Abstract
Objective
Distinct processes govern transition from quiescence to activation during term (TL) and preterm labor (PTL). We sought gene sets responsible for TL and PTL, along with the effector genes necessary for labor independent of gestation and underlying trigger.
Methods
Expression was analyzed in term and preterm +/− labor (n =6 subjects/group). Gene sets were generated using logic operations.
Results
34 genes were similarly expressed in PTL/TL but absent from nonlabor samples (Effector Set). 49 genes were specific to PTL (Preterm Initiator Set) and 174 to TL (Term Initiator Set). The gene ontogeny processes comprising Term Initiator and Effector Sets were diverse, though inflammation was represented in 4 of the top 10; inflammation dominated the Preterm Initiator Set.
Comments
TL and PTL differ dramatically in initiator profiles. Though inflammation is part of the Term Initiator and the Effector Sets, it is an overwhelming part of PTL associated with intraamniotic inflammation.
Keywords: effector, initiator, labor, myometrium, preterm birth
Background and Objectives
Successful parturition requires the synchronization of uterine events (myometrial activation, myometrial contraction, cervical ripening, cervical dilation and rupture of the fetal membranes) 1. The myometrium specifically must undergo a series of molecular and biochemical changes that transition it from the phase of quiescence, which is characterized by a loss of responsiveness to contractile agents, to the phase of activation with subsequent onset of labor 2, 3. Many prior investigators have assumed the triggers of parturition are similar regardless of the gestational age 2, 4–9 and focused on the control of term labor as a surrogate for preterm labor. This approach has not met with great success.
Genomics helps expand and characterize the number of molecular pathways that potentially define an underlying condition. Since our initial report in 200010, oligonucleotide / cDNA microarrays have been used by many groups for the study of biological processes involved in normal term labor 11–18. The results of such studies using myometrium obtained from term laboring women suggest that contractile stimulators of labor include but are not limited to hormone receptors, cell adhesion molecules, interleukins, prostaglandins, and gap junctions 10, 11, 13–15, 17. Others have attempted to correlate human myometrial transcriptional levels at term with samples from idiopathic, spontaneous preterm labor, and concluded the mechanisms underlying parturition at all stages of pregnancy are related1, 13, 17. This is surprising as there are several well accepted ‘causes’ of spontaneous preterm birth 19, 20. While molecules within these groups may well influence parturition during normal labor, there is little study of myometrial gene expression in women with either preterm or dysfunctional term/preterm labor. Array type investigations have also been used to explore myometrial gene expression in the pregnant rodent 11, 18, 21. However, the resulting conclusions should be interpreted cautiously as the gestational and hormonal patterns of these species are not homologous to the human. And while these studies provide insight, they tend as a group to be biased by the limited number of genes included on the array and the number of genes selected for confirmatory study.
Rather than compare term labor to one of several models for preterm birth, we investigated human pregnancy and hypothesized there should be a core set of genes whose expression was necessary for the process of labor independent of gestational age (GA) and the underlying trigger for the labor. We further hypothesized this Effector Gene Set should relate to myometrial contractility and the cellular activities necessary to sustain it. We also hypothesized there must be Initiator Gene Sets responsible for the transition of the myometrium from quiescence to activation. But unlike the Effector Set, which would be unaffected by the underlying labor stimulus, there should be separate Initiator Gene Sets for term and preterm labor that reflect the underlying mechanism of labor. The potential result of identifying these gene sets could be the development of alternative treatment options targeted at preterm and term or dysfunctional labor. The purpose of this investigation was to test our hypotheses in a series of women undergoing cesarean delivery at term or preterm, in labor or absent labor.
Material and Methods
Study Design
Myometrium was obtained from the upper pole of the transverse lower uterine segment incision of 4 groups of women (n=6 per group) at the time their primary cesarean section at Yale University: (i) preterm not in labor and no inflammation (PTNL; mean GA 28.8w, range 25.4– 32.5w); (ii) preterm in labor with inflammation (PTL; mean GA 29.7w, range 25.1– 32.6w); (iii) term not in labor (TNL; mean GA 39.3w, range 38.4– 41.0w); and (iv) term labor (TL; mean GA 40.2w, range 39.0– 41.2w). The Yale University IRB approved the protocol for sample collection, and all women provided informed written consent. Labor was defined by presence of regular uterine contractions accompanied by progressive cervical dilation. The diagnosis of intra-amniotic inflammation was based on an amniotic fluid Mass Restricted (MR) Score of 3 or 4 plus more than 100 WBCs/μL3 in the context of a positive amniotic fluid culture in a sample obtained by transabdominal amniocentesis 22–25. These tests provide the most accurate tools currently available to maximize the likelihood of sample homogeneity. The MR Score provides qualitative information regarding the presence or absence of intra-amniotic inflammation. Briefly, the Score ranges from 0 to 4, depending on the presence (assigned a value of 1) or absence (assigned a value of 0) of each of four protein biomarkers 25. A score of 3–4 indicates inflammation, whereas a score of 0–2 excludes it. This biomarker pattern is predictive of preterm birth, histological chorioamnionitis and adverse neonatal outcome. A detailed description of the MR method has previously been published 22–25. Indications for cesarean delivery in the PTNL group were all related to preeclampsia, and breech presentation in the TNL cesarean deliveries. The indication for cesarean in the TL group was an arrest of cervical dilation at 6 cm or greater. No normal laboring patient at term underwent cesarean section in this sample. Clinical data were retrieved from the medical records and statistical analysis of patient demographics performed using one-way ANOVA followed by Newman Keuls Post Hoc test. All laboratory studies were performed at either the University of Kansas School of Medicine or the University of Maryland Baltimore School of Pharmacy.
Isolation of RNA
Total RNA was isolated using TRIzol™ Reagent (Invitrogen™, Carlsbad, CA) according to the manufacturer’s protocol. The purity and integrity of each RNA sample was assessed by spectroscopy and formaldehyde-agarose gel electrophoresis.
Microarray Preparation
Myometrial gene profiling was performed on each individual RNA sample using the Affymetrix GeneChip Human Genome U133 Plus 2.0™ microarray (Affymetrix, Santa Clara, CA) containing some 38,500 human genes. RNA quality was reassessed prior to spotting using the Agilent 2100 Bioanalyzer™ (Agilent Technologies, Palo Alto, CA). Once the quality was confirmed, biotin-labeled cRNA was generated and 20 μg hybridized to the microarrays using the manufacturer’s standard conditions. Image processing utilized an Affymetrix GeneArray 3000™ scanner.
Microarray Data Processing and Statistical Analysis
Oligonucleotide microarrays were analyzed using the Affymetrix Expression Console™. Gene expression levels were normalized using the R Statistical package and software available through the Bioconductor Project (www.bioconductor.org). The process normalizes gene expression using a background adjustment procedure and a sequence-specific expression method as described by Wu et al 26. Normalized microarray data were then subject to further discriminative analysis. A detection P value was used to make a reliable call of gene expression (present, marginal, or absent). Genes present in less than 4 of the six patient samples were classified as absent overall and not considered further.
To identify the Effector and Initiator Gene Sets, we conducted a series of logic operations based on gene presence (detection P value) and illustrated by the Venn diagram in Figure 1. We first generated four groups of genes based on the following:
FIGURE 1.
Venn diagram illustrating the logic process for the derivation of the three unique gene sets. The number refers to the number of genes identified in the various subgroups.
Group A = (PTL-PTNL) | Group C = (TL-TNL) |
Group B = (Group A-TNL) | Group D = (Group C-PTNL) |
The Effector Gene Set was defined as those genes common to Groups B and D. The Effector Set was further filtered to exclude genes whose expression during PTL changed 2-fold or more in either direction compared to TL, reasoning there was something unique to the disease state influencing gene expression. The Preterm Initiator Gene Set was defined as those genes in Group A exclusive to PTL (minus Group C). And lastly, the Term Initiator Gene Set was defined as those genes in Group C exclusive of term labor (minus Group A).
Network Analysis and Biological Classification
Identification and visual analysis of gene networks were performed using MetaCore™ analytical suite version 2.0 (GeneGo, St. Joseph, MI). There were few direct interactions identified among the individual proteins of the Effector, Preterm Initiator, and Term Initiator genes. Therefore, we analyzed the possible networks that could be built from such relatively large gene sets using an algorithm that generates sub-networks highly saturated with input genes from each dataset (i.e., Effector set, Preterm Initiator set, and Term Initiator set). In this case, the network algorithm takes a list of root nodes (i.e., genes from Effector, Preterm Initiator, and Term Initiator sets) and for each one creates shortest paths networks to other root nodes in the list and stops the network expansion at a size of 50 nodes (standard number predefined in MetaCore). The resulting networks are evaluated and ranked according to their statistical significance (p-values). This high trust p-value calculation was also used to evaluate the network’s relevance to Gene Ontology (GO) biological processes classification. In general, GO is a method of standardizing the representation of gene and gene product attributes across species and databases. Three Gene Ontology functional ontologies (processes, molecular functions, and localizations) are used in Metacore™ for enrichment analysis. The advantage of using this network algorithm is that it may find a well-connected cluster of root nodes without any predefined restrictions and as a result offers more flexibility in identifying possible connections. These interactions were then assigned to specific biological processes, cellular components, and/or molecular functions to further characterize the underlying condition to yield insight into the underlying mechanisms. We selected some genes of interest for confirmation by q-rtPCR based on their participation in sub-networks with a low p-value. Other genes selected from the input list were selected for q-rtPCR analysis based on their statistically significant association with GO processes.
Quantitative Real Time PCR (Q-rtPCR)
Total RNA from the original samples used for the microarrays was used to quantify each gene. Primer sequences for amplifications were based on previously published cDNA sequences using the Beacon Designer program (BioRad, Hercules, CA). SYBR green (BioRad, Hercules, CA) was used for amplicon detection. All primer sets were tested to ensure the efficiency of amplification over a wide range of template concentrations. PCR reactions were carried out in the iQ5 real-time PCR detection system (BioRad, Hercules, CA). A melting curve was performed after amplification to ensure all samples exhibited a single amplicon. Gene expression of each individual myometrial sample was first normalized to the expression of 18s rRNA (internal control) using the ΔCT method 27 and then compared to the average of the corresponding control samples. mRNA relative expression is equal to 2-Δ ΔCT and determined by the following equations:
The point at which the fluorescence crosses the threshold is called the CT value, and is read by the RT-PCR instrument as a specific parameter.
Results
Clinical Characteristics of Myometrial Samples
The clinical characteristics of the pregnancies included are listed in Table 1. There were no statistically significant differences in gestational age or birth weight among women at term (no labor vs. labor) or preterm (no labor vs. labor). There were no statistically significant differences in maternal age as determined by one-way ANOVA. Thus, the observed differences in genes in the initiator groups are most likely the result of labor (term or preterm) rather than any variation in gestational age or maternal age.
Table 1.
Clinical Characteristics
Group | Gestational Age (weeks) | Maternal Age (years) | Birthweight (grams) | Indication for CS | Histological Chorioamnionitis |
---|---|---|---|---|---|
TNL | 39 ± 1 | 30 ± 3 | 3490 ± 618 | breech | NA |
TL | 40 ± 1 | 28 ± 6 | 3490 ± 333 | failure to progress | NA |
PNL | 29 ± 3 a,b | 26 ± 9 | 971 ± 380 a,b | preeclampsia | Stage 0 |
PTL | 30 ± 3 a,b | 34 ± 6 | 1299 ± 344 a,b | PPROM/ sPTL | Stage III |
Data presented as mean ± S.D. CS, cesarean section; PPROM, premature rupture of membranes; sPTL, spontaneous preterm labor; PE, preeclampsia; NA, not applicable.
p < 0.05 based on Newman-Keuls test compared to TNL
p < 0.05 based on Newman-Keuls test compared to TL
Identification of Effector Set and the Term Initiator and Preterm Initiator Sets
Sixty seven (67) genes were present in both PTL and TL but absent from all non-labor samples (n=6) (Groups B and D). This group was termed the Effector Set since the genes comprising it represent a distinct group that might act to sustain the labor itself rather than contributing to its onset. This Effector Set was then further filtered to exclude genes showing at least a 2-fold difference between PTL and TL based on the assumption there was something about the disease process which led to differential regulation. This left 34 genes in the Effector Set (Table 2).
Table 2.
Core Myometrial Genes of Labor (Effector Set).(excluding hypothetical and other unidentified/unnamed proteins)
Gene Symbol | Gene Name | Entrez ID |
---|---|---|
ABRA | Actin-binding rho activating protein | 137735 |
ALDH16A1 | Aldehyde dehydrogenase 16 family, member a1 | 126133 |
ANKS3 | Ankyrin repeat and sterile alpha motif domain containing 3 | 124401 |
ATRIP/TREX1 | ATR-interacting protein/Three prime repair exonuclease 1 | 84126 |
BAIAP2L1 | Bai1-associated protein 2-like 1 | 55971 |
CADM2 | Cell adhesion molecule 2 precursor | 253559 |
CCDC36 | Coiled-coil domain containing 36 | 339834 |
CFB | Complement factor b | 629 |
CORO2A | Coronin, actin binding protein, 2a | 7464 |
D4S234E | Dna segment on chromosome 4 (unique) 234 expressed sequence | 27065 |
EGFL7 | Egf-like-domain, multiple 7 | 51162 |
FPGS | Folylpolyglutamate synthase | 2356 |
GPATCH3 | G patch domain containing 3 | 63906 |
H2AFY2 | H2a histone family, member y2 | 55506 |
HNT | Neurotrimin | 50863 |
HTRA4 | Htra serine peptidase 4 | 203100 |
IL8RB | Interleukin 8 receptor, beta | 3579 |
KCNAB2 | Potassium voltage-gated channel, shaker-related subfamily, beta member 2 | 8514 |
KRTAP8-1 | Keratin associated protein 8-1 | 337879 |
LY6G5C | Lymphocyte antigen 6 complex, locus g5c | 80741 |
MPP3 | Membrane protein, palmitoylated 3 (maguk p55 subfamily member 3) | 4356 |
P2RY8 | Purinergic receptor p2y, g-protein coupled, 8 | 286530 |
PLAC8L1 | Plac8-like 1 | 153770 |
PLCXD1 | Phosphatidylinositol-specific phospholipase c, x domain containing 1 | 55344 |
POLR3D | Polymerase (rna) iii (dna directed) polypeptide d, 44kda | 661 |
RRAD | Ras-related associated with diabetes | 6236 |
SIRPB2 | Signal-regulatory protein beta 2 | 284759 |
SKIV2L | Superkiller viralicidic activity 2-like (s. Cerevisiae) | 6499 |
SLPI | Secretory leukocyte peptidase inhibitor | 6590 |
ST3GAL3 | St3 beta-galactoside alpha-2,3-sialyltransferase 3 | 6487 |
ZNF552 | Zinc finger protein 552 | 79818 |
ZNF718 | Zinc finger protein 718 | 255403 |
ZNF74 | Zinc finger protein 74 (cos52) | 7625 |
ZNF788 | Zinc finger protein 788 | 388507 |
While the Effector Gene Set was by definition independent of GA, we suspected there must exist gene sets that enabled the initiation of the labor either term or preterm. We detected 49 genes specific to preterm labor alone (Preterm Initiator Set, Table 3) and 174 specific to term labor alone (Term Initiator Set, Table 4). In light of the gestational ages of the preterm subjects, it is highly likely the selected gene sets represent or at least include molecular groups responsible for initiating the transition from myometrial quiescence to activation in their respective categories.
Table 3.
Myometrial Genes Initiating Preterm Labor (Preterm Initiator Set) (excluding hypothetical and other unidentified/unnamed proteins)
Genes Symbol | Gene Name | Entrez ID |
---|---|---|
ABCA3 | Atp-binding cassette, sub-family a (abc1), member 3 | 21 |
ABP1 | Amiloride binding protein 1 (amine oxidase (copper-containing)) | 26 |
ARSA | Arylsulfatase a | 410 |
CD3E | Cd3e antigen, epsilon polypeptide (tit3 complex) | 916 |
DGKQ | Diacylglycerol kinase, theta 110kda | 1609 |
GJA3 | Gap junction protein, alpha 3, 46kda (connexin 46) | 2700 |
GSTT2 | Glutathione s-transferase theta 2 | 2953 |
HLA-DOA | Major histocompatibility complex, class ii, do alpha | 3111 |
HYAL1 | Hyaluronoglucosaminidase 1 | 3373 |
IFNG | Interferon, gamma | 3458 |
IRF5 | Interferon regulatory factor 5 | 3663 |
LLGL1 | Lethal giant larvae homolog 1 (drosophila) | 3996 |
LYL1 | Lymphoblastic leukemia derived sequence 1 | 4066 |
MYCL1 | V-myc myelocytomatosis viral oncogene homolog 1, lung carcinoma derived (avian) | 4610 |
PDE1C | Phosphodiesterase 1c, calmodulin-dependent 70kda | 5137 |
MAPK11 | Mitogen-activated protein kinase 11 | 5600 |
PTPRZ1 | Protein tyrosine phosphatase, receptor-type, z polypeptide 1 | 5803 |
ZNF208 | Zinc finger protein 208 | 7757 |
ABCA7 | Atp-binding cassette, sub-family a (abc1), member 7 | 10347 |
CXCL13 | Chemokine (c-x-c motif) ligand 13 (b-cell chemoattractant) | 10563 |
OGFR | Opioid growth factor receptor | 11054 |
ELOVL2 | Elongation of very long chain fatty acids (fen1/elo2, sur4/elo3, yeast)-like 2 | 54898 |
CPXM | Carboxypeptidase x (m14 family) | 56265 |
AARSL | Alanyl-trna synthetase like | 57505 |
TINAGL1 | Tubulointerstitial nephritis antigen-like 1 | 64129 |
DIO3OS | Deiodinase, iodothyronine, type iii opposite strand | 64150 |
NDRG4 | Ndrg family member 4 | 65009 |
VPS33A | Vacuolar protein sorting 33a (yeast) | 65082 |
LRFN4 | Leucine rich repeat and fibronectin type iii domain containing 4 | 78999 |
TLE6 | Transducin-like enhancer of split 6 (e(sp1) homolog, drosophila) | 79816 |
TIGD6 | Tigger transposable element derived 6 | 81789 |
KRTAP4-8 | Keratin associated protein 4–8 | 83898 |
CHCHD6 | Coiled-coil-helix-coiled-coil-helix domain containing 6 | 84303 |
ZNF341 | Zinc finger protein 341 | 84905 |
CCDC97 | Coiled-coil domain-containing protein 97 | 90324 |
STK11IP | Serine/threonine kinase 11 interacting protein | 114790 |
SORCS1 | Sortilin-related vps10 domain containing receptor 1 | 114815 |
CATSPER2 | Cation channel, sperm associated 2 | 117155 |
LRGUK | Leucine-rich repeats and guanylate kinase domain containing | 136332 |
FAM69B | Family with sequence similarity 69, member b | 138311 |
BEAN | Brain expressed, associated with nedd4 | 146227 |
GRASP | Grp1 (general receptor for phosphoinositides 1)-associated scaffold protein | 160622 |
ZNF579 | Zinc finger protein 579 | 163033 |
DENND1B | Denn/madd domain containing 1b | 163486 |
SAMD14 | Sterile alpha motif domain containing 14 | 201191 |
ALS2CL | Als2 c-terminal like | 259173 |
STK32C | Serine/threonine kinase 32c | 282974 |
CATSPER2P1 | Cation channel, sperm associated 2 pseudogene | 440278 |
GSTT2B | Similar to glutathione s-transferase theta 2 (gst class-theta 2) | 653689 |
Table 4.
Genes Initiating Term Labor (Term Initiator Set) in Myometrium (excluding hypothetical and other unidentified/unnamed proteins)
Genes Symbol | Gene Name | Entrez ID |
---|---|---|
A1BG | Alpha-1-b glycoprotein | 1 |
ADCYAP1R1 | Adenylate cyclase activating polypeptide 1 (pituitary) receptor type i | 117 |
ALDOC | Aldolase c, fructose-bisphosphate | 230 |
AQP9 | Aquaporin 9 | 366 |
AREG | Amphiregulin (schwannoma-derived growth factor) | 374 |
ARHGAP4 | Rho gtpase activating protein 4 | 393 |
BCL2A1 | Bcl2-related protein a1 | 597 |
BDKRB1 | Bradykinin receptor b1 | 623 |
BUB1 | Bub1 budding uninhibited by benzimidazoles 1 homolog (yeast) | 699 |
BUB1B | Bub1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) | 701 |
CALCA | Calcitonin/calcitonin-related polypeptide, alpha | 796 |
RUNX3 | Runt-related transcription factor 3 | 864 |
CCNE1 | Cyclin e1 | 898 |
CD48 | Cd48 antigen (b-cell membrane protein) | 962 |
CDC20 | Cdc20 cell division cycle 20 homolog (s. Cerevisiae) | 991 |
CHI3L1 | Chitinase 3-like 1 (cartilage glycoprotein-39) | 1116 |
CSF3 | Colony stimulating factor 3 (granulocyte) | 1440 |
CSN2 | Casein beta | 1447 |
DDIT3 | Dna-damage-inducible transcript 3 | 1649 |
EFNB1 | Ephrin-b1 | 1947 |
EREG | Epiregulin | 2069 |
EYA4 | Eyes absent homolog 4 (drosophila) | 2070 |
ESRRA | Estrogen-related receptor alpha | 2101 |
FPRL1 | Formyl peptide receptor-like 1 | 2358 |
GALE | Udp-galactose-4-epimerase | 2582 |
GCHFR | Gtp cyclohydrolase i feedback regulator | 2644 |
GK | Glycerol kinase | 2710 |
GRIN2D | Glutamate receptor, ionotropic, n-methyl d-aspartate 2d | 2906 |
NRG1 | Neuregulin 1 | 3084 |
HK2 | Hexokinase 2 | 3099 |
NR4A1 | Nuclear receptor subfamily 4, group a, member 1 | 3164 |
IL1B | Interleukin 1, beta | 3553 |
IL9R | Interleukin 9 receptor | 3581 |
IL13RA2 | Interleukin 13 receptor, alpha 2 | 3598 |
INHBB | Inhibin, beta b (activin ab beta polypeptide) | 3625 |
KRT7 | Keratin 7 | 3855 |
LIF | Leukemia inhibitory factor (cholinergic differentiation factor) | 3976 |
MMP3 | Matrix metallopeptidase 3 (stromelysin 1, progelatinase) | 4314 |
MYH3 | Myosin, heavy polypeptide 3, skeletal muscle, embryonic | 4621 |
NEFH | Neurofilament, heavy polypeptide 200kda | 4744 |
NEK2 | Nima (never in mitosis gene a)-related kinase 2 | 4751 |
NPPB | Natriuretic peptide precursor b | 4879 |
SERPINB2 | Serpin peptidase inhibitor, clade b (ovalbumin), member 2 | 5055 |
PCSK1 | Proprotein convertase subtilisin/kexin type 1 | 5122 |
PFKFB4 | 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 | 5210 |
PGK2 | Phosphoglycerate kinase 2 | 5232 |
SERPINF2 | Serpin peptidase inhibitor, clade f (alpha-2 antiplasmin, pigment epithelium derived factor), member 2 | 5345 |
POLE | Polymerase (dna directed), epsilon | 5426 |
PRKCD | Protein kinase c, delta | 5580 |
S100P | S100 calcium binding protein p | 6286 |
CCL11 | Chemokine (c-c motif) ligand 11 | 6356 |
CCL19 | Chemokine (c-c motif) ligand 19 | 6363 |
CXCL6 | Chemokine (c-x-c motif) ligand 6 (granulocyte chemotactic protein 2) | 6372 |
SELE | Selectin e (endothelial adhesion molecule 1) | 6401 |
ST3GAL1 | St3 beta-galactoside alpha-2,3-sialyltransferase 1 | 6482 |
SLAMF1 | Signaling lymphocytic activation molecule family member 1 | 6504 |
SLC9A2 | Solute carrier family 9 (sodium/hydrogen exchanger), member 2 | 6549 |
SPAG4 | Sperm associated antigen 4 | 6676 |
STXBP2 | Syntaxin binding protein 2 | 6813 |
TAC1 | Tachykinin, precursor 1 (substance k, substance p, neurokinin 1, neurokinin 2, neuromedin l, neurokinin alpha, neuropeptide k, neuropeptide gamma) | 6863 |
VAV1 | Vav 1 oncogene | 7409 |
VIL1 | Villin 1 | 7429 |
ZNF31 | Zinc finger protein 31 (kox 29) | 7579 |
GCS1 | Glucosidase i | 7841 |
PLA2G7 | Phospholipase a2, group vii (platelet-activating factor acetylhydrolase, plasma) | 7941 |
NR4A3 | Nuclear receptor subfamily 4, group a, member 3 | 8013 |
FOSL1 | Fos-like antigen 1 | 8061 |
GPR68 | G protein-coupled receptor 68 | 8111 |
SLC7A5 | Solute carrier family 7 (cationic amino acid transporter, y+ system), member 5 | 8140 |
ENC1 | Ectodermal-neural cortex (with btb-like domain) | 8507 |
CPZ | Carboxypeptidase z | 8532 |
TNFRSF6B | Tumor necrosis factor receptor superfamily, member 6b, decoy | 8771 |
PROM1 | Prominin 1 | 8842 |
RRP9 | RRP9, small subunit (SSU) processome component, homolog (yeast) | 9136 |
MSC | Musculin (activated b-cell factor-1) | 9242 |
CYP7B1 | Cytochrome p450, family 7, subfamily b, polypeptide 1 | 9420 |
IL27RA | Interleukin 27 receptor, alpha | 9466 |
IKBKE | Inhibitor of kappa light polypeptide gene enhancer in b-cells, kinase epsilon | 9641 |
DHX34 | Deah (asp-glu-ala-his) box polypeptide 34 | 9704 |
SEC14L5 | Sec14-like 5 (s. Cerevisiae) | 9717 |
CENTB1 | Centaurin, beta 1 | 9744 |
CLSTN3 | Calsyntenin 3 | 9746 |
DHRS2 | Dehydrogenase/reductase (sdr family) member 2 | 10202 |
TACC3 | Transforming, acidic coiled-coil containing protein 3 | 10460 |
DPYSL4 | Dihydropyrimidinase-like 4 | 10570 |
IL24 | Interleukin 24 | 11009 |
LILRA1 | Leukocyte immunoglobulin-like receptor, subfamily a (with tm domain), member 1 | 11024 |
CIT | Citron (rho-interacting, serine/threonine kinase 21) | 11113 |
KPTN | Kaptin (actin binding protein) | 11133 |
RASSF1 | Ras association (ralgds/af-6) domain family 1 | 11186 |
IRAK3 | Interleukin-1 receptor-associated kinase 3 | 11213 |
ATXN2L | Ataxin 2-like | 11273 |
RRP12 | Ribosomal RNA processing 12 homolog (S. Cerevisiae) | 23223 |
SMG6 | Smg-6 homolog, nonsense mediated mrna decay factor (c. Elegans) | 23293 |
NUP188 | Nucleoporin 188kda | 23511 |
CLEC5A | C-type lectin domain family 5, member a | 23601 |
CLEC4E | C-type lectin domain family 4, member e | 26253 |
SIGLEC7 | Sialic acid binding ig-like lectin 7 | 27036 |
SULT1B1 | Sulfotransferase family, cytosolic, 1b, member 1 | 27284 |
CECR2 | Cat eye syndrome chromosome region, candidate 2 | 27443 |
DKFZP434P211 | Pom121-like protein | 29774 |
EMR2 | Egf-like module containing, mucin-like, hormone receptor-like 2 | 30817 |
ANGPTL4 | Angiopoietin-like 4 | 51129 |
ABI3 | Abi gene family, member 3 | 51225 |
RTEL1 | Regulator of telomere elongation helicase 1 | 51750 |
P2RY13 | Purinergic receptor p2y, g-protein coupled, 13 | 53829 |
GPR84 | G protein-coupled receptor 84 | 53831 |
SOX18 | Sry (sex determining region y)-box 18 | 54345 |
SDK2 | Sidekick homolog 2 (chicken) | 54549 |
RAB39 | Rab39, member ras oncogene family | 54734 |
GRAMD1C | Gram domain containing 1c | 54762 |
MCM10 | Mcm10 minichromosome maintenance deficient 10 (s. Cerevisiae) | 55388 |
AJAP1 | Adherens junction associated protein 1 | 55966 |
CCL28 | Chemokine (c-c motif) ligand 28 | 56477 |
ASAH2 | N-acylsphingosine amidohydrolase (non-lysosomal ceramidase) 2 | 56624 |
PDXP | Pyridoxal (pyridoxine, vitamin b6) phosphatase | 57026 |
ATP10A | Atpase, class v, type 10c | 57194 |
LOC57228 | Small trans-membrane and glycosylated protein | 57228 |
LRRN1 | Leucine rich repeat neuronal 1 | 57633 |
NLRC4 | NLR family, CARD domain containing 4 | 58484 |
PROK2 | Prokineticin 2 | 60675 |
CARD9 | Caspase recruitment domain family, member 9 | 64170 |
CDCP1 | Cub domain containing protein 1 | 64866 |
ZNF643 | Zinc finger protein 643 | 65243 |
ZNF557 | Zinc finger protein 557 | 79230 |
IQCA | Iq motif containing with aaa domain | 79781 |
VASH2 | Vasohibin 2 | 79805 |
DENND2D | Denn/madd domain containing 2d | 79961 |
LRRC8E | Leucine rich repeat containing 8 family, member e | 80131 |
ZC3H12A | Zinc finger ccch-type containing 12a | 80149 |
DEPDC2 | Dep domain containing 2 | 80243 |
CLPB | Clpb caseinolytic peptidase b homolog (e. Coli) | 81570 |
PPP1R14C | Protein phosphatase 1, regulatory (inhibitor) subunit 14c | 81706 |
KIF18A | Kinesin family member 18a | 81930 |
TMUB1 | Transmembrane and ubiquitin-like domain containing 1 | 83590 |
URP2 | Unc-112 related protein 2 | 83706 |
MND1 | Meiotic nuclear divisions 1 homolog (s. Cerevisiae) | 84057 |
PROK1 | Prokineticin 1 | 84432 |
DOT1L | Dot1-like, histone h3 methyltransferase (s. Cerevisiae) | 84444 |
SLC12A8 | Solute carrier family 12 (potassium/chloride transporters), member 8 | 84561 |
IGSF21 | Immunoglobin superfamily, member 21 | 84966 |
PNMA6A | Paraneoplastic antigen like 6a | 84968 |
TSLP | Thymic stromal lymphopoietin | 85480 |
PPP1R3F | Protein phosphatase 1, regulatory (inhibitor) subunit 3f | 89801 |
MTG1 | Mitochondrial gtpase 1 homolog (s. Cerevisiae) | 92170 |
SLC38A5 | Solute carrier family 38, member 5 | 92745 |
DDIT4L | Dna-damage-inducible transcript 4-like | 115265 |
ZMYND19 | Zinc finger, mynd-type containing 19 | 116225 |
SLC16A10 | Solute carrier family 16, member 10 (aromatic amino acid transporter) | 117247 |
OSCAR | Osteoclast-associated receptor | 126014 |
WTIP | Wilms tumor 1 interacting protein | 126374 |
PUSL1 | Pseudouridylate synthase-like 1 | 126789 |
B3GNTL1 | Udp-glcnac:betagal beta-1,3-n-acetylglucosaminyltransferase-like 1 | 146712 |
FAM132B | Family with sequence similarity 132, member B | 151176 |
SGOL1 | Shugoshin-like 1 (s. Pombe) | 151648 |
PRELID2 | PRELI domain containing 2 | 153768 |
CRYGN | Crystallin, gamma n | 155051 |
TMEM30B | Transmembrane protein 30b | 161291 |
CCDC138 | Coiled-coil domain containing 138 | 165055 |
SLC30A8 | Solute carrier family 30 (zinc transporter), member 8 | 169026 |
PPAPDC1A | Phosphatidic acid phosphatase type 2 domain containing 1a | 196051 |
ABHD7 | Abhydrolase domain containing 7 | 253152 |
OFCC1 | Orofacial cleft 1 candidate 1 | 266553 |
VMO1 | Vitelline membrane outer layer 1 homolog (chicken) | 284013 |
GLDN | Gliomedin | 342035 |
FMN1 | Formin 1 | 342184 |
AADACL2 | Arylacetamide deacetylase-like 2 | 344752 |
CA13 | Carbonic anhydrase xiii | 377677 |
RASL11A | Ras-like, family 11, member a | 387496 |
APOBEC4 | Apolipoprotein b mrna editing enzyme, catalytic polypeptide-like 4 (putative) | 403314 |
SPINK6 | Serine peptidase inhibitor, kazal type 6 | 404203 |
SNORD68 | Small nucleolar RNA, C/D box 68 | 606500 |
FAM110C | Family with sequence similarity 110, member C | 642273 |
PHLDB3 | Similar to pleckstrin homology-like domain, family b, member 1 | 653583 |
Characterization of Initiator and Effector Gene Sets
It is not adequate to categorize genes based solely on a given condition. Rather, there must be an understanding of how the encoded proteins interact. The result of these interactions is a universe representing the functional potential in terms of complex protein associations, such as pathways with successive reactions and transient structural complexes. We reasoned that characterization of networks based on the identified Initiator and Effector Gene Sets would add insight into the molecular events regulating preterm and term labor. Thus, we enriched the Initiator and Effector sets using the GO classifications. Unlike standard GO classification systems that produce a vague and general understanding of the molecular events underlying the given networks, GeneGo™ GO classifies gene groups within a specified realm of biological processes, molecular function, and cellular components. GeneGo processes are network modules of main cellular processes manually created on the basis of GO processes and pathway maps.
The specificity of each gene set allows for a gene to be present in only one of the three groups. The Effector Set (Figure 2a) and the Term Initiator Set (Figure 3a) were each dominated by inflammatory GO processes, though distinctly different from each other. Each had 4 significant processes (based on P-value and FDR calculation) within the top ten GeneGo processes identified involved with inflammation. These findings clearly support the concept that inflammation plays an important role in term labor.
FIGURE 2.
FIGURE 2a. The Gene Ontology table was generated from the genes of the Effector set in MetaCore. The top 10 Genego GO pathways are listed in the table based on the number of selected genes that saturate each biological area. These processes are prioritized by MetaCore™ based on their statistical significance (−log (p value) with respect to genes expressed in the dataset. A false discovery rate filter set at 10% was also used to illustrate significant processes. The bars representing experiment mappings that do not pass through this significance level are semi-transparent.
FIGURE 2b. Interactive network of the Effector Gene Set was determined using the analyze network algorithm. This algorithm designs sub-networks that are highly saturated with genes of the Effector Set. Selection of the network was based on significance (P-value). The p-value calculation was used to evaluate network’s relevance to GO biological processes classification. The network illustrates gene and gene interactions within Effector Set. Canonical pathways are illustrated by a thick light blue line and represent linear stretches of carefully defined sets of consecutive signals confirmed as a whole by experimental data. The small colored hexagons on vectors (lines) between nodes describe positive (green), negative (red), unspecified (black) interactions, or logical relationships (blue). A node corresponds to a network object (i.e. gene or protein) and is marked with a graphical symbol that reflects the type of the network object represented (i.e. enzyme, transcription factor, ligand, etc.). The large red circle next to the network object corresponds to those genes detected in the Effector Set. The network objects are placed in specific vectors of this network according to their sub-cellular localization. The localization sectors are Nucleus, Cytoplasm, Membrane, Extracellular, and Unspecified.
FIGURE 3.
FIGURE 3a. Similar to figure 2a, this Gene Ontology table is representative of the Term Initiator Gene Set. The genes included are more varied than those of the Preterm Initiator Set.
FIGURE 3b. Similar to figures 2b, this Term Initiator sub-network was generated using the analyze network algorithm (Metacore™). The large red circle next to the network object corresponds to those genes detected in the Term Initiator Group. Selection of the network was based on significance (P-value).
Perhaps not surprisingly, considering the patient selection criterion, the Preterm Initiator Set was also heavily associated with inflammation- all but two of the top ten GeneGo processes (Figure 4a). Of interest was the appearance of ‘Hypoxia and Oxidative Stress’ (number five in Figure 4a) as we have recently demonstrated that chronic hypoxia alone stimulates a response that is clinically the same as the Fetal Inflammatory Response Syndrome 28.
FIGURE 4.
FIGURE 4a. This figure illustrates the major Gene Ontology pathways underlying the Preterm Initiator Gene Set. There is a high correlation between inflammation and the Preterm Initiator Gene Set.
FIGURE 4b. The Preterm Initiator Set sub-network was generated using the analyze network algorithm (Metacore™). The large red circle next to the network object corresponds to those genes detected in the Preterm Initiator Group. Selection of the network was based on significance (P-value).
Visualization of Term Initiator, Preterm Initiator, and Effector Networks
The traditional approach to gene array analyses includes a list with the genes clustered based on biological similarity (Tables 2–4). While this method provides insight into the transcriptional activity of major biological processes, it fails to express how the encoded proteins might interact with each other and surrounding proteins. We previously demonstrated that the identification of gene networks provides a more robust tool by which to extract information from the microarrays than gene lists 16. These networks incorporate genomic data and represent the encoded proteins in the form of predicted interactions and reactions compiled from different experiments and experimental conditions.
There were few direct interactions identified among the proteins of the 34 Effector genes, the 49 Preterm Initiator and 174 Term Initiator genes. This supports our supposition of gene set uniqueness. We then analyzed the possible networks that could be built from such gene sets using an algorithm that generates sub-networks highly saturated with the selected objects which are represented in Figures 2b, 3b, and 4b with a large red circle next to the network object. We selected sub networks based on their P-values. Figures 2b, 3b and 4b illustrate the top ranked identified sub networks in the Effector (n=9), Preterm Initiator (n=11) and Term Initiator Sets (n=30), respectively. The inward and outward bound lines extending from the selected genes (genes in experimental sets (red circles)) illustrate the interactive environment surrounding the selected genes and can be used to show how their encoded proteins are affected (positively (green), negatively (red), unknown (grey)) upstream or downstream within the network pathway. This information could have significant implications for the development and design of therapeutic entities targeted at inhibiting or stimulating the activity of the targeted gene or protein in the pathway.
Validation of Initiator and Effector Gene Sets
The high sensitivity of Q-rtPCR makes it likely small changes in gene expression exist that were undetected by the microarray analyses. And while we assume for microarray analyses that relevant genes were described by gene expression above a set expression threshold, we recognize the sensitivity of Q-rtPCR might reveal enhanced expression in genes unselected in the microarray analyses. Thus, we focused on sub network genes with high mRNA levels.
The idea that a unique group of encoded proteins is responsible for sustaining myometrial contractility during labor irrespective of gestational age (Effector set) has not been investigated previously. Based on our analyses, we selected HNT (neutrimin precursor), KCNAB2 (voltage-gated potassium channel, shaker-related subfamily) and RRAD (Ras-related associated with diabetes) (Figure 5). The expression of these genes has not previously been localized to the myometrium; nor have they been associated with labor. The microarray analyses and the logic process were confirmed to identify genes that were in similarly increased during labor independent of gestational age and mechanism.
FIGURE 5.
The Effector Set represents genes that sustain myometrial contractility and are unaffected by stimulus. HNT, KCNAB2, RRAD were selected for study to verify the microarray results. mRNA levels were determined in the myometrium of term (n=6; 39.7w) and preterm with inflammation (n=6; 30.9w) pregnant women in active labor and not-in-labor (term n=6; 39.6w, preterm n=6; 28.9w) via Q-rtPCR using the Livak Method. Microarray findings were confirmed for all but one gene tested. In general, the findings confirm both the microarray findings and the presence of core genes associated with labor regardless of its timing.
By applying a similar analytic approach, we selected five genes for confirmation in the Term Initiator Set (Figure 6): PROK1 (prokineticin 1), IL9R (interleukin 9 receptor), EREG (epiregulin), BDKRB1 (bradykinin receptor B1), and IL13RA2 (interleukin 13 receptor, alpha 2). Of the 5, only PROK1 has previously been reported to be expressed in the reproductive tract (endometrial glands of nonpregnant women 29. In each instance except for IL9R (which declined significantly with labor), the microarray analyses and the logic process confirmed the identified genes were more highly expressed during term labor, though each was also effected by preterm labor but to a significantly smaller extent. There was a more than fourfold increase in expression of BDKRB1, EREG, and IL13RA2 during TL compared to PTL, and both EREG and BDKRB1 were increased in TL compared to TNL.
FIGURE 6.
Term Initiator Set genes EREG, BDKRB1, IL13RA2 mRNA levels were significantly greater at term labor (open bar) than preterm labor (close bar) in myometrium. mRNA levels were determined in the myometrium of term (n=6; 39.7w) and preterm with inflammation (n=6; 30.9w) pregnant women in active labor and not-in-labor (term n=6; 39.6w, preterm n=6; 28.9w) via Q-rtPCR using the Livak Method. Microarray findings were confirmed for all but one gene tested. EREG and BDKRB1 mRNA levels were significantly higher at labor (open bar) than non labor (close bar) in term myometrium. Only IL9R Q-rtPCR results different from the microarray.
The genes selected for validation in the Preterm Initiator genes were CATSPER2 (cation channel, sperm associated 2 pseudogene 1) and PTPRZ1 (protein tyrosine phosphatase, receptor-type, Z polypeptide 1). The existence of the latter in rodent myometrium has previously been suggested 30, 31. We both confirm the presence of mRNA from both genes in human myometrium, and that they are specifically increased in preterm labor associated with inflammation (Figure 7).
FIGURE 7.
Preterm Initiator Set- mRNA levels were determined as indicated previously. Changes in the mRNA levels for genes Catsper2 and Ptprz1 were consistent with the array data.
Comments
Models of labor previously proposed include endocrine and paracrine regulation, calcium signaling, inflammation secondary to infection, etc. Rather than compare term labor to one of many models of preterm birth, we hypothesized that labor is defined by a core set of genes whose expression is unaltered by gestational age and independent of the underlying labor trigger. We applied functional gene array profiling of myometrium obtained from preterm and term non-laboring and laboring women. While this is not the first time gene array technology has been used to map the molecular networks of labor (we first published such in 2006 16), it is apparently the first attempt to differentiate genomically the molecular events that initiate and maintain myometrial activity in human labor at term and preterm. In our original report, we noted how genomic networks could be used to profile myometrial events during pregnancy and herein apply more advanced methodology to generate signature gene networks.
It is often assumed the triggers or initiators of human labor are similar regardless of gestation, hence an investigative focus on term labor as a model to understand preterm labor. Numerous researchers have shown term labor is characterized by an inflammatory response, and at least the majority of spontaneous preterm births are associated with inflammation 8, 32–35. The findings of the present study support the premise that inflammation is a central mechanism at term as such genes were heavily represented in the Effector and the Term Initiator Gene Sets. While many clinicians chose a tocolytic agent which targets inflammation (e.g., indomethacin), this approach has failed to reduce the prevalence of spontaneous preterm birth or dysfunctional labor. The results of the present investigation are more than a simple cataloging of genomic events. We identify activity along several pathways not previously known to be involved which are part of the Effector and Initiator Gene Sets. In fact, a large percentage of the involved genes identified in the current investigation have not previously been described in myometrium, much less shown to be altered by disorders of labor. We recognize that this is a first step. It remains now to explore the functional roles of the identified pathways to see how altering them affects the process of labor.
The Effector Gene Set (Figure 2a) encompasses genes whose products are involve in chemotaxis, cell adhesion, reproduction and neurohormone signaling, signal transduction, muscle contraction, vascularization and as noted earlier, inflammation. Microarray findings were confirmed for HNT, KCNAB2, and RRAD. HNT is grouped in GO processes related to biological and cell adhesion and cell recognition, all logical needs to sustain labor. The protein encoded is a member of the Ig domain containing glycosylphosphatidylinositol-anchoring adhesion molecules. As such, HNT may play a role in the coordination of myometrial cell contractions. Its expression has not previously been shown in human myometrium or to be affected by labor.
We previously demonstrated that pregnancy and sex hormones (estrogen and progesterone) alter G-protein mediated signaling 36 at least in part by modulating myometrial GTPase activity. RRAD encodes a GTPase molecule previously identified in the myocardiocyte and shown to interact with calmodulin, tropomyosin and CaM kinase II among others. Its expression in laboring myometrium is a new finding. Analyses placed it into the node with the most significant likelihood of not having occurred at random (gScore = 50.44). As a member of the Effector Gene Set, it could play a role coordinating and modulating the strength of the myometrial contraction.
KCNAB2 is another Effector Gene Set member of interest. This voltage-gated potassium channel represents the most complex class of voltage-gated ion channels from both functional and structural standpoints and fell into the second highest GO group (gScore 33.6). In other anatomic structures, they are involved in the regulation of the contraction rate in regularly beating muscles. A number of investigators have concluded voltage-gated potassium channels are fundamentally involved in the regulation of rodent myometrial contractility 37–39. Other voltage-gated potassium channels are regulated by sex hormones 40, 41. We previously demonstrated that the human chorion produces a factor or factors that inhibit myometrial contractility via the opening of a large conductance calcium-activated potassium channels 42. KCNAB2 may help generate the increased frequency of myometrial contractions associated with labor regardless of gestational age.
The majority of pregnancy passes with the myometrium in a state of quiescence, a genomically distinct phase that renders it relatively unresponsive to contractile agonists. Labor follows myometrial activation, possibly due to complex alterations in the signaling mechanism(s). We hypothesized that in contrast to the Effector Set, there must exist specific Initiator Gene Sets responsible for that transition from quiescence to activation that reflect the specific underlying stimulus. The results of the current study support that working hypothesis. For example, the cytokine network is in sensitive balance throughout uncomplicated pregnancy, and we suspect a similar balance exists for encoded cytokines during pregnancy. However, despite the presence of several GO processes in the Effector Gene Set that reflect inflammation, interleukins are not seen in that grouping save for interleukin 8 receptor, beta. In myocardium, interleukin (IL)-8 is up regulated in areas of infarction and may induce neutrophil infiltration 43. In contrast to the Effector Gene Set, several cytokine genes are present in the Term Initiator Gene Set, including interleukin 1 receptor-associated kinase 3 (IRAK3), interleukin 24 (IL24), interleukin 1 beta (IL1B), IL13RA2, and IL9R (the latter was the only conflict between microarray and Q-rtPCR). Not found in any of the gene sets was interleukin 10 (IL-10), which has been implicated as an anti-inflammatory modulator of cytokine synthesis initiated by intrauterine infection 44–48. Its absence suggests it does not have a significant role in either inflammation preterm labor or term labor.
We have previously noted that myometrial quiescence and activation are associated with altered G protein expression and GTPase activity in both the guinea pig and human 16, 36. In addition to the expression of RRAD in the Effector Gene Set, there were several G-protein related proteins included in the Term Initiator Gene Set including G protein-coupled receptor 84 (GPR84), rab39 member of ras oncogene family (RAB39), ras-like family 11 member A (RASL11A), and ras association domain family 1 (RASSF1), most of which there is little known about and not previously documented to be expressed in the myometrium.
The presence of BDKRB1 and EREG expression in the Term Initiator Set are both provocative. There was more than a 4 fold increase in expression of BDKRB1 and EREG compared to PTL (Figure 6), suggesting preferential involvement in term labor. Contractile responses of nonpregnant human myometrium to bradykinin are reduced during the luteal phase49. Wassdal et al noted that bradykinin contracted rodent myometrium via the same pathway as did oxytocin 50. In cultured decidua-derived cells, bradykinin stimulates the release of arachidonic acid, interleukin 6 (IL-6), and interleukin 8 (IL-8). These effects are prevented by the specific B2R antagonist Hoe 140 51. Further, human decidua-derived cells express the B2R, and its expression is up regulated in response to IL-β, and bradykinin stimulates the secretion of further mediators by these cells. Finally, bradykinin is purported to trigger the release of PGE2 from human myometrium 52. Each of these characteristics of bradykinin could facilitate the onset of term labor. Epiregulin is expressed in myometrium from pregnant mice but not myometrium of pseudo pregnant mice 53. Induction of its synthesis has been linked to the RAF/MEK/ERK pathway 54.
In accordance with our current working hypothesis, we found that gene events associated with myometrial activation and term labor are not the same as those associated with preterm labor. Not surprisingly in light of the patient sample chosen for study, the Preterm Initiator Gene Set was dominated by inflammatory processes. The present study focused on inflammation mediated preterm labor as it is the most plentiful and the best described. Though not tested, our hypothesis requires the initiator set differ in women who experience preterm labor unassociated with inflammation (e.g., over distension with multiple gestation).
Despite the strong weighting of GeneGo processes toward inflammation in the Preterm Initiator Gene Set, there were a number of other genes worthy of follow-up in the future. For example, GSTT2, glutathione S-transferase theta 2is a member of a superfamily of proteins that catalyze the conjugation of reduced glutathione to a variety of electrophilic and hydrophobic compounds. Human GSTs are subdivided into five classes: Alpha, Mu, Pi, Theta, and Zeta. The theta members GSTT1 and GSTT2 share 55% amino acid sequence identity and are both thought to have an important role in human carcinogenesis. An increase in its protein could reflect an increase in oxygen free radical production. We previously demonstrated that inflammation related preterm labor is associated with a pro-oxidant state in the newborn characterized by a decrease in reduced glutathione 55.
The Preterm Initiator Set also included the transporter, ATP-binding cassette, sub-family A member 3 (ABCA3) whose protein is a member of the ABC1 subfamily. Members of the ABC1 subfamily comprise the only major ABC subfamily found exclusively in multicellular eukaryotes and may be involved in the development of resistance to xenobiotics and engulfment during programmed cell death. The function of ABCA3 in myometrium is unknown, but one possible role in the initiation of inflammation associated preterm labor could involve the exposure and presentation of potential antigens that trigger inflammation as a secondary response to the initiating event. The present study is the first report of its expression in myometrium and the impact of spontaneous preterm labor upon it.
It is becoming increasingly clear that the pattern of cytokine expression differs in preterm and term labor 56. Therefore, cytokine expression may also differ among various tissues (i.e. myometrium) at different gestations. Increased protein and/or mRNA concentrations of IL-1β, tumor necrosis factor alpha (TNF-α) and IL-6 in myometrium have each previously been associated with labor 44. In the present study, none were included in the Preterm Initiator Gene Set suggesting the production is a downstream event or not specific to preterm labor. This conclusion is consistent with findings of previous investigators who found that the levels of cytokines such as IL-1β, IL-6, and IL-8 were higher in TL compared to PTL myometrial samples 57. The results of the current study do not support the use of TNF-α as a biomarker for inflammation specifically associated preterm labor. The TNF-α gene encodes a multifunctional proinflammatory cytokine that belongs to the TNF superfamily. It is involved in the regulation of a wide spectrum of biological processes, including cell proliferation, differentiation, apoptosis, lipid metabolism, and coagulation. Elevated transcription and accumulation of TNF-α and other cytokines in gestational tissues is proposed to activate prostaglandin synthesis which, in turn, leads to the myometrial contractions 58, 59. Though not present in the Preterm Initiator Gene Set, it is a component of the Term Initiator Gene Set and thus may play a role with normal labor.
Regional differences in gene expression between the fundus, lower segment and cervix were reported in a prior study 12. In the current study, we used biopsies from the upper edge of the lower uterine segment and emphasize our findings must be interpreted in this context. However, we previously determined that the collagen/muscle ratio is 20%/80% in lower segment biopsies collected from the upper lip of the incision60. Thus, we believe that the muscle component to our biopsies is significant. Importantly, we found a significant increase in the contribution of the muscular component in laboring tissues indicating that the lower segment participates morphologically in the process of labor. In the current study, our non-reliance on differences in levels of gene expression to derive biological significance, but rather by intersecting the presence of genes in biologically relevant instances should circumvent minor differences in regionalization of the myometrium versus the collagen component with either gestational age or labor.
Finally, it is interesting to look at the genes not included on any of the three gene sets described herein. It is striking that no list includes oxytocin or an oxytocin receptor. As it is recognized that oxytocin can induce its own receptor in rodent myometrium, it is surprising neither gene was present in the Effector Set. Nor does one of the three lists include representation of the eicosanoids or their related enzymes. And while there are numerous cytokines or cytokine pathway elements included in one of the three sets, IL-6, its receptor, TNF- alpha or its receptor, or IL-10 are not included. Their absence does not suggest these compounds are not involved in human parturition. Rather, it suggests their primacy in the process is other than anticipated and that their actions may be downstream events. Alternatively, there is no uniqueness in their expression during spontaneous term or inflammation associated preterm labor.
In conclusion, we have identified through gene profiling a specific set of labor activation/ repression genes (the Effector Gene Set) whose expression is unaffected by the timing of the labor. Future searches for new tocolytic agents might benefit from a focus on these unique gene products. And while the Effector Gene Set is unchanged by the gestation of the labor, preterm labor and term labor differ dramatically in their Initiator Gene Sets. This finding is consistent with the suggestion that there are alternative pathways for preterm and term labor that trigger a common phenotype. Lastly, we confirm that term labor and preterm labor associated with inflammation are characterized by an inflammatory response, but they are not the same responses and they do not include several previously ‘in vogue’ genes. Thus, the classic evidence for inflammation as a cause of spontaneous preterm labor may well be a downstream event from myometrial gene activation.
Acknowledgments
Funding: This work was supported in part by grants from the PHS (U01 DP000187-02 [CPW] and R01HL049041-12 [CPW]
Footnotes
Presented in part at the 2006 annual meeting of the Society for Gynecologic Investigation
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