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Journal of Perinatal Medicine

Official Journal of the World Association of Perinatal Medicine

Editor-in-Chief: Dudenhausen, MD, FRCOG, Joachim W.

Editorial Board Member: / Bancalari, Eduardo / Greenough, Anne / Genc, Mehmet R. / Chervenak, Frank A. / Chappelle, Joseph / Bergmann, Renate L. / Bernardes, J.F. / Bevilacqua, G. / Blickstein, Isaac / Cabero Roura, Luis / Carbonell-Estrany, Xavier / Carrera, Jose M. / D`Addario, Vincenzo / D'Alton, MD, Mary E. / Dimitrou, G. / Grunebaum, Amos / Hentschel, Roland / Köpcke, W. / Kawabata, Ichiro / Keirse, Marc J.N.C. / Kurjak M.D., Asim / Lee, Ben H. / Levene, Malcolm / Lockwood, Charles J. / Marsal, Karel / Makatsariya, Alexander / Nishida, Hiroshi / Papp, Zoltán / Pejaver, Ranjan Kumar / Pooh, Ritsuko K. / Reiss, Irwin / Romero, Roberto / Saugstad, Ola D. / Schenker, Joseph G. / Sen, Cihat / Seri, Istvan / Vetter, Klaus / Winn, Hung N. / Young, Bruce K. / Zimmermann, Roland

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Volume 42, Issue 1 (Jan 2014)

Issues

The peripheral whole-blood transcriptome of acute pyelonephritis in human pregnancya

Ichchha Madan
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Nandor Gabor Than
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Roberto Romero
  • Corresponding author
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
  • Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA
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/ Piya Chaemsaithong
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Jezid Miranda
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Adi L. Tarca
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Computer Science, Wayne State University, Detroit, MI, USA
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/ Gaurav Bhatti
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Computer Science, Wayne State University, Detroit, MI, USA
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/ Sorin Draghici / Lami Yeo
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Moshe Mazor
  • Department of Obstetrics and Gynecology, Soroka University Medical Center, School of Medicine, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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/ Sonia S. Hassan
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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/ Tinnakorn Chaiworapongsa
  • Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Detroit, MI, and Bethesda, MD, USA
  • Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
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Published Online: 2013-11-30 | DOI: https://doi.org/10.1515/jpm-2013-0085

Abstract

Objective: Human pregnancy is characterized by activation of the innate immune response and suppression of adaptive immunity. The former is thought to provide protection against infection for the mother, and the latter, tolerance against paternal antigens expressed in fetal cells. Acute pyelonephritis is associated with an increased risk of acute respiratory distress syndrome and sepsis in pregnant (vs. nonpregnant) women. The objective of this study was to describe the gene expression profile (transcriptome) of maternal whole blood in acute pyelonephritis.

Method: A case-control study was conducted to include pregnant women with acute pyelonephritis (n=15) and women with a normal pregnancy (n=34). Affymetrix HG-U133 Plus 2.0 arrays (Affymetrix, Santa Clara, CA, USA) were used for gene expression profiling. A linear model was used to test the association between the presence of pyelonephritis and gene expression levels while controlling for white blood cell count and gestational age. A fold change of 1.5 was considered significant at a false discovery rate of 0.1. A subset of differentially expressed genes (n=56) was tested with real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) (cases, n=19; controls, n=59). Gene ontology and pathway analyses were applied.

Results: A total of 983 genes were differentially expressed in acute pyelonephritis: 457 were upregulated and 526 were downregulated. Significant enrichment of 300 biological processes and 63 molecular functions was found in pyelonephritis. Significantly impacted pathways in pyelonephritis included (a) cytokine-cytokine receptor interaction, (b) T-cell receptor signaling, (c) Jak-STAT signaling, and (d) complement and coagulation cascades. Of 56 genes tested by qRT-PCR, 48 (85.7%) had confirmation of differential expression.

Conclusion: This is the first study of the transcriptomic signature of whole blood in pregnant women with acute pyelonephritis. Acute infection during pregnancy is associated with the increased expression of genes involved in innate immunity and the decreased expression of genes involved in lymphocyte function.

Keywords: Adaptive immunity; high-dimensional biology; infection during pregnancy; innate immunity; mRNA; PAX gene; urinary tract infection

Introduction

Pregnancy is characterized by the activation of the innate immune response and suppression of adaptive immunity [1, 4, 10, 20, 21, 54, 57, 60, 73, 77–79, 88, 90, 101, 106, 107, 129–131, 133, 134, 137, 144]. This is thought to provide protection against infection for the mother and to promote tolerance of the fetal semi-allograft [1, 4, 10, 13, 20, 21, 54, 57, 60, 73, 77–80, 88, 90, 101, 104–108, 110, 120, 129–134, 137, 144].

The changes in the innate immune response in pregnancy include an increase in the numbers of neutrophils as well as phenotypic and metabolic alterations consistent with leukocyte activation [88, 106, 107]. Despite these physiological changes, pregnant women are more susceptible to the deleterious effects of microbial products than nonpregnant women [46, 81, 84, 101]. Moreover, pregnant animals develop a generalized Schwartzman reaction after a single injection of endotoxin, whereas nonpregnant animals require a priming dose of endotoxin and then a second injection [81–83]. We have attributed this to the physiological activation of innate immunity.

Acute pyelonephritis is a frequent complication of pregnancy [29, 49, 56, 75, 95, 111] and accounts for 12% of all antepartum admissions to an intensive care unit for sepsis [111]. Moreover, acute pyelonephritis during pregnancy can lead to preterm delivery [29, 43, 56, 58, 63, 74, 102, 109] and is more likely to be complicated by acute respiratory distress syndrome (ARDS) [5, 16, 17, 23–27, 33, 45, 49, 56, 66, 97, 116, 136, 147], sepsis [12, 49, 56], septic shock [28, 115], anemia [49, 56], and transient renal dysfunction [40, 49] than acute pyelonephritis in nonpregnant patients. The reasons for this increased susceptibility to microbial products remain unknown. However, acute pyelonephritis during pregnancy has been associated with changes in maternal blood concentrations of soluble cluster of differentiation (CD) 30 (an index of Th2 immune response) [61], adipocytokines (retinol-binding protein 4 [141], adiponectin [70], visfatin [71], and resistin [72]), T-cell chemokines (C-X-C motif chemokine 10, CXCL-10) [41], complement products (C5a [117] and fragment Bb [118]), protein Z [92], and soluble tumor necrosis factor-related apoptosis inducing ligand (TRAIL) [18].

Transcriptome analysis has been used to gain insight into the pathophysiology of disease states and the identification of biomarkers in many disciplines, including obstetrics [37, 42, 50, 56, 67, 76, 93, 99, 100, 113, 121, 135, 142, 145, 148]. The gene expression profiles of peripheral blood have shown promising results in elucidating the mechanisms of other disorders such as multiple sclerosis [2], rheumatoid arthritis [7, 139], sepsis [126, 127], and cancer [9, 62, 69, 138]. The transcriptomic profile of peripheral blood leukocytes after intravenous administration of bacterial endotoxin to healthy human subjects has been characterized [14, 123]. However, the peripheral whole-blood transcriptome of acute infection in human pregnancy has not been studied.

The objective of this study was to characterize the transcriptome of whole blood in pregnant women with acute pyelonephritis.

Materials and methods

Study design and sample collection

A cross-sectional study was conducted by searching our clinical database and bank of biological samples, including patients in the following groups: (1) normal pregnancy (n=34) and (2) acute pyelonephritis (n=15). Patients with multiple gestations and fetal anomalies were excluded. The normal pregnant control group consisted of women who were not in labor, without obstetrical, medical, or surgical complications of pregnancy, and had blood samples collected within the same gestational age window as patients with pyelonephritis. Pyelonephritis was diagnosed in the presence of fever (temperature ≥38°C), clinical signs of an upper urinary tract infection (e.g., flank pain, costovertebral angle tenderness), pyuria, and a positive urine culture for microorganisms.

All patients provided written informed consent for the collection and use of samples for research purposes under the protocols approved by the Institutional Review Boards of Wayne State University and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services.

RNA preparation

Maternal peripheral venous blood was collected at the time of routine clinical blood draw into PAXgene blood RNA tubes (PreAnalytiX GmbH, distributed by Becton Dickinson Company, Franklin Lakes, NJ, USA). Blood tubes were maintained initially at room temperature for 24 h and then frozen at –70°C until further processing. Blood lysates were reduced to pellets by centrifugation, washed, and resuspended in buffer. Proteins were removed by Proteinase K digestion, and cellular debris were removed by centrifugation through a PAXgene Shredder spin column (PreAnalytiX GmbH). RNA was semi-precipitated with ethanol and selectively bound to the silica membrane of a PAXgene spin column (PreAnalytiX GmbH). The membrane was treated with DNase I to remove any residual DNA and washed, and the purified total RNA was eluted in nuclease-free water. Purified total RNA was quantified by UV spectrophotometry using a DropSense96 Microplate Spectrophotometer (Trinean, Micronic North America LLC, McMurray, PA, USA), and RNA purity was assessed based on the A260/A280 and A260/A230 ratios. An aliquot of the RNA was assessed using the RNA 6000 Nano Assay for the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The electrophoretogram, RNA integrity number, and the ratio of the 28S/18S RNA bands were examined to determine the overall quality of the RNA.

Microarray analysis

Peripheral blood samples were profiled using Affymetrix GeneChip HG-U133 Plus 2.0 arrays. Briefly, RNA was amplified using the Ovation RNA Amplification System V2 (NuGEN Technologies, San Carlos, CA, USA). cDNA was synthesized using the Ovation buffer mix, first-strand enzyme mix, and first-strand primer mix with 5 μL (∼20 ng) of total RNA in specified thermal cycler protocols according to the manufacturer’s instructions. Amplification and purification of the generated cDNA was performed by combining SPIA Buffer Mix, Enzyme Mix, and nuclease-free water with the products of the second-strand cDNA synthesis reactions in prespecified thermal cycler programs. The optical densities of the amplified cDNA products were obtained to demonstrate product yield and verified purity. Fragmentation and labeling were done using the FL-Ovation cDNA Biotin Module V2 (NuGEN Technologies). In the primary step, a combined chemical and enzymatic fragmentation process was used to produce cDNA products in the 50- to 100-base pair range. Fragmented cDNA products were then biotin-labeled using the Encore Biotin Module (NuGEN Technologies). All reactions were carried out according to the manufacturer’s protocols. Amplified, fragmented, and biotin-labeled cDNAs were used for hybridization cocktail assembly, and then hybridized to the Affymetrix GeneChip HG-U133 Plus 2.0 arrays according to the Affymetrix standard protocol.

Quantitative reverse transcription-polymerase chain reaction

A subset of differentially expressed genes (n=56) was selected for validation in an extended set of samples (pyelonephritis cases, n=19; controls, n=59) using the Biomark high-throughput real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) system (Fluidigm, San Francisco, CA, USA) based on their rank in the list of all differentially expressed genes as well as biological plausibility. Briefly, the Invitrogen Superscript III First-Strand Synthesis System (Invitrogen, Life Technologies, Carlsbad, CA, USA) was used to generate complementary DNA. Pre-amplification procedures included combining 1.25 μL cDNA with 2.5 μL TaqMan PreAMP Mastermix and 1.25 μL pooled assay mix. The reaction was performed with a thermal cycler for one cycle at 95°C for 10 min and 14 cycles at 95°C for 15 s and 60°C for 4 min. After cycling, the reaction was diluted 1:5 by ddH2O to a final volume of 25 μL. The Fluidigm 96.96 Dynamic Array chip was used to perform the next step qRT-PCR assays. The 96.96 array chip was primed in an integrated fluidic circuit (IFC) controller with control fluid. After priming, 2.5-μL 20× TaqMan gene expression assays (Applied Biosystems) was mixed with a 2.5-μL 2× assay loading reagent (Fluidigm) and loaded into the assay inlet on the 96.96 array chip. A total of 2.25 μL preamplified cDNA was mixed with 2.5 μL TaqMan Universal PCR master mix (Applied Biosystems) and 0.25 μL 20× sample loading reagent (Fluidigm) and loaded into the sample inlet on the chip. The chip was returned to the IFC controller for loading. After loading, the chip was placed in the Biomark System to run the reactions. The cycle threshold (Ct) value of each reaction was obtained with the Fluidigm RT-PCR analysis software.

Statistical analysis

Analysis for microarray and real-time quantitative polymerase chain reaction data

A linear model was used to test the association between pyelonephritis and gene expression levels determined by microarray analysis while controlling for white blood cell (WBC) count [32, 35, 146] and gestational age. Moderated t-tests [114] were used to assess the significance of the coefficients in the linear model. Probe sets with false discovery rate-adjusted P-values (q-value) of <0.1 and a fold change of >1.5 were considered significant. Pathway analysis was performed on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database with an overrepresentation analysis [30] and the signal pathway impact analysis (SPIA) [31, 128]. The SPIA is a systems biology approach that takes into account the gene-gene signaling interactions as well as the magnitude and direction of gene expression changes to determine significantly impacted pathways [128]. Gene ontology analysis was performed using the GOstats package of Bioconductor [34].

The same statistical model was used for qRT-PCR data, and the –ΔCt values were used as a surrogate for log2 gene expression levels. qRT-PCR results were considered significant when P<0.05 with a one tailed t-test, using the direction of expression change obtained from the microarray data.

Mann-Whitney U- and χ2-tests were used to compare the differences in demographics and clinical characteristics between patients with acute pyelonephritis and the control group. SPSS (version 15.0; SPSS, Chicago, IL, USA) was used for the analysis of demographic and clinical characteristic data. A probability value of <0.05 was considered significant.

Results

The demographic and clinical characteristics of the study population are displayed in Table 1. Patients with acute pyelonephritis had a significantly lower median gestational age at venipuncture but higher WBC count in both the microarray and qRT-PCR study (P<0.0001 for each). Therefore, we adjusted gene expression data for these two covariates in the microarray and qRT-PCR data analyses. Patients with pyelonephritis had a significantly higher neutrophil count (P<0.001 for each study) and lower lymphocyte count (microarray, P<0.05; qRT-PCR, P=0.001) than controls. Among patients with acute pyelonephritis (in the qRT-PCR experiment), 12 (63.2%) had a positive urine culture for Escherichia coli, 4 (21.1%) for Klebsiella pneumonia, and the rest were positive for Enterococcus faecalis (n=1), Enterobacter (n=1), and lactose-fermenting Gram-negative bacilli (n=1).

Table 1

Demographic and clinical characteristics of the study groups.

Microarray analysis

A total of 1309 probe sets corresponding to 983 unique genes demonstrated a differential expression between the two groups (q-value <0.1; fold change >1.5). A total of 457 genes were upregulated and 526 genes were downregulated in acute pyelonephritis. Table 2 shows the top 100 probe sets with differential expression between the study groups ranked by P-value.

Table 2

Top 100 probe sets differentially expressed between acute pyelonephritis and normal controls.

A volcano plot (Figure 1A) displays the differential expression of all the annotated probe sets on the microarray as effect size vs. significance of expression change. An unsupervised principal component analysis (PCA)-based visualization of the microarray data (using all probes on the array, Figure 1B) revealed the between-group differences and no outlier samples.

Volcano plot and three dimensional principal component analysis (PCA) plot. (A) The volcano plot shows probability values of all probes in the microarray plotted against the fold change. In this figure, the log (base 10) of the false discovery rate-adjusted probability values are plotted against the log (base 2) of fold change between patients with pyelonephritis and normal controls. On the Y-axis, values higher than the gray-line threshold represent significant probes with an adjusted probability value of <0.1. On the X-axis, values outside the red lines represent fold change >1.5. (B) The three-dimensional PCA plot demonstrates a degree of segregation between women with acute pyelonephritis and normal controls. Blue dots indicate individual samples from the normal control group, whereas black dots represent individual samples from the acute pyelonephritis group.
Figure 1

Volcano plot and three dimensional principal component analysis (PCA) plot.

(A) The volcano plot shows probability values of all probes in the microarray plotted against the fold change. In this figure, the log (base 10) of the false discovery rate-adjusted probability values are plotted against the log (base 2) of fold change between patients with pyelonephritis and normal controls. On the Y-axis, values higher than the gray-line threshold represent significant probes with an adjusted probability value of <0.1. On the X-axis, values outside the red lines represent fold change >1.5. (B) The three-dimensional PCA plot demonstrates a degree of segregation between women with acute pyelonephritis and normal controls. Blue dots indicate individual samples from the normal control group, whereas black dots represent individual samples from the acute pyelonephritis group.

To gain further insight into the biology of the differences in the transcriptome of whole blood between pregnant women with acute pyelonephritis and controls, gene ontology analysis was used. Significant enrichment of 300 biological processes (Table 3) was found in acute pyelonephritis, including the innate immune response, signal transduction, regulation of cytokine production, regulation of adaptive immune response, immunoglobulin (Ig)-mediated immune response, T-cell immunity, B- and T-cell differentiation, positive regulation of leukocyte activation and proliferation, positive regulation of T-cell receptor signaling pathway, and blood coagulation. Moreover, gene ontology analysis revealed that 63 molecular functions were associated with differentially expressed genes in acute pyelonephritis (Table 4).

Table 3

Gene ontology analysis: top 100 biological processes with enrichment in acute pyelonephritis.

Table 4

Gene ontology analysis: 63 molecular functions associated with differentially expressed genes in acute pyelonephritis.

Pathway analysis of differentially expressed genes was undertaken with an overrepresentation method and the SPIA method. Using the overrepresentation method, three KEGG pathways were significantly impacted (q-value <0.1) in the comparison between the study groups (Table 5): (1) “primary immunodeficiency”, (2) “hematopoietic cell lineage”, and (3) “T-cell receptor signaling pathway”. SPIA identified four pathways that were significantly impacted (Table 6). Three of these pathways had not been identified by the overrepresentation method (the “Jak-STAT signaling pathway”, “cytokine-cytokine receptor interaction”, and “complement and coagulation cascade”) (Table 6, Figure 2).

Table 5

Pathway analysis using the overrepresentation method.

Table 6

Pathway analysis using the SPIA method.

Two-dimensional plot illustrates the relationship between the two types of evidence considered by SPIA. The X-axis shows the overrepresentation evidence (–log [P-value]), whereas the Y-axis shows the perturbation evidence (–log [perturbation P-value]). Each pathway is represented by a point. Pathways above the oblique red line (red dots) are significant at 5% after Bonferroni correction; pathways (blue dots and red dots) above the oblique blue line are significant at 5% after false discovery rate correction. The vertical and horizontal thresholds represent the same corrections for the two types of evidence considered individually.
Figure 2

Two-dimensional plot illustrates the relationship between the two types of evidence considered by SPIA.

The X-axis shows the overrepresentation evidence (–log [P-value]), whereas the Y-axis shows the perturbation evidence (–log [perturbation P-value]). Each pathway is represented by a point. Pathways above the oblique red line (red dots) are significant at 5% after Bonferroni correction; pathways (blue dots and red dots) above the oblique blue line are significant at 5% after false discovery rate correction. The vertical and horizontal thresholds represent the same corrections for the two types of evidence considered individually.

Quantitative real-time reverse transcription-polymerase chain reaction

qRT-PCR was performed on an extended set of samples (normal controls, n=59; acute pyelonephritis, n=19) to validate microarray results. Of the 56 genes selected for testing from the differentially expressed gene list in the microarray, we confirmed differential expression (in terms of both direction and significance) in 48 (85.7%) of the tested genes by qRT-PCR (Table 7).

Table 7

Comparison of microarray gene expression data to qRT-PCR gene expression data of selected genes in an extended sample set.

Discussion

Principal findings of the study

We report for the first time the transcriptome of maternal whole blood in acute pyelonephritis in pregnancy. The main findings are the following: (1) There was a gene expression signature consistent with a systemic maternal inflammatory response; (2) the transcriptome of peripheral WBCs in pyelonephritis was similar to that reported after intravenous endotoxin administration to nonpregnant individuals [14]. In both conditions, there was upregulation of genes involved in innate immune responses and downregulation of those involved in lymphocyte function. (3) We observed an upregulated expression of genes involved in the induction of apoptosis and downregulation of those with anti-apoptotic properties.

Local and systemic immune responses in infection of the urinary tract during pregnancy

The innate limb of the immune response represents the first line of defense against bacterial invasion of the urinary tract [91, 119]. Urinary epithelial cells are the first to enter into contact with microorganisms. Bacterial attachment can trigger exfoliation of bacteria-laden epithelial cells, reconstitution of the urothelium, and an inflammatory response [47, 85–87, 143]. Microorganisms and their products are recognized by pattern recognition receptors, and this leads to the production of chemokines, cytokines, and antimicrobial peptides, and the generation of an acute inflammatory response [47, 85–87, 91, 119, 143]. Neutrophils play an important role in host defense in the urinary tract, and they appear in the bladder and kidney within hours of transurethral inoculation with uropathogenic E. coli [38, 48]. Disruption of neutrophil chemotaxis in animals with a gene deletion for the interleukin (IL) 8 receptor homologue [38] or depletion of neutrophils with a granulocyte-specific antibody [48] can lead to an increased bacterial burden in the bladder and kidney [38, 48] as well as bacteremia [38].

In addition to the local host defense in the urinary tract, acute pyelonephritis is also associated with a systemic inflammatory response that is characterized by fever, increased serum concentrations of cytokines (IL-6, IL-8) and acute phase reactant proteins, and an elevated WBC and neutrophil count [68]. Consistent with this, we found in the current study that the median WBC count of patients with pyelonephritis was higher than that of pregnant women with a normal pregnancy outcome (Table 1). We had previously reported that the maternal serum concentrations of a panel of chemokines and cytokines are also higher in this condition than in normal pregnant women [19]. Indeed, the median maternal serum concentrations of IL-8, TNF-α, IL-6, IL-7, IL-10, and interferon (IFN) γ were higher in pregnant women with acute pyelonephritis than in gestational age-matched normal pregnant women [19]. Moreover, acute pyelonephritis in pregnancy was found to be associated with higher median maternal serum concentrations of the pro-inflammatory chemokine CXCL-10 (also known as IP-10) [41] and higher median maternal plasma concentrations of the pro-inflammatory adipokine resistin [72] than in normal pregnant women. Resistin concentrations are considered an index of the severity of sepsis and a prognostic factor for survival in critically ill nonpregnant patients [55, 72, 122]. Of interest, median maternal plasma concentrations of the anti-inflammatory adipokine adiponectin [70] were lower in patients with pyelonephritis than in normal pregnant women. We have also reported the activation of the complement system, a component of the innate immune system, in acute pyelonephritis in pregnancy, as the median plasma concentrations of complement fragment Bb [118] and complement C5a [117] are higher in pregnant patients with acute pyelonephritis than in normal pregnant women. Complement C5a is a potent chemoattractant for neutrophils, and can upregulate the activating IgG Fc receptors and downregulate the inhibitory IgG Fc receptors on leukocytes, linking the complement system and IgG Fc receptor effector pathways [112]. This is consistent with the observations made in the present study, in which we observed an upregulation of FCGR1A and FCGR1B expression in pregnant women with acute pyelonephritis. These genes encode for the high-affinity IgG Fc receptor (CD64), which is expressed on neutrophils and other myeloid cells and is involved in the binding of IgG1 and IgG3 [94]. Consistent with this finding, Naccasha et al. [88] reported higher expression of CD64 on granulocyte and monocyte surfaces (determined by flow cytometry as median mean channel brightness) in pregnant women with pyelonephritis than in normal pregnant women. Neutrophil CD64 has emerged as a biomarker for the diagnosis of bacterial infection [22, 64, 94], because resting neutrophils express very low levels of CD64, whereas the expression of CD64 is upregulated in the context of acute bacterial infections [94]. Using flow cytometry analysis of whole blood, a CD64 index (ratio of mean fluorescent intensity of the cell to the beads) of >1.66 in hospitalized patients had a 100% sensitivity and a 95% specificity in the identification of sepsis, defined as the combination of bacteremia and clinical signs of infection [39]. Meta-analysis of 13 studies showed a pooled sensitivity of 79% [95% confidence interval (CI), 70%–86%)] and a pooled specificity of 91% (95% CI, 85%–95%) in the diagnosis of bacterial infection [22]. No studies have addressed the value of this marker in the assessment of pyelonephritis during pregnancy.

Changes in the transcriptome of whole-blood leukocytes in acute pyelonephritis in pregnancy

This is the first report of the transcriptome of whole-blood cells in pregnant women with pyelonephritis. This snapshot of the global mRNA expression of peripheral blood leukocytes and subsequent pathway analyses revealed interesting features of the systemic inflammatory response to bacterial infection in human pregnancy. We found 1309 probe sets corresponding to 983 unique genes differentially expressed in pregnant women with pyelonephritis, of which 457 genes were upregulated and 526 were downregulated. Gene ontology analysis indicated that these findings were associated with 63 molecular functions enriched in leukocytes, many of them strongly related to the innate and adaptive immune responses (e.g., “C-C chemokine receptor activity”, “complement receptor activity”, MHC class I protein binding”, “immunoglobulin receptor activity”, “T-cell receptor binding”, “chemokine binding”, “scavenger receptor activity”, “peptide antigen binding”, “cytokine receptor binding”) (Table 4). In accordance, several of the most enriched biological processes in pyelonephritis during pregnancy are related to immune responses (e.g., “positive regulation of leukocyte activation”, “innate immune response”, “activation of immune response” “regulation of lymphocyte activation”, “inflammatory response”). Of interest, biological processes related to apoptosis (i.e., “positive regulation of apoptosis”, “positive regulation of cell death”) are also among the most enriched processes (Table 3).

To identify pathways significantly impacted in pyelonephritis during pregnancy, we applied two pathway analysis methods. The overrepresentation analysis method identified three KEGG pathways significantly impacted in pyelonephritis (“primary immunodeficiency”, “hematopoietic cell lineage”, “T-cell receptor signaling pathway”) (Table 5). The SPIA method, which takes also into account the gene-gene signaling interactions as well as the magnitude and direction of gene expression changes besides differential expression [31, 128], identified one pathway in common with the overrepresentation method (“T-cell receptor signaling pathway”) and three pathways that the overrepresentation method could not identify (the “Jak-STAT signaling pathway”, “cytokine-cytokine receptor interaction”, and “complement and coagulation cascade”) (Table 6). Importantly, all of these impacted pathways are related to immune responses, suggesting that the systemic inflammatory response elicited in pyelonephritis in pregnancy has a characteristic gene expression signature in peripheral blood leukocytes.

To get further insight into the cellular pathways of systemic inflammation in pyelonephritis in pregnancy, we compared transcriptomic changes in our study to those documented in systemic inflammation in response to bacterial endotoxin in nonpregnant individuals (see below).

Changes in the transcriptome of whole-blood leukocytes from nonpregnant individuals after treatment with bacterial endotoxin

The transcriptome of peripheral blood leukocytes of nonpregnant volunteers has been studied after the administration of a single dose of bacterial endotoxin [14, 123]. Calvano et al. [14] reported dysregulation of 3714 genes in whole-blood cells at 2, 4, and 9 h after endotoxin administration and noted that gene expression returned to baseline by 24 h after endotoxin injection. The endotoxin quickly and transiently activated genes involved in the innate immune response, and after an initial pro-inflammatory phase, a self-limiting counter-regulatory response followed, with eventual resolution of gene expression changes within a day of endotoxin administration. Specifically, there was an increased expression of pro-inflammatory cytokines and chemokines (e.g., IL1A, IL1B, IL8, TNF) and NFκB family transcription factors within 2–4 h of endotoxin treatment [14]. There was upregulation of transcription factors critical in both the initiation and the containment of an innate immune response [e.g., signal transducer and activators of transcription (STAT) genes, suppressor of cytokine signaling 3, SOCS3], which was observed within 4–6 h of endotoxin administration. There was also increased expression of genes encoding membrane-bound and secreted proteins that limit the inflammatory response (e.g., IL1R2, IL1RAP, IL10) [14].

Similar observations were made by Talwar et al. [123], who investigated temporal gene expression changes in peripheral blood mononuclear cells and whole-blood cells from nonpregnant volunteers after a single dose of endotoxin. An upregulation of genes associated with pattern recognition receptors, intracellular signaling, cell mobility, and defense function was reported. The largest change in gene expression occurred 6 h after endotoxin treatment, with changes returning to baseline within 24 h [123]. Collectively, these results suggest that leukocyte response to bacterial products include a short pro-inflammatory phase followed by a counter-regulatory phase and resolution of inflammation [14, 123].

Similarities in the expression of innate immune genes in pregnant women with acute pyelonephritis and nonpregnant individuals after endotoxin administration

As the microarray data set of whole-blood leukocytes after endotoxin administration was available online from the study of Calvano et al. [14], we compared such data set with our findings (this comparison included only those genes from the study of Calvano et al. [14] that were differentially expressed at three to five time points after endotoxin administration). We found that 296 of the 983 genes in our study changed in the same direction as that of the Calvano et al. study [14] (Table 1).

Differentially expressed genes involved in the innate immune response in both studies were mainly upregulated (Table 8). Among the functions of the proteins encoded by these genes, the following groups emerged: (a) cell adhesion and cell-cell signaling (CD44, CLEC4D, CLEC4E, CLEC5A, ICAM1), (b) activation and/or differentiation of macrophages (CEBPD), (c) inflammasome priming (CASP1, CASP4, CASP5), (d) activation of the nuclear factor (NF) κB and mitogen-activated protein kinase (MAPK) pathways (IL18R1, IL18RAP, IRAK2, IRAK3), (e) cellular binding to particles and immune complexes that have activated complement (CR1), (f) phagocytosis and antibody-dependent cell-mediated cytotoxicity (FCAR, FCGR1A, FCGR1B, MARCO), and (g) breakdown of extracellular matrix and type IV and V collagens (MMP9). These results suggest that acute pyelonephritis during pregnancy elicits a host response similar to that induced by intravenous bacterial endotoxin in nonpregnant volunteers.

Table 8

Differentially expressed innate immune genes common in acute pyelonephritis during pregnancy and in bacterial endotoxin administration in nonpregnant individuals.

Similarities in the expression of genes involved in lymphocyte functions in pregnant women with acute pyelonephritis and nonpregnant individuals after endotoxin administration

SPIA pathway analysis of the commonly differentially expressed genes in pyelonephritis and in the endotoxin-induced model of acute bacterial infection revealed five impacted pathways in both conditions: (1) “T-cell receptor signaling pathway”, (2) “natural killer cell mediated cytotoxicity”, (3) “cytokine-cytokine receptor interaction”, (4) “RIG-I-like receptor signaling pathway”, and (5) “complement and coagulation cascades”. We observed that the pathways inhibited in pyelonephritis included those generally implicated in adaptive immune responses. This is consistent with the findings of Talwar et al. [123], who described the downregulation of T lymphocyte-associated genes after endotoxin administration. Moreover, differentially expressed genes involved in lymphocyte functions common in our study and in the study reported by Calvano et al. [14] were mainly downregulated (Table 9).

Table 9

Differentially expressed genes associated with lymphocyte function common in acute pyelonephritis during pregnancy and in bacterial endotoxin administration in nonpregnant individuals.

The decreased expression of these genes and the encoded proteins may result in impairment of (a) T-cell recognition of antigens displayed by antigen presenting cells (CD3D, CD3E, CD8A, CD8B, CD247), (b) T-cell chemotaxis and migration to inflamed tissues (CXCR3), (c) T-helper lineage development (GATA3, STAT4, TBX21), (d) T-cell activation, proliferation, development, signal transduction, survival, and cytokine production (CCR7, CD6, CD28, DPP4, IL23A, IL23R, IL2RB, IL5RA, IL9R, ITK, LCK, PRKCQ, TCF7, ZAP70), (e) generation and long-term maintenance of T cell immunity (CD27), (f) T-cell-mediated cytotoxicity (GNLY, GZMA), and (g) regulation of B-cell activation, V(D)J recombination, and Ig synthesis (CCR7, IL7R).

These observations are consistent with the findings derived from transcriptome analysis of patients with sepsis [65, 125]. By analyzing multiple microarray data sets, Lindig et al. [65] found that the upregulated gene ontology categories in patients with sepsis include those related to innate immune responses, whereas the downregulated categories include those related to adaptive immune responses. The systematic review of the transcriptomic data of 12 studies by Tang et al. [125] revealed reduced expression of genes associated with immune response in lymphocytes (e.g., CCR7, CD28, CXCR3, IL2RB, IL7R) and upregulation of genes limiting inflammatory responses (e.g., SOCS1, SOCS3), which also changed in the same direction in our study.

Immunosuppression in sepsis

Contrary to what was originally believed, sepsis does not represent a steady and uncontrolled systemic pro-inflammatory response [6, 51]. Some patients have a state consistent with immune suppression [51, 53, 140], which has been termed “immunoparalysis” [3, 53], characterized by a decreased Th1-like response [3, 51]. The initial pro-inflammatory state in sepsis is followed by a compensatory anti-inflammatory state, or in some cases, both pro-inflammatory and anti-inflammatory responses can occur at the onset of sepsis [51, 140]. The composition and direction of this complex systemic host response to infection depends on the load and virulence of the pathogen, the genetic characteristics of the host, and coexisting illnesses [6, 140].

Of importance, the majority of deaths occur in patients with sepsis who are immunosuppressed [53], and the prevention of immunosuppression improves the survival rate in animal models of sepsis [51]. The occurrence of the immunosuppression state has been attributed to the following[3, 11, 44, 51, 53, 98, 103, 140]: (1) an adaptive compensatory response characterized by increased expression of anti-inflammatory mediators (e.g., IL1RN, SOCS1, SOCS3) and the activation of T regulatory cells and myeloid derived suppressor cells, (2) apoptosis of T and B lymphocytes due to activation of Fas-Fas-ligand system and caspases as well as decreased expression and/or function of anti-apoptotic molecules (e.g., Bcl-2), (3) anti-inflammatory responses in phagocytic cells induced by the uptake of apoptotic immune cells, and (4) activation of a neuroinflammatory reflex through vagal nerve stimulation, which leads to acetylcholine secretion by a subset of T-helper lymphocytes and the subsequent suppression of proinflammatory cytokine release from acetylcholine receptor expressing macrophages.

Patients with sepsis may have a complex set of immunologic defects attributable to the cross-talk between specialized cells in the immune system that coordinate microbial eradication. For example, T lymphocytes play a pivotal role in the initial response to microbial infection because they produce IFN-γ, which activates macrophages [52, 53], and reduced Th1 function due to apoptotic cell death of T lymphocytes in sepsis leads to dampened cytokine production [52]. Indeed, the anti-inflammatory responses in sepsis lead to enhanced susceptibility to secondary infections [3, 6].

Differential expression of genes implicated in immunosuppression and apoptosis

We found upregulation of IL1RN (IL-1 receptor antagonist) and suppressors of cytokine signaling (SOCS1, SOCS3) in women with pyelonephritis in pregnancy – these findings are consistent with a compensatory anti-inflammatory response. Moreover, we found upregulation of FAS (CD95/Fas cell surface death receptor), which plays a central role in the apoptosis of lymphocytes in sepsis and in the pathogenesis of ARDS [36], a severe complication of pyelonephritis in pregnancy [5, 16, 17, 23–27, 33, 45, 49, 56, 66, 97, 116, 136, 147].

Consistent with the observation of increased apoptosis of lymphocytes in sepsis [3, 44, 51, 53, 98], we found upregulation of pro-apoptotic genes (CFLAR, PDCD1LG2) as well as downregulation of anti-apoptotic genes (BCL2, FAIM3) in cases of acute pyelonephritis (Table 10). Moreover, the expression of CD36 (thrombospondin receptor), which is involved in the phagocytosis of apoptotic cells, was increased in pyelonephritis during pregnancy. We also found that the median absolute lymphocyte count of patients with pyelonephritis was significantly lower than that of in controls in both the microarray (P<0.05) and qRT-PCR (P=0.001) populations in the current report (Table 1).

Table 10

Differentially expressed genes involved in apoptosis common in acute pyelonephritis during pregnancy and in bacterial endotoxin administration in nonpregnant individuals.

In contrast, the median absolute neutrophil count was higher in patients with pyelonephritis than in controls (P<0.001, Table 1). This finding is consistent with the well-known phenomenon of delayed apoptosis of neutrophils in sepsis [8, 96, 124]. Previous studies also reported a higher median maternal plasma concentration of visfatin [71], a pro-inflammatory adipokine that promotes delayed neutrophil apoptosis as well as a lower median maternal plasma concentration of TRAIL [18], one of the mediators responsible for neutrophil apoptosis, in patients with pyelonephritis in pregnancy than in controls.

Differences in gene expression patterns between pregnant women with acute pyelonephritis and nonpregnant individuals after endotoxin administration

There were 22 differentially expressed genes in our study that changed in the opposite direction from that reported by Calvano et al. [14]. In addition, there were 665 differentially expressed genes in our study that did not change in expression after bacterial endotoxin administration [14]. Enrichment analyses showed that these 665 genes play a role in “immune response”, “immune effector process”, “inflammatory response”, “lymphocyte activation”, and “response to viruses”, among other biological processes. These results suggest that, although the pathways fundamentally impacted in pyelonephritis during pregnancy and endotoxin challenge in nonpregnant women are similar, the increased susceptibility of pregnant women to microbial products [46, 81, 84, 101] may have a well-defined molecular basis, and such differences (qualitative and quantitative) may be responsible for the difference in nature of the immune response to microbial products or infection in pregnant women. This requires further study of nonpregnant patients with pyelonephritis.

The administration of a single intravenous dose of endotoxin has been used as a model to study the systemic effects of a microbial product (endotoxin) and assumed by many to represent a state similar to systemic infection. However, this experimental approach cannot be equated with intravenous administration of live bacteria or actual systemic infection in humans. Therefore, the comparison of our results in pregnant women with pyelonephritis to those reported by Calvano et al. [14] should be interpreted with caution. The findings reported herein can be considered to reflect real bacterial infection in pregnant women.

There are technical differences between our study and that of Calvano et al. [14]. (1) methods used in blood collection, leukocyte lysis, storage, and RNA isolation were not the same. Whole-blood samples were collected into PAX gene tubes in our study, whereas leukocyte separation by centrifugation was undertaken by Calvano et al. before RNA isolation. (2) Our study was cross-sectional, whereas blood was collected at several time points [before (0 h) and at 2, 4, 6, 9, and 24 h after endotoxin infusion] in the study of Calvano et al. [14]. (3) Our population had several bacteria identified in urine and/or blood, whereas nonpregnant volunteers in the study of Calvano et al. received a single dose of endotoxin [14]. (4) We adjusted our gene expression results as a function of WBC count, but this was not performed by Calvano et al. [14].

Differential expression of FAM20A and ETV7

The top three significantly upregulated probe sets in our study correspond to transcripts encoded by the FAM20A (family with sequence similarity 20, member A) gene. FAM20A belongs to an evolutionarily conserved family of three proteins (FAM20A, FAM20B, and FAM20C) secreted by hematopoietic cells [89]. FAM20A is a glycoprotein with high expression levels in hematopoietic tissues [89], especially in those cells committed to the granulocytic lineage [89]. Another gene involved in hematopoiesis and upregulated in pyelonephritis was ETV7 (encoding for ETS variant 7). The expression of ETV7 in normal and leukemic hematopoietic cells suggests an important role for this gene in normal hematopoietic development as well as in oncogenesis [15, 59]. As gene expression in our data was adjusted for WBC count, the results are not simply the reflection of a higher WBC count in patients with pyelonephritis but probably reflect enhanced hematopoiesis that involves the upregulation of these genes in response to acute microbial infection.

Strengths and limitations

This is the first study to characterize the transcriptome of whole blood in pregnant women with an acute episode of infection. A limitation of this study was that the differentially expressed genes identified reflect the changes in the total intracellular mRNA in whole blood. However, it is not possible to attribute these changes to a particular population of leukocytes or reticulocytes. Meanwhile, if we had attempted to separate WBCs before RNA isolation, artifacts derived from cell separation procedures may have been introduced.

Conclusions

This is the first report of the transcriptome of whole-blood cells in pregnant women with acute pyelonephritis. We found increased expression of genes involved in innate immunity and decreased expression of genes that participate in lymphocyte function. These findings are similar to the transcriptional changes reported in nonpregnant individuals exposed to bacterial endotoxin. However, we identified a set of differentially expressed genes that were unique in pyelonephritis during pregnancy. Our study provides necessary information to characterize the nature of a systemic inflammatory response in pregnant women. A major reason for this study is the interest in comparing conditions in which there is acute intravascular inflammation (such as preeclampsia) with that induced by microorganisms (such as pyelonephritis).

This research was supported, in part, by the Perinatology Research Branch, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services (NICHD/NIH), and, in part, with federal funds from NICHD/NIH under contract no. HHSN275201300006C.

References

  • [1]

    Abrahams VM, Straszewski-Chavez SL, Guller S, Mor G. First trimester trophoblast cells secrete Fas ligand which induces immune cell apoptosis. Mol Hum Reprod. 2004;10:55–63.CrossrefGoogle Scholar

  • [2]

    Achiron A, Grotto I, Balicer R, Magalashvili D, Feldman A, Gurevich M. Microarray analysis identifies altered regulation of nuclear receptor family members in the pre-disease state of multiple sclerosis. Neurobiol Dis. 2010;38:201–9.CrossrefGoogle Scholar

  • [3]

    Adib-Conquy M, Cavaillon JM. Compensatory anti-inflammatory response syndrome. Thromb Haemost. 2009;101:36–47.Google Scholar

  • [4]

    Aluvihare VR, Kallikourdis M, Betz AG. Regulatory T cells mediate maternal tolerance to the fetus. Nat Immunol. 2004;5:266–71.CrossrefGoogle Scholar

  • [5]

    Amstey MS. Frequency of adult respiratory distress syndrome in pregnant women who have pyelonephritis. Clin Infect Dis. 1992;14:1260–1.CrossrefGoogle Scholar

  • [6]

    Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369:840–51.CrossrefGoogle Scholar

  • [7]

    Bansard C, Lequerre T, Derambure C, Vittecoq O, Hiron M, Daragon A, et al. Gene profiling predicts rheumatoid arthritis responsiveness to IL-1Ra (anakinra). Rheumatology (Oxford). 2011;50:283–92.CrossrefGoogle Scholar

  • [8]

    Beutler B. Innate immunity: an overview. Mol Immunol. 2004;40:845–59.CrossrefGoogle Scholar

  • [9]

    Black ER, Falzon L, Aronson N. Gene expression profiling for predicting outcomes in stage II colon cancer. Rockville, MD: Agency for Healthcare Research and Quality. December 2012. www.effectivehealthcare.ahrq.gov/reports/final.cfm.

  • [10]

    Blois SM, Ilarregui JM, Tometten M, Garcia M, Orsal AS, Cordo-Russo R, et al. A pivotal role for galectin-1 in fetomaternal tolerance. Nat Med. 2007;13:1450–7.CrossrefGoogle Scholar

  • [11]

    Bone RC, Grodzin CJ, Balk RA. Sepsis: a new hypothesis for pathogenesis of the disease process. Chest. 1997;112:235–43.CrossrefGoogle Scholar

  • [12]

    Bubeck RW. Acute pyelonephritis during pregnancy with anuria, septicemia and thrombocytopenia. Del Med J. 1968;40:143–7.Google Scholar

  • [13]

    Burt TD. Fetal regulatory T cells and peripheral immune tolerance in utero: implications for development and disease. Am J Reprod Immunol. 2013;69:346–58.CrossrefGoogle Scholar

  • [14]

    Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, Cho RJ, et al. A network-based analysis of systemic inflammation in humans. Nature. 2005;437:1032–7.CrossrefGoogle Scholar

  • [15]

    Carella C, Potter M, Bonten J, Rehg JE, Neale G, Grosveld GC. The ETS factor TEL2 is a hematopoietic oncoprotein. Blood. 2006;107:1124–32.Google Scholar

  • [16]

    Catanzarite VA, Willms D. Adult respiratory distress syndrome in pregnancy: report of three cases and review of the literature. Obstet Gynecol Surv. 1997;52:381–92.CrossrefGoogle Scholar

  • [17]

    Catanzarite V, Willms D, Wong D, Landers C, Cousins L, Schrimmer D. Acute respiratory distress syndrome in pregnancy and the puerperium: causes, courses, and outcomes. Obstet Gynecol. 2001;97:760–4.CrossrefGoogle Scholar

  • [18]

    Chaemsaithong P, Romero R, Korzeniewski SJ, Schwartz AG, Stampalija T, Dong Z, et al. Soluble TRAIL in normal pregnancy and acute pyelonephritis: a potential explanation for the susceptibility of pregnant women to microbial products and infection. J Matern Fetal Neonatal Med. 2013;26:1568–75.Google Scholar

  • [19]

    Chaiworapongsa T, Romero R, Gotsch F, Kusanovic JP, Mittal P, Kim SK, et al. Acute pyelonephritis during pregnancy changes the balance of angiogenic and anti-angiogenic factors in maternal plasma. J Matern Fetal Neonatal Med. 2010;23: 167–78.Google Scholar

  • [20]

    Challis JR, Lockwood CJ, Myatt L, Norman JE, Strauss JF III, Petraglia F. Inflammation and pregnancy. Reprod Sci. 2009;16:206–15.CrossrefGoogle Scholar

  • [21]

    Chaouat G, Voisin GA, Daeron M, Kanellopoulos J. [Enhancing antibodies and supressive cells in maternal anti-fetal immune reaction]. Ann Immunol (Paris). 1977;128:21–4.Google Scholar

  • [22]

    Cid J, Aguinaco R, Sanchez R, Garcia-Pardo G, Llorente A. Neutrophil CD64 expression as marker of bacterial infection: a systematic review and meta-analysis. J Infect. 2010;60:313–9.CrossrefGoogle Scholar

  • [23]

    Cole DE, Taylor TL, McCullough DM, Shoff CT, Derdak S. Acute respiratory distress syndrome in pregnancy. Crit Care Med. 2005;33:S269–78.CrossrefGoogle Scholar

  • [24]

    Cunningham FG. Urinary tract infections complicating pregnancy. Baillieres Clin Obstet Gynaecol. 1987;1:891–908.CrossrefGoogle Scholar

  • [25]

    Cunningham FG, Lucas MJ. Urinary tract infections complicating pregnancy. Baillieres Clin Obstet Gynaecol. 1994;8:353–73.CrossrefGoogle Scholar

  • [26]

    Cunningham FG, Leveno KJ, Hankins GD, Whalley PJ. Respiratory insufficiency associated with pyelonephritis during pregnancy. Obstet Gynecol. 1984;63:121–5.Google Scholar

  • [27]

    Cunningham FG, Lucas MJ, Hankins GD. Pulmonary injury complicating antepartum pyelonephritis. Am J Obstet Gynecol. 1987;156:797–807.CrossrefGoogle Scholar

  • [28]

    Cunningham FG, Morris GB, Mickal A. Acute pyelonephritis of pregnancy: a clinical review. Obstet Gynecol. 1973;42:112–7.Google Scholar

  • [29]

    Dawkins JC, Fletcher HM, Rattray CA, Reid M, Gordon-Strachan G. Acute pyelonephritis in pregnancy: a retrospective descriptive hospital based-study. ISRN Obstet Gynecol. 2012;2012:519321.Google Scholar

  • [30]

    Draghici S, Khatri P, Martins RP, Ostermeier GC, Krawetz SA. Global functional profiling of gene expression. Genomics. 2003;81:98–104.Google Scholar

  • [31]

    Draghici S, Khatri P, Tarca AL, Amin K, Done A, Voichita C, et al. A systems biology approach for pathway level analysis. Genome Res. 2007;17:1537–45.CrossrefGoogle Scholar

  • [32]

    Eady JJ, Wortley GM, Wormstone YM, Hughes JC, Astley SB, Foxall RJ, et al. Variation in gene expression profiles of peripheral blood mononuclear cells from healthy volunteers. Physiol Genomics. 2005;22:402–11.CrossrefGoogle Scholar

  • [33]

    Elkington KW, Greb LC. Adult respiratory distress syndrome as a complication of acute pyelonephritis during pregnancy: case report and discussion. Obstet Gynecol. 1986;67:18S–20S.CrossrefGoogle Scholar

  • [34]

    Falcon S, Gentleman R. Using GOstats to test gene lists for GO term association. Bioinformatics. 2007;23:257–8.CrossrefGoogle Scholar

  • [35]

    Fan H, Hegde PS. The transcriptome in blood: challenges and solutions for robust expression profiling. Curr Mol Med. 2005;5:3–10.CrossrefGoogle Scholar

  • [36]

    Farnand AW, Eastman AJ, Herrero R, Hanson JF, Mongovin S, Altemeier WA, et al. Fas activation in alveolar epithelial cells induces KC (CXCL1) release by a MyD88-dependent mechanism. Am J Respir Cell Mol Biol. 2011;45:650–8.Google Scholar

  • [37]

    Founds SA. Bridging global gene expression candidates in first trimester placentas with susceptibility loci from linkage studies of preeclampsia. J Perinat Med. 2011;39:361–8.Google Scholar

  • [38]

    Frendeus B, Godaly G, Hang L, Karpman D, Lundstedt AC, Svanborg C. Interleukin 8 receptor deficiency confers susceptibility to acute experimental pyelonephritis and may have a human counterpart. J Exp Med. 2000;192:881–90.Google Scholar

  • [39]

    Gerrits JH, McLaughlin PM, Nienhuis BN, Smit JW, Loef B. Polymorphic mononuclear neutrophils CD64 index for diagnosis of sepsis in postoperative surgical patients and critically ill patients. Clin Chem Lab Med. 2013;51:897–905.Google Scholar

  • [40]

    Gilstrap LC 3rd, Cunningham FG, Whalley PJ. Acute pyelonephritis in pregnancy: an anterospective study. Obstet Gynecol. 1981;57:409–13.Google Scholar

  • [41]

    Gotsch F, Romero R, Espinoza J, Kusanovic JP, Mazaki-Tovi S, Erez O, et al. Maternal serum concentrations of the chemokine CXCL10/IP-10 are elevated in acute pyelonephritis during pregnancy. J Matern Fetal Neonatal Med. 2007;20:735–44.Google Scholar

  • [42]

    Goyal R, Yellon SM, Longo LD, Mata-Greenwood E. Placental gene expression in a rat ‘model’ of placental insufficiency. Placenta. 2010;31:568–75.CrossrefGoogle Scholar

  • [43]

    Graham JM, Oshiro BT, Blanco JD, Magee KP. Uterine contractions after antibiotic therapy for pyelonephritis in pregnancy. Am J Obstet Gynecol. 1993;168:577–80.CrossrefGoogle Scholar

  • [44]

    Green DR, Beere HM. Apoptosis. Gone but not forgotten. Nature. 2000;405:28–9.Google Scholar

  • [45]

    Gurman G, Schlaeffer F, Kopernic G. Adult respiratory distress syndrome as a complication of acute pyelonephritis during pregnancy. EurJ Obstet Gynecol Reprod Biol. 1990;36:75–80.CrossrefGoogle Scholar

  • [46]

    Hankins GD, Whalley PJ. Acute urinary tract infections in pregnancy. Clin Obstet Gynecol. 1985;28:266–78.CrossrefGoogle Scholar

  • [47]

    Hannan TJ, Mysorekar IU, Hung CS, Isaacson-Schmid ML, Hultgren SJ. Early severe inflammatory responses to uropathogenic E. coli predispose to chronic and recurrent urinary tract infection. PLoS Pathog. 2010;6:e1001042.CrossrefGoogle Scholar

  • [48]

    Haraoka M, Hang L, Frendeus B, Godaly G, Burdick M, Strieter R, et al. Neutrophil recruitment and resistance to urinary tract infection. J Infect Dis. 1999;180:1220–9.CrossrefGoogle Scholar

  • [49]

    Hill JB, Sheffield JS, McIntire DD, Wendel GD Jr. Acute pyelonephritis in pregnancy. Obstet Gynecol. 2005;105:18–23.CrossrefGoogle Scholar

  • [50]

    Hoegh AM, Borup R, Nielsen FC, Sorensen S, Hviid TV. Gene expression profiling of placentas affected by pre-eclampsia. J Biomed Biotechnol. 2010;2010:787545.Google Scholar

  • [51]

    Hotchkiss RS, Karl IE. The pathophysiology and treatment of sepsis. N Engl J Med. 2003;348:138–50.CrossrefGoogle Scholar

  • [52]

    Hotchkiss RS, Chang KC, Swanson PE, Tinsley KW, Hui JJ, Klender P, et al. Caspase inhibitors improve survival in sepsis: a critical role of the lymphocyte. Nat Immunol. 2000;1:496–501.CrossrefGoogle Scholar

  • [53]

    Hotchkiss RS, Coopersmith CM, McDunn JE, Ferguson TA. The sepsis seesaw: tilting toward immunosuppression. Nat Med. 2009;15:496–7.CrossrefGoogle Scholar

  • [54]

    Hunt JS, Petroff MG, McIntire RH, Ober C. HLA-G and immune tolerance in pregnancy. Faseb J. 2005;19:681–93.CrossrefGoogle Scholar

  • [55]

    Johansson L, Linner A, Sunden-Cullberg J, Haggar A, Herwald H, Lore K, et al. Neutrophil-derived hyperresistinemia in severe acute streptococcal infections. J Immunol. 2009;183:4047–54.CrossrefGoogle Scholar

  • [56]

    Jolley JA, Kim S, Wing DA. Acute pyelonephritis and associated complications during pregnancy in 2006 in US hospitals. J Matern Fetal Neonatal Med. 2012;25:2494–8.Google Scholar

  • [57]

    Kahn DA, Baltimore D. Pregnancy induces a fetal antigen-specific maternal T regulatory cell response that contributes to tolerance. Proc Natl Acad Sci USA. 2010;107:9299–304.CrossrefGoogle Scholar

  • [58]

    Kaul AK, Khan S, Martens MG, Crosson JT, Lupo VR, Kaul R. Experimental gestational pyelonephritis induces preterm births and low birth weights in C3H/HeJ mice. Infect Immun. 1999;67:5958–66.Google Scholar

  • [59]

    Kawagoe H, Potter M, Ellis J, Grosveld GC. TEL2, an ETS factor expressed in human leukemia, regulates monocytic differentiation of U937 Cells and blocks the inhibitory effect of TEL1 on ras-induced cellular transformation. Cancer Res. 2004;64:6091–100.Google Scholar

  • [60]

    Kisielewicz A, Schaier M, Schmitt E, Hug F, Haensch GM, Meuer S, et al. A distinct subset of HLA-DR+-regulatory T cells is involved in the induction of preterm labor during pregnancy and in the induction of organ rejection after transplantation. Clin Immunol. 2010;137:209–20.CrossrefGoogle Scholar

  • [61]

    Kusanovic JP, Romero R, Esoinoza J, Gotsch F, Edwin S, Chaiworapongsa T, et al. Maternal serum soluble CD30 is increased in pregnancies complicated with acute pyelonephritis. J Matern Fetal Neonatal Med. 2007;20:803–11.Google Scholar

  • [62]

    Law PT, Qin H, Ching AK, Lai KP, Co NN, He M, et al. Deep sequencing of small RNA transcriptome reveals novel non-coding RNAs in hepatocellular carcinoma. J Hepatol. 2013;58:1165–73.CrossrefGoogle Scholar

  • [63]

    Ledger WJ. Infection and premature labor. Am J Perinatol. 1989;6:234–6.CrossrefGoogle Scholar

  • [64]

    Li S, Huang X, Chen Z, Zhong H, Peng Q, Deng Y, et al. Neutrophil CD64 expression as a biomarker in the early diagnosis of bacterial infection: a meta-analysis. Int J Infect Dis. 2013;17:e12–23.CrossrefGoogle Scholar

  • [65]

    Lindig S, Quickert S, Vodovotz Y, Wanner GA, Bauer M. Age-independent co-expression of antimicrobial gene clusters in the blood of septic patients. Int J Antimicrob Agents. 2013;42:S2–7.CrossrefGoogle Scholar

  • [66]

    Mabie WC, Barton JR, Sibai BM. Adult respiratory distress syndrome in pregnancy. Am J Obstet Gynecol. 1992;167: 950–7.CrossrefGoogle Scholar

  • [67]

    Madsen-Bouterse SA, Romero R, Tarca AL, Kusanovic JP, Espinoza J, Kim CJ, et al. The transcriptome of the fetal inflammatory response syndrome. Am J Reprod Immunol. 2010;63:73–92.Google Scholar

  • [68]

    Mahyar A, Ayazi P, Maleki MR, Daneshi-Kohan MM, Sarokhani HR, Hashemi HJ, et al. Serum levels of interleukin-6 and interleukin-8 as diagnostic markers of acute pyelonephritis in children. Korean J Pediatr. 56:218–23.Google Scholar

  • [69]

    Martin-Subero JI, Ammerpohl O, Bibikova M, Wickham-Garcia E, Agirre X, Alvarez S, et al. A comprehensive microarray-based DNA methylation study of 367 hematological neoplasms. PLoS One. 2009;4:e6986.CrossrefGoogle Scholar

  • [70]

    Mazaki-Tovi S, Romero R, Vaisbuch E, Chaiworapongsa T, Erez O, Mittal P, et al. Low circulating maternal adiponectin in patients with pyelonephritis: adiponectin at the crossroads of pregnancy and infection. J Perinat Med. 2010;38:9–17.Google Scholar

  • [71]

    Mazaki-Tovi S, Vaisbuch E, Romero R, Kusanovic JP, Chaiworapongsa T, Kim SK, et al. Maternal plasma concentration of the pro-inflammatory adipokine pre-B-cell-enhancing factor (PBEF)/visfatin is elevated in pregnant patients with acute pyelonephritis. Am J Reprod Immunol. 2010;63:252–62.CrossrefGoogle Scholar

  • [72]

    Mazaki-Tovi S, Vaisbuch E, Romero R, Kusanovic JP, Chaiworapongsa T, Kim SK, et al. Hyperresistinemia – a novel feature in systemic infection during human pregnancy. Am J Reprod Immunol. 2010;63:358–69.CrossrefGoogle Scholar

  • [73]

    Medawar P. Some immunological and endocrinological problems raised by the evolution of viviparity in vertebrates. Symp Soc Exp Biol. 1953;44:320–38.Google Scholar

  • [74]

    Millar LK, DeBuque L, Wing DA. Uterine contraction frequency during treatment of pyelonephritis in pregnancy and subsequent risk of preterm birth. J Perinat Med. 2003;31:41–6.Google Scholar

  • [75]

    Mittal P, Wing DA. Urinary tract infections in pregnancy. Clin Perinatol. 2005;32:749–64.CrossrefGoogle Scholar

  • [76]

    Mittal P, Romero R, Tarca AL, Gonzalez J, Draghici S, Xu Y, et al. Characterization of the myometrial transcriptome and biological pathways of spontaneous human labor at term. J Perinat Med. 2010;38:617–43.Google Scholar

  • [77]

    Moffett A, Loke C. Immunology of placentation in eutherian mammals. Nat Rev Immunol. 2006;6:584–94.CrossrefGoogle Scholar

  • [78]

    Mold JE, Venkatasubrahmanyam S, Burt TD, Michaelsson J, Rivera JM, Galkina SA, et al. Fetal and adult hematopoietic stem cells give rise to distinct T cell lineages in humans. Science. 2010;330:1695–9.CrossrefGoogle Scholar

  • [79]

    Mor G, Cardenas I. The immune system in pregnancy: a unique complexity. Am J Reprod Immunol. 2010;63:425–33.CrossrefGoogle Scholar

  • [80]

    Mor G, Cardenas I, Abrahams V, Guller S. Inflammation and pregnancy: the role of the immune system at the implantation site. Ann NY Acad Sci. 2011;1221:80–7.CrossrefGoogle Scholar

  • [81]

    Mori W. The Shwartzman reaction: a review including clinical manifestations and proposal for a univisceral or single organ third type. Histopathology. 1981;5:113–26.CrossrefGoogle Scholar

  • [82]

    Moritz AR, Weir D. Unilateral inhibition of the renal Shwartzman phenomenon following injection of bacterial filtrate into the renal artery. J Exp Med. 1937;66:755–60.CrossrefGoogle Scholar

  • [83]

    Muller-Berghaus G, Obst R. Induction of the generalized Shwartzman reaction in pregnant and nonpregnant rats by colchicine. Am J Pathol. 1972;69:131–8.Google Scholar

  • [84]

    Muller-Berghaus G, Schmidt-Ehry B. The role of pregnancy in the induction of the generalized Shwartzman reaction. Am J Obstet Gynecol. 1972;114:847–9.Google Scholar

  • [85]

    Mysorekar IU, Hultgren SJ. Mechanisms of uropathogenic Escherichia coli persistence and eradication from the urinary tract. Proc Natl Acad Sci USA. 2006;103:14170–5.CrossrefGoogle Scholar

  • [86]

    Mysorekar IU, Isaacson-Schmid M, Walker JN, Mills JC, Hultgren SJ. Bone morphogenetic protein 4 signaling regulates epithelial renewal in the urinary tract in response to uropathogenic infection. Cell Host Microbe. 2009;5:463–75.Google Scholar

  • [87]

    Mysorekar IU, Mulvey MA, Hultgren SJ, Gordon JI. Molecular regulation of urothelial renewal and host defenses during infection with uropathogenic Escherichia coli. J Biol Chem. 2002;277:7412–9.CrossrefGoogle Scholar

  • [88]

    Naccasha N, Gervasi MT, Chaiworapongsa T, Berman S, Yoon BH, Maymon E, et al. Phenotypic and metabolic characteristics of monocytes and granulocytes in normal pregnancy and maternal infection. Am J Obstet Gynecol. 2001;185:1118–23.CrossrefGoogle Scholar

  • [89]

    Nalbant D, Youn H, Nalbant SI, Sharma S, Cobos E, Beale EG, et al. FAM20: an evolutionarily conserved family of secreted proteins expressed in hematopoietic cells. BMC Genomics. 2005;6:11.CrossrefGoogle Scholar

  • [90]

    Niederkorn JY. See no evil, hear no evil, do no evil: the lessons of immune privilege. Nat Immunol. 2006;7:354–9.CrossrefGoogle Scholar

  • [91]

    Nielubowicz GR, Mobley HL. Host-pathogen interactions in urinary tract infection. Nat Rev Urol. 2010;7:430–41.CrossrefGoogle Scholar

  • [92]

    Nien JK, Romero R, Hoppensteadt D, Erez O, Espinoza J, Soto E, et al. Pyelonephritis during pregnancy: a cause for an acquired deficiency of protein Z. J Matern Fetal Neonatal Med. 2008;21:629–37.Google Scholar

  • [93]

    Nishizawa H, Pryor-Koishi K, Kato T, Kowa H, Kurahashi H, Udagawa Y. Microarray analysis of differentially expressed fetal genes in placental tissue derived from early and late onset severe pre-eclampsia. Placenta. 2007;28:487–97.CrossrefGoogle Scholar

  • [94]

    Nuutila J. The novel applications of the quantitative analysis of neutrophil cell surface FcgammaRI (CD64) to the diagnosis of infectious and inflammatory diseases. Curr Opin Infect Dis. 2010;23:268–74.CrossrefGoogle Scholar

  • [95]

    Pitukkijronnakorn S, Chittacharoen A, Herabutya Y. Maternal and perinatal outcomes in pregnancy with acute pyelonephritis. Int J Gynaecol Obstet. 2005;89:286–7.CrossrefGoogle Scholar

  • [96]

    Power CP, Wang JH, Manning B, Kell MR, Aherne NJ, Wu QD, et al. Bacterial lipoprotein delays apoptosis in human neutrophils through inhibition of caspase-3 activity: regulatory roles for CD14 and TLR-2. J Immunol. 2004;173:5229–37.Google Scholar

  • [97]

    Pruett K, Faro S. Pyelonephritis associated with respiratory distress. Obstet Gynecol. 1987;69:444–6.Google Scholar

  • [98]

    Raff M. Cell suicide for beginners. Nature. 1998;396:119–22.CrossrefGoogle Scholar

  • [99]

    Rajakumar A, Chu T, Handley DE, Bunce KD, Burke B, Hubel CA, et al. Maternal gene expression profiling during pregnancy and preeclampsia in human peripheral blood mononuclear cells. Placenta. 2011;32:70–8.CrossrefGoogle Scholar

  • [100]

    Reimer T, Koczan D, Gerber B, Richter D, Thiesen HJ, Friese K. Microarray analysis of differentially expressed genes in placental tissue of pre-eclampsia: up-regulation of obesity-related genes. Mol Hum Reprod. 2002;8:674–80.CrossrefGoogle Scholar

  • [101]

    Romero R, Gotsch F, Pineles B, Kusanovic JP. Inflammation in pregnancy: its roles in reproductive physiology, obstetrical complications, and fetal injury. Nutr Rev. 2007;65:S194–202.CrossrefGoogle Scholar

  • [102]

    Romero R, Oyarzun E, Mazor M, Sirtori M, Hobbins JC, Bracken M. Meta-analysis of the relationship between asymptomatic bacteriuria and preterm delivery/low birth weight. Obstet Gynecol. 1989;73:576–82.Google Scholar

  • [103]

    Rosas-Ballina M, Olofsson PS, Ochani M, Valdes-Ferrer SI, Levine YA, Reardon C, et al. Acetylcholine-synthesizing T cells relay neural signals in a vagus nerve circuit. Science. 2011;334:98–101.CrossrefGoogle Scholar

  • [104]

    Rowe JH, Ertelt JM, Aguilera MN, Farrar MA, Way SS. Foxp3(+) regulatory T cell expansion required for sustaining pregnancy compromises host defense against prenatal bacterial pathogens. Cell Host Microbe. 2011;10:54–64.CrossrefGoogle Scholar

  • [105]

    Rowe JH, Ertelt JM, Xin L, Way SS. Pregnancy imprints regulatory memory that sustains anergy to fetal antigen. Nature. 2012;490:102–6.CrossrefGoogle Scholar

  • [106]

    Sacks G, Sargent I, Redman C. An innate view of human pregnancy. Immunol Today. 1999;20:114–8.CrossrefGoogle Scholar

  • [107]

    Sacks GP, Studena K, Sargent K, Redman CW. Normal pregnancy and preeclampsia both produce inflammatory changes in peripheral blood leukocytes akin to those of sepsis. Am J Obstet Gynecol. 1998;179:80–6.CrossrefGoogle Scholar

  • [108]

    Samstein RM, Josefowicz SZ, Arvey A, Treuting PM, Rudensky AY. Extrathymic generation of regulatory T cells in placental mammals mitigates maternal-fetal conflict. Cell. 2012;150:29–38.CrossrefGoogle Scholar

  • [109]

    Schaeffer AJ. Experimental gestational pyelonephritis induces preterm births and low birth weights in C3H/HeJ mice. J Urol. 2000;164:260–1.CrossrefGoogle Scholar

  • [110]

    Schober L, Radnai D, Schmitt E, Mahnke K, Sohn C, Steinborn A. Term and preterm labor: decreased suppressive activity and changes in composition of the regulatory T-cell pool. Immunol Cell Biol. 2012;90:935–44.CrossrefGoogle Scholar

  • [111]

    Sheffield JS, Cunningham FG. Urinary tract infection in women. Obstet Gynecol. 2005;106:1085–92.CrossrefGoogle Scholar

  • [112]

    Shushakova N, Skokowa J, Schulman J, Baumann U, Zwirner J, Schmidt RE, et al. C5a anaphylatoxin is a major regulator of activating versus inhibitory FcgammaRs in immune complex-induced lung disease. J Clin Invest. 2002;110:1823–30.CrossrefGoogle Scholar

  • [113]

    Sitras V, Paulssen RH, Gronaas H, Leirvik J, Hanssen TA, Vartun A, et al. Differential placental gene expression in severe preeclampsia. Placenta. 2009;30:424–33.CrossrefGoogle Scholar

  • [114]

    Smyth GK. Limma. Linear models for microarray data. In: Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W, editors. Bioinformatics and computational biology solutions using R and bioconductor. New York: Springer; 2005:397–420.Google Scholar

  • [115]

    Snyder CC, Barton JR, Habli M, Sibai BM. Severe sepsis and septic shock in pregnancy: indications for delivery and maternal and perinatal outcomes. J Matern Fetal Neonatal Med. 2013;26:503–6.Google Scholar

  • [116]

    Soisson AP, Eldridge E, Kopelman JN, Duff P. Acute pyelonephritis complicated by respiratory insufficiency. A case report. J Reprod Med. 1986;31:525–7.Google Scholar

  • [117]

    Soto E, Richani K, Romero R, Espinoza J, Chaiworapongsa T, Nien JK, et al. Increased concentration of the complement split product C5a in acute pyelonephritis during pregnancy. J Matern Fetal Neonatal Med. 2005;17:247–52.Google Scholar

  • [118]

    Soto E, Romero R, Vaisbuch E, Erez O, Mazaki-Tovi S, Kusanovic JP, et al. Fragment Bb: evidence for activation of the alternative pathway of the complement system in pregnant women with acute pyelonephritis. J Matern Fetal Neonatal Med. 2010;23:1085–90.Google Scholar

  • [119]

    Spencer JD, Schwaderer AL, Becknell B, Watson J, Hains DS. The innate immune response during urinary tract infection and pyelonephritis. Pediatr Nephrol. 2013 [Epub ahead of print].CrossrefGoogle Scholar

  • [120]

    Steinborn A, Schmitt E, Kisielewicz A, Rechenberg S, Seissler N, Mahnke K, et al. Pregnancy-associated diseases are characterized by the composition of the systemic regulatory T cell (Treg) pool with distinct subsets of Tregs. Clin Exp Immunol. 2012;167:84–98.CrossrefGoogle Scholar

  • [121]

    Sun CJ, Zhang L, Zhang WY. Gene expression profiling of maternal blood in early onset severe preeclampsia: identification of novel biomarkers. J Perinat Med. 2009;37:609–16.Google Scholar

  • [122]

    Sunden-Cullberg J, Nystrom T, Lee ML, Mullins GE, Tokics L, Andersson J, et al. Pronounced elevation of resistin correlates with severity of disease in severe sepsis and septic shock. Crit Care Med. 2007;35:1536–42.Google Scholar

  • [123]

    Talwar S, Munson PJ, Barb J, Fiuza C, Cintron AP, Logun C, et al. Gene expression profiles of peripheral blood leukocytes after endotoxin challenge in humans. Physiol Genomics. 2006;25:203–15.CrossrefGoogle Scholar

  • [124]

    Taneja R, Parodo J, Jia SH, Kapus A, Rotstein OD, Marshall JC. Delayed neutrophil apoptosis in sepsis is associated with maintenance of mitochondrial transmembrane potential and reduced caspase-9 activity. Crit Care Med. 2004;32:1460–9.CrossrefGoogle Scholar

  • [125]

    Tang BM, Huang SJ, McLean AS. Genome-wide transcription profiling of human sepsis: a systematic review. Crit Care. 2010;14:R237.CrossrefGoogle Scholar

  • [126]

    Tang BM, McLean AS, Dawes IW, Huang SJ, Cowley MJ, Lin RC. Gene-expression profiling of gram-positive and gram-negative sepsis in critically ill patients. Crit Care Med. 2008;36:1125–8.CrossrefGoogle Scholar

  • [127]

    Tang BM, McLean AS, Dawes IW, Huang SJ, Lin RC. Gene-expression profiling of peripheral blood mononuclear cells in sepsis. Crit Care Med. 2009;37:882–8.CrossrefGoogle Scholar

  • [128]

    Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, et al. A novel signaling pathway impact analysis. Bioinformatics. 2009;25:75–82.CrossrefGoogle Scholar

  • [129]

    Terness P, Kallikourdis M, Betz AG, Rabinovich GA, Saito S, Clark DA. Tolerance signaling molecules and pregnancy: IDO, galectins, and the renaissance of regulatory T cells. Am J Reprod Immunol. 2007;58:238–54.CrossrefGoogle Scholar

  • [130]

    Than NG, Romero R, Erez O, Weckle A, Tarca AL, Hotra J, et al. Emergence of hormonal and redox regulation of galectin-1 in placental mammals: implication in maternal-fetal immune tolerance. Proc Natl Acad Sci USA. 2008;105:15819–24.CrossrefGoogle Scholar

  • [131]

    Than NG, Romero R, Goodman M, Weckle A, Xing J, Dong Z, et al. A primate subfamily of galectins expressed at the maternal-fetal interface that promote immune cell death. Proc Natl Acad Sci USA. 2009;106:9731–6.CrossrefGoogle Scholar

  • [132]

    Than NG, Romero R, Kim CJ, McGowen MR, Papp Z, Wildman DE. Galectins: guardians of eutherian pregnancy at the maternal-fetal interface. Trends Endocrinol Metab. 2012;23:23–31.CrossrefGoogle Scholar

  • [133]

    Thaxton JE, Sharma S. Interleukin-10: a multi-faceted agent of pregnancy. Am J Reprod Immunol. 2010;63:482–91.CrossrefGoogle Scholar

  • [134]

    Thellin O, Coumans B, Zorzi W, Igout A, Heinen E. Tolerance to the foeto-placental ‘graft’: ten ways to support a child for nine months. Curr Opin Immunol. 2000;12:731–7.CrossrefGoogle Scholar

  • [135]

    Toft JH, Lian IA, Tarca AL, Erez O, Espinoza J, Eide IP, et al. Whole-genome microarray and targeted analysis of angiogenesis-regulating gene expression (ENG, FLT1, VEGF, PlGF) in placentas from pre-eclamptic and small-for-gestational-age pregnancies. J Matern Fetal Neonatal Med. 2008;21:267–73.Google Scholar

  • [136]

    Towers CV, Kaminskas CM, Garite TJ, Nageotte MP, Dorchester W. Pulmonary injury associated with antepartum pyelonephritis: can patients at risk be identified? Am J Obstet Gynecol. 1991;164:974–8.CrossrefGoogle Scholar

  • [137]

    Trowsdale J, Betz AG. Mother’s little helpers: mechanisms of maternal-fetal tolerance. Nat Immunol. 2006;7:241–6.CrossrefGoogle Scholar

  • [138]

    Tyner JW. Rapid identification of therapeutic targets in hematologic malignancies via functional genomics. Ther Adv Hematol. 2011;2:83–93.CrossrefGoogle Scholar

  • [141]

    Vaisbuch E, Romero R, Mazaki-Tovi S, Kusanovic JP, Chaiworapongsa T, Dong Z, et al. Maternal plasma retinol binding protein 4 in acute pyelonephritis during pregnancy. J Perinat Med. 2010;38:359–66.Google Scholar

  • [139]

    van Baarsen LG, Bos WH, Rustenburg F, van der Pouw Kraan TC, Wolbink GJ, Dijkmans BA, et al. Gene expression profiling in autoantibody-positive patients with arthralgia predicts development of arthritis. Arthritis Rheum. 2010;62:694–704.CrossrefGoogle Scholar

  • [140]

    van der Poll T, Opal SM. Host-pathogen interactions in sepsis. Lancet Infect Dis. 2008;8:32–43.Google Scholar

  • [142]

    Varkonyi T, Nagy B, Fule T, Tarca AL, Karaszi K, Schonleber J, et al. Microarray profiling reveals that placental transcriptomes of early-onset HELLP syndrome and preeclampsia are similar. Placenta. 2011;32:S21–9.CrossrefGoogle Scholar

  • [143]

    Wang C, Mendonsa GR, Symington JW, Zhang Q, Cadwell K, Virgin HW, et al. Atg16L1 deficiency confers protection from uropathogenic Escherichia coli infection in vivo. Proc Natl Acad Sci USA. 2012;109:11008–13.CrossrefGoogle Scholar

  • [144]

    Wegmann TG, Lin H, Guilbert L, Mosmann TR. Bidirectional cytokine interactions in the maternal-fetal relationship: is successful pregnancy a TH2 phenomenon? Immunol Today. 1993;14:353–6.Google Scholar

  • [145]

    Whitehead CL, Walker SP, Ye L, Mendis S, Kaitu’u-Lino TJ, Lappas M, et al. Placental specific mRNA in the maternal circulation are globally dysregulated in pregnancies complicated by fetal growth restriction. J Clin Endocrinol Metab. 2013;98:E429–36.CrossrefGoogle Scholar

  • [146]

    Whitney AR, Diehn M, Popper SJ, Alizadeh AA, Boldrick JC, Relman DA, et al. Individuality and variation in gene expression patterns in human blood. Proc Natl Acad Sci USA. 2003;100:1896–901.CrossrefGoogle Scholar

  • [147]

    Yazigi R, Lerner S, Tejani N. Association of acute pyelonephritis with pulmonary complications in pregnancy. A report of two cases. J Reprod Med. 1990;35:562–4.Google Scholar

  • [148]

    Zhou R, Zhu Q, Wang Y, Ren Y, Zhang L, Zhou Y. Genomewide oligonucleotide microarray analysis on placentae of pre-eclamptic pregnancies. Gynecol Obstet Invest. 2006;62:108–14.CrossrefGoogle Scholar

The authors stated that there are no conflicts of interest regarding the publication of this article.

About the article

Corresponding author: Roberto Romero, MD, DMedSci, Perinatology Research Branch, NICHD, NIH, DHHS, Wayne State University/Hutzel Women’s Hospital, 3990 John R, Box 4, Detroit, MI 48201, USA, Tel.: +1-313-993-2700, Fax: +1-313-993-2694, E-mail:


Published Online: 2013-11-30

Published in Print: 2014-01-01


Presented at the 58th Annual Meeting of the Society for Gynecologic Investigation, March 16–19, 2011, Miami, FL, USA


Citation Information: Journal of Perinatal Medicine, ISSN (Online) 1619-3997, ISSN (Print) 0300-5577, DOI: https://doi.org/10.1515/jpm-2013-0085.

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