glucosaminoglycans and bone matrix proteins. Proteins known to facilitate interaction between cells and ECM are aminoproteinases/peptidases (e.g. PCOLCE and PEPD), protease inhibitors (e.g. TIMP2) and numerous cell-cell or cell-matrix adhesion molecules (e.g. CDH5 and ANTRX1).

Discussion

This study provides evidence of a population plasma inflammasome, defined in relation to the continuous distribution of an established biomarker of inflammation, α-1-acid glycoprotein. We virtually ensured identification of nearly 100 plasma proteins associated with AGP by applying a stringent family-wise error rate threshold of 0.1%. Approximately three-quarters of the same proteins were similarly correlated with a second acute phase reactant in plasma, CRP. Study children in rural Nepal were undernourished, similar to many child populations in rural Asia, but were active and not acutely ill, with only 14% reporting any illness symptom in the previous week. As such, the set of proteins observed to covary with AGP can be inferred to reflect homeostatic control of inflammation within the environment of this typical South Asian rural setting.

Positive plasma inflammasome proteins exhibited stronger associations with AGP and greater variation in their degree of change per unit difference in AGP concentration than negatively associated proteins, possibly reflecting higher metabolic priority and functional specificity. In addition to established acute phase proteins, our quantitative proteomics approach identified numerous intracellular signaling, membrane-bound, and extracellular matrix molecules not widely regarded as acute phase reactants, appearing to reflect a systemic repertoire of proteins that respond to inflammation.

Acute phase proteins, complement components, protease inhibitors and transport proteins with anti-oxidant activity positively covaried with plasma AGP, in accordance with their expected roles in responding to stress [1]. Many of these biomarkers are produced in the liver and secreted into plasma [10]. As AGP abundance in plasma is attributable to expression of homologous ORM1 (AGP1) and ORM2 (AGP2) genes [42], ORM1 and ORM2 were expected, and observed, to be among the strongest correlates of AGP (measured by radial immunodiffusion), offering evidence that mass spectrometry is a valid method to detect and quantify relative protein abundance. LRG1, HP, SERPINA3, CRP, SAA1, C9, and LBP were positively associated with AGP (all P <1.0x10^-25), suggesting these proteins increase in circulation during inflammation [10]. Substantial variation in the strength of association with AGP likely reflects wide differences in expression across acute and chronic phase proteins [43–45]. It is likely that rises in complement components, LRG1 and SERPINA3 reflect a persistent inflammation that accompanies a modest elevation in AGP where exposure to parasites, bacteria [46–48] and environmental toxins, such as aflatoxin and arsenic, are common [49, 50]. Positively associated proteins we observed are known to largely be involved in immune activation (e.g., CRP, SAA, LBP, and complement components), proteolytic attack processes (SERPINA3, SERPING1, and SEPRIND1), and transport of pro-oxidative metabolites (CP and HP) [44]. ORM1/2 and LRG1 are involved in immunomodulation and granulocyte differentiation, respectively, although their molecular roles have not been fully elucidated [51–53]. Collectively, our results suggest that hepatic-driven proteins that positively covary with inflammation are involved in host defense.

Fourteen of 41 positive correlates of AGP are intracellular proteins whose larger numbers of missing values (Table 2) support the notion that these proteins may be low in abundance, and leaked or secreted from tissues as part of normal metabolism and tissue maintenance. The strongest positive correlate (P = 7.6x10^-112), sharing a nearly 1:1 association with AGP, was TNIP1, suggesting their co-regulation during inflammation, although no study to our knowledge has drawn this direct metabolic linkage. TNIP1 regulates inflammation by inhibiting cell signal transduction such as in the NF-kappa-B activation pathway [54]. However, unknown extracellular functions of TNIP1 leave its positive association with AGP in plasma unexplained. A 30~60% increase in AGP concentration was associated with a 100% increase in intracellular proteins involved in signal transduction, and protein transcription, translation, maturation and secretion. High correlations between intracellular proteins and circulating ORM1, LBP, and LRG1 suggest their abundance in plasma could reflect biosynthesis of inflammatory mediators [55], or act themselves as acute phase proteins.

Among proteins negatively correlated with plasma AGP, about half are known to transport and regulate bioavailability of nutrients and hormones. Correlations among these proteins were negligible, suggesting independent regulation and metabolic pathways, while still being susceptible to hepatic-directed reduction during inflammation [56]. Some negative correlates are components of lipoprotein particles, involved in anti-inflammation (APOA1/2), antioxidant functions (PON1, PON3, and PCYOX1) and reverse cholesterol transport (PLTP, CLU and LCAT) (all P <1.0x10^-4). These observations coupled with those of increased abundance in pro-inflammatory serum amyloid A (SAAs) apoliporoteins with AGP support considerable alterations in plasma lipoprotein composition during homeostatic regulation of inflammation [57]. RBP4, TTR, AHSG, and APOA1/2 are well-known negative acute phase proteins [10] that are consistent with known redistributions of vitamin A, calcium, phosphate and lipids during inflammation [57–60].

In our analysis, a small decrement in AGP per two-fold increment in relative protein abundance identifies proteins that are likely to decrease markedly during acute inflammation. The smallest decrease in AGP (20–24%) was observed with a two-fold rise in sex hormone binding globulin (SHBG), insulin-like growth factor (IGF) acid labile subunit and IGF binding protein (BP) 3 (all P <1.0x10^-5), consistent with expected reductions in insulin-like growth factor 1 and androgens during inflammation [10, 61]. IGFALS and IGFBP3 form a ternary complex with most plasma IGFs which regulate somatic growth and development [62, 63]. SHBG binds and regulates circulating androgens and estrogens [64]. Population studies have revealed inverse associations between SHBG and inflammatory markers and adiposity-related early onset of puberty among girls [65, 66]. Observed inverse associations between AGP and hepatic proteins may reflect metabolic adaptation to altered endocrine signaling in response to inflammation.

Proteins that serve as components or regulators of the extracellular matrix (ECM) were negatively associated with inflammation [67]. Our PCA results revealed that variance in the abundance of these proteins differed from those of hepatic origin, possibly due to differences in intravascular concentration between classic plasma and extravascular proteins. Lumican (LUM), cartilage oligomeric matrix protein (COMP), tetranectin (CLEC3B), osteomodulin (OMD), and collagen α-1 and -3 type VI (COL6A1/3) are enriched in cartilage, bone matrix, skeletal muscle and adipose tissues [68–72]. Beyond structural and functional components of ECM, many cell surface molecules or enzymatic proteins are involved in penetrating the vascular endothelial cells, regulation of pericellular proteolysis of ECM, and cell migration into inflamed tissues, critical to tissue repair and turnover [73–81]. Our results suggest that proteins that maintain integrity of the ECM are down-regulated, possibly reflecting metabolic rebalancing between host defense and healing mechanisms [82]. These proteins are particularly important in chronic inflammatory conditions that commonly accompany degradation of connective tissue [83–86].

Our findings corroborate those in -omics studies in animals that have examined changes in gene or protein expression levels of acute phase proteins during inflammation. Yoo et al. showed in mice that 898 out of 8,551 protein-encoding genes (~7%) in the hepatic transcriptome were altered, equally up and down, by endotoxin-induced inflammation [87]. Similarly, we observed that half of the population plasma inflammasome was primarily hepatic in origin, equally divided across positive and negative correlates of AGP, and possibly reflecting a need to maintain protein equilibria in the vascular compartment [44]. Kelly-Spratt et al. reported that a third of ~500 plasma proteins detected in mice increased or decreased by more than 1.25 fold in response to induced-inflammation [22]. We observed that a large fraction (~20%) of our measured plasma proteome covaried with inflammation, at a false discovery rate below 1% (S1 and S2 Tables). The study also showed that induced-inflammation reduced the abundance of proteins involved in ECM and collagen network remodeling [22], which were also similarly observed in the present study.

The diversity of plasma proteins observed to be associated with AGP in this ambient population offer an unbiased view of inflammation. With this large-scale and untargeted approach, we identified potential networks of interaction and a large number of candidate biomarkers. Defining the plasma inflammasome with respect to AGP, an established index of subclinical inflammation, enabled us to identify proteins that are likely relevant to the homeostatic response to inflammation. Results of additional analyses in relation to plasma CRP concentration and children’s recent morbidity offer further support of the validity of the population plasma inflammasome indexed by AGP. While our unit of estimated protein amount, i.e., relative abundance, restricts ability to directly apply these findings, biomarkers of strongest association can be considered candidates for absolute quantification to expand the repertoire of biomarkers that reflect diverse mechanisms and possibly sources inflammation. However, with a cross-sectional design, we could not infer metabolic proximity or causality of association among proteins. We also did not have information about specific parasitic or bacterial infection or environmental toxins that could reveal greater specificity of protein associations with causal agents. We depleted, but did not completely remove, plasma samples of 6 highly abundant proteins, and the employed iTRAQ technology could not quantify low abundant cytokines and chemokines which mediate inflammation. These limitations reveal challenges of profiling a whole plasma inflammasome of a likely vast dynamic range in protein abundance. However, it may be promising to investigate and integrate less abundant proteins from different spectrums of abundance to build a more complete profile of a population plasma inflammasome. Lastly, although many proteins are involved in non-specific response to inflammation, the findings of this study will be most likely generalizable to populations living in areas where undernutrition, infections and environmental hazards are common.

Conclusions

This study provides evidence of strong association between an index biomarker of chronic inflammation and proteins of host defense, nutrient and hormonal metabolism and tissue remodeling. It is tempting to speculate that the low-grade inflammation seen in this study of young children could reflect mild pathological processes early in life, and thus risk, of adult chronic diseases of rising prominence in impoverished societies of South Asia.

Supporting Information

Acknowledgments

The Johns Hopkins Nutriproteomics Research Team, in addition to co-authors, includes Margia Arguello, Raghothama Chaerkady, Hongie Cui, Lauren R. DeVine, Jaime Johnson, Robert O’Meally, Subarna K. Khatry, Ashika Nanayakkara-Bind, Hee-Sool Rho, Sudeep Shrestha and Fredrick Van Dyke. We thank C. Conover Talbot, Jr. for assistance with the HUGO gene annotation.