Objective
Intraamniotic inflammation/infection is the only mechanism of disease with persuasive evidence of causality for spontaneous preterm labor/delivery. Previous studies about the behavior of cytokines in preterm labor have been largely based on the analysis of the behavior of each protein independently. Emerging evidence indicates that the study of biologic networks can provide insight into the pathobiology of disease and improve biomarker discovery. The goal of this study was to characterize the inflammatory-related protein network in the amniotic fluid of patients with preterm labor.
Study Design
A retrospective cohort study was conducted that included women with singleton pregnancies who had spontaneous preterm labor and intact membranes (n = 135). These patients were classified according to the results of amniotic fluid culture, broad-range polymerase chain reaction coupled with electrospray ionization mass spectrometry, and amniotic fluid concentration of interleukin (IL)-6 into the following groups: (1) those without intraamniotic inflammation (n = 85), (2) those with microbial-associated intraamniotic inflammation (n = 15), and (3) those with intraamniotic inflammation without detectable bacteria (n = 35). Amniotic fluid concentrations of 33 inflammatory-related proteins were determined with the use of a multiplex bead array assay.
Results
Patients with preterm labor and intact membranes who had microbial-associated intraamniotic inflammation had a higher amniotic fluid inflammatory-related protein concentration correlation than those without intraamniotic inflammation (113 perturbed correlations). IL-1β, IL-6, macrophage inflammatory protein (MIP)-1α, and IL-1α were the most connected nodes (highest degree) in this differential correlation network (degrees of 20, 16, 12, and 12, respectively). Patients with sterile intraamniotic inflammation had correlation patterns of inflammatory-related proteins, both increased and decreased, when compared to those without intraamniotic inflammation (50 perturbed correlations). IL-1α, MIP-1α, and IL-1β were the most connected nodes in this differential correlation network (degrees of 12, 10, and 7, respectively). There were more coordinated inflammatory-related protein concentrations in the amniotic fluid of women with microbial-associated intraamniotic inflammation than in those with sterile intraamniotic inflammation (60 perturbed correlations), with IL-4 and IL-33 having the largest number of perturbed correlations (degrees of 15 and 13, respectively).
Conclusions
We report for the first time an analysis of the inflammatory-related protein network in spontaneous preterm labor. Patients with preterm labor and microbial-associated intraamniotic inflammation had more coordinated amniotic fluid inflammatory-related proteins than either those with sterile intraamniotic inflammation or those without intraamniotic inflammation. The correlations were also stronger in patients with sterile intraamniotic inflammation than in those without intraamniotic inflammation. The findings herein could be of value in the development of biomarkers of preterm labor.
Preterm birth is the leading cause of neonatal morbidity and mortality worldwide and occurs after the spontaneous onset of preterm labor in two-thirds of cases. Accumulating evidence suggests that preterm parturition is a syndrome caused by multiple pathological processes that include intrauterine infection, vascular disease, uterine overdistension, decline in progesterone action, breakdown of maternal-fetal tolerance, decidual senescence, and other pathological processes yet to be discovered. Of these, intraamniotic infection (also termed microbial-associated intraamniotic inflammation : the presence of microorganisms in the amniotic cavity and intraamniotic inflammation) has been causally linked to spontaneous preterm delivery. Indeed, at least 1 of every 4 preterm infants is born to a mother with an intraamniotic infection that is largely subclinical.
The amniotic cavity is normally sterile, but microorganisms can gain access to the lower genital tract through an ascending pathway, although other pathways have been proposed as well (hematogenous dissemination from distant sites, such as the oral cavity). Bacteria and their products elicit an intraamniotic inflammatory response after they are recognized by pattern recognition receptors and induce the production of cytokines and chemokines as well as other inflammatory mediators that include prostaglandins and proteases.
Although intraamniotic inflammation has been traditionally attributed to microorganisms and their products (such as lipopolysaccharide, lipoteichoic acid or peptidoglycans, lipoglycans, or others), it has now become clear that a subgroup of patients with intraamniotic inflammation does not have microorganisms (bacteria or viruses) identifiable by cultivation methods or molecular microbiologic techniques. We have coined the term sterile intraamniotic inflammation to refer to this condition.
Previous studies about the behavior of cytokines in spontaneous labor at term and preterm labor have been based on data derived from bioassays for these molecules and from other specific individual immunoassays. Because biologic functions are the expression of integrated and interdependent networks of cells and molecules, the study of biologic networks, rather than individual cells/molecules, is considered necessary to improve the understanding of the pathophysiology of the disease. The objective of this study was to characterize the behavior of the inflammatory-related protein network in the amniotic fluid of women in preterm labor, according to the presence/absence of intraamniotic inflammation and microorganisms in the amniotic cavity.
Materials and Methods
Study population
A cohort of women (n = 135) with singleton pregnancies who experienced spontaneous preterm labor and intact membranes was selected from the clinical database and Bank of Biological Samples maintained by Wayne State University, the Detroit Medical Center, and the Perinatology Research Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The inclusive criteria were as follows: (1) singleton gestation, (2) transabdominal amniocentesis performed between 20 and 35 weeks of gestation before the rupture of the chorioamniotic membranes, (3) absence of chromosomal or structural fetal anomalies, and (4) sufficient amniotic fluid for molecular microbiologic studies. These patients were included in previous studies that provided descriptions of microbiologic studies, amniotic fluid interleukin (IL)-6 concentration, and high mobility group box-1 (HMGB-1). Each patient provided written informed consent; the use of biologic specimens and clinical data for research purposes was approved by the Institutional Review Boards of the Eunice Kennedy Shriver National Institute of Child Health and Human Development and Wayne State University.
Clinical definitions
Microbial invasion of the amniotic cavity was defined according to the results of amniotic fluid culture and polymerase chain reaction/electrospray ionization-mass spectrometry (PCR-ESI/MS; Ibis Biosciences, Carlsbad, CA). Intraamniotic inflammation was diagnosed when the amniotic fluid IL-6 concentration was ≥2.6 ng/mL. Based on the results of amniotic fluid cultures, PCR-ESI/MS, and amniotic fluid concentrations of IL-6, patients with preterm labor and intact membranes were classified into three groups: group 1 included those without intraamniotic inflammation (n = 85); group 2 comprised those with microbial-associated intraamniotic inflammation (a combination of microbial invasion of the amniotic cavity and intraamniotic inflammation; n = 35), and group 3 included those with intraamniotic inflammation without detectable microorganisms (an elevated amniotic fluid IL-6 concentration without evidence of microorganisms in the amniotic cavity by cultivation and molecular microbiologic methods; n = 15). Those patients with the presence of microorganisms in the amniotic cavity, but without intraamniotic inflammation, were classified into group 3 (no intraamniotic inflammation) as the presence of such microorganisms may represent contamination.
Spontaneous preterm labor was diagnosed by the presence of at least two regular uterine contractions every 10 minutes associated with cervical changes in patients with gestational ages of 20 to 36 6/7 weeks. Preterm delivery was defined as birth before 37 weeks of gestation.
Multiplex determination of inflammatory-related proteins
Amniotic fluid concentrations of 33 inflammatory-related proteins were determined using a multiplex bead array assay developed by the investigators ( Table 1 ). The mediators are cytokines (chemokines are a subset of cytokines); we also included the prototypic alarmin, HMGB-1, that is elevated in cases of sterile intraamniotic inflammation, calgranulin A and C, the antimicrobial peptides, and the antimicrobial protein, lactoferrin. All capture antibodies were purchased from R&D Systems (Minneapolis, MN) with the exception of the capture antibodies for IL-4 and IL-10 (BioLegend, San Diego, CA), IL-12p70 (Becton Dickinson Labware, Franklin Lakes, NJ), IL-18 (eBioscience Inc, San Diego, CA), and lactoferrin (Abcam Inc, Cambridge, MA). Individual Luminex bead sets (Luminex Corporation, Riverside, CA) were coupled to inflammatory-related protein-specific capture antibodies, according to the manufacturer’s recommendations. Conjugated beads were washed and kept at 4°C until use. The standards for each analyte were purchased from R&D Systems [with the exception of calgranulin A (US Biological Corporation, Salem, MA), HMGB-1, and lactoferrin (Abcam Inc)], resuspended at concentrations ranging from 50 μg/mL to 8 ng/mL, and diluted serially 1:3 to generate standard curves. Detection antibodies were purchased from R&D Systems as biotinylated affinity purified goat polyclonal antibodies or from BioLegend (IL-10), Becton Dickinson (IL-12), eBiosciences (IL-18), Abcam (lactoferrin), and ThermoFisher Scientific Inc (Waltham, MA; HMGB-1). Biotinylated detection antibodies were used at twice the concentrations recommended for a classic enzyme-linked immunosorbent assay. All assay procedures were performed in assay buffer containing phosphate-buffered saline solution supplemented with 1% normal mouse serum (Gibco BRL, Grand Island, NY), 1% normal goat serum (Gibco BRL), and 20 mmol/L Tris-HCl (pH 7.4). The assays were run using 2000 beads per set of each of the 33 inflammatory-related proteins measured per well in a total volume of 50 μL. Samples were diluted in assay buffer and run in duplicates at 2 dilutions—1:2 and 1:32. Fifty microliters of each amniotic fluid sample were added to the well and incubated overnight at 4°C in a Millipore Multiscreen plate (Millipore Corporation, Billerica, MA). The liquid was then aspirated with a BioPlex Pro II plate washer (Bio-Rad Laboratories, Hercules, CA), and the plates were washed twice with 200 μL of assay buffer. The beads were then resuspended in 50 μL of assay buffer containing biotinylated polyclonal antibodies against the measured inflammatory-related proteins for 30 minutes at room temperature. The plates were washed twice with phosphate-buffered saline solution; the beads were resuspended in 50 μL of assay buffer, and 50 μL of a 16-μg/mL solution of streptavidin-PE (Molecular Probes, Eugene, OR) was added to each well. The plates were read on a Luminex-100 platform. For each bead set of the 33 tested, a minimum of 100 beads was collected. The median fluorescence intensity was recorded for each bead and used for analysis with the Bioplex Manager software (version 6.1; Bio-Rad Laboratories) using a 5-parameter regression algorithm. The assay characteristics are described in Table 1 .
| Analyte | Lower limit of detection, pg/mL |
|---|---|
| Interleukin | |
| 1α | 0.98 |
| 1β | 0.88 |
| 2 | 3.49 |
| 4 | 30 |
| 6 | 0.37 |
| 7 | 0.37 |
| 8 | 0.95 |
| 10 | 0.37 |
| 12 | 0.37 |
| 13 | 0.37 |
| 15 | 0.37 |
| 16 | 20 |
| 18 | 0.34 |
| 33 | 88 |
| Calgranulin | |
| A | 25.4 |
| C | 1128 |
| Eotaxin | 0.27 |
| Granulocyte macrophage colony-stimulating factor | 0.27 |
| Gro-α/CXCL1: C-X-C motif ligand 1 | 72.7 |
| High-mobility group box protein 1 | 6000 |
| Interferon-γ | 6.60 |
| Interferon gamma-induced protein 10 | 237 |
| Interferon-inducible T-cell alpha chemoattractant/C-X-C motif ligand 11 | 8.50 |
| Lactoferrin | 6.39 |
| Macrophage colony-stimulating factor | 0.99 |
| Monocyte chemoattractant protein-1 | 2.81 |
| Monokine induced by gamma interferon or CXCL-9 | 64.2 |
| Macrophage inflammatory protein | |
| 1α | 10.661 |
| 1β | 10.661 |
| 3α | 5513 |
| Regulated on activation (RANTES), normal T cell expressed and secreted | 2.758 |
| T-cell growth factor-β | 7.422 |
| Tumor necrosis factor-α | 0.818 |
Statistical analysis
The goals of the statistical analysis were to (1) assess the differences in analyte concentration among the groups, (2) determine whether pairwise analyte correlations were different among the groups, and (3) build the network of significantly perturbed correlations and identify highly connected nodes and network modules.
Demographics data analysis
The Kolmogorov-Smirnov test was used to test whether the distribution of continuous variables was normal. Chi-square or Fisher’s exact tests were used for comparisons of proportions. The Kruskal-Wallis and Mann-Whitney U tests compared median concentrations of analytes between and among groups. Statistical analysis of demographics data was performed with SPSS software (version 19; IBM Corporation, Armonk, NY). A probability value of < .05 was considered statistically significant.
Analysis of the difference in concentrations among groups
Analyte concentration data was log (base 2) transformed to improve normality of the data distribution. To test for differential analyte concentration among the groups, a linear model was fit to the analyte concentration using the group indicator (eg, no intraamniotic inflammation vs sterile intraamniotic inflammation) and gestational age as predictors. Significant probability values for the group coefficient were adjusted with the Benjamini and Hochberg method over all 33 analytes to compute q values. Significance of differences in concentration was determined based on a q-value <0.1 and fold change >1.5.
Differential correlation analysis
The goal of this analysis was to test whether the correlation of concentrations between each possible pair of analytes (eg, IL-1α and IL-6; IL-1α and IL-33, etc) differed among the groups with adjustment for the effect of gestational age. Adjustment for gestational age was performed to account for differences in the duration of pregnancy at the time of amniocentesis among the groups. A linear model was fit to the log-transformed data of each analyte as a function of gestational age using samples from each group separately. The residuals (actual value – fitted value) were then used to compute Pearson correlations for each pair of analytes within each group of patients. Because these correlations were determined from data adjusted for a covariate (gestational age), these correlations are also called partial correlations. To test for differences in partial correlations among the groups, the partial correlations were first converted into an intermediary variable z, using Fisher’s transformation. Under the null hypothesis (partial correlations are equal between groups), the standardized differences in z values among groups were assumed to follow a standard normal distribution. Significant differences in partial correlations were considered to be present when the probability value was < .01 and the magnitude of correlation differences was at least 0.2. The rationale for the use of more stringent criteria is that, when 528 differential correlations are tested simultaneously, one would expect an average 26.4 false positive differential correlation due to chance alone (528 × 0.05). With the use of the criteria of a probability value < .01, the number of false positives would be reduced to 5 (528 × 0.01). The additional requirement that the magnitude of differential correlation be >0.2 reduces even further the number of false positives, because differential correlations with higher magnitude are less likely to be observed because of chance alone.
Network analysis
A network was constructed for each between-group comparison (eg, sterile intraamniotic inflammation vs no intraamniotic inflammation) by linking/connecting the analytes with a significantly different correlation among the respective groups. For each node (analyte) in the network, we calculated the degree and the average absolute difference in correlations. Although the first metric gives the number of links (significantly perturbed correlations) of a given node to all others, the latter describes the typical between-group change in correlation (regardless of direction). The network was analyzed further to identify modules (groups of analytes) so that analytes (network nodes) within modules are more connected with others within the same module than would be expected by chance.
Results
Demographic characteristics
The characteristics of the study population stratified by the presence or absence of microorganisms in the amniotic cavity and intraamniotic inflammation were the subject of a detailed report in this Journal. Briefly, the frequencies of sterile intraamniotic inflammation, microbial-associated intraamniotic inflammation, and no intraamniotic inflammation were 26% (35/135), 11% (15/135), and 63% (85/135), respectively. The most frequent microorganisms identified in the amniotic cavity were Ureaplasma spp. Patients with sterile and microbial-associated intraamniotic inflammation had a significantly lower median gestational age at delivery than those without intraamniotic inflammation [26 weeks (interquartile range: IQR) 24-33 vs. 27 weeks (IQR 24-32 weeks) vs. 36 weeks (IQR 34-38 weeks); each P < 0.001; Table 2 ]. There was no significant difference in the median gestational age at delivery between patients with microbial-associated intraamniotic inflammation and those with sterile intraamniotic inflammation ( P = .6; Table 2 ). The amniotic fluid inflammatory response (IL-6, white blood cell count) was significantly greater in microbial-associated intraamniotic inflammation than in sterile intraamniotic inflammation [amniotic fluid IL-6 median: microbial-associated intraamniotic inflammation of 96 ng/mL (IQR, 17-266 ng/mL) vs sterile intraamniotic inflammation of 12 ng/mL (IQR, 5-21 ng/mL); P < .001; median white blood cell counts: 295 cells/mm 3 (IQR 2-960 cells/mm 3 ) vs 3 cells/mm 3 (IQR, 1-17 cells/mm 3 ); P = 0.018; Table 2 ]. Our study was conducted before the publication of studies reporting that vaginal progesterone reduces the rate of preterm delivery and neonatal morbidity; thus, none of our patients received vaginal progesterone.
| Variable | No intraamniotic inflammation (n = 85) | Sterile intraamniotic inflammation (n = 35) | P value (no intraamniotic inflammation vs sterile intraamniotic inflammation) | Microbial-associated intraamniotic inflammation (n = 15) | P value | |
|---|---|---|---|---|---|---|
| No intraamniotic inflammation vs microbial associated intraamniotic inflammation | Sterile intraamniotic inflammation vs microbial associated intraamniotic inflammation | |||||
| Maternal age, y a | 23 (20–26) | 23 (20–26.2) | .8 | 24 (20–30) | .7 | .4 |
| Body mass index, kg/m 2 a | 23 (20–29) | 23 (20–32) | .6 | 27 (23–37) | .04 | .2 |
| Frequency of sonographic short cervix, % (n/N) | 16.5 (14/85) | 11.8 (10/85) | .04 | 20 (3/15) | .35 | .9 |
| Antenatal corticosteroid administration, % (n/N) | 45 (37/82) b | 20 (7/35) | .012 | 46.7 (7/15) | 1 | .06 |
| Gestational age at amniocentesis, wk a | 32 (29–33) | 25 (23–32) | < .001 | 26 (23–32) | .006 | .83 |
| Amniotic fluid | ||||||
| White blood cells, cells/mm 3 a | 1 (0–5) | 3 (1–17) | .007 | 295 (2–960) | < .001 | .018 |
| Glucose, mg/dL a | 29 (24–34) | 22 (18–28) | .001 | 11 (10–20) | < .001 | .002 |
| Interleukin-6, ng/mL a | 0.8 (0.5–1.1) | 12 (5–21) | < .001 | 96 (17–266) | < .001 | < .001 |
| Gestational age at delivery, wk a | 36 (34–38) | 27 (24–32) | < .001 | 26 (24–33) | < .001 | .64 |
| Composite neonatal morbidity, % (n) c | 11 (9) | 68 (24) | < .001 | 67 (10) | < .001 | 1.0 |
| Acute placental inflammation, % (n/N) d , e | 22.5 (18/80) | 61 (19/31) | < .001 | 79 (11/14) | < .001 | .14 |
| Acute histologic chorioamnionitis, % (n/N) | 21 (17/80) | 58 (18/31) | < .001 | 79 (11/14) | < .001 | .04 |
| Funisitis, % (n/N) | 13 (10/80) | 29 (9/31) | .06 | 57 (8/14) | < .001 | .26 |
a Data are given as median (interquartile range)
b Data were not available in 3 patients
c Composite neonatal morbidity: the presence of respiratory distress syndrome, bronchopulmonary dysplasia, grade III or IV intraventricular hemorrhage, periventricular leukomalacia, proven neonatal sepsis, and necrotizing enterocolitis or perinatal death
d Acute placental inflammation: acute histologic chorioamnionitis and/or acute funisitis
e Acute placental inflammation was calculated over a total of 125 specimens.
Inflammatory-related protein concentrations among the subgroups with preterm labor and intact membranes
Sterile intraamniotic inflammation vs no intraamniotic inflammation
The geometric mean amniotic fluid concentration for all 33 inflammatory-related analytes was higher in patients with sterile intraamniotic inflammation than in those without intraamniotic inflammation (fold change range, 1.1-11.4). The differences were significant for 27 of the 33 analytes (q-value, <0.1; fold change, >1.5; Table 3 ). The largest fold changes were observed for IL-6 and IL-8 (10.6 and 11.4, respectively).
| Proteins | Sterile intraamniotic inflammation vs no intraamniotic inflammation | Microbial-associated intraamniotic inflammation vs no intraamniotic inflammation | Microbial-associated intraamniotic inflammation vs sterile intraamniotic inflammation | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Fold change | P value | Q value | Fold change | P value | Q value | Fold change | P value | Q value | |
| IL-8 | 11.4 | .000 | 0.000 | 106.0 | .000 | 0.000 | 9.3 | .000 | 0.000 |
| IL-6 | 10.6 | .000 | 0.000 | 115.4 | .000 | 0.000 | 10.9 | .000 | 0.000 |
| MIP-1β | 5.3 | .000 | 0.000 | 64.8 | .000 | 0.000 | 12.3 | .000 | 0.000 |
| MCP-1 | 3.8 | .000 | 0.000 | 18.5 | .000 | 0.000 | 4.8 | .000 | 0.000 |
| MIP-1α | 3.4 | .000 | 0.000 | 39.8 | .000 | 0.000 | 11.6 | .000 | 0.000 |
| Calgranulin C | 3.1 | .000 | 0.000 | 12.0 | .000 | 0.000 | 3.9 | .000 | 0.000 |
| IL-1β | 2.8 | .002 | 0.006 | 30.6 | .000 | 0.000 | 11.1 | .000 | 0.000 |
| RANTES | 2.5 | .001 | 0.002 | 6.6 | .000 | 0.000 | 2.6 | .010 | 0.010 |
| MIP-3α | 2.5 | .000 | 0.000 | 10.9 | .000 | 0.000 | 4.4 | .000 | 0.000 |
| Gro-α/CXCL1 | 2.4 | .000 | 0.000 | 8.7 | .000 | 0.000 | 3.6 | .000 | 0.000 |
| Calgranulin A | 2.1 | .003 | 0.007 | 15.2 | .000 | 0.000 | 7.2 | .000 | 0.000 |
| IL-10 | 2.1 | .001 | 0.004 | 12.9 | .000 | 0.000 | 6.3 | .000 | 0.000 |
| MIG | 1.8 | .003 | 0.007 | 4.6 | .000 | 0.000 | 2.5 | .001 | 0.001 |
| ITAC/CXCL11 | 1.8 | .000 | 0.001 | 4.6 | .000 | 0.000 | 2.6 | .000 | 0.000 |
| IP-10/CXCL10 | 1.8 | .020 | 0.028 | 4.0 | .000 | 0.000 | 2.3 | .017 | 0.017 |
| IL-1α | 1.7 | .047 | 0.060 | 11.0 | .000 | 0.000 | 6.6 | .000 | 0.000 |
| IL-12 | 1.7 | .010 | 0.019 | 6.6 | .000 | 0.000 | 3.9 | .000 | 0.000 |
| TNF-α | 1.7 | .008 | 0.016 | 7.7 | .000 | 0.000 | 4.6 | .000 | 0.000 |
| IL-16 | 1.6 | .003 | 0.007 | 5.3 | .000 | 0.000 | 3.2 | .000 | 0.000 |
| IL-2 | 1.6 | .037 | 0.051 | 5.3 | .000 | 0.000 | 3.3 | .000 | 0.000 |
| IL-13 | 1.6 | .013 | 0.023 | 4.6 | .000 | 0.000 | 2.9 | .000 | 0.000 |
| IL-15 | 1.6 | .014 | 0.023 | 4.4 | .000 | 0.000 | 2.8 | .000 | 0.000 |
| GM-CSF | 1.5 | .058 | 0.068 | 5.3 | .000 | 0.000 | 3.4 | .000 | 0.000 |
| IFN-γ | 1.5 | .013 | 0.023 | 6.1 | .000 | 0.000 | 4.0 | .000 | 0.000 |
| HMGB-1 | 1.5 | .072 | 0.082 | 7.4 | .000 | 0.000 | 4.9 | .000 | 0.000 |
| TGF-β | 1.5 | .016 | 0.024 | 4.2 | .000 | 0.000 | 2.8 | .000 | 0.000 |
| MCSF | 1.5 | .050 | 0.061 | 5.6 | .000 | 0.000 | 3.8 | .000 | 0.000 |
| IL-4 | 1.5 | .155 | 0.165 | 5.1 | .000 | 0.000 | 3.5 | .001 | 0.001 |
| Eotaxin | 1.4 | .014 | 0.023 | 4.3 | .000 | 0.000 | 3.0 | .000 | 0.000 |
| Lactoferrin | 1.4 | .039 | 0.051 | 3.5 | .000 | 0.000 | 2.4 | .000 | 0.000 |
| IL-7 | 1.4 | .076 | 0.084 | 5.0 | .000 | 0.000 | 3.6 | .000 | 0.000 |
| IL-33 | 1.1 | .629 | 0.649 | 3.5 | .001 | 0.001 | 3.1 | .003 | 0.003 |
| IL-18 | 1.1 | .698 | 0.698 | 2.5 | .000 | 0.000 | 2.4 | .000 | 0.000 |
Microbial-associated intraamniotic inflammation vs no intraamniotic inflammation
The geometric mean amniotic fluid concentration for all 33 inflammatory-related analytes was significantly higher in patients with microbial-associated intraamniotic inflammation than in those without intraamniotic inflammation (q value, < 0.1; fold change, > 1.5; Table 3 ). IL-6, IL-8, and macrophage inflammatory protein (MIP)-1β had the largest magnitude of change (fold changes, 115.4, 106, and 64.8, respectively; Table 3 ).
Microbial-associated intraamniotic inflammation vs sterile intraamniotic inflammation
Patients with microbial-associated intraamniotic inflammation had higher concentrations of inflammatory-related proteins than those with sterile intraamniotic inflammation with fold changes ranging from 2.3-12.3 for all 33 analytes ( Table 3 ). The fold changes for MIP-1β, MIP-1α, IL-1β, IL-6, and IL-8 were approximately 10 ( Table 3 ).
Differential correlation and network analysis
Differences in the correlation patterns of pairs of analytes were assessed among all the 3 groups of patients ( Figure 1 , A). The detailed results of this analysis for each pairwise comparison are given.
Sterile intraamniotic inflammation vs no intraamniotic inflammation
The inflammatory-related protein differential correlation network between the sterile intraamniotic inflammation and no intraamniotic inflammation groups is displayed in Figure 2 , A. Of the 33 analytes, 28 had at least 1 correlation significantly perturbed in patients with sterile intraamniotic inflammation compared to that of patients without intraamniotic inflammation. The perturbed correlations between pairs of analytes are represented by lines in Figure 2 A. Among 50 perturbed correlations shown in this Figure, 33 were positive (increased correlation), and 17 were negative (decreased correlation). The number of perturbed correlations (degree) was the largest for IL-1α, MIP-1α, and IL-1β (degrees, 12, 10, and 7, respectively). The average absolute difference in correlation ranged from 0.28 (for HMGB-1) to 0.61 (calgranulin-A), indicating a considerable magnitude of differential correlation between groups. For example, the correlation between IL-1β and MIP-1α was –0.28 ( P = .01) in the group without intraamniotic inflammation, but it was reversed to 0.61 ( P < .001) in the group with sterile intraamniotic inflammation (absolute difference in correlation of 0.61 – (–0.28) = 0.89; P < .001; Supplementary Table ). Of the 3 modules identified in this network, the MIP-1α and IL-1β modules included analytes with larger differences in concentration and higher degree than those in the other 2 modules. IL-1α and CXCL-9/monokine induced by gamma interferon had the largest degree in the second and third modules, respectively.
Microbial-associated intraamniotic inflammation vs no intraamniotic inflammation
The network of inflammatory-related protein differential correlations between patients with microbial-associated intraamniotic inflammation and those without intraamniotic inflammation is shown in Figure 2 , B. Of the 33 analytes, 31 had at least 1 correlation significantly perturbed in microbial-associated intraamniotic inflammation, compared to no intraamniotic inflammation. Similar to the comparison between sterile intraamniotic inflammation and no intraamniotic inflammation, IL-1β and MIP-1α belonged to the same module; IL-1α belonged to a different module. However, in contrast with the comparison between the group with sterile intraamniotic inflammation and the group without intraamniotic inflammation, the degree of IL-1β was the largest in this network (degree, 20). The total number of perturbed correlations (n = 113) in this comparison (microbial-associated intraamniotic inflammation vs no intraamniotic inflammation) was larger than in the previous comparison (n = 50; sterile intraamniotic inflammation vs no intraamniotic inflammation; Figure 2 , A). All perturbed correlations were increased in this comparison ( Figure 2 , B); this was the case for only some of the perturbed correlations in the contrast described in Figure 2 , A.
Microbial-associated intraamniotic inflammation vs sterile intraamniotic inflammation
There were 60 perturbed (all increased) correlations in microbial-associated intraamniotic inflammation compared with sterile intraamniotic inflammation ( Figure 2 , C). IL-4 and IL-33 had the largest number of disrupted correlations (degrees, 15 and 13, respectively); each of these 2 analytes belonged to a different module.
As the frequency with which patients received glucocorticoids in the group with sterile intraamniotic inflammation was lower than in the other 2 groups ( Table 1 ), we determined whether steroid administration could have been a confounder in the differential expression and differential correlation analyses. Since no significant association was found between analyte concentration and steroid administration in any of the 3 groups, we concluded that steroid administration was not a confounding factor in these analyses.
Results
Demographic characteristics
The characteristics of the study population stratified by the presence or absence of microorganisms in the amniotic cavity and intraamniotic inflammation were the subject of a detailed report in this Journal. Briefly, the frequencies of sterile intraamniotic inflammation, microbial-associated intraamniotic inflammation, and no intraamniotic inflammation were 26% (35/135), 11% (15/135), and 63% (85/135), respectively. The most frequent microorganisms identified in the amniotic cavity were Ureaplasma spp. Patients with sterile and microbial-associated intraamniotic inflammation had a significantly lower median gestational age at delivery than those without intraamniotic inflammation [26 weeks (interquartile range: IQR) 24-33 vs. 27 weeks (IQR 24-32 weeks) vs. 36 weeks (IQR 34-38 weeks); each P < 0.001; Table 2 ]. There was no significant difference in the median gestational age at delivery between patients with microbial-associated intraamniotic inflammation and those with sterile intraamniotic inflammation ( P = .6; Table 2 ). The amniotic fluid inflammatory response (IL-6, white blood cell count) was significantly greater in microbial-associated intraamniotic inflammation than in sterile intraamniotic inflammation [amniotic fluid IL-6 median: microbial-associated intraamniotic inflammation of 96 ng/mL (IQR, 17-266 ng/mL) vs sterile intraamniotic inflammation of 12 ng/mL (IQR, 5-21 ng/mL); P < .001; median white blood cell counts: 295 cells/mm 3 (IQR 2-960 cells/mm 3 ) vs 3 cells/mm 3 (IQR, 1-17 cells/mm 3 ); P = 0.018; Table 2 ]. Our study was conducted before the publication of studies reporting that vaginal progesterone reduces the rate of preterm delivery and neonatal morbidity; thus, none of our patients received vaginal progesterone.
| Variable | No intraamniotic inflammation (n = 85) | Sterile intraamniotic inflammation (n = 35) | P value (no intraamniotic inflammation vs sterile intraamniotic inflammation) | Microbial-associated intraamniotic inflammation (n = 15) | P value | |
|---|---|---|---|---|---|---|
| No intraamniotic inflammation vs microbial associated intraamniotic inflammation | Sterile intraamniotic inflammation vs microbial associated intraamniotic inflammation | |||||
| Maternal age, y a | 23 (20–26) | 23 (20–26.2) | .8 | 24 (20–30) | .7 | .4 |
| Body mass index, kg/m 2 a | 23 (20–29) | 23 (20–32) | .6 | 27 (23–37) | .04 | .2 |
| Frequency of sonographic short cervix, % (n/N) | 16.5 (14/85) | 11.8 (10/85) | .04 | 20 (3/15) | .35 | .9 |
| Antenatal corticosteroid administration, % (n/N) | 45 (37/82) b | 20 (7/35) | .012 | 46.7 (7/15) | 1 | .06 |
| Gestational age at amniocentesis, wk a | 32 (29–33) | 25 (23–32) | < .001 | 26 (23–32) | .006 | .83 |
| Amniotic fluid | ||||||
| White blood cells, cells/mm 3 a | 1 (0–5) | 3 (1–17) | .007 | 295 (2–960) | < .001 | .018 |
| Glucose, mg/dL a | 29 (24–34) | 22 (18–28) | .001 | 11 (10–20) | < .001 | .002 |
| Interleukin-6, ng/mL a | 0.8 (0.5–1.1) | 12 (5–21) | < .001 | 96 (17–266) | < .001 | < .001 |
| Gestational age at delivery, wk a | 36 (34–38) | 27 (24–32) | < .001 | 26 (24–33) | < .001 | .64 |
| Composite neonatal morbidity, % (n) c | 11 (9) | 68 (24) | < .001 | 67 (10) | < .001 | 1.0 |
| Acute placental inflammation, % (n/N) d , e | 22.5 (18/80) | 61 (19/31) | < .001 | 79 (11/14) | < .001 | .14 |
| Acute histologic chorioamnionitis, % (n/N) | 21 (17/80) | 58 (18/31) | < .001 | 79 (11/14) | < .001 | .04 |
| Funisitis, % (n/N) | 13 (10/80) | 29 (9/31) | .06 | 57 (8/14) | < .001 | .26 |
a Data are given as median (interquartile range)
b Data were not available in 3 patients
c Composite neonatal morbidity: the presence of respiratory distress syndrome, bronchopulmonary dysplasia, grade III or IV intraventricular hemorrhage, periventricular leukomalacia, proven neonatal sepsis, and necrotizing enterocolitis or perinatal death
d Acute placental inflammation: acute histologic chorioamnionitis and/or acute funisitis
e Acute placental inflammation was calculated over a total of 125 specimens.
Inflammatory-related protein concentrations among the subgroups with preterm labor and intact membranes
Sterile intraamniotic inflammation vs no intraamniotic inflammation
The geometric mean amniotic fluid concentration for all 33 inflammatory-related analytes was higher in patients with sterile intraamniotic inflammation than in those without intraamniotic inflammation (fold change range, 1.1-11.4). The differences were significant for 27 of the 33 analytes (q-value, <0.1; fold change, >1.5; Table 3 ). The largest fold changes were observed for IL-6 and IL-8 (10.6 and 11.4, respectively).
| Proteins | Sterile intraamniotic inflammation vs no intraamniotic inflammation | Microbial-associated intraamniotic inflammation vs no intraamniotic inflammation | Microbial-associated intraamniotic inflammation vs sterile intraamniotic inflammation | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Fold change | P value | Q value | Fold change | P value | Q value | Fold change | P value | Q value | |
| IL-8 | 11.4 | .000 | 0.000 | 106.0 | .000 | 0.000 | 9.3 | .000 | 0.000 |
| IL-6 | 10.6 | .000 | 0.000 | 115.4 | .000 | 0.000 | 10.9 | .000 | 0.000 |
| MIP-1β | 5.3 | .000 | 0.000 | 64.8 | .000 | 0.000 | 12.3 | .000 | 0.000 |
| MCP-1 | 3.8 | .000 | 0.000 | 18.5 | .000 | 0.000 | 4.8 | .000 | 0.000 |
| MIP-1α | 3.4 | .000 | 0.000 | 39.8 | .000 | 0.000 | 11.6 | .000 | 0.000 |
| Calgranulin C | 3.1 | .000 | 0.000 | 12.0 | .000 | 0.000 | 3.9 | .000 | 0.000 |
| IL-1β | 2.8 | .002 | 0.006 | 30.6 | .000 | 0.000 | 11.1 | .000 | 0.000 |
| RANTES | 2.5 | .001 | 0.002 | 6.6 | .000 | 0.000 | 2.6 | .010 | 0.010 |
| MIP-3α | 2.5 | .000 | 0.000 | 10.9 | .000 | 0.000 | 4.4 | .000 | 0.000 |
| Gro-α/CXCL1 | 2.4 | .000 | 0.000 | 8.7 | .000 | 0.000 | 3.6 | .000 | 0.000 |
| Calgranulin A | 2.1 | .003 | 0.007 | 15.2 | .000 | 0.000 | 7.2 | .000 | 0.000 |
| IL-10 | 2.1 | .001 | 0.004 | 12.9 | .000 | 0.000 | 6.3 | .000 | 0.000 |
| MIG | 1.8 | .003 | 0.007 | 4.6 | .000 | 0.000 | 2.5 | .001 | 0.001 |
| ITAC/CXCL11 | 1.8 | .000 | 0.001 | 4.6 | .000 | 0.000 | 2.6 | .000 | 0.000 |
| IP-10/CXCL10 | 1.8 | .020 | 0.028 | 4.0 | .000 | 0.000 | 2.3 | .017 | 0.017 |
| IL-1α | 1.7 | .047 | 0.060 | 11.0 | .000 | 0.000 | 6.6 | .000 | 0.000 |
| IL-12 | 1.7 | .010 | 0.019 | 6.6 | .000 | 0.000 | 3.9 | .000 | 0.000 |
| TNF-α | 1.7 | .008 | 0.016 | 7.7 | .000 | 0.000 | 4.6 | .000 | 0.000 |
| IL-16 | 1.6 | .003 | 0.007 | 5.3 | .000 | 0.000 | 3.2 | .000 | 0.000 |
| IL-2 | 1.6 | .037 | 0.051 | 5.3 | .000 | 0.000 | 3.3 | .000 | 0.000 |
| IL-13 | 1.6 | .013 | 0.023 | 4.6 | .000 | 0.000 | 2.9 | .000 | 0.000 |
| IL-15 | 1.6 | .014 | 0.023 | 4.4 | .000 | 0.000 | 2.8 | .000 | 0.000 |
| GM-CSF | 1.5 | .058 | 0.068 | 5.3 | .000 | 0.000 | 3.4 | .000 | 0.000 |
| IFN-γ | 1.5 | .013 | 0.023 | 6.1 | .000 | 0.000 | 4.0 | .000 | 0.000 |
| HMGB-1 | 1.5 | .072 | 0.082 | 7.4 | .000 | 0.000 | 4.9 | .000 | 0.000 |
| TGF-β | 1.5 | .016 | 0.024 | 4.2 | .000 | 0.000 | 2.8 | .000 | 0.000 |
| MCSF | 1.5 | .050 | 0.061 | 5.6 | .000 | 0.000 | 3.8 | .000 | 0.000 |
| IL-4 | 1.5 | .155 | 0.165 | 5.1 | .000 | 0.000 | 3.5 | .001 | 0.001 |
| Eotaxin | 1.4 | .014 | 0.023 | 4.3 | .000 | 0.000 | 3.0 | .000 | 0.000 |
| Lactoferrin | 1.4 | .039 | 0.051 | 3.5 | .000 | 0.000 | 2.4 | .000 | 0.000 |
| IL-7 | 1.4 | .076 | 0.084 | 5.0 | .000 | 0.000 | 3.6 | .000 | 0.000 |
| IL-33 | 1.1 | .629 | 0.649 | 3.5 | .001 | 0.001 | 3.1 | .003 | 0.003 |
| IL-18 | 1.1 | .698 | 0.698 | 2.5 | .000 | 0.000 | 2.4 | .000 | 0.000 |
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