HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) A correction has been published Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Wurfel, M. M. Articles by Martin, T. R. Search for Related Content PubMed PubMed Citation Articles by Wurfel, M. M. Articles by Martin, T. R.

Identification of High and Low Responders to Lipopolysaccharide in Normal Subjects: An Unbiased Approach to Identify Modulators of Innate Immunity ¹

Mark M. Wurfel^*, William Y. Park^*, Frank Radella^*, John Ruzinski^*, Andrew Sandstrom^*, Jeanna Strout^*, Roger E. Bumgarner and Thomas R. Martin^2,*

^* Medical Research Service, Veterans Affairs Puget Sound Medical Center and Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Department of Microbiology, University of Washington School of Medicine, Seattle, WA 98105

	Abstract

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
LPS stimulates a vigorous inflammatory response from circulating leukocytes that varies greatly from individual to individual. The goal of this study was to use an unbiased approach to identify differences in gene expression that may account for the high degree of interindividual variability in inflammatory responses to LPS in the normal human population. We measured LPS-induced cytokine production ex vivo in whole blood from 102 healthy human subjects and identified individuals who consistently showed either very high or very low responses to LPS (denoted lps_high and lps_low, respectively). Comparison of gene expression profiles between the lps_high and lps_low individuals revealed 80 genes that were differentially expressed in the presence of LPS and 21 genes that were differentially expressed in the absence of LPS (p < 0.005, ANOVA). Expression of a subset of these genes was confirmed using real-time RT-PCR. Functional relevance for one gene confirmed to be expressed at a higher level in lps_high, adipophilin, was inferred when reduction in adipophilin mRNA by small interfering RNA in the human monocyte-like cell line THP-1 resulted in a modest but significant reduction in LPS-induced MCP-1 mRNA expression. These data illustrate a novel approach to the identification of factors that determine interindividual variability in innate immune inflammatory responses and identify adipophilin as a novel potential regulator of LPS-induced MCP-1 production in human monocytes.

	Introduction

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
Sepsis syndrome is an important clinical entity characterized by massive inflammation that occurs in the setting of severe infection. The sepsis syndrome can progress to sepsis and septic shock, and these entities collectively account for 125,000–180,000 deaths per year in the United States (1, 2, 3). There is substantial variation in how different patients respond to severe infection, and this variability is attributable to multiple genetic and environmental factors acting on different aspects of cellular and systemic physiology. Given the complex nature of sepsis pathophysiology, the study of "intermediate phenotypes" is necessary to facilitate the discovery of host susceptibility factors. Intermediate phenotypes are quantitative traits, measurable before the onset of the clinical phenotype, that explain a portion of the variance witnessed in the clinical phenotype (4). Early innate immune inflammatory responses to bacterial components such as LPS play a role in determining the trajectory of host responses to clinical infection (5). Therefore, leukocyte responses to purified LPS in vitro represent a potentially useful intermediate phenotype for sepsis. Genetic and environmental factors that account for variance in this intermediate phenotype may account for a portion of the variance in the clinical phenotype of sepsis.

Innate immune responses by monocytes, macrophages, and neutrophils are largely driven through the recognition of specific bacterial products, such as LPS. This recognition results in the production of inflammatory cytokines and chemokines involved in the cascade of events leading to sepsis and septic shock. Although innate immunity is necessary for adequate host responses to infection, inflammatory mediators such as TNF- and IL-1 also induce microvascular thrombosis and capillary leak seen in septic shock (6, 7, 8). Thus, the quality and magnitude of early leukocyte responses to bacterial products such as LPS may determine the risk for an individual to progress to septic shock during severe infection. An understanding of the mechanisms that determine variability in this intermediate phenotype may provide new diagnostic and therapeutic modalities in sepsis and septic shock. We hypothesized that evidence for the mechanisms determining variability of LPS-induced inflammatory cytokine production in the general population would be revealed by differences in gene expression between individuals at the extremes of the distribution of responses.

We screened a cohort of 102 healthy individuals to study the distribution of inflammatory responses to LPS in the normal population and to investigate gene expression patterns associated with high and low inflammatory responses. First, we measured concentrations of LPS-induced cytokines produced in whole-blood samples from these individuals, then we identified a subset of individuals who consistently produced high (designated lps_high) or low (designated lps_low) concentrations of cytokines. We then performed gene expression profiling to identify differentially regulated genes between the two phenotypic subgroups. We show that lps_high and lps_low individuals can be identified within this cohort, that these intermediate phenotypes are stable, and that significant gene expression differences exist between the two groups. We also show that the expression of one of these genes, adipophilin (ADFP), ³ is expressed at higher levels in the lps_high subphenotype and may regulate LPS-induced responses.

	Materials and Methods

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
Reagents

The reagents used were Salmonella minnesota Re595 LPS (List Biologicals), S-[2,3-bis(palmitoyloxy)-(2-RS)-propyl]-N-palmitoyl-(R)-Cys-(S)-Ser-Lys4-OH, trihydrochloride (Pam3Cys; EMC Microcollections), RPMI 1640 (BioWhittaker), and citrate buffer (100 mM, pH 7.2).

Study subjects

Healthy subjects (n = 102) between 18 and 65 years of age were recruited from the University of Washington community and gave written informed consent for the studies. Volunteers were excluded if they had a history of smoking or major illnesses (coronary artery disease, cancer, chronic obstructive pulmonary disease, and diabetes), active anti-inflammatory therapy (steroid or non-steroidal), or vigorous exercise within the previous 24 h. Premenopausal women were excluded because of reported variation in cytokine responses related to time in the menstrual cycle (9). This protocol was approved by the University of Washington Human Subjects Research Review Committee.

Whole-blood assay

The whole-blood assay was performed essentially as described previously (10). Phlebotomy was performed on fasting subjects between 8:00 and 10:00 A.M. The 23.5 ml of blood were anti-coagulated with 2.5 ml of 100 mM citrate (pH 7.2). Re595 LPS (final concentration, 10 ng/ml) was added to anti-coagulated whole blood (10 ml) in a 50-ml polypropylene tube, mixed gently, and incubated for 6 h at 37°C. This dose of LPS was chosen based on preliminary studies showing that 10 ng/ml consistently induced cytokine responses near the midpoint of the log-linear phase of the LPS dose-response curve. After the incubation, plasma supernatants were isolated by centrifugation at 1000 x g for 10 min and stored at –80°C. Incubation of whole blood with medium alone resulted in negligible cytokine production (data not shown). For the determination of the temporal stability of the high and low response phenotypes, we obtained two additional blood samples, spaced 14 days apart, from three high-responding and three low-responding individuals (see Results for selection criteria) and performed the whole-blood assay using the conditions described above, except that a series of LPS doses were used.

Cytokine measurements

The concentrations of human IL-1, IL-1ra, IL-6, IL-8, IL-10, TNF-, and MCP-1 in plasma supernatants were determined using sandwich immunoassays (ELISAs). Ab pairs were obtained from R&D Systems, and the assays were performed according to the manufacturer’s protocol. The detection limits of the assays were all 10 pg/ml.

Gene expression profiling

Total RNA was purified from 10 ml of citrate-anti-coagulated whole blood incubated for 4 h in the presence or absence of Re595 LPS (10 ng/ml). After the incubation, the blood was mixed with 40 ml of erythrocyte lysis buffer (5 mM MgCl₂, 10 mM NaCl, and 10 mM Tris-HCl (pH 7.0)), incubated for 10 min on ice, then spun for 10 min at 1000 x g. The leukocyte pellet was washed twice with cold hypotonic lysis buffer to lyse remaining erythrocytes, and the RNA was purified using the Rneasy Midi kit (Qiagen). The quality of the purified total RNA was verified by capillary electrophoresis. Biotin-labeled cRNA was synthesized by in vitro transcription and hybridized with the Affymetrix U95AV2 human oligonucleotide array, followed by staining and scanning per the manufacturer’s protocol (Affymetrix). Fluorescence intensity values were log₁₀-transformed and normalized across all arrays, and genes significantly differentially regulated between the lps_high and lps_low groups were identified by one-way ANOVA incorporating error modeling using the Rosetta Resolver gene expression data analysis system (Rosetta Biosoftware) (11). Genes were considered significantly differentially regulated if the fold change was greater than ±1.5 and p < 0.005. All gene annotations were acquired from LocusLink (www.ncbi.nlm.nih.gov/LocusLink/) using RefSeq ID numbers associated with the array probe set.

Real-time PCR

Reverse transcription, real-time PCR was performed using Taqman as described previously (12, 13). Primer-probe sets for selected genes (see Table VI) were obtained from the Applied Biosystems Assays-on-Demand repository, a set of validated primer-probe sets for TaqMan-based real-time PCR. The reference numbers are as follows: IL-8, Hs00174103_m1; fibronectin, Hs00277509_m1; immediate-early response 3, Hs001746474_m1; heme oxygenase-1, Hs00157965_m1; regulator of G protein signaling 14, Hs00374626_m1; TRAIL receptor 3, Hs00427795_g1; G-CSF receptor 1 (G-CSFR-1), Hs00357085_g1; and -actin, Hs99999903_m1. Primer-probe sets for two genes were obtained through Applied Biosystems Assays-by-design service, and the sequences were as follows: ADFP: forward primer 5'GCCCCTCAACTGGCTGGTA3', reverse primer 5'TTGGTCCTGAGCATTCTGAGACT3', probe 5'CAGTCAGCTGAGGATAA3'; L-3-phosphoserine-phosphatase: forward primer 5'CCAAACAACTTCAGATGAATTTTTACA3', reverse primer 5'AGATCATCTGTACCAACTTTCTATAGCAA3', probe 5'TGTTTGCTTACAATTGC3'. cDNA was synthesized from 15 ng of total RNA by reverse transcription with Superscript (Stratagene), and real-time PCR was performed using ABI PRISM 7700 (Applied Biosystems) with the following conditions: 95°C for 15 s, 60°C for 1 min repeated for 40 cycles. Quantities of the specific transcripts were determined by comparing Ct values observed in each sample with Ct values obtained from a dilution series of reverse transcribed pooled reference RNA (Stratagene). Values obtained for each transcript of interest were normalized to the level of -actin mRNA detected in each sample. The values obtained for the lps_high (n = 3) and lps_low (n = 3) individuals were compared by Student’s t test.

The acute monocytic leukemia cell line THP-1 was obtained from the American Type Culture Collection. Cells were cultured in RPMI 1640 medium supplemented with 10% FCS (complete medium) and maintained at 3–6 x 10⁵ cells/ml. THP-1 differentiation was induced by treatment with 1,25-dihydroxyvitamin D₃ (50 nM) for a total of 72 h at a cell concentration of 2.5 x 10⁵ cells/ml (14). After differentiation and treatment with small interfering RNA (siRNA) (see below), the cells were treated with LPS (S. minnesota Re595, 10 ng/ml), Pam3Cys (10 ng/ml), or RPMI 1640 alone for 6 h at 37°C, supernatants were removed for cytokine analysis, and the remaining cells were harvested for RNA purification using an RNeasy Midi kit (Qiagen). Measurements of ADFP, MCP-1, TNF-, and IL-8 mRNA were then performed using real-time PCR as above. The experiments were repeated three times.

siRNA knockdown of ADFP expression

After treatment of THP-1 cells with 1,25-dihydroxyvitamin D₃ for 48 h, two siRNA constructs (160 nM) specific for ADFP (CTGCAGGATAGACCAGTTAAA, TCCGTTGCAGTTGATCCACAA) or scrambled controls (AACGTCCTTGGATAAGAGCAA, AAGTTCTGCGCTCATTGCCAA) were added to the cells in the presence of Lipofectamine and Optimem (Invitrogen Life Technologies) and incubated an additional 24 h at 37°C before stimulation with LPS or Pam3Cys.

	Results

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
Whole-blood cytokine responses to LPS show high interindividual variability

To identify individuals who consistently showed high or low cytokine responses to LPS, whole blood from 102 healthy, non-smoking individuals was stimulated with LPS (Re595, 10 ng/ml), and cytokine production was measured by ELISA. We observed a wide range of cytokine production in response to LPS (Fig. 1). Values for TNF- varied more than three orders of magnitude, and values for IL-1 spanned a 300-fold range. This variation is much greater than would be expected due to technical variation. Optimization experiments demonstrated that assay-to-assay variation was consistently <20%. Blood monocyte counts, another potential cause for interindividual variation, were only weakly correlated with a subset of the cytokine measurements. Linear regression analysis showed that monocyte counts explained only 11% and 17% (both p < 0.001) of the variance for IL-1 and TNF- values, respectively, and that monocyte counts had no significant relationship with other cytokine measurements. These findings extend previous reports demonstrating high interindividual variation in LPS-induced cytokine production (15, 16).

View larger version (21K): [in this window] [in a new window]   FIGURE 1. Variability of whole-blood cytokine responses to LPS in 102 normal subjects. Whole blood from 102 healthy, nonsmoking individuals was incubated with LPS (Re595, 10 ng/ml) for 6 h at 37°C, plasma was isolated, and cytokine concentrations were determined by ELISA.

Individuals with a propensity to produce very high or very low amounts of inflammatory cytokines in response to an innate immune stimulus, such as LPS, may have differing abilities to respond to a bacterial infection and differing risk for developing severe inflammatory syndromes such as sepsis and septic shock. Molecular determinants of a high or low innate immune response are likely to be enriched in individuals at the extremes of a response distribution (17). We chose to study individuals whose LPS-induced cytokine production was very high or low across all cytokines tested. We chose this phenotypic definition because it is likely to select individuals with molecular variations that cause differences early in the LPS-signaling process, affecting multiple downstream events. To identify these individuals, we reorganized the data presented in Fig. 1 by rank order (lowest (1) to highest (102)) and selected individuals with cytokine responses all below the 40th percentile or all above the 60th percentile (Fig. 2). Selection in this fashion identified four high responders and three low responders whom we designated lps_high and lps_low, respectively. There are more individuals in each subgroup than would be expected by chance, because the probability of seven independent cytokine measurements all falling above the 60th percentile would be 0.0016 ((1 – 0.6)⁷ = 0.0016). This finding suggests that these individuals represent true phenotypic subgroups that share factors that modulate cytokine production in early stages of cell signaling.

View larger version (88K): [in this window] [in a new window]   FIGURE 2. Rank order of cytokine production in 102 normal subjects. Cytokine concentrations shown in Fig. 1 were ranked (1, lowest; 102, highest), and ranked values for each individual are joined by a line. Individuals who had high (four individuals with all seven cytokine ranks above the 40th percentile, yellow lines) or low (three individuals with all seven cytokine ranks below the 40th percentile, red lines) cytokine responses are highlighted.

We obtained two serial blood samples from individuals demonstrating the lps_high (n = 3) and lps_low (n = 3) phenotypes to confirm the stability of these phenotypes over time. These two blood samples were obtained 14 days apart, 6 mo after the initial screening sample. We found that the lps_high and lps_low individuals showed essentially identical dose-response characteristics for LPS-induced cytokine responses (IL-1, IL-6, IL-8, IL-10, and TNF-) in both of the serial blood draws (Fig. 3). For each individual, cytokine production was very reproducible in the serially obtained blood samples (Table I). For example, LPS-induced TNF- production measured in the two samples showed a correlation (r) of 0.98 (Table I). These data are consistent with previous studies showing reproducible interindividual differences in LPS-induced IL-1 (16, 18, 19), TNF- (15, 16, 20), and IL-10 production (15). These findings establish the temporal stability of the LPS-induced cytokine expression phenotype in whole blood.

View larger version (28K): [in this window] [in a new window]   FIGURE 3. Stability of low and high response phenotypes on repeat measurement. Increasing doses of LPS were incubated with blood from high-responding (• and ) and a low-responding ( and ) individuals for 6 h at 37°C on two different occasions (solid and dashed lines), 14 days apart.

Genome-scale expression analysis has been used to examine changes in RNA expression profiles in response to bacterial products in purified peripheral blood monocytes and macrophages and has revealed that a large number of genes are differentially regulated by bacterial products such as LPS (21, 22). However, to maintain maximum sensitivity in the study of interindividual differences in gene expression, variability due to sample preparation must be minimized. Therefore, we chose to purify total RNA from whole blood immediately after stimulation with LPS to minimize any variability due to differences in sample handling. To determine the feasibility of this approach, we first measured LPS-induced changes in gene expression in whole blood ex vivo (n = 6). Exposure of whole blood to LPS caused increased expression of 743 genes (p < 0.005, ANOVA) and decreased expression of 1125 genes (p < 0.005, ANOVA). Thus, 16% of the 12,000 features present on the oligonucleotide array were found to be differentially regulated by LPS, a proportion similar to that seen in a previous report (21). This study, Boldrick et al. (21), showed that the expression levels of 6% of 7619 genes changed after incubation of human PBMCs with Bordetella pertussis LPS, heat-killed Bordetella pertussis, or heat-killed Staphyloccocus aureus. Differences in the number of genes found to be differentially expressed in our study vs that of Boldrick et al. (21) could be explained by differences in array platform (oligonucleotide vs cDNA) and stimulation conditions (whole blood vs PBMC).

The 15 most up- and down-regulated genes are shown in Table II. The selected genes included many known to be regulated by LPS. Among the genes up-regulated by LPS were IL-1, IL-6, MIP-3, IL-12B, and CXCL11 (I-TAC). CCR2 and CD14 were down-regulated by LPS. This pattern is similar to that seen in purified peripheral blood monocytes and macrophages (21, 22, 23). These data show that array-based analysis of LPS-induced gene expression in whole blood is feasible and detects a gene expression pattern similar to that seen in purified monocytes and macrophages. Other genes identified as down-regulated by LPS, such as versican, an important matrix proteoglycan, and CYP1B1, a member of the cytochrome p450 family, are known to be expressed in macrophages (24, 25). However, this is the first report of regulation of these genes by LPS exposure.

We then evaluated the differences in gene expression between the lps_high and lps_low phenotypes using whole-blood gene expression profiling. We selected three lps_high and three lps_low individuals to use for analysis of differential gene expression. The mean monocyte count, white blood cell count, age, and gender distribution were not different between the two groups (Table III). By definition, mean values for LPS-induced cytokines were significantly different (Table III). Comparison of gene expression profiles in LPS-stimulated whole blood from lps_high and lps_low individuals identified 126 genes with increased expression in high responders and 28 genes with increased expression in the low responders (p < 0.005, ANOVA). These differentially regulated genes suggest relative differences in the activation of signaling pathways. A program of increased chemokine production (Gro- (CXCL3), MIP-2a (CXCL2), and Gro- (CXCL1)) was seen in the high responders (Table IV), whereas a program of type I IFN-response genes (IFITM2 (IFN-induced transmembrane protein 2), IFIT2 (IFN-induced protein with tetratricopeptide repeats 2), and IFIT1) was activated in the low responders. This suggests that an underlying difference in signaling pathways exists between the two groups, leading to differential regulation of these gene families.

To confirm the differences in gene expression between lps_high and lps_low phenotypes in unstimulated whole blood, we measured the abundance of a selected group of transcripts using real-time PCR. To test whether these differences in gene expression were stable over time, we performed this analysis on total RNA isolated on a separate occasion from the specimens used for the microarray analysis. We confirmed significant differences in expression for approximately half of the genes tested (Table VI). These genes included fibronectin, ADFP, L-3 phosphoserine phosphatase, and G-CSFR-1. IL-8 was regulated in the same direction by real-time PCR as by array analysis but did not reach statistical significance. These data confirm that the expression of specific genes is associated with high or low cytokine responses in this sample.

Role of ADFP in LPS-induced MCP-1 mRNA production

ADFP is an intracellular protein that associates with intracellular lipid droplets in adipocytes, monocytes, and macrophages and is thought to facilitate the accumulation of cholesterol esters from acetylated low-density lipoprotein (26, 27). Gene expression profiling showed that ADFP is expressed in higher quantities at baseline in lps_high than lps_low individuals (Table VI), suggesting that increased ADFP expression marks a cell that is predisposed to produce higher amounts of LPS-induced cytokines and that ADFP may have a functional effect on LPS-induced cellular responses.

To test the hypothesis that ADFP has a role in LPS recognition and signaling, ADFP mRNA was depleted in the human monocytic cell line THP-1, using a specific siRNA. LPS-induced cytokine and chemokine mRNA expression was then measured by real-time PCR. ADFP-specific siRNA successfully reduced the detectable ADFP mRNA by >70% compared with a scrambled-sequence siRNA control (Fig. 4A). THP-1 cells treated with siRNA were then exposed to LPS (1 ng/ml) for 6 h, and production of MCP-1, IL-8, and TNF- mRNA was measured. ADFP siRNA treatment resulted in a modest but significant decrease in LPS-induced MCP-1 mRNA (Fig. 4). In contrast, levels of LPS-induced IL-8 and TNF- mRNA were not significantly altered by ADFP siRNA treatment, showing that the reduction in ADFP mRNA by siRNA did not cause a general poisoning of cell function. To test whether ADFP is involved in responses of cells to TLR ligands other than LPS, THP-1 cells treated with ADFP siRNA were stimulated with Pam3Cys, a synthetic bacterial lipoprotein that specifically activates cells via TLR2 and TLR1 (28). Reduction in ADFP mRNA (Fig. 4) had no effect on the MCP-1 mRNA expression in response to Pam3Cys (Fig. 4), strongly suggesting that ADFP plays a specific role in LPS-induced cellular responses, particularly in the MCP-1 expression pathway.

View larger version (24K): [in this window] [in a new window]   FIGURE 4. Reduction in ADFP mRNA attenuates LPS-induced, but not Pam3Cys-induced, MCP-1 mRNA production. THP-1 cells were transfected with ADFP-specific or scrambled (control) siRNA for 24 h, followed by incubation in media (B and D, ), LPS (10 ng/ml) (B, ), or Pam3Cys (10 ng/ml) (D, ) for 6 h. ADFP (A and C) or MCP-1 (B and D) mRNA was measured by real-time PCR, and fold change was calculated relative to mock-transfected cells. Data are shown as the mean of three replicate experiments (±SEM). +, p = 0.01, *, p = 0.03, #, p = 0.02 (Student’s t test).

	Discussion

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

The goal of this study was to measure the degree of interindividual variability in innate immune responses to LPS and to determine the mechanisms underlying this variability. We showed that responses of whole-blood leukocytes to LPS varied considerably in a population of 102 healthy individuals. Variation in monocyte counts explained only a small portion of this variation, suggesting that the majority of this variation is secondary to factors that affect cellular function. Because innate immune inflammatory responses to LPS play an important role in determining host responses to an infection, this variation may account for a portion of the variation in clinical outcomes seen in Gram-negative infections.

Quantitative intermediate phenotypes can be useful to isolate environmental and genetic factors influencing a clinical phenotype. If there are common genetic or environmental factors that influence the intermediate phenotype, these factors should be most discernable by comparing individuals who have very high or very low values for the quantitative intermediate phenotype. By comparing individuals with very high or very low levels of circulating high-density lipoprotein C, investigators have identified gene variants that explain a significant portion of the variability of high-density lipoprotein C levels (44). In this study, we identified individuals who produced very high or very low amounts of inflammatory mediators in response to LPS. By selecting individuals who showed very high or very low values across all seven mediators tested, we minimized the influence of measurement error and selected for individuals who were truly hyporesponsive or hyperresponsive to LPS. Furthermore, selection in this fashion should identify individuals with variations that cause differences in cell responsiveness at a very early stage, before divergence of signaling pathways to activate the production of different mediators. These response phenotypes were shown to be stable during a period of >6 mo, providing additional evidence that this intermediate phenotype is stable over time.

There are many potential explanations for the differing responses seen in the lps_high and lps_low individuals, such as gender, age, monocyte count, circadian rhythms, diet, exercise, CD14 expression, use of anti-inflammatory medications, and underlying diseases. Gender distribution, average age, and average monocyte count were very similar between the lps_high and lps_low individuals. The use of anti-inflammatory medications and concurrent chronic or acute disease were grounds for exclusion from this study. All blood samples were obtained in the fasting state in the early morning, minimizing any effect of circadian rhythms or postprandial lipid changes. Finally, in studies we have performed after the gene expression studies, cell surface CD14 expression was found not to be correlated with the degree of LPS-induced cytokine responses (data not shown). In contrast, when we looked for differences in gene expression patterns between the lps_high and lps_low individuals by oligonucleotide array, we found several genes that were significantly differentially regulated between the two groups. Confirmation of these differentially regulated genes by real-time PCR on RNA samples obtained on a separate occasion showed that >50% of the genes identified by microarray were stably different between the two groups. These genes included several IFN-regulated transcripts (IFITM2, IFIT2, and IFIT1) (45, 46, 47), suggesting a differential activation of the so-called slow pathway of LPS-induced intracellular signaling through TIR domain-containing adapter protein, TRIF-related adapter molecule, and IFH regulatory factor-3 that leads to the production of IFN- and IFN- as opposed to the fast pathway that acts through MyD88 and preferentially activates proinflammatory cytokines such as IL-1 and TNF- (5). Whether these differences are causative remains to be shown.

ADFP was among the genes overrepresented in the lps_high individuals at baseline. ADFP is an 50 kDa protein that is highly expressed as adipocytes differentiate into mature adipocytes (48), as well as in monocytes (27) and macrophages (49), and belongs to the perilipin family of lipid storage proteins (50). Immunofluorescence staining has shown that ADFP coats the cytosolic surface of intracellular neutral lipid droplets (51). There are no reports to date linking ADFP with innate immune responses. Our studies showed that reduction in ADFP mRNA in a monocyte-like cell line using siRNA caused a reduction in LPS-induced MCP-1 mRNA expression. In contrast, LPS-induced expression of TNF- and IL-8 mRNA was not significantly affected. MCP-1 protein was similarly reduced by a reduction in ADFP mRNA but did not achieve statistical significance (data not shown). The specificity of this effect for the TLR4 agonist LPS was demonstrated by the fact that MCP-1 expression induced by Pam3Cys, a TLR1/TLR2 agonist (28), was not affected by a reduction in ADFP expression by siRNA. These data strongly suggest that expression levels of ADFP in peripheral blood predict whether an individual is a high or low responder to LPS and that ADFP may be directly involved in modulating some aspects of LPS responses in whole-blood leukocytes. The incomplete effect of ADFP siRNA treatment on LPS responses may be explained by the incomplete suppression of ADFP mRNA or differences in cellular machinery between the THP-1 cell line and primary human leukocytes, as has been described previously (52). We have recently found that THP-1 cells express levels of ADFP mRNA more than five times higher than that seen in PBMCs purified from random donors (data not shown). Thus, even with the reduction in ADFP expression achieved using siRNA (70% reduction), THP-1 cells still had relatively high levels of mRNA remaining, potentially minimizing the effect of this reduction on LPS-induced responses. Studies to further establish the role of ADFP in LPS-induced responses using alternative methods are underway.

Other genes confirmed to be differentially regulated between the two phenotypes, fibronectin 1, L-3-phosphoserine phosphatase, and G-CSFR-1, may also play a causative role in modulating cell responses to LPS. In particular, fibronectin may be a ligand for TLR4 (53) and has been shown to enhance LPS-induced priming of neutrophils (54). Thus, fibronectin could work in consort with LPS, resulting in increased production of inflammatory cytokines and chemokines. Additional studies are ongoing to establish the role of these genes in modulating cell responses to LPS.

The major limitation of this study is the small number of individuals used in each group for expression profiling. However, the high and low responders in this study were well matched for age and gender. This serendipitous occurrence reduced the background gene expression noise and permitted us to detect a modest number of differentially regulated genes. A larger study is currently under way that will expand the numbers of high and low responders tested, improving our ability to detect smaller changes in gene expression that differentiate the two phenotypes.

This study represents the first attempt to identify, in an unbiased fashion, factors that influence human innate immune responses to bacterial products. Studies in mice have revealed multiple loci that are associated with innate immune responses to LPS. The human genome has evolved in response to a differing set of selective environmental pressures and population mixings that are likely to have resulted in a unique set of genetic loci that control innate immune responses. Studies such as detailed in this report will help to elucidate these loci in humans and potentially provide new genetic markers of risk for diseases of inflammation such as sepsis and septic shock.

	Disclosures

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
The authors have no financial conflict of interest.

	Footnotes

 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

¹ This work was supported in part by National Heart, Lung, and Blood Institute K23 Awards 62-9063 (to M.M.W.) and 1 P50 HL073996-01, by National Institute of Allergy and Infectious Diseases Grant U54 AI057141, and by the Medical Research Service of the Department of Veterans Affairs.

² Address correspondence and reprint requests to Dr. Thomas R. Martin, Pulmonary Research Laboratories, 151L, Veterans Affairs Puget Sound Medical Center, 1660 South Columbian Way, Seattle, WA 98108. E-mail address: trmartin{at}u.washington.edu

³ Abbreviations used in this paper: ADFP, adipophilin; Pam3Cys, S-[2,3-bis(palmitoyloxy)-(2-RS)-propyl]-N-palmitoyl-(R)-Cys-(S)-Ser-Lys4-OH, trihydrochloride; G-CSFR-1, G-CSF receptor 1.

Received for publication December 8, 2004. Accepted for publication May 18, 2005.

	References

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 

1. Centers for Disease Control 1990. Increase in National Hospital Discharge Survey rates for septicemia–United States, 1979–1987. JAMA 263: 937-938. [Medline]
2. Bernard, G. R., J. L. Vincent, P. F. Laterre, S. P. LaRosa, J. F. Dhainaut, A. Lopez-Rodriguez, J. S. Steingrub, G. E. Garber, J. D. Helterbrand, E. W. Ely, C. J. Fisher, Jr. 2001. Efficacy and safety of recombinant human activated protein C for severe sepsis. N. Engl. J. Med. 344: 699-709. [Abstract/Free Full Text]
3. Abraham, E., P. F. Laterre, J. Garbino, S. Pingleton, T. Butler, T. Dugernier, B. Margolis, K. Kudsk, W. Zimmerli, P. Anderson, et al 2001. Lenercept (p55 tumor necrosis factor receptor fusion protein) in severe sepsis and early septic shock: a randomized, double-blind, placebo-controlled, multicenter phase III trial with 1,342 patients. Crit. Care Med. 29: 503-510. [Medline]
4. Carlson, C. S., M. A. Eberle, L. Kruglyak, D. A. Nickerson. 2004. Mapping complex disease loci in whole-genome association studies. Nature 429: 446-452. [Medline]
5. Beutler, B., K. Hoebe, X. Du, R. J. Ulevitch. 2003. How we detect microbes and respond to them: the Toll-like receptors and their transducers. J. Leukocyte Biol. 74: 479-485. [Abstract/Free Full Text]
6. Beutler, B., I. W. Milsark, A. C. Cerami. 1985. Passive immunization against cachectin/tumor necrosis factor protects mice from lethal effect of endotoxin. Science 229: 869-871. [Abstract/Free Full Text]
7. Tracey, K. J., Y. Fong, D. G. Hesse, K. R. Manogue, A. T. Lee, G. C. Kuo, S. F. Lowry, A. Cerami. 1987. Anti-cachectin/TNF monoclonal antibodies prevent septic shock during lethal bacteraemia. Nature 330: 662-664. [Medline]
8. Eichacker, P. Q., W. D. Hoffman, A. Farese, S. M. Banks, G. C. Kuo, T. J. MacVittie, C. Natanson. 1991. TNF but not IL-1 in dogs causes lethal lung injury and multiple organ dysfunction similar to human sepsis. J. Appl. Physiol. 71: 1979-1989. [Abstract/Free Full Text]
9. Konecna, L., M. S. Yan, L. E. Miller, J. Scholmerich, W. Falk, R. H. Straub. 2000. Modulation of IL-6 production during the menstrual cycle in vivo and in vitro. Brain Behav. Immun. 14: 49-61. [Medline]
10. Kovach, N. L., E. Yee, R. S. Munford, C. R. Raetz, J. M. Harlan. 1990. Lipid IVA inhibits synthesis and release of tumor necrosis factor induced by lipopolysaccharide in human whole blood ex vivo. J. Exp. Med. 172: 77-84. [Abstract/Free Full Text]
11. Hughes, T. R., M. J. Marton, A. R. Jones, C. J. Roberts, R. Stoughton, C. D. Armour, H. A. Bennett, E. Coffey, H. Dai, Y. D. He, et al 2000. Functional discovery via a compendium of expression profiles. Cell 102: 109-126. [Medline]
12. Fink, L., W. Seeger, L. Ermert, J. Hanze, U. Stahl, F. Grimminger, W. Kummer, R. M. Bohle. 1998. Real-time quantitative RT-PCR after laser-assisted cell picking. Nat. Med. 4: 1329-1333. [Medline]
13. Gibson, U. E., C. A. Heid, P. M. Williams. 1996. A novel method for real time quantitative RT-PCR. Genome Res. 6: 995-1001. [Abstract/Free Full Text]
14. Martin, T. R., S. M. Mongovin, P. S. Tobias, J. C. Mathison, A. M. Moriarty, D. J. Leturcq, R. J. Ulevitch. 1994. The CD14 differentiation antigen mediates the development of endotoxin responsiveness during differentiation of mononuclear phagocytes. J. Leukocyte Biol. 56: 1-9. [Abstract]
15. van der Linden, M. W., T. W. Huizinga, D. J. Stoeken, A. Sturk, R. G. Westendorp. 1998. Determination of tumour necrosis factor- and interleukin-10 production in a whole blood stimulation system: assessment of laboratory error and individual variation. J. Immunol. Methods 218: 63-71. [Medline]
16. Yaqoob, P., E. A. Newsholme, P. C. Calder. 1999. Comparison of cytokine production in cultures of whole human blood and purified mononuclear cells. Cytokine 11: 600-605. [Medline]
17. Motulsky, A. G., J. D. Brunzell. 1992. The genetics of coronary atherosclerosis. R. A. King, Jr, and J. I. Rotter, Jr, and A. G. Motulsky, Jr, eds. The Genetic Basis of Common Diseases 150 Oxford University Press, New York.
18. Endres, S., J. G. Cannon, R. Ghorbani, R. A. Dempsey, S. D. Sisson, G. Lonnemann, J. W. Van der Meer, S. M. Wolff, C. A. Dinarello. 1989. In vitro production of IL1, IL1, TNF and IL2 in healthy subjects: distribution, effect of cyclooxygenase inhibition and evidence of independent gene regulation. Eur. J. Immunol. 19: 2327-2333. [Medline]
19. Endres, S., R. Ghorbani, G. Lonnemann, J. W. van der Meer, C. A. Dinarello. 1988. Measurement of immunoreactive interleukin-1 from human mononuclear cells: optimization of recovery, intrasubject consistency, and comparison with interleukin-1 and tumor necrosis factor. Clin. Immunol. Immunopathol. 49: 424-438. [Medline]
20. Schraut, W., P. Wendelgass, J. C. Calzada-Wack, M. Frankenberger, H. W. Ziegler-Heitbrock. 1997. TNF gene expression in monocytes of low and high responder individuals. Cytokine 9: 206-211. [Medline]
21. Boldrick, J. C., A. A. Alizadeh, M. Diehn, S. Dudoit, C. L. Liu, C. E. Belcher, D. Botstein, L. M. Staudt, P. O. Brown, D. A. Relman. 2002. Stereotyped and specific gene expression programs in human innate immune responses to bacteria. Proc. Natl. Acad. Sci. USA 99: 972-977. [Abstract/Free Full Text]
22. Nau, G. J., J. F. Richmond, A. Schlesinger, E. G. Jennings, E. S. Lander, R. A. Young. 2002. Human macrophage activation programs induced by bacterial pathogens. Proc. Natl. Acad. Sci. USA 99: 1503-1508. [Abstract/Free Full Text]
23. Parker, L. C., M. K. Whyte, S. N. Vogel, S. K. Dower, I. Sabroe. 2004. Toll-like receptor (TLR)2 and TLR4 agonists regulate CCR expression in human monocytic cells. J. Immunol. 172: 4977-4986. [Abstract/Free Full Text]
24. Chaussabel, D., R. T. Semnani, M. A. McDowell, D. Sacks, A. Sher, T. B. Nutman. 2003. Unique gene expression profiles of human macrophages and dendritic cells to phylogenetically distinct parasites. Blood 102: 672-681. [Abstract/Free Full Text]
25. Baron, J. M., G. Zwadlo-Klarwasser, F. Jugert, W. Hamann, A. Rubben, H. Mukhtar, H. F. Merk. 1998. Cytochrome P450 1B1: a major P450 isoenzyme in human blood monocytes and macrophage subsets. Biochem. Pharmacol. 56: 1105-1110. [Medline]
26. Larigauderie, G., C. Furman, M. Jaye, C. Lasselin, C. Copin, J. C. Fruchart, G. Castro, M. Rouis. 2004. Adipophilin enhances lipid accumulation and prevents lipid efflux from THP-1 macrophages: potential role in atherogenesis. Arterioscler. Thromb. Vasc. Biol. 24: 504-510. [Abstract/Free Full Text]
27. Buechler, C., M. Ritter, C. Q. Duong, E. Orso, M. Kapinsky, G. Schmitz. 2001. Adipophilin is a sensitive marker for lipid loading in human blood monocytes. Biochim. Biophys. Acta 1532: 97-104. [Medline]
28. Takeuchi, O., S. Sato, T. Horiuchi, K. Hoshino, K. Takeda, Z. Dong, R. L. Modlin, S. Akira. 2002. Cutting edge: role of Toll-like receptor 1 in mediating immune response to microbial lipoproteins. J. Immunol. 169: 10-14. [Abstract/Free Full Text]
29. Eng, H. L., C. H. Chen, C. C. Kuo, J. S. Wu, C. H. Wang, T. M. Lin. 2003. Association of CD14 promoter gene polymorphism and Chlamydia pneumoniae infection. J. Infect. Dis. 188: 90-97. [Medline]
30. Gomi, K., Y. Tokue, T. Kobayashi, H. Takahashi, A. Watanabe, T. Fujita, T. Nukiwa. 2004. Mannose-binding lectin gene polymorphism is a modulating factor in repeated respiratory infections. Chest 126: 95-99. [Abstract/Free Full Text]
31. Mombo, L. E., C. Y. Lu, S. Ossari, I. Bedjabaga, L. Sica, R. Krishnamoorthy, C. Lapoumeroulie. 2003. Mannose-binding lectin alleles in sub-Saharan Africans and relation with susceptibility to infections. Genes Immun. 4: 362-367. [Medline]
32. Mullighan, C. G., S. Heatley, K. Doherty, F. Szabo, A. Grigg, T. P. Hughes, A. P. Schwarer, J. Szer, B. D. Tait, L. Bik To, P. G. Bardy. 2002. Mannose-binding lectin gene polymorphisms are associated with major infection following allogeneic hemopoietic stem cell transplantation. Blood 99: 3524-3529. [Abstract/Free Full Text]
33. Bochud, P. Y., T. R. Hawn, A. Aderem. 2003. Cutting edge: a Toll-like receptor 2 polymorphism that is associated with lepromatous leprosy is unable to mediate mycobacterial signaling. J. Immunol. 170: 3451-3454. [Abstract/Free Full Text]
34. Smirnova, I., N. Mann, A. Dols, H. H. Derkx, M. L. Hibberd, M. Levin, B. Beutler. 2003. Assay of locus-specific genetic load implicates rare Toll-like receptor 4 mutations in meningococcal susceptibility. Proc. Natl. Acad. Sci. USA 100: 6075-6080. [Abstract/Free Full Text]
35. Hawn, T. R., A. Verbon, K. D. Lettinga, L. P. Zhao, S. S. Li, R. J. Laws, S. J. Skerrett, B. Beutler, L. Schroeder, A. Nachman, et al 2003. A common dominant TLR5 stop codon polymorphism abolishes flagellin signaling and is associated with susceptibility to legionnaires’ disease. J. Exp. Med. 198: 1563-1572. [Abstract/Free Full Text]
36. Picard, C., A. Puel, M. Bonnet, C. L. Ku, J. Bustamante, K. Yang, C. Soudais, S. Dupuis, J. Feinberg, C. Fieschi, et al 2003. Pyogenic bacterial infections in humans with IRAK-4 deficiency. Science 299: 2076-2079. [Abstract/Free Full Text]
37. Medvedev, A. E., A. Lentschat, D. B. Kuhns, J. C. Blanco, C. Salkowski, S. Zhang, M. Arditi, J. I. Gallin, S. N. Vogel. 2003. Distinct mutations in IRAK-4 confer hyporesponsiveness to lipopolysaccharide and interleukin-1 in a patient with recurrent bacterial infections. J. Exp. Med. 198: 521-531. [Abstract/Free Full Text]
38. Currie, A. J., D. J. Davidson, G. S. Reid, S. Bharya, K. L. MacDonald, R. S. Devon, D. P. Speert. 2004. Primary immunodeficiency to pneumococcal infection due to a defect in Toll-like receptor signaling. J. Pediatr. 144: 512-518. [Medline]
39. Gibot, S., A. Cariou, L. Drouet, M. Rossignol, L. Ripoll. 2002. Association between a genomic polymorphism within the CD14 locus and septic shock susceptibility and mortality rate. Crit. Care Med. 30: 969-973. [Medline]
40. Hubacek, J. A., F. Stuber, D. Frohlich, M. Book, S. Wetegrove, M. Ritter, G. Rothe, G. Schmitz. 2001. Gene variants of the bactericidal/permeability increasing protein and lipopolysaccharide binding protein in sepsis patients: gender-specific genetic predisposition to sepsis. Crit. Care Med. 29: 557-561. [Medline]
41. Garred, P., J. Strom, L. Quist, E. Taaning, H. O. Madsen. 2003. Association of mannose-binding lectin polymorphisms with sepsis and fatal outcome, in patients with systemic inflammatory response syndrome. J. Infect. Dis. 188: 1394-1403. [Medline]
42. Lorenz, E., J. P. Mira, K. L. Frees, D. A. Schwartz. 2002. Relevance of mutations in the TLR4 receptor in patients with Gram-negative septic shock. Arch. Intern. Med. 162: 1028-1032. [Abstract/Free Full Text]
43. Agnese, D. M., J. E. Calvano, S. J. Hahm, S. M. Coyle, S. A. Corbett, S. E. Calvano, S. F. Lowry. 2002. Human toll-like receptor 4 mutations but not CD14 polymorphisms are associated with an increased risk of gram-negative infections. J. Infect. Dis. 186: 1522-1525. [Medline]
44. Cohen, J. C., R. S. Kiss, A. Pertsemlidis, Y. L. Marcel, R. McPherson, H. H. Hobbs. 2004. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science 305: 869-872. [Abstract/Free Full Text]
45. Lewin, A. R., L. E. Reid, M. McMahon, G. R. Stark, I. M. Kerr. 1991. Molecular analysis of a human interferon-inducible gene family. Eur. J. Biochem. 199: 417-423. [Medline]
46. Wathelet, M. G., P. M. Berr, G. A. Huez. 1992. Regulation of gene expression by cytokines and virus in human cells lacking the type-I interferon locus. Eur. J. Biochem. 206: 901-910. [Medline]
47. DeYoung, K. L., M. E. Ray, Y. A. Su, S. L. Anzick, R. W. Johnstone, J. A. Trapani, P. S. Meltzer, J. M. Trent. 1997. Cloning a novel member of the human interferon-inducible gene family associated with control of tumorigenicity in a model of human melanoma. Oncogene 15: 453-457. [Medline]
48. Jiang, H. P., G. Serrero. 1992. Isolation and characterization of a full-length cDNA coding for an adipose differentiation-related protein. Proc. Natl. Acad. Sci. USA 89: 7856-7860. [Abstract/Free Full Text]
49. Wang, X., T. J. Reape, X. Li, K. Rayner, C. L. Webb, K. G. Burnand, P. G. Lysko. 1999. Induced expression of adipophilin mRNA in human macrophages stimulated with oxidized low-density lipoprotein and in atherosclerotic lesions. FEBS Lett. 462: 145-150. [Medline]
50. Londos, C., D. L. Brasaemle, C. J. Schultz, J. P. Segrest, A. R. Kimmel. 1999. Perilipins, ADRP, and other proteins that associate with intracellular neutral lipid droplets in animal cells. Semin. Cell Dev. Biol. 10: 51-58. [Medline]
51. Brasaemle, D. L., T. Barber, N. E. Wolins, G. Serrero, E. J. Blanchette-Mackie, C. Londos. 1997. Adipose differentiation-related protein is an ubiquitously expressed lipid storage droplet-associated protein. J. Lipid Res. 38: 2249-2263. [Abstract]
52. Kohro, T., T. Tanaka, T. Murakami, Y. Wada, H. Aburatani, T. Hamakubo, T. Kodama. 2004. A comparison of differences in the gene expression profiles of phorbol 12-myristate 13-acetate differentiated THP-1 cells and human monocyte-derived macrophage. J. Atheroscler. Thromb. 11: 88-97. [Medline]
53. Okamura, Y., M. Watari, E. S. Jerud, D. W. Young, S. T. Ishizaka, J. Rose, J. C. Chow, J. F. Strauss, III. 2001. The extra domain A of fibronectin activates Toll-like receptor 4. J. Biol. Chem. 276: 10229-10233. [Abstract/Free Full Text]
54. Bortolussi, R., K. Rajaraman, G. Qing, R. Rajaraman. 1997. Fibronectin enhances in vitro lipopolysaccharide priming of polymorphonuclear leukocytes. Blood 89: 4182-4189. [Abstract/Free Full Text]

This article has been cited by other articles:

				M. M. Wurfel, A. C. Gordon, T. D. Holden, F. Radella, J. Strout, O. Kajikawa, J. T. Ruzinski, G. Rona, R. A. Black, S. Stratton, et al. Toll-like Receptor 1 Polymorphisms Affect Innate Immune Responses and Outcomes in Sepsis Am. J. Respir. Crit. Care Med., October 1, 2008; 178(7): 710 - 720. [Abstract] [Full Text] [PDF]

				T. R. Martin Interactions between Mechanical and Biological Processes in Acute Lung Injury Proceedings of the ATS, April 15, 2008; 5(3): 291 - 296. [Abstract] [Full Text] [PDF]

				M. Hedl, J. Li, J. H. Cho, and C. Abraham Chronic stimulation of Nod2 mediates tolerance to bacterial products PNAS, December 4, 2007; 104(49): 19440 - 19445. [Abstract] [Full Text] [PDF]

				J. U. Raj, C. Aliferis, R. M. Caprioli, A. W. Cowley Jr., P. F. Davies, M. W. Duncan, D. J. Erle, S. C. Erzurum, P. W. Finn, H. Ischiropoulos, et al. Genomics and proteomics of lung disease: conference summary Am J Physiol Lung Cell Mol Physiol, July 1, 2007; 293(1): L45 - L51. [Full Text] [PDF]

				J. S. Lee, M. M. Wurfel, G. Matute-Bello, C. W. Frevert, M. R. Rosengart, M. Ranganathan, V. W. Wong, T. Holden, S. Sutlief, A. Richmond, et al. The Duffy Antigen Modifies Systemic and Local Tissue Chemokine Responses following Lipopolysaccharide Stimulation J. Immunol., December 1, 2006; 177(11): 8086 - 8094. [Abstract] [Full Text] [PDF]

				T. R. Martin and C. W. Frevert Innate Immunity in the Lungs Proceedings of the ATS, December 1, 2005; 2(5): 403 - 411. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) A correction has been published Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Wurfel, M. M. Articles by Martin, T. R.